Tapioca

tapioca

Scientific American Supplement, No. 799, April 25, 1891 by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . STARCHES FOR THE FINISHING OF COTTON FABRICS. here STARCHES FOR THE FINISHING OF COTTON FABRICS. The starches have been classified by Dr. Muter, according to the appearance they give under the microscope, into five groups: .—Hilum and concentric rings visible. All the granules, oval or ovate. Tous-le-mois, potato, arrowroot, etc. Class I .—The concentric rings are all but invisible, the hilum is stellate. Maize, pea, bean, etc. Class II .—The concentric rings are all but invisible, also the hilum in the majority of granules. Wheat, barley, rye, chestnut, etc. Class III .—All the granules truncated at one end. Sago, tapioca, etc. Class IV .—All the granules angular in form. Rice, tacca, arrowroot, oats, etc. Class V The principal starches used for finishing cotton fabrics are potato (farina), wheat, Indian corn (maize), rice, tapioca, arrowroot, sago; the last three not so often as those previously named. 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. Various (2004). Scientific American Supplement, No. 799, April 25, 1891. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/11649/pg11649-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 , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

STARCHES FOR THE FINISHING OF COTTON FABRICS

Yields Existence Over the centuries, many theories and stories have advanced to explain the existence of 'yield' ('interest') and its role in coordinating capital allocation within financial markets according to preferences for risk. Still, a near-infinite variety of definitions and assumptions continues to perpetuate financial and economic theory with projections including a "reward for abstinence" or, as noted, "time had value." In contrast, financial historian William Goetzmann described the emergence of interest as "the most significant of all " Conventional wisdom holds that the most encompassing view of yield is "the price of time" or the 'reward for idleness.' Bastiat innovations in the history of finance. Moreover, yields are a pertinent metric for investors when channeling for risk. Generally, the ability to generate greater than market returns (benchmark dependent) is a function of taking more risk (beta) or exuding a superiority in identifying mis-priced assets relative to their intrinsic value (alpha). Put more concretely, yield is the percentage return derived from deploying particular investment strategies and can be represented via the following succinct formula; = Net gain/Loss in principle value + realized Yield Total return Precedent suggests that "yields" are essential. This piece will endeavor to describe the first iteration of yield within decentralized finance (DeFi), the problems of perpetual inflation and incentive misalignment regarding the most prevalent source of yield within DeFi (aka Liquidity Mining), and the notion of "real yield." Conceptualising Liquidity Mining In crypto-economic systems, and the distribution of tokens are used to compensate agents who commit different kinds of capital and behavior to a protocol: to block producers for their 'work' or to investors for their capital and liquidity over time. Liquidity mining (LM) is associated with the latter. mechanism design LM is a bootstrapping mechanism and incentive strategy in which rewards are denominated in the protocol's native token and paid out to liquidity providers to augment/subsidize their costs and generate organic' network effects' of liquidity and volume in the long term beyond the product's utility. As , the incentive design must: proposed by Gauntlet Increase liquidity equilibrium once incentives are removed. Liquidity can be lower once the reward structure is removed, but liquidity and fees must be higher than prior. Steepen Lps elasticity or "stickiness": the efficacy of the program is dependent on whether Lps stay around following token distribution and do not respond to alternative protocol incentives Sybil resistant: the incentives program must be difficult/impossible to exploit Although some of the assumptions hold in , the overwhelming analysis concluded that the first iteration of LM was ineffective at creating long-term flywheels and incentive alignment, which bore more similarities to the perpetual money printing of the federal bank. This outcome is essentially a function of unacceptable incentive designs: particular cases As the circulating supply increases due to inflationary issuance, the value claim on each additional token is diluted. Governance also comes into play as these sophisticated entities presumably have a more significant token consideration (whale characteristics) and thus can exude more concentrated