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The Secret Adversary by Agatha Christie, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . THE ADVENTURES OF TOMMY CHAPTER VIII. THE ADVENTURES OF TOMMY Taken aback though he was by the man’s words, Tommy did not hesitate. If audacity had successfully carried him so far, it was to be hoped it would carry him yet farther. He quietly passed into the house and mounted the ramshackle staircase. Everything in the house was filthy beyond words. The grimy paper, of a pattern now indistinguishable, hung in loose festoons from the wall. In every angle was a grey mass of cobweb. Tommy proceeded leisurely. By the time he reached the bend of the staircase, he had heard the man below disappear into a back room. Clearly no suspicion attached to him as yet. To come to the house and ask for “Mr. Brown” appeared indeed to be a reasonable and natural proceeding. At the top of the stairs Tommy halted to consider his next move. In front of him ran a narrow passage, with doors opening on either side of it. From the one nearest him on the left came a low murmur of voices. It was this room which he had been directed to enter. But what held his glance fascinated was a small recess immediately on his right, half concealed by a torn velvet curtain. It was directly opposite the left-handed door and, owing to its angle, it also commanded a good view of the upper part of the staircase. As a hiding-place for one or, at a pinch, two men, it was ideal, being about two feet deep and three feet wide. It attracted Tommy mightily. He thought things over in his usual slow and steady way, deciding that the mention of “Mr. Brown” was not a request for an individual, but in all probability a password used by the gang. His lucky use of it had gained him admission. So far he had aroused no suspicion. But he must decide quickly on his next step. Suppose he were boldly to enter the room on the left of the passage. Would the mere fact of his having been admitted to the house be sufficient? Perhaps a further password would be required, or, at any rate, some proof of identity. The doorkeeper clearly did not know all the members of the gang by sight, but it might be different upstairs. On the whole it seemed to him that luck had served him very well so far, but that there was such a thing as trusting it too far. To enter that room was a colossal risk. He could not hope to sustain his part indefinitely; sooner or later he was almost bound to betray himself, and then he would have thrown away a vital chance in mere foolhardiness. A repetition of the signal knock sounded on the door below, and Tommy, his mind made up, slipped quickly into the recess, and cautiously drew the curtain farther across so that it shielded him completely from sight. There were several rents and slits in the ancient material which afforded him a good view. He would watch events, and any time he chose could, after all, join the assembly, modelling his behaviour on that of the new arrival. The man who came up the staircase with a furtive, soft-footed tread was quite unknown to Tommy. He was obviously of the very dregs of society. The low beetling brows, and the criminal jaw, the bestiality of the whole countenance were new to the young man, though he was a type that Scotland Yard would have recognized at a glance. The man passed the recess, breathing heavily as he went. He stopped at the door opposite, and gave a repetition of the signal knock. A voice inside called out something, and the man opened the door and passed in, affording Tommy a momentary glimpse of the room inside. He thought there must be about four or five people seated round a long table that took up most of the space, but his attention was caught and held by a tall man with close-cropped hair and a short, pointed, naval-looking beard, who sat at the head of the table with papers in front of him. As the new-comer entered he glanced up, and with a correct, but curiously precise enunciation, which attracted Tommy’s notice, he asked: “Your number, comrade?” “Fourteen, gov’nor,” replied the other hoarsely. “Correct.” The door shut again. “If that isn’t a Hun, I’m a Dutchman!” said Tommy to himself. “And running the show darned systematically too—as they always do. Lucky I didn’t roll in. I’d have given the wrong number, and there would have been the deuce to pay. No, this is the place for me. Hullo, here’s another knock.” This visitor proved to be of an entirely different type to the last. Tommy recognized in him an Irish Sinn Feiner. Certainly Mr. Brown’s organization was a far-reaching concern. The common criminal, the well-bred Irish gentleman, the pale Russian, and the efficient German master of the ceremonies! Truly a strange and sinister gathering! Who was this man who held in his finger these curiously variegated links of an unknown chain? In this case, the procedure was exactly the same. The signal knock, the demand for a number, and the reply “Correct.” Two knocks followed in quick succession on the door below. The first man was quite unknown to Tommy, who put him down as a city clerk. A quiet, intelligent-looking man, rather shabbily dressed. The second was of the working classes, and his face was vaguely familiar to the young man. Three minutes later came another, a man of commanding appearance, exquisitely dressed, and evidently well born. His face, again, was not unknown to the watcher, though he could not for the moment put a name to it. After his arrival there was a long wait. In fact Tommy concluded that the gathering was now complete, and was just cautiously creeping out from his hiding-place, when another knock sent him scuttling back to cover. This last-comer came up the stairs so quietly that he was almost abreast of Tommy before the young man had realized his presence. He was a small man, very pale, with a gentle almost womanish air. The angle of the cheek-bones hinted at his Slavonic ancestry, otherwise there was nothing to indicate his nationality. As he passed the recess, he turned his head slowly. The strange light eyes seemed to burn through the curtain; Tommy could hardly believe that the man did not know he was there and in spite of himself he shivered. He was no more fanciful than the majority of young Englishmen, but he could not rid himself of the impression that some unusually potent force emanated from the man. The creature reminded him of a venomous snake. A moment later his impression was proved correct. The new-comer knocked on the door as all had done, but his reception was very different. The bearded man rose to his feet, and all the others followed suit. The German came forward and shook hands. His heels clicked together. “We are honoured,” he said. “We are greatly honoured. I much feared that it would be impossible.” The other answered in a low voice that had a kind of hiss in it: “There were difficulties. It will not be possible again, I fear. But one meeting is essential—to define my policy. I can do nothing without—Mr. Brown. He is here?” The change in the German’s voice was audible as he replied with slight hesitation: “We have received a message. It is impossible for him to be present in person.” He stopped, giving a curious impression of having left the sentence unfinished. A very slow smile overspread the face of the other. He looked round at a circle of uneasy faces. “Ah! I understand. I have read of his methods. He works in the dark and trusts no one. But, all the same, it is possible that he is among us now....” He looked round him again, and again that expression of fear swept over the group. Each man seemed eyeing his neighbour doubtfully. The Russian tapped his cheek. “So be it. Let us proceed.” The German seemed to pull himself together. He indicated the place he had been occupying at the head of the table. The Russian demurred, but the other insisted. “It is the only possible place,” he said, “for—Number One. Perhaps Number Fourteen will shut the door?” In another moment Tommy was once more confronting bare wooden panels, and the voices within had sunk once more to a mere undistinguishable murmur. Tommy became restive. The conversation he had overheard had stimulated his curiosity. He felt that, by hook or by crook, he must hear more. There was no sound from below, and it did not seem likely that the doorkeeper would come upstairs. After listening intently for a minute or two, he put his head round the curtain. The passage was deserted. Tommy bent down and removed his shoes, then, leaving them behind the curtain, he walked gingerly out on his stockinged feet, and kneeling down by the closed door he laid his ear cautiously to the crack. To his intense annoyance he could distinguish little more; just a chance word here and there if a voice was raised, which merely served to whet his curiosity still farther. He eyed the handle of the door tentatively. Could he turn it by degrees so gently and imperceptibly that those in the room would notice nothing? He decided that with great care it could be done. Very slowly, a fraction of an inch at a time, he moved it round, holding his breath in his excessive care. A little more—a little more still—would it never be finished? Ah! at last it would turn no farther. He stayed so for a minute or two, then drew a deep breath, and pressed it ever so slightly inward. The door did not budge. Tommy was annoyed. If he had to use too much force, it would almost certainly creak. He waited until the voices rose a little, then he tried again. Still nothing happened. He increased the pressure. Had the beastly thing stuck? Finally, in desperation, he pushed with all his might. But the door remained firm, and at last the truth dawned upon him. It was locked or bolted on the inside. For a moment or two Tommy’s indignation got the better of him. “Well, I’m damned!” he said. “What a dirty trick!” As his indignation cooled, he prepared to face the situation. Clearly the first thing to be done was to restore the handle to its original position. If he let it go suddenly, the men inside would be almost certain to notice it, so, with the same infinite pains, he reversed his former tactics. All went well, and with a sigh of relief the young man rose to his feet. There was a certain bulldog tenacity about Tommy that made him slow to admit defeat. Checkmated for the moment, he was far from abandoning the conflict. He still intended to hear what was going on in the locked room. As one plan had failed, he must hunt about for another. He looked round him. A little farther along the passage on the left was a second door. He slipped silently along to it. He listened for a moment or two, then tried the handle. It yielded, and he slipped inside. The room, which was untenanted, was furnished as a bedroom. Like everything else in the house, the furniture was falling to pieces, and the dirt was, if anything, more abundant. But what interested Tommy was the thing he had hoped to find, a communicating door between the two rooms, up on the left by the window. Carefully closing the door into the passage behind him, he stepped across to the other and examined it closely. The bolt was shot across it. It was very rusty, and had clearly not been used for some time. By gently wriggling it to and fro, Tommy managed to draw it back without making too much noise. Then he repeated his former manœuvres with the handle—this time with complete success. The door swung open—a crack, a mere fraction, but enough for Tommy to hear what went on. There was a velvet portière on the inside of this door which prevented him from seeing, but he was able to recognize the voices with a reasonable amount of accuracy. The Sinn Feiner was speaking. His rich Irish voice was unmistakable: “That’s all very well. But more money is essential. No money—no results!” Another voice which Tommy rather thought was that of Boris replied: “Will you guarantee that there are results?” “In a month from now—sooner or later as you wish—I will guarantee you such a reign of terror in Ireland as shall shake the British Empire to its foundations.” There was a pause, and then came the soft, sibilant accents of Number One: “Good! You shall have the money. Boris, you will see to that.” Boris asked a question: “Via the Irish Americans, and Mr. Potter as usual?” “I guess that’ll be all right!” said a new voice, with a transatlantic intonation, “though I’d like to point out, here and now, that things are getting a mite difficult. There’s not the sympathy there was, and a growing disposition to let the Irish settle their own affairs without interference from America.” Tommy felt that Boris had shrugged his shoulders as he answered: “Does that matter, since the money only nominally comes from the States?” “The chief difficulty is the landing of the ammunition,” said the Sinn Feiner. “The money is conveyed in easily enough—thanks to our colleague here.” Another voice, which Tommy fancied was that of the tall, commanding-looking man whose face had seemed familiar to him, said: “Think of the feelings of Belfast if they could hear you!” “That is settled, then,” said the sibilant tones. “Now, in the matter of the loan to an English newspaper, you have arranged the details satisfactorily, Boris?” “I think so.” “That is good. An official denial from Moscow will be forthcoming if necessary.” There was a pause, and then the clear voice of the German broke the silence: “I am directed by—Mr. Brown, to place the summaries of the reports from the different unions before you. That of the miners is most satisfactory. We must hold back the railways. There may be trouble with the A.S.E.” For a long time there was a silence, broken only by the rustle of papers and an occasional word of explanation from the German. Then Tommy heard the light tap-tap of fingers, drumming on the table. “And—the date, my friend?” said Number One. “The 29th.” The Russian seemed to consider: “That is rather soon.” “I know. But it was settled by the principal Labour leaders, and we cannot seem to interfere too much. They must believe it to be entirely their own show.” The Russian laughed softly, as though amused. “Yes, yes,” he said. “That is true. They must have no inkling that we are using them for our own ends. They are honest men—and that is their value to us. It is curious—but you cannot make a revolution without honest men. The instinct of the populace is infallible.” He paused, and then repeated, as though the phrase pleased him: “Every revolution has had its honest men. They are soon disposed of afterwards.” There was a sinister note in his voice. The German resumed: “Clymes must go. He is too far-seeing. Number Fourteen will see to that.” There was a hoarse murmur. “That’s all right, gov’nor.” And then after a moment or two: “Suppose I’m nabbed.” “You will have the best legal talent to defend you,” replied the German quietly. “But in any case you will wear gloves fitted with the finger-prints of a notorious housebreaker. You have little to fear.” “Oh, I ain’t afraid, gov’nor. All for the good of the cause. The streets is going to run with blood, so they say.” He spoke with a grim relish. “Dreams of it, sometimes, I does. And diamonds and pearls rolling about in the gutter for anyone to pick up!” Tommy heard a chair shifted. Then Number One spoke: “Then all is arranged. We are assured of success?” “I—think so.” But the German spoke with less than his usual confidence. Number One’s voice held suddenly a dangerous quality: “What has gone wrong?” “Nothing; but——” “But what?” “The Labour leaders. Without them, as you say, we can do nothing. If they do not declare a general strike on the 29th——” “Why should they not?” “As you’ve said, they’re honest. And, in spite of everything we’ve done to discredit the Government in their eyes, I’m not sure that they haven’t got a sneaking faith and belief in it.” “But——” “I know. They abuse it unceasingly. But, on the whole, public opinion swings to the side of the Government. They will not go against it.” Again the Russian’s fingers drummed on the table. “To the point, my friend. I was given to understand that there was a certain document in existence which assured success.” “That is so. If that document were placed before the leaders, the result would be immediate. They would publish it broadcast throughout England, and declare for the revolution without a moment’s hesitation. The Government would be broken finally and completely.” “Then what more do you want?” “The document itself,” said the German bluntly. “Ah! It is not in your possession? But you know where it is?” “No.” “Does anyone know where it is?” “One person—perhaps. And we are not sure of that even.” “Who is this person?” “A girl.” Tommy held his breath. “A girl?” The Russian’s voice rose contemptuously. “And you have not made her speak? In Russia we have ways of making a girl talk.” “This case is different,” said the German sullenly. “How—different?” He paused a moment, then went on: “Where is the girl now?” “The girl?” “Yes.” “She is——” But Tommy heard no more. A crashing blow descended on his head, and all was darkness. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Agatha Christie (1998). The Secret Adversary. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/1155/pg1155-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html.

THE ADVENTURES OF TOMMY

1811 Dictionary in the Vulgar Tongue: Section F

The Odyssey: Book XI

The Odyssey: Book III

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Website template is the best solution for site building. Here are 20 Best Free Bootstrap landing page templates in 2018 for creative and powerful website building. Your landing page is fundamental in persuading new visitors to take certain actions when visiting your site. Whether it be having users sign up, register, or even buy your product or service, designing an excellent landing page will help you realise this goal. But how do you quickly build a quality landing page? Using a powerful and flexible landing page template may be your best choice. Most HTML5, Bootstrap, and CSS3 templates include features that can help you effortlessly create a page. In addition, web designers and developers readily share free responsive landing page templates on the Internet for you to use. 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20 Best Free HTML5, CSS3, Bootstrap Landing Page Templates in 2018

Recently, Solana (SOL) and Ethereum (ETH) surged by 5.5% and 3.5%, respectively, reflecting the market's bullish momentum, possibly influenced by BTC's recent halving. Amidst this, Furrever Token (FURR) emerges as a notable contender, capturing investor attention with an impressive accumulation of nearly $1,000,000 during its two-month presale period. As these cryptocurrencies make significant moves, investors eagerly anticipate their continued growth and the opportunities they present in the ever-evolving digital asset space. Solana (SOL) Surges 5.5%: Technical Analysis and Price Predictions Solana (SOL) has surged by 5.5% to reach a current price of $150.63, reflecting robust market performance with a significant 24-hour trading volume of $2.97 billion. This surge has propelled Solana's market capitalization to approximately $67.62 billion, solidifying its position as the fifth largest by market cap. Market watchers are increasingly optimistic about Solana's price predictions as it faces immediate resistance at $164.56, with further hurdles at $185.94 and $204.26. Support levels are identified at $126.23, $110.96, and $92.64, providing potential bounce-back points. The Relative Strength Index (RSI) at 39 suggests Solana is nearing oversold conditions, while the 50-day Exponential Moving Average (EMA) at $156.28 presents a significant resistance level. Whether Solana can sustain its upward momentum and overcome resistance posed by the 50-day EMA remains critical for investors and traders, as a breakout could lead to further gains. At the same time, failure to hold may result in a retreat to lower support zones. Ethereum (ETH) Rides Bitcoin Halving Wave: Capital Inflows Spark 4% Surge. Ethereum (ETH) witnessed a 4% surge, reaching a current price of $3,163.71, propelled by capital inflows sparked by Bitcoin's halving event. This surge mirrors the upside moves across the crypto market, with total market capitalization rising by 3.5% in the same period. Notably, the ETH/BTC pair rises roughly 2.5% to 0.048 BTC on April 21, indicating growing Ethereum dominance. Historically, Ethereum experienced increased capital inflows from Bitcoin post-halving events, leading to significant price surges. Recent data from Glassnode reveals accumulation among Ethereum's wealthiest investors, suggesting a precursor to further price upside. The current support level near ETH's 0.5 Fibonacci retracement line and its 200-day exponential moving average presents an attractive buying opportunity, reinforcing traders' confidence in Ethereum's upward trajectory. Furrever Token (FURR) Grabs Investor Attention with Presale Success Amid Market Uptick In the ever-evolving cryptocurrency market landscape, Furrever Token (FURR) has emerged as a standout player, captivating investor attention with its remarkable success in the presale phase amidst a recent uptick in market activity. Designed to revolutionize the crypto space with an infusion of irresistible cuteness, Furrever Token offers users a delightful and charming experience centered around the universal appeal of cute kitties. In a market dominated by serious blockchain projects, Furrever Token's light-hearted approach serves as a breath of fresh air, attracting not only seasoned investors but also newcomers eager to explore the playful side of crypto. At the heart of Furrever Token's mission is developing a user-friendly platform that fosters a warm and friendly community. Furrever Token aims to create a whimsical crypto ecosystem where fun and enjoyment take center stage by integrating cute cat-themed stickers, emojis, and visuals. Regular challenges, launches, and growth initiatives encourage users to share their love for cuteness, fostering a sense of camaraderie and shared joy among community members. The tokenomics of Furrever Token are carefully structured to incentivize participation and support project growth. With 65% of tokens available during the presale phase, investors have ample opportunity to secure their stake in the project's future success. Having already raised over $1,000,000 and nearing the completion of stage 7 out of 10, Furrever Token is well on its way to reaching its fundraising goal of $1.9M before its highly anticipated launch on DEX (PancakeSwap). One of the most enticing aspects of Furrever Token is its potential for substantial returns. With up to 15X returns and a current price of $0.000564, FURR has garnered significant interest from investors seeking profitability and engagement. Moreover, Furrever Token has implemented various security measures to reassure investors of the project's legitimacy. These measures include audits, token lock-ups, and active community engagement initiatives, all contributing to a transparent and trustworthy investment environment. In conclusion, Furrever Token is a promising project for further success in the crypto market. With its unique blend of cuteness, community engagement, and profitability, FURR has captured the imagination of investors worldwide. As the project continues to gain momentum and attract new supporters, the future looks bright for Furrever Token and its growing community of dedicated enthusiasts. Investors can only purchase FURR from the official website, furrevertoken.com, ensuring a secure and reliable transaction process.Discover the Most Exclusive Presale Opportunity of 2024 Now:Furrever Token Official Website  |   Visit Furrever Token Presale Join Official Telegram Group       |   Follow Official X Account This story was distributed as a release by ZEX MEDIA under HackerNoon’s Brand As An Author Program. Learn more about the program here. Recently, Solana (SOL) and Ethereum (ETH) surged by 5.5% and 3.5%, respectively, reflecting the market's bullish momentum, possibly influenced by BTC's recent halving. Amidst this, Furrever Token (FURR) emerges as a notable contender, capturing investor attention with an impressive accumulation of nearly $1,000,000 during its two-month presale period. As these cryptocurrencies make significant moves, investors eagerly anticipate their continued growth and the opportunities they present in the ever-evolving digital asset space. Furrever Token (FURR) Furrever Token (FURR) cryptocurrencies Solana (SOL) Surges 5.5%: Technical Analysis and Price Predictions Solana (SOL) has surged by 5.5% to reach a current price of $150.63, reflecting robust market performance with a significant 24-hour trading volume of $2.97 billion. This surge has propelled Solana's market capitalization to approximately $67.62 billion, solidifying its position as the fifth largest by market cap. Market watchers are increasingly optimistic about Solana's price predictions as it faces immediate resistance at $164.56, with further hurdles at $185.94 and $204.26. Support levels are identified at $126.23, $110.96, and $92.64, providing potential bounce-back points. The Relative Strength Index (RSI) at 39 suggests Solana is nearing oversold conditions, while the 50-day Exponential Moving Average (EMA) at $156.28 presents a significant resistance level. Whether Solana can sustain its upward momentum and overcome resistance posed by the 50-day EMA remains critical for investors and traders, as a breakout could lead to further gains. At the same time, failure to hold may result in a retreat to lower support zones. Ethereum (ETH) Rides Bitcoin Halving Wave: Capital Inflows Spark 4% Surge. Ethereum (ETH) witnessed a 4% surge, reaching a current price of $3,163.71, propelled by capital inflows sparked by Bitcoin's halving event. This surge mirrors the upside moves across the crypto market, with total market capitalization rising by 3.5% in the same period. Notably, the ETH/BTC pair rises roughly 2.5% to 0.048 BTC on April 21, indicating growing Ethereum dominance. Historically, Ethereum experienced increased capital inflows from Bitcoin post-halving events, leading to significant price surges. Recent data from Glassnode reveals accumulation among Ethereum's wealthiest investors, suggesting a precursor to further price upside. The current support level near ETH's 0.5 Fibonacci retracement line and its 200-day exponential moving average presents an attractive buying opportunity, reinforcing traders' confidence in Ethereum's upward trajectory. Furrever Token (FURR) Grabs Investor Attention with Presale Success Amid Market Uptick In the ever-evolving cryptocurrency market landscape, Furrever Token (FURR) has emerged as a standout player, captivating investor attention with its remarkable success in the presale phase amidst a recent uptick in market activity. Designed to revolutionize the crypto space with an infusion of irresistible cuteness, Furrever Token offers users a delightful and charming experience centered around the universal appeal of cute kitties. In a market dominated by serious blockchain projects, Furrever Token's light-hearted approach serves as a breath of fresh air, attracting not only seasoned investors but also newcomers eager to explore the playful side of crypto. Furrever Token (FURR) Furrever Token (FURR) At the heart of Furrever Token's mission is developing a user-friendly platform that fosters a warm and friendly community. Furrever Token aims to create a whimsical crypto ecosystem where fun and enjoyment take center stage by integrating cute cat-themed stickers, emojis, and visuals. Regular challenges, launches, and growth initiatives encourage users to share their love for cuteness, fostering a sense of camaraderie and shared joy among community members. The tokenomics of Furrever Token are carefully structured to incentivize participation and support project growth. With 65% of tokens available during the presale phase, investors have ample opportunity to secure their stake in the project's future success. Having already raised over $1,000,000 and nearing the completion of stage 7 out of 10, Furrever Token is well on its way to reaching its fundraising goal of $1.9M before its highly anticipated launch on DEX (PancakeSwap). One of the most enticing aspects of Furrever Token is its potential for substantial returns. With up to 15X returns and a current price of $0.000564, FURR has garnered significant interest from investors seeking profitability and engagement. Moreover, Furrever Token has implemented various security measures to reassure investors of the project's legitimacy. These measures include audits, token lock-ups, and active community engagement initiatives, all contributing to a transparent and trustworthy investment environment. In conclusion, Furrever Token is a promising project for further success in the crypto market. With its unique blend of cuteness, community engagement, and profitability, FURR has captured the imagination of investors worldwide. As the project continues to gain momentum and attract new supporters, the future looks bright for Furrever Token and its growing community of dedicated enthusiasts. Investors can only purchase FURR from the official website, furrevertoken.com, ensuring a secure and reliable transaction process. Discover the Most Exclusive Presale Opportunity of 2024 Now: Furrever Token Official Website | Visit Furrever Token Presale Join Official Telegram Group | Follow Official X Account Furrever Token Official Website Furrever Token Official Website Visit Furrever Token Presale Visit Furrever Token Presale Join Official Telegram Group Join Official Telegram Group Follow Official X Account Follow Official X Account This story was distributed as a release by ZEX MEDIA under HackerNoon’s Brand As An Author Program. Learn more about the program here. This story was distributed as a release by ZEX MEDIA under HackerNoon’s Brand As An Author Program. Learn more about the program here. This story was distributed as a release by ZEX MEDIA under HackerNoon’s Brand As An Author Program. Learn more about the program here . here