voting power over future token distribution (plutocratic governance) Incentive misalignment between the natural users who contribute to the growth of the protocol and financially optimizing mercenaries: Accordingly, selling pressure is a pre-committed and programmatic economic forcing function. From a mechanism design perspective, LPs enter the , whereby the welfare of the participants can be better off by not selling yet they reach an inferior economic outcome. Still, it is locally rational (self-interest) to sell before the next LP such that → supply capital → receive rewards → sell. Yield realization is dependent on the sale of the native token: Prisoner's dilemma The direction of emissions is more akin to renting liquidity and activity over time rather than a long term creation of economic growth. Mercenary, non-loyal LPs will rotate to other yield-bearing opportunities. LM participants are profit maximizers and lack "stickiness": As the value of the emitted token depreciates, incentives become less valuable (when denominated in USD) and less effective at siphoning liquidity. Note this has the opposite effect when the token price is increasing. Reflexivity bound system: Onchain capital movements and historical implosions (e.g., OHM) suggest a weak statistical relationship between liquidity mining and the retention of liquidity over the long term. For instance, Nansen reported that the majority of farmers exit within 5 days of entering a farm. Seemingly, Buying growth with dilution is only sustainable when the equity value outpaces the issuance rate. Real Yield: Meme or movement? Vanity or value? Born out of the ashes of LM, 'real yield' is an emissions design philosophy such that APR outlayed to those committing capital is a function of the protocol's revenue (fee generation) rather than a fixed emission schedule and is typically denominated in Eth or USDC. In this realm, there is a measurable nexus between sustainable economic growth and the costs to acquire said growth. However, the 'real yield' thesis is flawed in isolation when not coupled with sophisticated constraints addressing the token supply, levers for demand, and designing the incentive itself. Inspired by its predecessors, including and , time-weighted average magnitude lock ($twAML) is the next canonical and sound representation of 'real yield' in an incentive-compatible economic model. The reader can dive into the granularities . OHM GMX TapiocaDAO's here Whether real yield is objectively 'better' is a nuanced point of discussion. What can be said with relative conviction is that its reliance on defensible product market fit and value capture means there is no free lunch - " " -and the net positive of the stimulus should always exceed the costs. to get something, you to give something Though not all 'real yield' is created equal, with reflexivity still bound to the effectiveness of the incentives, ‘real yield’ has become a vanity metric to justify the multiple used in valuation. Instead, we should be asking whether the protocol's defensible revenue flow supports the distributions of free cash flow at this nascent stage. Compound, one of the most entrenched DeFi protocols with staying power, plunges further into unprofitability upon further issuance.. It is highly uncommon to distribute earnings for early-stage businesses, and surprisingly, EVERYTHING in crypto is venture stage with shaky product market fit. Thus, the value of tokens not conforming to the real yield narrative is based on the probability of future claims on protocol earnings once they have exhausted ALL internal ROI opportunities locally within the protocol. Although we are in crypto, we do not depart from the bounds of financial physics. Founders and developers of early-stage protocols should be optimizing for market share, not P/E ratios, for our friend Mr Buffet. Questions remain: What collective summoning of actions/behavior deserves to be incentivized? What defines a token's value or discounted Future value if it does not share in generated fees? Timing: when to distribute based on measurable data points? Perhaps, this forms the basis of future pieces. As discussed above, the definition of what constitutes "real yield" is a consideration theorized over discourse dating back centuries. Perhaps the new substrate of programmatic yields mathematically defined by code better demonstrates the "true rate" as opposed to the perpetual inflation of a nation's currency based on electioneering decisions by central banks. Still, there remain open design questions within our realm of "real yield" that we must confront. If you are building a DeFi application that is experimenting with variations in the scalar of yield design and distribution, please comment or reach out!