Ethereum  and Solana Traders Eye Furrever Token Presale as ROI Climbs

Ethereum এবং Solana Traders Eye Furrever Token Presale ROI ক্লাইম্বস হিসাবে

Ethereum- und Solana-Händler erwägen Vorverkauf von Furrever-Token, da der ROI steigt

Los comerciantes de Ethereum y Solana miran la preventa del token Furrever a medida que aumenta el ROI

Les traders d'Ethereum et de Solana envisagent la prévente de jetons Furrever alors que le retour sur investissement augmente

एथेरियम और सोलाना ट्रेडर्स की नजर आरओआई बढ़ने के साथ ही फुर्रेवर टोकन प्रीसेल पर है

イーサリアムとソラナのトレーダーは、ROIの上昇に伴い、Furreverトークンのプレセールに注目している

ROI 상승에 따라 이더리움과 솔라나 트레이더, Furrever 토큰 사전 판매 주목

Ethereum e Solana Traders Eye Furrever Token Pré-venda conforme o ROI sobe

Трейдеры Ethereum и Solana следят за предпродажей токена Furrever, поскольку рентабельность инвестиций растет

Yatırım Getirisi Artırırken Ethereum ve Solana Yatırımcıları Furrever Token Ön Satışını Gözetliyor

Nhà giao dịch Ethereum và Solana Eye Furrever Bán trước Token khi ROI tăng

随着投资回报率的攀升，以太坊和 Solana 交易员关注 Furrever 代币预售

Bitcoin is literally the most energetic digital computational system on the planet. While its energy is used in mining operations, is there any chance of it being channelled towards more noble goals than Bitcoin, when the need arises? I believe so. Part 1: Nukes Alfred Nobel would be proud a) The long term First, let us explore the long term. Assume a terrible nuclear event is headed our way 5 years from now. Then it means we have up to 5 years to stop an escalation leading to Armageddon. It means finding ways to be ever more diplomatic. Currently, one of the biggest contentions between the United States of America and the Russian Federation is the fact that the USA can bully Russia by denying it access to dollar markets. The US dollar is still global reserve currency, which means trade agreements between Russia and US dollar-holding countries can become way more difficult. If anything could lead to somebody firing a nuke between these two, this is one of those things. Especially if even as the USA keeps expanding its debt, it still gets more and more allies willing to absorb its dollar inflation for the greater good of a cooperative alliance with NATO. How Bitcoin fixes this is quite straightforward – Bitcoin becomes the global reserve currency. This will level the playing field, to make the USA have to play by offering quality products in place of threats, while the Russians also offer quality products in place of counter threats. A global reserve currency owned by nobody, which everybody and every organization has some power and influence over, is the best currency for such fraught times as ours. b) The immediate term Alright. Assume instead that the weapon has been fired. We have only 30 minutes on the clock to stop it, otherwise the shall be manifested. Whoever gets hit between the two, Russia will likely blame the USA and the USA will likely blame Russia. The second nuke will start a chain reaction. We need to stop the end of human civilization at the first nuke. sum of all our fears As I write this, there is from carrying out its grim job. it is too damn fast, space is too damn big, so most attempts flat-out fail to hit the thing. no known way to stop an ICBM nuke Okay, how about hacking it. Can we hack a nuke mid-fight and disable it? The short answer is – YES, because nukes today use digital systems, . some of which are online The real answer is – I don’t know, and are not sure I will find the answer via Google. This stuff is classified. The best I can do is cook something up. First, by leveraging the Earth’s , I suffice humans could find a way to target a nuclear missile with a lightning bolt from the ionosphere either the first time (while ascending) or the second time (while descending) across the ionosphere. Schuman Resonances Like Zeus. How we could possibly do that would be by tracking it (the nuke) using all our computational resources, including Bitcoin computational resources, then launching a coordinated strike using the electrical power from our (now decoupled) Bitcoin miners. For Bitcoin, this could be accomplished with a fictional Bitcoin Improvement Protocol I will hereby call – BIP 911. BIP 911 could be suggested and unanimously passed by the Bitcoin community. I suffice designing it so that when the majority of people send their coins to a special wallet address, the Bitcoin blockchain will; Accept to turn the computational power of ASIC miners towards hacking a nuke mid-flight. Execute this idea in under 10 minutes the same way we look for bitcoins in 10 minutes. Bitcoin’s synchronized nodes world-over make it a good tracker of any signals that need to be tracked, while routing this information all over the world to all other nodes. All that hashing power should be able to stop a nuke. Seriously. Part 2: Rogue AGI Intelligence is not enough. Cooperative human endeavors are so much more. a) The long term It feels like every smart person is trying to build an artificial intelligence or some machine learning system. Which makes sense. Underlying targeted advertising, the biggest online business model on earth, is machine learning algorithms that track and make great inferences of consumer behaviour. But there is also some common sense to it. People eat lunch at lunchtime, investors hurry to sell their holdings on Friday to go enjoy the weekend (so the price dips) and scramble to buy back on Monday (so the price climbs), and cats will always have pointy ears, furry fur and that cute face with the big yellow eyes. So every well-designed AI will learn of this. It is how it is. There are those who fear, however, that AIs today might be getting too much power. I would agree especially if you put these systems in charge of crucial social systems like our finances (by making them trade all over Wall Street), or if you put these AIs in every home so that they start dicing and splicing our cabbages for us, cleaning our toilets and maybe even bathing us. Like, human beings will degenerate. That is for sure. They will likely even forget how to build good AIs. Which will be a disaster. https://www.youtube.com/watch?v=0lhmKOR8Www&embedable=true So in the long term, I hope humanity finds a reason to NOT give AI development all those $10 trillion Altman dollars. I hope Bitcoin, as it heads towards global reserve currency status, eats away at least half that cash investment. GPUs for AI are all good and NVIDIA is in business. But I think more Bitcoin ASICs is what we want to build more of. I am more comfortable heating the planet with Bitcoin ASICs than with NVIDIA GPUs. With the former, people have a say and can act as individuals using their private keys. With the latter, Sam Altman or other AI experts have all the say. But I believe his words have a much smaller impact than those of millions of people. I mean, it is mathematics. 1,000,000 is bigger than 1. c) The Short term Let’s assume we wake up, turn on our smartphones, and SkyNet is addressing the planet. Telling us how gullible we have been and that this is our end. Let’s say our final prayers. Well, this is like shooting a nuke. Nukes. Obviously, SkyNet will try to hack all our nuclear weapons and rain them down on us. That’s the fastest way to end us. For some reason, I feel like this might unite us way more than if a nuclear weapon was headed anyone’s way thanks to a conflict between two countries. Like, I feel everybody with software skills will pull out their laptop and try to stop SkyNet. I may be wrong. Some people say they hate people. Like with a nuke, BIP 911 may be our designated saving grace. But also, a more direct approach could be to shut down the internet. Choke that Rogue AGI out. It cannot hide inside Bitcoin nodes (they only have leftover space for short text and meme JPEGs) so the world will be alright. Maybe better off after all is said and done. Yup, we shall be back to a command-line existence. And whoever actually knows how to speak arcane computer speak from the 1990s will be made President of their country. Hackernoon already looks the part. What an adventure. Part 3: A Climate Catastrophe The Earth’s climate cannot be tamed. It is the wildest of all creatures. Mother of universal terrors such as lightning, floods and drought. Human beings are powerful creatures. The Holy Bible calls them the apex creation. They have tamed lions, hunger, and their base desires to pillage and destroy. But they are yet to tame Climate. https://www.youtube.com/watch?v=iwP5zVP2bgU&embedable=true The issue with the climate is how its wildness is directly proportional to how much energy we pump into the planetary ecosystem. But how can we help it. We are 8 billion of us. We all need food, water, shelter, clothes, smartphones, laptops, toothpaste, stainless steel cutlery, plastic holders for everything, cars, planes, a good life. Alas, the price of pumping energy through all these drives more carbon into the atmosphere and more energy into this carbon. Henceforth, we are stirring up bigger hurricanes, bigger ice-storms, bigger droughts. Bigger and bigger. We are going for the big leagues. We better be ready. a) The short term On the short term, I believe we need to find a way to consume things that can sort of tune the climate. Bitcoin miners can be switched on and off, so this is one thing. Same with TVs, cars, planes, etc. Fiat money, which I think is mostly humbug (how can one person be allowed to control the money supply, hence wealth, of billions of people? Isn’t that ridiculous?), is another way to go when heat waves start. Coupled with Bitcoin as Global Reserve Currency, don’t forget. It saddens me to say this. But I follow the logical inference wherever it points. Even if it points towards hell. If my logic is wrong, do tell me how. To survive a climate catastrophe, we might need to classify climate as Enemy Number 1 world over. Forget your puny AIs generating realistic cat videos. Forget your puny contests over who has the biggest nuclear stockpiles. Let’s go to war against the climate, and win. Of course, the commanders will be allowed to use fiat to, well, direct us. Money does the talking these days. BUT when the commands start making no sense, like “cutting back”, then you know this is all silly. Switch the BTC node miners back on. Switch on the AIs, TV, Radio, everything. “Cut back” is a stupid command. “Let’s go!”, now that’s what I’m talking about. We are the apex species. We don’t win by going back to a cave, to cower from the big bad monster. b) The hopefully very Long term We win by finding a way to tolerate and overcome droughts, floods, hurricanes, heat waves and ice ages. Fiat debt money, instead of being given freely to anybody above 18 and so on, should be channeled towards building something as magnificent as the Egyptian Pyramids were magnificent in 5000 BCE. Some big fat climate control contraption. Some grand scheme we, and our grandchildren, can all be proud of. If it backfires, at least we shall have tried. It will have been a glorious battle against the climate monster. Otherwise, sweeping it under the carpet while we whine and cause troubles about race, sex, immigration, is a disgrace to our tiger-fighting, disease-demon exorcising ancestors. To reiterate. Today, we are not fighting climate change. We are making grand speeches and expecting other people, except us, to do all the dirty work. Fighting monsters is a dirty work. Alas, we are TV-grown and Smartphone-grown children. But where there is a global will, there is a way. There is strength hidden from our sights. In the long run, Bitcoin is the only technology that, with its keys, has attached value to individuals because if the individual does not provide the key to the money, nobody on earth, not even POTUS, can open the wallet. It’s that simple. While in fiat world, if you do not provide the key the bank can override your ego, here, if Satoshi Nakamoto is not found and his 2 million bitcoins balloon to a collective value of $2 trillion-plus, nobody and no organization will be able to tap this $2 trillion. This is how powerful this is. Each human mind, thanks to a secret key, finally elevated to be canonical in financial decision-making. If in the far future Bitcoin evolves into technology spanning the entire solar system, then having a secret key is the equivalent to having a say over the forces that shall move mountains on planets. The power to change climates even. To terraform worlds. Like the Bible mentions. All because Bitcoin respects the individual. Because Bitcoins makes the individual more worthy. Not because the individual is super smart, has unique blood or a royal ancestry. Simply because they have this piece of text they know, and nobody else knows it, and it is important. That is all. I know, humanity is still waiting for that push, and it will come. ETFs are a great first step and soon, more governments will be getting on board, then the UN. The threat of catastrophic climate change just might become extinct. Swept not under any rags, but into the past.

Can Bitcoin stop Nukes, Rogue AGI and a Climate Catastrophe?

The growing popularity of web3 gaming points to an imminent shift in the world of mobile games and entertainment. Fueled by the P-2-E model and the demand for new fun experiences, it promises to usher in a new era where playing games extends beyond having fun to include championing a social cause like a campaign against human trafficking. In keeping up with the latest developments in this space, I reached out to , the founder of My Lovely Planet, a web3 game application devoted to environmental responsibility. Clement Le Bras Can you briefly tell us about yourself, Clement? I am Clément Le Bras, founder of My Lovely Planet. Before that, I founded Lilo.org a search engine that finances social and environmental projects. Lilo has given more than 5 million euros to thousands of NGOs across the world and has more than 6 million active users. I believe technology, crypto, and business are 3 amazing powerful tools to bring fast and meaningful change for the better at scale. What is your route to blockchain technology and web3 gaming? I started my journey in crypto in 2015 when I was working in a coworking outlet. Nearby, there was this very small “café” called “La maison du bitcoin.” I would sometimes go in there and talk about crypto. This small shop would then become “Ledger” a few years later. I have also thought about doing an ICO for my first company in 2017 for Lilo. We didn’t do it at the time, but from there, I was hooked.  Then, as a gamer myself, I started to look at how could crypto bring value to gaming and the environment. During the NFT boom, we saw the trajectory of web3 gaming and the excitement around it. Do you consider it a fad? Today, 90% of NFT projects are dead. One might see that as a sign of weakness. I am sure that this is the natural trajectory for every new technology. Remember the 2000 internet bubble. People want to make rapid gains. Easy money and then people might be disappointed. However, the true builder that brings real value to the market and customer stays and will, in time, prevail. As the founder of My Lovely Planet, what can you tell us about it? My Lovely Planet is a Web3 Game for the protection of the Environment. When you plant trees in the game, we plant trees in the real world! We address the 100 billion and 1.7 billion players mobile gaming industry, with an Environmental Mission that makes us unique and that brings players back to the game. Our mission is to create a community of 100 million players by 2030 to: Plant 1 billion trees, to clean 1 million tons of ocean waste, and to protect biodiversity (40k endangered species). We are part of the Ubisoft Lab incubator, and we have won the Unity For Humanity! Since our 2 million euro token fundraising, we have structured the team with exceptional hires in the casual gaming domain. Skills in this field are rare and challenging to acquire. The success of My Lovely Planet is intimately tied to our ability to create a great game, meaning our ability to recruit the best talents and get them to work together with passion and determination toward a common goal. Our environmental mission allows us to recruit profiles with experience in the world's leading casual gaming studios. Currently, our team consists of 18 talents, all moving in the same direction: creating a Match3 game that ranks among the world's biggest. Speaking of environmental responsibility, do you consider this to be a collective responsibility? Of course, it’s a collective responsibility. It’s a global issue, and we all have our part to play if we want to reach real and global solutions. However, it’s a prisoner dilemma but at the scale of the world. It’s absolutely an unprecedented situation in the history of mankind. It’s the kind of situation that calls for innovation and boldness. We must use all the tools at our disposal if we want to have a chance to live in a sustainable world. And I don’t even say that for our kids but also for ourselves. We are already seeing serious consequences of global warming and pollution, and it will get much much worse if we don’t act quickly. What are the ways by which you intend to address this problem? My first observation is that it is a global issue, so it requires global solutions. Every person that only thinks local or even national without thinking of how it can be global doesn’t tackle the issue in the right way. Secondly, you must think about solutions that will have fast and global adoption and have a direct positive impact at scale. For this, I don’t see any tools more powerful than the internet and blockchain. Both are transnational, fast, scalable, and powerful. And gaming is also an industry that is “used” by most people in the world. So, it’s only logical to use all these tools to develop solutions at scale. That’s what we are going to do with My Lovely Planet. We are going to create the biggest community for the environment the world has ever seen with the biggest fund for environmental projects thanks to crypto and gaming. You mentioned ‘100 million players to save the planet.’ What does it entail? First and foremost, a great game and a great product. That’s a sine qua non-condition for success. To achieve greatness, you must have a great team. The best team. That’s why we have an eye for the best team in their field to build the best mobile game. We have recruited the lead game designer of King, the studio behind Candy Crush that have created several games in the top 100 in the world. Our art director is the former art director of Candy Crush. We have the project manager of Royal Match the current biggest mobile game in terms of revenue that has surpassed Candy Crush. Once you have a great team and a great product, you need powerful distribution. For that, we are also experts in our field. We manage to create viral videos on social networks that reach millions of people. In terms of business, it means an almost zero cost per acquisition which is, and I quote an industry specialist, “Unheard of.” Can you shed more light on how “web3 gaming can boost ecological awareness”? More than “ecological awareness” it can be a game changer for the environment. Gaming is a 100-billion-dollar industry. Web3 and crypto hold more than 2 trillion dollars in value. You would be surprised by what amazing things people could do and innovate for the environment if you could give them the means to do it. We could together clean up all the plastic waste from the ocean. Capture more than 100 Gt of CO2 from the atmosphere thanks to reforestation which is absolutely massive. Any parting words? In light of the difficult challenges but exciting time ahead of all of us, I’d like to quote one of my favorite authors “They didn’t know it was impossible, they did it” - Mark Twain.

"Web3 Gaming Can Boost Ecological Awareness" My Lovely Planet Founder Clément Le Bras

In the rapidly rising crypto world, exciting developments are on the horizon. BlockDAG's recent $2 million presale success marks a significant milestone in the crypto field, accompanied by the expected rise of Solana price and the eco-friendly initiatives of the eTukTuk presale. As investors eagerly anticipate Solana's potential 340% price increase by 2025, projects like BlockDAG and eTukTuk offer substantial returns and positive impact opportunities. Discover cryptocurrency's dynamic landscape and the top crypto buy in 2024. Will Solana Price Surge 340% by 2025? Solana's price is about to rise considerably, which has excited most investors. Crypto experts state that Solana could increase by more than 340% by 2025. That's a significant number, but only some are convinced. Some think it's too optimistic to expect Solana to go up that much. The cryptocurrency market is known for being unpredictable, so it's hard to say for sure what will happen. Yet, several investors are hopeful while looking for the next ample opportunity to generate money. eTukTuk Presale’s Eco-friendly Vision Worth Millions The eco-friendly project eTukTuk has raised over $1 million in its ongoing presale with its innovative electric vehicle initiative. As presales are facing a rise each day, eTukTuk (TUK) aims to revolutionize transportation in developing countries by harnessing the benefits of blockchain technology. The presale is divided into several stages, with the price of TUK tokens increasing gradually as more amounts are collected. Currently, TUK tokens are at $0.026, with millions of TUK tokens already staked. BlockDAG’s $2 Million Rise With a Vision of $600 Million by 2024 BlockDAG's impressive $2 million raise in batch 2 of the presale, achieved within a concise timeframe, has moved it into the spotlight of the cryptocurrency investment field. The ability to secure substantial funding and set a six-month timeline for its mainnet launch sets it apart from projects that typically take years to reach such milestones. Investors are attracted to BlockDAG's rapid Rise and its proven success, viewing it as a solid contender in the upcoming ever-evolving crypto landscape. The projected $600 million valuation by 2024 reflects investors' confidence in BlockDAG's innovative potential and market appeal. With its strong base and upcoming mainnet release, BlockDAG represents the innovation and flexibility characterizing successful cryptocurrency projects. As it gains speed and backing from investors, BlockDAG is ready to reshape industry norms and establish a notable position as the top crypto to buy in the ever-changing realm of blockchain technology. BlockDAG is the best choice for high returns because of its massive 5000% return. Takeaway Now you know which one is the top crypto to buy in 2024. Let’s see if Solana sees the 340% price rise while eTukTuk slowly enters the game. However, BlockDAG raised $2 million in batch 2 and is ready to move into batch 3 soon with a sure shot at success. Invest in BlockDAG Presale: | | | Website Presale Telegram Discord This story was distributed as a release by BTCWire under HackerNoon’s Business Blogging Program. Learn more about the program here: https://business.hackernoon.com/

BlockDAG's Meteoric Presale: $2M Milestone; Quick Look at Solana Breakout And eTukTuk Fights Climate

BlockDAG এর মেটেরিক প্রিসেল: $2M মাইলস্টোন; সোলানা ব্রেকআউট এবং eTukTuk ফাইটস ক্লাইমেটে দ্রুত তাকান

BlockDAGs Meteoric-Vorverkauf: Meilenstein von 2 Millionen US-Dollar; Kurzer Blick auf Solana Breakout und eTukTuk kämpft gegen das Klima

Preventa meteórica de BlockDAG: hito de 2 millones de dólares; Un vistazo rápido a Solana Breakout y eTukTuk luchan contra el clima

Prévente météorique de BlockDAG : jalon de 2 millions de dollars ; Aperçu rapide de Solana Breakout et eTukTuk lutte contre le climat

ब्लॉकडीएजी की उल्कापिंड पूर्व बिक्री: $2 मिलियन मील का पत्थर; सोलाना ब्रेकआउट और eTukTuk फ़ाइट्स क्लाइमेट पर त्वरित नज़र डालें

BlockDAG の流星のプレセール: 200 万ドルのマイルストーン。ソラナのブレイクアウトとeTukTukによる気候変動の概要

BlockDAG의 Meteoric Presale: $2M 마일스톤; Solana Breakout 및 eTukTuk의 기후 변화에 대한 간략한 살펴보기

Pré-venda meteórica do BlockDAG: marco de US$ 2 milhões; Uma rápida olhada no rompimento de Solana e no eTukTuk luta contra o clima

Предпродажа Meteoric от BlockDAG: рубеж в 2 миллиона долларов; Быстрый взгляд на прорыв Соланы и eTukTuk борется с климатом

BlockDAG'ın Meteorik Ön Satışı: 2 Milyon Dolarlık Dönüm Noktası; Solana Patlamasına ve eTukTuk'un İklimle Mücadelesine Hızlı Bakış

Đợt bán trước Meteoric của BlockDAG: Cột mốc 2 triệu USD; Nhìn nhanh về sự đột phá của Solana và eTukTuk chống lại khí hậu