Real Yield: Norm or Narrative

Will Algorithmic Stablecoins Ever Find Enough Support? 

¿Alguna vez las Stablecoins algorítmicas encontrarán suficiente apoyo?

Les Stablecoins algorithmiques trouveront-ils jamais assez de soutien ?

क्या एल्गोरिथम स्थिर मुद्रा को कभी पर्याप्त समर्थन मिलेगा?

アルゴリズムのステーブルコインは十分なサポートを見つけることができますか?

As stablecoins algorítmicas encontrarão suporte suficiente?

Liệu các Stablecoin thuật toán có bao giờ tìm đủ hỗ trợ không?

算法稳定币会得到足够的支持吗？

The Monster Men by Edgar Rice Burroughs is part of the HackerNoon Books Series. You can jump to any chapter in this book here . PERFIDY PERFIDY On the morning that Bulan set out with his three monsters from the deserted long-house in which they had spent the night, Professor Maxon’s party was speeding up the river, constantly buoyed with hope by the repeated reports of natives that the white girl had been seen passing in a war prahu. In translating this information to Professor Maxon, von Horn habitually made it appear that the girl was in the hands of Number Thirteen, or Bulan, as they had now come to call him owing to the natives’ constant use of that name in speaking of the strange, and formidable white giant who had invaded their land. At the last long-house below the gorge, the head of which had witnessed Virginia Maxon’s escape from the clutches of Ninaka and Barunda, the searching party was forced to stop owing to a sudden attack of fever which had prostrated the professor. Here they found a woman who had a strange tale to relate of a remarkable sight she had witnessed that very morning. It seemed that she had been straining tapioca in a little stream which flowed out of the jungle at the rear of the long-house when her attention was attracted by the crashing of an animal through the bushes a few yards above her. As she looked she saw a huge Mias Pappan cross the stream, bearing in his arms the dead, or unconscious form of a white-skinned girl with golden hair. Her description of the Mias Pappan was such as to half convince von Horn that she might have seen Number Three carrying Virginia Maxon, although he could not reconcile the idea with the story that the two Dyaks had told him of losing all of Bulan’s monsters in the jungle. Of course it was possible that they might have made their way over land to this point, but it seemed scarcely credible—and then, how could they have come into possession of Virginia Maxon, whom every report except this last agreed was still in the hands of Ninaka and Barunda. There was always the possibility that the natives had lied to him, and the more he questioned the Dyak woman the more firmly convinced he became that this was the fact. The outcome of it was that von Horn finally decided to make an attempt to follow the trail of the creature that the woman had seen, and with this plan in view persuaded Muda Saffir to arrange with the chief of the long-house at which they then were to furnish him with trackers and an escort of warriors, promising them some splendid heads should they be successful in overhauling Bulan and his pack. Professor Maxon was too ill to accompany the expedition, and von Horn set out alone with his Dyak allies. For a time after they departed Sing Lee fretted and fidgeted upon the verandah of the long-house. He wholly distrusted von Horn, and from motives of his own finally decided to follow him. The trail of the party was plainly discernible, and the Chinaman had no difficulty in following them, so that they had gone no great way before he came within hearing distance of them. Always just far enough behind to be out of sight, he kept pace with the little column as it marched through the torrid heat of the morning, until a little after noon he was startled by the sudden cry of a woman in distress, and the answering shout of a man. The voices came from a point in the jungle a little to his right and behind him, and without waiting for the column to return, or even to ascertain if they had heard the cries, Sing ran rapidly in the direction of the alarm. For a time he saw nothing, but was guided by the snapping of twigs and the rustling of bushes ahead, where the authors of the commotion were evidently moving swiftly through the jungle. Presently a strange sight burst upon his astonished vision. It was the hideous Number Three in mad pursuit of a female ourang outang, and an instant later he saw Number Twelve and Number Ten in battle with two males, while beyond he heard the voice of a man shouting encouragement to some one as he dashed through the jungle. It was in this last event that Sing’s interest centered, for he was sure that he recognized the voice as that of Bulan, while the first cry for help which he had heard had been in a woman’s voice, and Sing knew that its author could be none other than Virginia Maxon. Those whom he pursued were moving rapidly through the jungle which was now becoming more and more open, but the Chinaman was no mean runner, and it was not long before he drew within sight of the object of his pursuit. His first glimpse was of Bulan, running swiftly between two huge bull ourang outangs that snapped and tore at him as he bounded forward cutting and slashing at his foes with his heavy whip. Just in front of the trio was another bull bearing in his arms the unconscious form of Virginia Maxon who had fainted at the first response to her cry for help. Sing was armed with a heavy revolver but he dared not attempt to use it for fear that he might wound either Bulan or the girl, and so he was forced to remain but a passive spectator of what ensued. Bulan, notwithstanding the running battle the two bulls were forcing upon him, was gaining steadily upon the fleeing ourang outang that was handicapped by the weight of the fair captive he bore in his huge, hairy arms. As they came into a natural clearing in the jungle the fleeing bull