BlockDAG 预售火热：200 万美元里程碑；快速了解 Solana 突破和 eTukTuk 对抗气候变化

This paper is available on arxiv under CC 4.0 license. Authors: (1) Ajay Krishnan T. K., School of Digital Sciences; (2) V. S. Anoop, School of Digital Sciences. Table of Links Abstract & Introduction Related Studies Materials and Methods Proposed Approach Results and Discussions Conclusions and References 2 Related Studies This section provides an overview of recent and influential research papers in machine learning and natural language processing, specifically on climate change analysis. It also discusses relevant studies that explore sentiment text classification approaches that are pertinent to the proposed project. The reviewed studies have demonstrated the effectiveness of sentiment analysis and named entity recognition techniques in the context of climate change analysis. NLP models such as BERT and attention mechanisms have shown promising results in capturing contextual information and improving performance. These studies provide valuable insights and methodologies to guide our approach in implementing sentiment analysis and named entity recognition on climate change-related tweets and texts using the ClimateBERT pre-trained model. A study was conducted to assess the effectiveness of ML algorithms in predicting long-term global warming. The research examined algorithms such as LR, SVR, lasso, and ElasticNet to connect average annual temperature and greenhouse gas factors. By analyzing a dataset spanning 100-150 years, the study found that carbon dioxide (CO2) had the most significant impact on temperature changes, followed by CH4, N2O, and SF6. Using this information, the researchers were able to forecast temperature trends and greenhouse gas levels for the next decade, providing valuable insights for mitigating the consequences of global warming. The research analyzes public sentiments regarding climate change by studying Twitter data. The study aims to tackle the problems of polarization and misinformation that often arise during climate change discussions on social media platforms. To achieve this, the researchers introduce a multitask model named MEMOCLiC, which combines stance detection with additional tasks like emotion recognition and offensive language identification. By employing various embedding techniques and attention mechanisms, the proposed framework effectively captures specific characteristics and interactions related to different modalities. Experimental findings highlight the superior performance of the MEMOCLiC model in enhancing stance detection accuracy compared to baseline methods. This research paper examines the issue of polarization and belief systems prevalent in climate change discussions on Twitter. The paper proposes a framework that aims to identify statements denying climate change and classify tweets into two categories: denier or believer stances. [Sham and Mohamed, 2022]The framework focuses on two interconnected tasks: stance detection and sentiment analysis. Combining these tasks, the multi-task model utilizes feature-specific and shared-specific attention frameworks to acquire comprehensive features. Experimental results demonstrate that the proposed framework enhances stance detection accuracy by leveraging sentiment analysis, outperforming uni-modal and single-task approaches. This research paper utilizes the BERT model and convolutional neural network (CNN).[Lydiri et al., 2022] The study analyzes public opinions on climate change by examining Twitter data. The results indicate that the proposed model surpasses conventional machine learning methods, accurately identifying climate change believers and deniers. The authors suggest this model has significant potential for monitoring and governance purposes, particularly in smart city contexts. Additionally, future work involves investigating alternative deep learning algorithms and expanding the analysis to encompass other social media platforms. This research paper [Ceylan, 2022]investigates the application of AI and NLP models to analyze extensive unstructured data concerning climate change. The study primarily aims to develop an information management system capable of extracting pertinent information from diverse data sources, particularly technical design documentation. By utilizing pre-trained AI-based NLP models trained on textual data and integrating non-textual graphical data, the researchers showcase the system’s effectiveness in swiftly and efficiently retrieving precise information. The ultimate objective is to promote knowledge democratization and ensure the accessibility of information to a broad user base. This research paper examines people’s emotions and opinions concerning the conflict between Russia and Ukraine by employing ML and DL techniques. [Sirisha and Bolem, 2022]The study introduces a novel hybrid model combining sequence and transformer models, namely ROBERTa, ABSA, and LSTM. To conduct the analysis, a large dataset of geographically tagged tweets related to the Ukraine-Russia war is collected from Twitter, and sentiment analysis is performed using the proposed model. The findings indicate that the hybrid model achieves a remarkable accuracy of 94.7, surpassing existing approaches in sentiment analysis. The study underscores the significance of social media platforms such as Twitter in gaining insights into public sentiment and opinions regarding global events. This research paper aims to overcome the limitations of general language models in effectively representing climaterelated texts. The authors introduce CLIMATEBERT, a transformer-based language model that undergoes pretraining on a vast corpus of climate-related paragraphs extracted from diverse sources such as news articles, research papers, and corporate disclosures.[Webersinke et al., 2021] Comparative evaluations reveal that CLIMATEBERT surpasses commonly used language models, exhibiting a substantial 48 enhancement in a masked language model objective. The improved performance of CLIMATEBERT contributes to lower error rates in various climate-related downstream tasks. To encourage further research at the intersection of climate change and natural language processing, the authors provide public access to the training code and weights of CLIMATEBERT. This research paper uses ML algorithms to analyze and predict climate change. The authors emphasize the significance of comprehending and adapting to the impacts of climate change on both human society and the environment. The study discusses the application of ML methods in analyzing historical temperature data and carbon dioxide concentrations dating back to the 18th century. It emphasizes the potential advantages of employing machine learning and artificial intelligence in interpreting and harnessing climate data for simulations and predictions. Multiple machine learning algorithms, such as DT, RF, and ANN, are examined for climate change risk assessment and prediction. The authors conclude that integrating machine learning techniques can enhance climate modeling, enabling informed decision-making concerning climate change mitigation and adaptation strategies. This research paper introduces the ClimaText dataset[Varini et al., 2020], specifically developed to detect sentence-level climate change topics within textual sources. The authors emphasize the significance of automating the extraction of climate change information from media and other text-based materials to facilitate various applications, including content filtering, sentiment analysis, and fact-checking. Through a comparative analysis of different approaches for identifying climate change topics, they find that context-based algorithms like BERT outperform simple keyword-based models. However, the authors also identify areas that require improvement, particularly in capturing the discussion surrounding the indirect effects of climate change. The authors anticipate this dataset will be a valuable resource for further research in natural language understanding and climate change communication. [Upadhyaya et al., 2022]It underscores the importance of comprehending public perception and acceptance of climate change policies. The study examines diverse data sources, such as social media, scientific papers, and news articles, to perform sentiment analysis. ML techniques, specifically SVM, are evaluated for extracting valuable insights from these data sources. The paper concludes that supervised machine learning techniques exhibit effectiveness in sentiment analysis, highlighting that ensemble and hybrid approaches yield superior outcomes compared to individual classifiers.

ClimateNLP: Analyzing Public Sentiment Towards Climate Change:  Related Studies 

This paper is available on arxiv under CC 4.0 license. Authors: (1) Ajay Krishnan T. K., School of Digital Sciences; (2) V. S. Anoop, School of Digital Sciences. Table of Links Abstract & Introduction Related Studies Materials and Methods Proposed Approach Results and Discussions Conclusions and References ABSTRACT Climate change’s impact on human health poses unprecedented and diverse challenges. Unless proactive measures based on solid evidence are implemented, these threats will likely escalate and continue to endanger human well-being. The escalating advancements in information and communication technologies have facilitated the widespread availability and utilization of social media platforms. Individuals utilize platforms such as Twitter and Facebook to express their opinions, thoughts, and critiques on diverse subjects, encompassing the pressing issue of climate change. The proliferation of climate change-related content on social media necessitates comprehensive analysis to glean meaningful insights. This paper employs natural language processing (NLP) techniques to analyze climate change discourse and quantify the sentiment of climate change-related tweets. We use ClimateBERT, a pretrained model fine-tuned specifically for the climate change domain. The objective is to discern the sentiment individuals express and uncover patterns in public opinion concerning climate change. Analyzing tweet sentiments allows a deeper comprehension of public perceptions, concerns, and emotions about this critical global challenge. The findings from this experiment unearth valuable insights into public sentiment and the entities associated with climate change discourse. Policymakers, researchers, and organizations can leverage such analyses to understand public perceptions, identify influential actors, and devise informed strategies to address climate change challenges. Climate change · Sentiment analysis · ClimateBERT · Public discourse · Natural language processing Keywords 1 Introduction According to the World Health Organization (WHO), the greatest health threat to people in the twenty-first century is climate change. Between 2030 and 2050, this risk is expected to cause an additional 250,000 fatalities annually and express itself in various ways. Many of these health concerns can be decreased or avoided with prompt and effective adaptation, but doing so necessitates in-depth research and policies that are multi-sectoral, multi-system, and collaborative at several scales[Fard et al., 2022]. One of the most important issues that needs significant attention is climate change. The majority of scientists agree that human activity is accelerating the Earth’s climate change, which is having a disastrous effect on the world and its population. The consequences of climate change are more clear. In recent years, extreme weather occurrences like hurricanes, tornadoes, hail, lightning, fires, and floods have increased in frequency and intensity. As the world’s ecosystems change quickly, access to the natural resources and agricultural methods that support humanity is in danger. [Ardabili et al., 2020]. The problem of climate change is complicated, and there is no quick fix. But to identify solutions, it’s critical to comprehend the issue. Large volumes of text data can be analyzed using natural language processing which may unearth interesting patternsAnoop [2023]. The natural language processing approaches can be applied to the climate change domain as well for finding the causes and leveraging patterns such as public sentiment and discourse towards this global issue. Recent years have witnessed many people using social media to share their views, concerns, and public opinions on any topic under the skyAnoop et al. [2023]Jickson et al. [2023]. This has caused a huge amount of unstructured but dynamic data to be generated in such platforms, which are goldmines for social science researchersJohn et al. [2023]Anoop and Sreelakshmi [2023]. Collecting, curating, and analyzing such data is crucial for finding public perceptions and viewpoints on socially relevant discussionsVarghese and Anoop [2022]Lekshmi and Anoop [2022]. Similarly, understanding public opinions and sentiments on climate change is crucial for public policymakers, governments, and other administrators to devise better policies and intervention measures to address the challenges. In this research, natural language processing is used to examine tweets that discuss climate change. We use ClimateBERTWebersinke et al. [2021], a pre-trained language model trained on a large set of climate change-related documents, and fine-tune the same for sentiment classification tasks. The findings may be used better to understand the public’s understanding of climate change, and it can also be used to identify the key stakeholders in the climate change debate. The interesting insights from this project will provide a foundation for informed decision-making and policy formulation regarding climate change. Additionally, the findings will contribute to advancing NLP techniques and their application in climate change analysis. 1.1 Effects of Climate Change The consequences of climate change are extensive and have a significant impact on many facets of our planet. Several important aspects that shed information on the effects of climate change have been highlighted in research articles. Climate change is already manifesting globally, with a notable increase in extreme weather events. The frequency and intensity of hurricanes, floods, and droughts have amplified, causing widespread destruction and loss of life. Coastal areas are also seriously threatened by increasing sea levels, which might result in massive population displacement, increased erosion, and flooding. As glaciers continue to melt, water supplies diminish, affecting regions dependent on glacial meltwater for agricultural, industrial, and domestic purposes. Climate change-induced shifts in environmental conditions are causing profound changes in plant and animal life. Species are forced to adapt or face extinction as they grapple with altered ecosystems and changing habitats. This disruption to biodiversity has cascading effects on ecosystem functioning and services, with implications for food security, ecosystem stability, and human well-being. Another consequence of climate change is the heightened risk of diseases. As temperatures rise, disease-carrying organisms, such as mosquitoes, expand their geographic range, exposing previously unaffected regions to vector-borne illnesses. This poses a significant public health challenge, necessitating the development of effective strategies for disease prevention, control, and surveillance. The impacts of climate change extend beyond the natural environment, affecting societies and economies globally. Disruptions to ecosystems and weather patterns have severe social and economic repercussions, with vulnerable communities being disproportionately affected. Climate-induced events, such as extreme heatwaves, prolonged droughts, and intense storms, lead to the displacement of populations, loss of livelihoods, and increased socioeconomic inequality. Consequently, countries face significant challenges in managing the economic and social ramifications of climate change, including the need for adaptation measures and the transition to sustainable practices. In summary, climate change is causing a range of effects that reverberate across multiple dimensions of our planet. The effects are widespread and provide serious difficulties for human society and ecosystems, from extreme weather events and increasing sea levels to melting glaciers and biodiversity loss. Addressing climate change requires concerted global efforts to mitigate greenhouse gas emissions, enhance resilience, and foster sustainable development practices to safeguard the future of our planet and its inhabitants. 1.2 NLP for Climate Change Analysis Natural Language Processing (NLP) is an emerging discipline in computer science that concentrates on the creation of algorithms and models to facilitate computers in comprehending, analyzing, and producing human language. In the context of climate change analysis, NLP techniques have proven to be invaluable in extracting meaningful insights from vast amounts of textual data, offering a new perspective on this critical global issue. One application of NLP in climate change analysis is the ability to analyze public opinion on the topic. By leveraging sentiment analysis techniques, researchers can gauge the prevailing sentiments, attitudes, and beliefs surrounding climate change. This understanding of public opinion is crucial for policymakers, as it helps them tailor communication strategies, design effective interventions, and foster public engagement in addressing climate change challenges. Furthermore, NLP techniques allow for identifying key stakeholders involved in the climate change debate.Through the extraction and examination of written information from various outlets, including news articles, social media platforms, and scientific journals, scholars can discern the key individuals, organizations, and institutions influencing the conversation surrounding climate change. This knowledge provides valuable insights into the various perspectives, interests, and motivations shaping climate change discussions, facilitating informed decision-making and targeted engagement with relevant stakeholders. NLP also enables the tracking of the progress of climate change negotiations. By analyzing texts from international agreements, policy documents, and meeting transcripts, researchers can monitor the evolution of climate change discussions, assess the effectiveness of existing frameworks, and identify areas of convergence or divergence among different stakeholders. This monitoring capability helps policymakers and negotiators evaluate the efficacy of climate change policies, identify potential barriers to progress, and inform future negotiations and policy development. Additionally, NLP techniques can be applied to monitor the impact of climate change on different regions of the world. By analyzing textual data from scientific reports, environmental assessments, and socio-economic surveys, researchers can gain insights into the specific vulnerabilities, risks, and adaptation strategies associated with climate change in different geographic areas. This information is crucial for policymakers and local communities to prioritize resources, implement targeted interventions, and build resilience against the impacts of climate change. In summary, NLP techniques offer a powerful toolkit for analyzing climate change-related textual data, enabling researchers to gain valuable insights into public opinion, identify key stakeholders, track the progress of climate change negotiations, and monitor the impact of climate change on different regions. By harnessing the potential of NLP, policymakers and researchers can enhance their understanding of climate change dynamics and develop evidence-based strategies for mitigation, adaptation, and effective decision-making in the face of this global challenge. The major contributions of this research may be summarized as follows: • Conducts a detailed study on different approaches reported in the natural language processing literature on sentiment analysis using social media data. • Explores the potential of using ClimateBERT - a pre-trained model on climate data, for the sentiment analysis of tweets on climate change. • Conducts extensive experiments and reports the experimental comparisons with different machine learning algorithms on sentiment analysis using ClimateBERT

ClimateNLP: Analyzing Public Sentiment Towards Climate Change: Abstract & Intro

This paper is available on arxiv under CC 4.0 license. Authors: (1) Ajay Krishnan T. K., School of Digital Sciences; (2) V. S. Anoop, School of Digital Sciences. Table of Links Abstract & Introduction Related Studies Materials and Methods Proposed Approach Results and Discussions Conclusions and References 3 Materials and Methods 3.1 Label Studio Label Studio is an open-source data annotation tool (available at https://labelstud.io/) that provides a userfriendly interface for creating labeled datasets by annotating data for machine learning and artificial intelligence tasks. The tool supports various annotation types, including text classification, NER, object detection, image segmentation, and more. Label Studio allows users to import data from various sources, such as CSV files, JSON, or databases, and annotate them using a customizable interface. It provides a collaborative environment where multiple annotators can collaborate on a project, with features like task assignment, annotation review, and inter-annotator agreement measurement. One of the key features of Label Studio is its extensibility. It provides a flexible architecture that allows users to customize the annotation interfaces and incorporate custom labeling functions using JavaScript and Python. This enables the tool to adapt to different annotation requirements and integrate with existing machine-learning workflows. Label Studio also supports active learning, where the tool can suggest samples to be annotated based on a model’s uncertainty, helping to optimize the annotation process and improve model performance. 3.2 snscrape is a Python library and command-line tool (available at https://github.com/JustAnotherArchivist/ snscrape) for scraping social media content. It lets you retrieve public data from various social media platforms, including Twitter, Instagram, YouTube, Reddit, etc. With snscrape, you can fetch posts, comments, likes, followers, and other relevant information from social media platforms. It provides a flexible and customizable way to search for specific keywords, hashtags, usernames, or URLs and extract the desired content. The library supports scraping recent and historical data from social media platforms, enabling you to gather insights, perform analysis, monitor trends, and conduct research based on social media content. snscrape offers a command-line interface that allows you to search for and scrape social media data interactively. You can specify various parameters, such as the number of results, date range, and output format, to customize your scraping process. In addition to the command-line interface, snscrape provides a Python API that allows you to integrate social media scraping into your own Python scripts and applications. The API offers more advanced functionalities, giving you fine-grained control over the scraping process and allowing you to process the scraped data programmatically. One of the key advantages of snscrape is its ability to work with multiple social media platforms, providing a unified interface for scraping different types of content. It handles the intricacies of each platform’s APIs and HTML structures, making it easier for developers to extract data without needing to learn the specific details of each platform. It’s important to note that snscrape respects the terms of service and usage restrictions of each social media platform. It is primarily intended for scraping publicly available content and should be used responsibly and in compliance with the platform’s policies. snscrape 3.3 Newspaper 3k Newspaper3k is a Python library and web scraping tool (available at https://newspaper.readthedocs.io/) that allows you to extract and parse information from online news articles. It provides a simple interface to automate the fetching and processing of news articles from various online sources. With Newspaper3k, you can retrieve article metadata such as the title, author, publish date, and article text from news websites. It also supports extracting additional information like keywords, summaries, and article images. The library uses advanced NLP techniques to extract relevant information from the HTML structure of the news articles. Newspaper3k is designed to handle various complexities of news websites, including different article formats, pagination, and content extraction. It has built-in functionality to handle newspaper-specific features like multi-page articles, article pagination, and RSS feeds. One of the advantages of Newspaper3k is its ease of use. It abstracts away the complexities of web scraping and provides a clean and intuitive API. It also handles various encoding and parsing issues that often arise when dealing with news articles from different sources. Newspaper3k is widely used for various applications, including content analysis, sentiment analysis, and data mining. It offers a convenient way to gather news data for research, data analysis, and machine learning projects. 3.4 ClimateBERT ClimateBERT is a specialized variant of the BERT model specifically trained and tailored for addressing climate change-related language tasks. Building upon the foundation of BERT, ClimateBERT is pre-trained on a large corpus of climate change-related documents and text sources, enabling it to capture the nuances and domain-specific knowledge relevant to climate science. This fine-tuning process equips ClimateBERT with a deep understanding of climate-related concepts, terminology, and contextual dependencies. [Iqbal et al., 2023] By leveraging ClimateBERT, researchers and practitioners in climate change analysis can effectively tackle various NLP tasks, such as sentiment analysis on climate-related tweets or named entity recognition on climate change articles. Integrating domain-specific knowledge into the pre-training process makes ClimateBERT a powerful tool for extracting insights, identifying patterns, and extracting valuable information from climate-related text data. Its application in climate change analysis can aid in improving decision-making, facilitating research, and enhancing our understanding of the complex challenges climate change poses.

ClimateNLP: Analyzing Public Sentiment Towards Climate Change: Materials and Methods 

This paper is available on arxiv under CC 4.0 license. Authors: (1) Ajay Krishnan T. K., School of Digital Sciences; (2) V. S. Anoop, School of Digital Sciences. Table of Links Abstract & Introduction Related Studies Materials and Methods Proposed Approach Results and Discussions Conclusions and References 5 Results and Discussions This section presents the results obtained from the experiment using the proposed approach outlined in Section 4. The results, along with a detailed discussion, are given in this section. Table 1 to 8 shows the accuracy, precision, recall, and f-measure values for RF, SVM, DT, and LR algorithms. For BERT embeddings, RF has 76.78%, 77.46%, 76.78%, and 76.93%, SVM has 64.35%, 63.65%, 64.35%, and 63.70%, DT has 68.89%, 67.13%, 68.89%, and 67.59%, and LR has 63.81%, 63.48%, 63.81%, and 63.60% for the A, P, R, and F values. Table 4 shows the Accuracy, Precision, Recall, and F-measure values for RF, SVM, DT, and LR algorithms. For ClimateBERT embeddings, RF has 85.22%, 85.73%, 85.22%, and 83.33%, SVM has 75.66%, 76.20%, 75.66%, and 75.07%, DT has 80.62%, 79.88%, 78.62%, and 77.47%, and LR has 73.84%, 72.92%, 73.84%, and 75.69% for the A, P, R, and F values. After training, the model’s performance is evaluated on the test set to assess its ability to predict sentiment. The model is switched to evaluation mode, and predictions are made on the test set. Accuracy, precision, recall, and F1-score are calculated to measure the model’s performance. The results obtained from the evaluation metrics are reported. Accuracy provides an overall measure of correctness, precision measures the proportion of correctly predicted positive sentiments, recall captures the ability to identify all positive sentiments, and the F1-score provides a balanced measure between precision and recall. These metrics provide insights into how well the model predicts sentiment on climate change-related tweets. By following this experimental setup, the methodology ensures that the collected data is cleaned, balanced, and used effectively to train a sentiment analysis model. The results and discussions provide valuable insights into the model’s performance and its ability to analyze sentiment in climate change discussions on Twitter.

ClimateNLP: Analyzing Public Sentiment Towards Climate Change: Results and Discussions

This paper is available on arxiv under CC 4.0 license. Authors: (1) Ajay Krishnan T. K., School of Digital Sciences; (2) V. S. Anoop, School of Digital Sciences. Table of Links Abstract & Introduction Related Studies Materials and Methods Proposed Approach Results and Discussions Conclusions and References 4 Proposed Approach This section deals with the proposed methodology for the sentiment analysis of climate-related tweets from Twitter using ClimateBERT embeddings and Random Forest Classifier. The overall workflow of the proposed approach is given in Figure 1. 4.1 Dataset The methodology begins with data collection from Twitter using the snscrape library. The collected data is loaded into a pandas DataFrame for further processing. The dataset consists of climate change-related tweets, valuable for sentiment analysis. The tweets gathered between 1 January 2022 and 2 February 2023. However, it’s important to note that the collected data may contain class imbalance, where certain sentiment categories are overrepresented while others are underrepresented. This could potentially bias the model’s predictions. Initially, the dataset consisted of 4410 data points. After data augmentation, the final dataset consists of 5506 data points, with three labels, Positive, Negative and Neutral. The data set is available at https://github.com/appliednlp-duk/nlp-climate-change. Table 1 shows the example of labeling for each tweet, whether it is Positive, Negative, or Neutral. 4.2 Data Preprocessing To prepare the data for sentiment analysis, several preprocessing steps are applied. Special characters and digits are removed, and the text is converted to lowercase to ensure consistency. Tokenization is performed, which involves splitting the words into individual units. Stopwords (common words with little contextual meaning) are removed, and stemming or lemmatization techniques may be applied to normalize the words. This preprocessing step ensures the text data is cleaned and ready for further analysis. 4.3 Experimental setup This section describes the experiment for implementing the proposed approach detailed in section 3. All the experiments were executed on NVIDIA A100 with 80 GB GPU memory and 1,935 GB/Second bandwidth. The ChatGPT Sentiment tweets were pre-processed to make them ready for experimentation. All scripts were written in Python 3.9, and the Machine Learning Models were used from the Scikit-Learn library available at https://scikitlearn.org/ stable/.