glanced back to see his pursuer almost upon him, and with an angry roar turned to meet the charge. In another instant Bulan and the three bulls were rolling and tumbling about the ground, a mass of flying fur and blood from which rose fierce and angry roars and growls, while Virginia Maxon lay quietly upon the sward where her captor had dropped her. Sing was about to rush forward and pick her up, when he saw von Horn and his Dyaks leap into the clearing, to which they had been guided by the sounds of the chase and the encounter. The doctor halted at the sight that met his eyes—the prostrate form of the girl and the man battling with three huge bulls. Then he gathered up Virginia Maxon, and with a sign to his Dyaks, who were thoroughly frightened at the mere sight of the white giant of whom they had heard such terrible stories, turned and hastened back in the direction from which they had come, leaving the man to what seemed must be a speedy and horrible death. Sing Lee was astounded at the perfidy of the act. To Bulan alone was due the entire credit of having rescued Professor Maxon’s daughter, and yet in the very presence of his self-sacrificing loyalty and devotion von Horn had deserted him without making the least attempt to aid him. But the wrinkled old Chinaman was made of different metal, and had started forward to assist Bulan when a heavy hand suddenly fell upon his shoulder. Looking around he saw the hideous face of Number Ten snarling into his. The bloodshot eyes of the monster were flaming with rage. He had been torn and chewed by the bull with which he had fought, and though he had finally overcome and killed the beast, a female which he had pursued had eluded him. In a frenzy of passion and blood lust aroused by his wounds, disappointment and the taste of warm blood which still smeared his lips and face, he had been seeking the female when he suddenly stumbled upon the hapless Sing. With a roar he grasped the Chinaman as though to break him in two, but Sing was not at all inclined to give up his life without a struggle, and Number Ten was quick to learn that no mean muscles moved beneath that wrinkled, yellow hide. There could, however, have been but one outcome to the unequal struggle had Sing not been armed with a revolver, though it was several seconds before he could bring it into play upon the great thing that shook and tossed him about as though he had been a rat in the mouth of a terrier. But suddenly there was the sharp report of a firearm, and another of Professor Maxon’s unhappy experiments sank back into the nothingness from which he had conjured it. Then Sing turned his attention to Bulan and his three savage assailants, but, except for the dead body of a bull ourang outang upon the spot where he had last seen the four struggling, there was no sign either of the white man or his antagonists; nor, though he listened attentively, could he catch the slightest sound within the jungle other than the rustling of the leaves and the raucous cries of the brilliant birds that flitted among the gorgeous blooms about him. For half an hour he searched in every direction, but finally, fearing that he might become lost in the mazes of the unfamiliar forest he reluctantly turned his face toward the river and the long-house that sheltered his party. Here he found Professor Maxon much improved—the safe return of Virginia having acted as a tonic upon him. The girl and her father sat with von Horn upon the verandah of the long-house as Sing clambered up the notched log that led to it from the ground. At sight of Sing’s wrinkled old face Virginia Maxon sprang to her feet and ran forward to greet him, for she had been very fond of the shrewd and kindly Chinaman of whom she had seen so much during the dreary months of her imprisonment within the campong. “Oh, Sing,” she cried, “where have you been? We were all so worried to think that no sooner was one of us rescued than another became lost.” “Sing takee walk, Linee, las all,” said the grinning Chinaman. “Velly glad see Linee black ’gain,” and that was all that Sing Lee had to say of the adventures through which he had just passed, and the strange sights that he had seen. Again and again the girl and von Horn narrated the stirring scenes of the day, the latter being compelled to repeat all that had transpired from the moment that he had heard Virginia’s cry, though it was apparent that he only consented to speak of his part in her rescue under the most considerable urging. Very pretty modesty, thought Sing when he had heard the doctor’s version of the affair. “You see,” said von Horn, “when I reached the spot Number Three, the brute that you thought was an ape, had just turned you over to Number Thirteen, or, as the natives now call him, Bulan. You were then in a faint, and when I attacked Bulan he dropped you to defend himself. I had expected a bitter fight from him after the wild tales the natives have been telling of his ferocity, but it was soon evident that he is an arrant coward, for I did not even have to fire my revolver—a few thumps with the butt of it upon his brainless skull sent him howling into the jungle with his pack at his heels.” “How fortunate it is, my dear doctor,” said Professor Maxon, “that you were bright enough to think of trailing the miscreant into the jungle. But for that Virginia would still be in his clutches and by this time he would have been beyond all hope of capture. How can we ever repay you, dear friend?” “That you were generous enough to arrange when we first embarked upon the search for your daughter,” replied von Horn. “Just so, just so,” said the professor, but a shade of trouble tinged the expression of his face, and a moment later he arose, saying that he felt weak and tired and would go to his sleeping room and lie down for a while. The fact was that Professor Maxon regretted the promise he had made von Horn relative to his daughter. Once before he had made plans for her marriage only to regret them later; he hoped that he had made no mistake this time, but he realized that it had scarcely been fair to Virginia to promise her to his assistant without first obtaining her consent. Yet a promise was a promise, and, again, was it not true that but for von Horn she would have been dead or worse than dead in a short time had she not been rescued from the clutches of the soulless Bulan? Thus did the old man justify his action, and clinch the determination that he had before reached to compel Virginia to wed von Horn should she, from some incomprehensible motive, demur. Yet he hoped that the girl would make it easy, by accepting voluntarily the man who had saved her life. Left alone, or as he thought alone, with the girl in the growing shadows of the evening, von Horn thought the moment propitious for renewing his suit. He did not consider the natives squatting about them as of sufficient consequence to consider, since they would not understand the language in which he addressed Virginia, and in the dusk he failed to note that Sing squatted with the Dyaks, close behind them. “Virginia,” he commenced, after an interval of silence, “often before have I broached the subject nearest to my heart, yet never have you given me much encouragement. Can you not feel for the man who would gladly give his life for you, sufficient affection to permit you to make him the happiest man in the world? I do not ask for all your love at first—that will come later. Just give me the right to cherish and protect you. Say that you will be my wife, Virginia, and we need have no more fears that the strange vagaries of your father’s mind can ever again jeopardize your life or your happiness as they have in the past.” “I feel that I owe you my life,” replied the girl in a quiet voice, “and while I am now positive that my father has entirely regained his sanity, and looks with as great abhorrence upon the terrible fate he planned for me as I myself, I cannot forget the debt of gratitude which belongs to you. “At the same time I do not wish to be the means of making you unhappy, as surely would be the result were I to marry you without love. Let us wait until I know myself better. Though you have spoken to me of the matter before, I realize now that I never have made any effort to determine whether or not I really can love you. There is time enough before we reach civilization, if ever we are fortunate enough to do so at all. Will you not be as generous as you are brave, and give me a few days before I must make you a final answer?” With Professor Maxon’s solemn promise to insure his ultimate success von Horn was very gentle and gracious in deferring to the girl’s wishes. The girl for her part could not put from her mind the disappointment she had felt when she discovered that her rescuer was von Horn, and not the handsome young giant whom she had been positive was in close pursuit of her abductors. When Number Thirteen had been mentioned she had always pictured him as a hideous monster, similar to the creature that had seized her in the jungle beside the encampment that first day she had seen the mysterious stranger, of whom she could obtain no information either from her father or von Horn. When she had recently insisted that the same man had been at the head of her father’s creatures in an attempt to rescue her, both von Horn and Professor Maxon scoffed at the idea, until at last she was convinced that the fright and the firelight had conspired to conjure in her brain the likeness of one who was linked by memory to another time of danger and despair. Virginia could not understand why it was that the face of the stranger persisted in obtruding itself in her memory. That the man was unusually good looking was undeniable, but she had known many good looking men, nor was she especially impressionable to mere superficial beauty. No words had passed between them on the occasion of their first meeting, so it could have been nothing that he said which caused the memory of him to cling so tenaciously in her mind. What was it then? Was it the memory of the moments that she had lain in his strong arms—was it the shadow of the sweet, warm glow that had suffused her as his eyes had caught hers upon his face? The thing was tantalizing—it was annoying. The girl blushed in mortification at the very thought that she could cling so resolutely to the memory of a total stranger, and—still greater humiliation—long in the secret depths of her soul to see him again. She was angry with herself, but the more she tried to forget the young giant who had come into her life for so brief an instant, the more she speculated upon his identity and the strange fate that had brought him to their little, savage island only to snatch him away again as mysteriously as he had come, the less was the approval with which she looked upon the suit of Doctor von Horn. Von Horn had left her, and strolled down to the river. Finally Virginia arose to seek the crude couch which had been spread for her in one of the sleeping rooms of the long-house. As she passed a group of natives squatted nearby one of the number arose and approached her, and as she halted, half in fright, a low voice whispered: “Lookee out, Linee, dloctor Hornee velly bad man.” “Why, Sing!” exclaimed Virginia. “What in the world do you mean by saying such a thing as that?” “Never mind, Linee; you always good to old Sing. Sing no likee see you sadee. Dloctor Hornee velly bad man, las allee,” and without another word the Chinaman turned and walked away. 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. Edgar Rice Burroughs (1994). The Monster Men. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/96/pg96-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 .