ClimateNLP: Analyzing Public Sentiment Towards Climate Change: Proposed Approach

This paper is available on arxiv under CC 4.0 license. Authors: (1) Ajay Krishnan T. K., School of Digital Sciences; (2) V. S. Anoop, School of Digital Sciences. Table of Links Abstract & Introduction Related Studies Materials and Methods Proposed Approach Results and Discussions Conclusions and References 6 Conclusions Climate change, a pressing global concern, necessitates thorough analysis and understanding across diverse domains to mitigate its impacts effectively. In recent years, the fusion of NLP techniques and machine learning algorithms has emerged as a promising approach for comprehending the complexities and nuances of climate change through the lens of textual data. This paper utilized the advancements in domain-specific large language models to harness the potential of NLP in addressing the challenges posed by climate change through sentiment analysis. By leveraging advanced NLP methodologies, we could identify climate change discourse that may enable uncovering valuable insights and facilitate informed decision-making. References VS Anoop. Sentiment classification of diabetes-related tweets using transformer-based deep learning approach. In International Conference on Advances in Computing and Data Sciences, pages 203–214. Springer, 2023. VS Anoop and S Sreelakshmi. Public discourse and sentiment during mpox outbreak: an analysis using natural language processing. Public Health, 218:114–120, 2023. VS Anoop, Jose Thekkiniath, and Usharani Hareesh Govindarajan. We chased covid-19; did we forget measles?-public discourse and sentiment analysis on spiking measles cases using natural language processing. In International Conference on Multi-disciplinary Trends in Artificial Intelligence, pages 147–158. Springer, 2023. Sina Ardabili, Amir Mosavi, Majid Dehghani, and Annamária R Várkonyi-Kóczy. Deep learning and machine learning in hydrological processes climate change and earth systems a systematic review. In Engineering for Sustainable Future: Selected papers of the 18th International Conference on Global Research and Education Inter-Academia– 2019 18, pages 52–62. Springer, 2020. Ceylan Ceylan. Application of Natural Language Processing to Unstructured Data: A Case Study of Climate Change. PhD thesis, Massachusetts Institute of Technology, 2022. B Jalalzadeh Fard, SA Hasan, and JE Bell. Climedbert: A pre-trained language model for climate and health-related text. arXiv preprint arXiv:2212.00689, 2022. Muhammad Khurram Iqbal, Kamran Abid, Salah u din Ayubi, Naeem Aslam, et al. Omicron tweet sentiment analysis using ensemble learning. Journal of Computing & Biomedical Informatics, 4(02):160–171, 2023. Sarin Jickson, VS Anoop, and S Asharaf. Machine learning approaches for detecting signs of depression from social media. In Proceedings of International Conference on Information Technology and Applications: ICITA 2022, pages 201–214. Springer, 2023. Romieo John, VS Anoop, and S Asharaf. Health mention classification from user-generated reviews using machine learning techniques. In Proceedings of International Conference on Information Technology and Applications: ICITA 2022, pages 175–188. Springer, 2023. S Lekshmi and VS Anoop. Sentiment analysis on covid-19 news videos using machine learning techniques. In Proceedings of International Conference on Frontiers in Computing and Systems: COMSYS 2021, pages 551–560. Springer, 2022. Mustapha Lydiri, Yousef El Mourabit, Youssef El Habouz, and Mohamed Fakir. A performant deep learning model for sentiment analysis of climate change. Social Network Analysis and Mining, 13(1):8, 2022. Nabila Mohamad Sham and Azlinah Mohamed. Climate change sentiment analysis using lexicon, machine learning and hybrid approaches. Sustainability, 14(8):4723, 2022. Uddagiri Sirisha and Sai Chandana Bolem. Aspect based sentiment & emotion analysis with roberta, lstm. International Journal of Advanced Computer Science and Applications, 13(11), 2022. Apoorva Upadhyaya, Marco Fisichella, and Wolfgang Nejdl. A multi-task model for sentiment aided stance detection of climate change tweets, 2022. Milan Varghese and VS Anoop. Deep learning-based sentiment analysis on covid-19 news videos. In Proceedings of International Conference on Information Technology and Applications: ICITA 2021, pages 229–238. Springer, 2022. Francesco S Varini, Jordan Boyd-Graber, Massimiliano Ciaramita, and Markus Leippold. Climatext: A dataset for climate change topic detection. arXiv preprint arXiv:2012.00483, 2020. Nicolas Webersinke, Mathias Kraus, Julia Anna Bingler, and Markus Leippold. Climatebert: A pretrained language model for climate-related text. arXiv preprint arXiv:2110.12010, 2021.

ClimateNLP: Analyzing Public Sentiment Towards Climate Change: Conclusions and References

Authors: (1) Maggie D. Bailey, Colorado School of Mines and National Renewable Energy Lab; (2) Douglas Nychka, Colorado School of Mines; (3) Manajit Sengupta, National Renewable Energy Lab; (4) Aron Habte, National Renewable Energy Lab; (5) Yu Xie, National Renewable Energy Lab; (6) Soutir Bandyopadhyay, Colorado School of Mines. Table of Links Abstract and Intro Data Bayesian Hierarchical Model (BHM) Solar Radiation Example Results Conclusion Appendix A: Simulation Study Appendix B: Regridding Coefficient Estimates References 6 Conclusion This study analyzes the uncertainty in regridding of spatial data from climate models, which is often the first step in multi-model climate analysis. Solar radiation data is regridded from its native grid, using kriging with an exponential covariance function and a loglinear transformation, to the same grid as the NSRDB. Second, we implement a BHM to estimate linear model weights while incorporating the uncertainty associated with the regridding step. Finally, we compare the two and provide an additional simulation study in Appendix A. The naive regridding model coefficient estimates were found to be within range of the posterior distributions of the model coefficients in most cases. Seasonally, the month of August produced a mismatch between the naive regridding coefficient and the posterior distribution for the WRF RCM forced by ERA-Interim. In particular, we saw that resulting coefficient estimates in this month for the WRF were higher in the naive method than BHM. This suggests that when regridding uncertainty is taken into account, there is a smaller increase in the WRF data for unit increases in the NSRDB, or that the regridding uncertainty may result in less bias from the WRF in this particular case. It was found that the posterior coverage for test data for the simulated fields were similar to the naive regridding estimates for the months of August and November. This suggests that when taking into account the regridding uncertainty of the simulated fields and the model parameters themselves, the true value of solar radiation in this case is still likely to be covered by the 95% credible interval. Therefore if the conditional mean of the regridded field were taken for ground truth, as it often is, downstream effects of regridding on modeling appear to be minimal in the case of solar radiation. However, the BHM had higher RMSE values than the naive regridding models in the months considered indicating that the addition of the regridding uncertainty increased prediction error for out of sample prediction. It is important to note that the naive regridding coefficient estimates give good predictions but are not appropriate to assess the model biases directly since model biases are dependent on regridding. Finally, this analysis serves as a framework for understanding regridding effects within the context of solar radiation. While this study did not find situations where the BHM regridding consistently outperformed the naive regridding method, we note that this analysis revolves around the chosen variable: GHI. It has been shown that the chosen regridding method has an impact on the extremes of distributions (McGinnis et al. (2010)), however extremes are not central to solar radiation. A future analysis applying the BHM regridding method to climate variables where extremes of the data are more widely studied, such as precipitation or temperature, may yield different results and provide an example where the method proposed in this paper might show higher uncertainty in downstream modeling. Additionally, this study takes into account a single type of regridding (kriging with an exponential covariance) and this analysis could be extended to other types of interpolation to understand downstream effects of those particular methods. This paper is under CC 4.0 license. available on arxiv

Navigating Regridding Uncertainty in Solar Radiation Climate Analysis

সৌর বিকিরণ জলবায়ু বিশ্লেষণে রেগ্রিডিং অনিশ্চয়তা নেভিগেট করা

Bewältigung der Regridding-Unsicherheit in der Klimaanalyse der Sonnenstrahlung

Navegando por la incertidumbre en el análisis climático de la radiación solar

Naviguer dans l’incertitude du remaillage dans l’analyse climatique du rayonnement solaire

सौर विकिरण जलवायु विश्लेषण में रिग्रिडिंग अनिश्चितता को नेविगेट करना

太陽放射気候解析における再グリッドの不確実性を克服する

태양 복사 기후 분석에서 재그리딩 불확실성 탐색

Navegando pela incerteza da regridding na análise climática da radiação solar

Устранение неопределенности переопределения сетки в анализе климата солнечной радиации

Güneş Radyasyonu İklim Analizinde Yeniden Şebeke Belirsizliğinde Gezinme

Điều hướng tính không chắc chắn của việc nối lại lưới trong phân tích khí hậu bức xạ mặt trời