Professor Maxon’s party was speeding up the river

Love and Mr. Lewisham by H. G. Wells, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . EPITHALAMY CHAPTER XXII. — EPITHALAMY. For three indelible days Lewisham’s existence was a fabric of fine emotions, life was too wonderful and beautiful for any doubts or forethought. To be with Ethel was perpetual delight—she astonished this sisterless youngster with a thousand feminine niceties and refinements. She shamed him for his strength and clumsiness. And the light in her eyes and the warmth in her heart that lit them! Even to be away from her was a wonder and in its way delightful. He was no common Student, he was a man with a Secret Life. To part from her on Monday near South Kensington station and go up Exhibition Road among all the fellows who lived in sordid, lonely lodgings and were boys to his day-old experience! To neglect one’s work and sit back and dream of meeting again! To slip off to the shady churchyard behind the Oratory when, or even a little before, the midday bell woke the great staircase to activity, and to meet a smiling face and hear a soft, voice saying sweet foolish things! And after four another meeting and the walk home—their own home. No little form now went from him and flitted past a gas lamp down a foggy vista, taking his desire with her. Never more was that to be. Lewisham’s long hours in the laboratory were spent largely in a dreamy meditation, in—to tell the truth—the invention of foolish terms of endearment: “Dear Wife,” “Dear Little Wife Thing,” “Sweetest Dearest Little Wife,” “Dillywings.” A pretty employment! And these are quite a fair specimen of his originality during those wonderful days. A moment of heart-searching in that particular matter led to the discovery of hitherto undreamt-of kindred with Swift. For Lewisham, like Swift and most other people, had hit upon, the Little Language. Indeed it was a very foolish time. Such section cutting as he did that third day of his married life—and he did very little—was a thing to marvel at. Bindon, the botany professor, under the fresh shock of his performance, protested to a colleague in the grill room that never had a student been so foolishly overrated. And Ethel too had a fine emotional time. She was mistress of a home—their home together. She shopped and was called “Ma’am” by respectful, good-looking shopmen; she designed meals and copied out papers of notes with a rich sense of helpfulness. And ever and again she would stop writing and sit dreaming. And for four bright week-days she went to and fro to accompany and meet Lewisham and listen greedily to the latest fruits of his imagination. The landlady was very polite and conversed entertainingly about the very extraordinary and dissolute servants that had fallen to her lot. And Ethel disguised her newly wedded state by a series of ingenious prevarications. She wrote a letter that Saturday evening to her mother—Lewisham had helped her to write it—making a sort of proclamation of her heroic departure and promising a speedy visit. They posted the letter so that it might not be delivered until Monday. She was quite sure with Lewisham that only the possible dishonour of mediumship could have brought their marriage about—she sank the mutual attraction beyond even her own vision. There was more than a touch of magnificence, you perceive, about this affair. It was Lewisham had persuaded her to delay that reassuring visit until Monday night. “One whole day of honeymoon,” he insisted, was to be theirs. In his prenuptial meditations he had not clearly focussed the fact that even after marriage some sort of relations with Mr. and Mrs. Chaffery would still go on. Even now he was exceedingly disinclined to face that obvious necessity. He foresaw, in spite of a resolute attempt to ignore it, that there would be explanatory scenes of some little difficulty. But the prevailing magnificence carried him over this trouble. “Let us at least have this little time for ourselves,” he said, and that seemed to settle their position. Save for its brevity and these intimations of future trouble it was a very fine time indeed. Their midday dinner together, for example—it was a little cold when at last they came to it on Saturday—was immense fun. There was no marked subsidence of appetite; they ate extremely well in spite of the meeting of their souls, and in spite of certain shiftings of chairs and hand claspings and similar delays. He really made the acquaintance of her hands then for the first time, plump white hands with short white fingers, and the engagement ring had come out of its tender hiding-place and acted as keeper to the wedding ring. Their eyes were perpetually flitting about the room and coming back to mutual smiles. All their movements were faintly tremulous. She professed to be vastly interested and amused by the room and its furniture and her position, and he was delighted by her delight. She was particularly entertained by the chest of drawers in the living room, and by Lewisham’s witticisms at the toilet tidies and the oleographs. And after the chops and the most of the tinned salmon and the very new loaf were gone they fell to with fine effect upon a tapioca pudding. Their talk was fragmentary. “Did you hear her call me Madame? Madame—so!” “And presently I must go out and do some shopping. There are all the things for Sunday and Monday morning to get. I must make a list. It will never do to let her know how little I know about things.... I wish I knew more.” At the time Lewisham regarded her confession of domestic ignorance as a fine basis for facetiousness. He developed a fresh line of thought, and condoled with her on the inglorious circumstances of their wedding. “No bridesmaids,” he said; “no little children scattering flowers, no carriages, no policemen to guard the wedding presents, nothing proper—nothing right. Not even a white favour. Only you and I.” “Only you and I. Oh!” “This is nonsense,” said Lewisham, after an interval. “And think what we lose in the way of speeches,” he resumed. “Cannot you imagine the best man rising:—‘Ladies and gentlemen—the health of the bride.’ That is what the best man has to do, isn’t it?” By way of answer she extended her hand. “And do you know,” he said, after that had received due recognition, “we have never been introduced!” “Neither have we!” said Ethel. “Neither have we! We have never been introduced!” For some inscrutable reason it delighted them both enormously to think that they had never been introduced.... In the later afternoon Lewisham, having unpacked his books to a certain extent, and so forth, was visible to all men, visibly in the highest spirits, carrying home Ethel’s shopping. There were parcels and cones in blue and parcels in rough grey paper and a bag of confectionery, and out of one of the side pockets of that East-end overcoat the tail of a haddock protruded from its paper. Under such magnificent sanctions and amid such ignoble circumstances did this honeymoon begin. On Sunday evening they went for a long rambling walk through the quiet streets, coming out at last into Hyde Park. The early spring night was mild and clear and the kindly moonlight was about them. They went to the bridge and looked down the Serpentine, with the little lights of Paddington yellow and remote. They stood there, dim little figures and very close together. They whispered and became silent. Presently it seemed that something passed and Lewisham began talking in his magnificent vein. He likened the Serpentine to Life, and found Meaning in the dark banks of Kensington Gardens and the remote bright lights. “The long struggle,” he said, “and the lights at the end,”—though he really did not know what he meant by the lights at the end. Neither did Ethel, though the emotion was indisputable. “We are Fighting the World,” he said, finding great satisfaction in the thought. “All the world is against us—and we are fighting it all.” “We will not be beaten,” said Ethel. “How could we be beaten—together?” said Lewisham. “For you I would fight a dozen worlds.” It seemed a very sweet and noble thing to them under the sympathetic moonlight, almost indeed too easy for their courage, to be merely fighting the world. “You ‘aven’t bin married ver’ long,” said Madam Gadow with an insinuating smile, when she readmitted Ethel on Monday morning after Lewisham had been swallowed up by the Schools. “No, I haven’t very long,” admitted Ethel. “You are ver’ ‘appy,” said Madam Gadow, and sighed. “I was ver’ ‘appy,” said Madam Gadow. 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. H. G. Wells (2006). Love and Mr. Lewisham. Urbana, Illinois: Project Gutenberg. Retrieved October 2022, from https://www.gutenberg.org/files/11640/11640-h/11640-h.htm 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.