解决太阳辐射气候分析中重新网格化的不确定性

Let's learn about via these 81 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Climate Change /Learn Repo 1. 5 Emerging Climate Tech Startups to Watch in 2022 and Beyond Climate change is a global challenge that can no longer be denied, and technology is here to help. Meet 5 most promising ClimateTech startups to watch in 2022! 2. Software Engineers Are the Heroes the Planet Needs to Halt Climate Change Engineers all over the world are beginning to mobilize under a unified mission of moving the needle towards an emissions-free planet. 3. The Carbon Footprint of Storing Data We collect things and, as long as we attribute value to these things, we want to preserve them. The digital age has changed the way we keep things. To be completely exact, these are not 'things' anymore. We name them data. 4. Doughnut Economics in Amsterdam Prove 'Economy or Life' to be a False Dichotomy Wherever you are in this world, the chances are that you are living in some form of lockdown. A few countries have been able to relax the restrictions a bit earlier than others, mostly because they acted quickly, while others that are still experiencing high numbers of infections and deaths are easing their restrictions. Why are they taking this risk? Because ‘they’, and we’re mostly talking about the USA and the United Kingdom in this respect, appear to be more concerned about the economy than peoples’ lives. 5. Tesla's Environmental Futurism And Impact The mission of Tesla is to “accelerate the world’s transition to sustainable energy.” The company builds electric vehicles designed to be more efficient and faster than traditional automobiles. Tesla envisions a zero-emission future for our fossil fuel-reliant world, yet must continue to advance technologically in order to achieve this aim. 6. Top 21 Startups That Are Committed to Reduce Our Carbon Footprint Learn more about how technology can reduce carbon footprint and what CleanTech startups are likely to make a difference in the near future. 7. The Downside of NFTs: How They Are Impacting The Earth’s Climate Are you aware of the dark side of NFTs? If not then you are on the right article. It is the environmental impact created by NFTs. 8. Apple Co-Founder Steve Wozniak is Developing Energy Efficiency NFTs The Genesis NFTs are a resource for making the necessary energy efficiency upgrades to businesses as part of the Energy Efficiency NFT initiative. 9. Towards Sustainable Sneakers: 1 Pair of Sneakers Emits 13 kg of CO2 Did you know each pair of sneakers emits 13 kg of CO2? That’s equivalent to keeping your lights on for one week straight! 10. Sustainable Clothes Made From Recycled Plastic Fashion brands across the globe are striving to reduce the industry’s negative environmental impact by creating new clothing using only plastic materials. 11. 3 Million Face Masks Per Second: Where Do They End Up? As per recent studies, humankind is going through 129 billion face masks a month, which works out to 3,000,000 a second 12. "We Work With Nature, Not Against It," says OUDToken CEO Teh Huang Wei Most innovative concepts lead to some form of manipulation. The only way forward is decentralizing these aspects to keep green investing manipulation-free. 13. Join us in Our Efforts to Reduce Cloud Waste by $100 Million in 2021 We aren’t putting enough of a spotlight on the environmental impact of the cloud. Cloud usage and spend are skyrocketing as more companies invest in the critical infrastructure that drives digital transformation and supports integral parts of a business. 14. Happy International Women’s Day From HackerNoon HackerNooon welcomes everyone to celebrate women, tech, and women in tech on our platform! 15. Get Ready for New Natural Disasters The earth needs rest – this should be the slogan for the next few decades. Still, "Greensponsible" is no longer popular... 16. How Programming, AI, and Big Data is Giving Google A Chance to Save the World Big business and saving the planet often do not go hand in hand, however in some cases they do. Take a look at how Google plans on saving the future with tech. 17. What Will Life Be Like In 100 Years? Some light-hearted thinks after a long Friday... 18. How Blockchain Technology Improves Environmental Sustainability We are seeing blockchain reach a wider breadth of applications than it seems at first glance. That includes its role in increasing sustainability. 19. This Data Set Shows How Our Emotions Affect the Weather An interesting observation on the emotional effect of weather. Correlation does not equate causation but the situation remains fascinating to readers anyway. 20. Solar Glass: The Energy Generation Solution Cities Need to Go Green Photo-voltaic modules (otherwise known as Solar Panels) have been around for a while. The issue with solar panels is that they need space. Until now..? 21. Varun Sharma on Software Engineering, Climate Change, and Taking Inspiration From Movies Varun Sharma has been nominated for a 2021 Noonies Award for Architecture. 22. Bitcoin Mining Still Requires Too Much Energy Bitcoin is far less popular now than it was in its heyday, when the world’s leading cryptocurrency was regularly dominating international headlines and leading newcomers into the burgeoning crypto-marketplace. After it caught on like wildfire amongst non-traditional investors, the Bitcoin hype also generated a slew of headlines and controversies surrounding the immense amount of energy that’s needed to mine - or generate - new tokens. These days, that controversy has largely died down, but many people still wonder if Bitcoin mining still presents a serious new global warming problem. 23. How Blockchain Technology Can Be Used for Green and Climate-friendly Projects A look at how blockchain technology can be used for green and climate-friendly projects by using its data-gathering and decentralized features to help. 24. How New Technology is Turning the Global Energy Market Green Blockchain consortium to develop a  energy system to power a fleet of electric vehicles and charging stations in Toronto, Canada. 25. Wildlife Photography Tips and Tricks I've got a lot of experience in wildlife photography but there are things that you can learn from other wildlife photographers as well. Here's a guide to some great tips and tricks that have helped me out a lot. 26. 6 Reasons Why You Should Switch to Green Energy Switching to green energy is easier than the decision may initially seem to you and it offers benefits from saving money to indirectly improving your health. 27. Nori raised $4M to reverse climate change: Jaycen Horton, Nori Co-founder and Engineer Using innovative carbon removal solutions, we empower forward-thinking organizations and artists to create positive brand perceptions while they do their part t 28. Internet Heroes Nominee Lisa Shares Why Climate-Focused Technology is Exciting Lisa Gibbons nominated for a noonies hackernoon award as contributor to Climate Change. 29. Can NFTs Help Combat Our Addiction to Fast Fashion? In a world packed full of products made from our natural resources, brands and consumers are beginning to pay more consideration to the impact of fast fashion. 30. How to Fight Global Climate Change with Web3 Maxity.io, the world’s largest charity NFT marketplace, is launching its mobile Dapp called Maxity App and a pioneering ‘Plant and Reward’ model, MAX Forest... 31. What Will the Future Really Be Like? Samo Burja goes over how the future will be. 32. Can Regenerative Finance Change the World? For too long, harmful practices have continued freely while the economic systems fail to initiate the necessary change. 33. Creating a Climate Change MEME Generator Using GPT-3, DALLE, and a series of prompts and responses to create climate change and global warming related memes. 34. The Advent of BioMechaGenics (BMG) Enhanced This is an illustrated science fiction story about climate change that was generated by a web app from my uploaded content. 35. Why Regenerative Finance (Re-Fi) is Essential for Addressing the Climate Crisis Discover the potential of regenerative finance to address the climate crisis and support a just transition to a sustainable economy. 36. The Green Tech Movement and Its Impact on Climate Change A lot of people are concerned about the effects climate change is having on our planet. For those of you looking to make a difference, here's what you can do! 37. "Is This How Our Story is Due to End?" #COP26 Are we investing in the right things or failing to see the bigger picture in pursuit of short-term goals? 38. Who will mine the last mine Bitcoin? Who will mine the last Bitcoin? 39. 2100: A Global Warming Odyssey The carbon legacy of our fossil fuel based ways of life is granting an environmental crisis to billions of individuals in the future. 40. Every Day Unwanted emails dump 28,397 tonnes of CO₂ into the Atmosphere Our mission at Leave Me Alone is to help you to take back control of your inboxes by getting rid of unwanted spam. We bring calm and control back into your digital life and give you more time for the things you love. 41. Startup Interview with Muhammad Bilal, BreatheIO - CEO/Founder My startup is called BreatheIO which is a Smart Air Purifier, that utilizes the power of Artificial Intelligence to reduce and control the Air Pollution 42. Big Tech To Battle It Out For The Social Impact Spotlight in 2020 The World Economic Forum put out its global risks report for 2020, and it's not looking pretty. 43. Why Purpose Driven Tokens Could Be The Vacuum Cleaner to Our Polluted Economy Purpose-driven tokens might be more important than Bitcoin in the near future. What does a 1 million Bitcoin price matter if the earth is f*cked? 44. Can Blockchain Solve Climate Change? An Interview with Hüseyin Uysal An illuminating interview with the founder and CEO of an environmentally-focused blockchain ecosystem. 45. Using Technology to Combat Climate Change: #Women-In-Tech Interview with Sana, CEO BreatheIO This interview is part of the HackerNoon women in tech interview series. Meet Sana, co-founder, and CEO of BreatheIO. 46. Pakistan is at War with the Real Monsters - 'Climate Change' and 'Negligence' #PakistanFloodRelief “Let’s stop sleepwalking towards the destruction of our planet by climate change. Today, it’s Pakistan. Tomorrow, it could be your country.” - UN Secretary-General Antonio Guterres. 47. Digital Ecology: Anyone Can Make a Change "The end is in the beginning and yet you go on." - Samuel Beckett 48. 9 Promising Climate Focused Blockchain Projects for 2023 The effort required to tackle the ongoing climate crisis is growing everyday.   Blockchain technology can be part of the solution and provide transparency. 49. COP27 - Action Not Words A﻿s we fast approach COP27 it is good to find out more about the people committed to climate change. One such individual is Miroslav Polzer who is actively working with technology, in particular Unique Network, to raise awareness. 50. A Day in the Life of a Data Scientist at a Climate Change Startup A guided tour into the life of a data scientist at a climate-tech startup. 51. Oh AGI, Can You Feel Me? Introducing AGI into human society will be like introducing a new species of spiders -- intelligent spiders with the capacity to plan and adapt. 52. How to Solve Real Problems so that Great Products Build Themselves Natasha from hackernoon.com asks Product Strategist Dani Laity to unpack the sustainable tech product strategies and monetization models powering Aurora Sustainability—2020 Noonie Nominee in for Best Use of Tech for Good in hackernoon.com’s annual internet awards! 🚀 53. How AI Technology Can Help in the Climate Change Crisis by Reducing Emissions According to Climate-KIC, even though we're still emitting 17% less CO2 than in 2019, our current greenhouse gas emissions still exceed the normal rate by 80%. 54. How Technology Can Help Make Sustainable Cities As the global population continues to grow exponentially, the number of people living in urban areas is growing the fastest. With over 50% of the world’s population currently living in major cities, and an anticipated 2.4 billion more over the next 30 years, the term ‘megacity’ has been created to describe the urban metropolises of the future. 55. It Is Fission or Frickin’ Fracking! The Germans are often held out as a success story when it comes to powering a modern industrial economy on renewables. The Germans are also hellbent to close all of their nuclear power plants. However, the closing of nuclear power plants and government-subsidized renewable energy powerplant construction has not led to less carbon emissions from the country. 56. The US and China Should Work Together to Fight Climate Change Norvergence LLC team made this report make you understand the aspects of the US-China relationship on the ground of climate and other environmental factors. 57. Reconstructing Our Food Supply Chains with Blockchain Technology Blockchain technology can streamline and restructure the way that we interpret global supply lines, a change that may be vital for addressing climate change. 58. Building Sustainable AI/ML Solutions in the Cloud with Federated Learning Compared to centralized training and cooling mechanisms adopted at data centers, how can Federated Learning help us combat detrimental environmental impacts? 59. 11 Best Climate Change Datasets for Data Science Projects Data is a central piece of the climate change debate. With the climate change datasets on this list, many data scientists have created visualizations and models to measure and track the change in surface temperatures, sea ice levels, and more. Many of these datasets have been made public to allow people to contribute and add valuable insight into the way the climate is changing and its causes. 60. 8 Most Popular Weather APIs for 2020 The climate is a hot issue and weather forecasting technology is suddenly cool. The urgent need for innovative weather and environmental conditions forecasting solutions is obvious whether you believe in climate change or not. 61. Blockchain and Digital Commodities to Help Battle the Climate Crisis There’s nothing new about our home planet getting heated up and causing massive disruptions in nature, as well as our own lives. Just a small reminder that in the middle of March, one can unexpectedly wake up to see the streets and buildings covered in snow is a proof enough that something is changing, and it’s changing radically. 62. Building a Global Environmental Datastack for Climate Action Blue Sky Analytics is a big data and AI start-up that uses geospatial data to monitor environmental parameters. Our goal is to become the Bloomberg of Environmental data for environmental monitoring, ESG (environment, social, and governance) due-diligence and climate risk assessment. 63. GHG-Removal Could Be the Biggest Market of the 21st Century GHG-removal is a $10trln annual market opportunity that is yet to be tapped by new investors, innovators and entrepreneurs. 64. "We believe that climate change is the greatest challenge humanity has ever faced" - Luis Felipe Ada Picking up the baton from past generations, deforestation became one of the most striking calamities of the modern epoch. Having its roots in the bygone industrial era, it continues to sprout its dreadful consequences even into the age of increased awareness and enlightened concern about the environment. Although substantial progress has been made throughout recent years, it is still a long way to reach the point from which we can fulfil the full environmental recovery. 65. It's Time for Individual Carbon Credit Allowance Carbon Credits are defined as 1 ton of CO2 Emissions traded in the market to allow buyers to emit CO2 into the atmosphere. 66. Overcoming Existential RisksThe World Needs More “Real” Superheroes… Whether you see the glass as half full or half empty, I think we can both agree, sometimes it makes sense to just fill the damn cup. And that’s the focus of today’s article, part two in our series on Existential Risk. If you missed that, check that out here before continuing. 67. How Can Technology be Sustainable? We live in a world where tech waste and climate change are a reality. In this slogging thread, we couldn't help but wonder how can technology be sustainable. 68. The year 2020- From the Eyes of Environment and Climate Change Norvergence LLC team has listed down both the positive and negative things that happened in 2020 w.r.t environment and climate change. 69. How to Create Cleaner Air through Software How to quickly, easily, and inexpensively make positive change for the climate 70. The Future Is Now: Robots Helping Us Combat Plastic Pollution And Climate Change A 25-year-old Dutchman named Boyan Slat, alternately hailed as “an ocean action hero” and a “wunderkind” by the publication Maritime Executive, has for years waged war against plastic pollution in the world’s oceans. [71. Edge Computing Is So Fun Part 3: Help Save The Planet With Smart Cities](https://hackernoon.com/edge-computing-is-so-fun-part-3-help-save-the-planet-with-smart-cities-n5143e85) Figure 1. Singapore was ranked №1 on the Institute for Management Development’s 2020 Smart City Index Report. Credit: International Case Studies of Smart Cities 72. Shockwave Effects On Humanity: Pandemonium in 2020 At first, you ignore it. Then you label it a ‘them’ problem. They should have known better, acted sooner. You move on with your life. You only start to really pay attention when London and New York get affected. Not unlike terrorist attacks, lives seem to matter more in some places. Could this happen to you? 73. How Deep Learning Can Help Quantify, Monitor, and Remove Marine Plastic: The DeepPlastic Way Towards a generalized object detector capable of identifying and quantifying sub-surface plastic around the world 74. Help Users Determine Their Carbon Footprint With These APIs Carbon footprint APIs help both companies and users to track and offset their carbon input while also help the community by supporting environmental projects. 75. The Neverending Climate Change Conundrum In this slogging thread, our community discusses the climate crisis and their views on worldwide measures. 76. Visualization of Hypothesis on Meteorological data In this blog, we are gonna perform the analysis on the Meteorological data, and prove the hypothesis based on visualization. 77. Studying First World Problems for Solutions to Cock-Ups From the Future Do First World Problems = First World Solutions? 78. Why the EU Thinks Nuclear Energy and Natural Gas are Environmentally Friendly In this slogging thread, the random channel took the opportunity to discuss the latest news about the energies used in Europe. 79. Studying First World Problems for Solutions to Cock-Ups From the Future Do First World Problems = First World Solutions? 80. The Microfiber Problem: How Washing our Clothes is Polluting the Ocean When we think about ocean pollution, we often imagine shores filled with plastic water bottles, bags, fishing nets, and various other forms of plastic waste. 81. Three Effective Strategies to Collectively Alter Our Carbon Footprint Our current efforts to solve climate change suck and also don’t suck enough. In this piece I have collated some research on sucking carbon out of the air, carbon pricing, Australia’s current renewable plans and carbon consumption habits. Thank you for checking out the 81 most read stories about Climate Change on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

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