EPITHALAMY

(Scroll down to the hack) ‘Lying’ by Sam Harris explores why we lie to one another. Is someone with makeup lying to us about their appearance? We’ve all been Seinfeld & Aziz at the restaurant. And we do it because lying is easier. The social scientist will point out ☝️the effort vs benefit of ethical responsibility is too high☝️ And so, we shouldn’t be surprised that our users lie to us. It’s what makes listening to users an underrated skill. Most times, we don’t even intend to lie. We just forget to think about the truth. We fall prey to biases and tricks that the mind plays on us. Like the availability bias. Someone asks us “What’s keeping you up at night?” and we blurt out the first thing our minds make available to us. Not a great question to ask. By the way, congratulations if you’re already talking to users. Having spent hundreds of hours doing it at multiple ventures, I can tell you’re already. Most people don’t even do it. People don’t talk to users for a variety of reasons. It’s uncomfortable. You’re troubling someone. You need to say please and thank you. It’s scary. You may mess it up. You’re thinking about what to ask next. And not listening to what they’re saying. As such, many organizations and individuals hide behind surveys, or just read support tickets and data. Others justify different priorities, or.. just look busy. Hack Question (HQ) Get started on a call today by simply asking the user this again and again “And what did you do next?” Some theory and nuance follow, but if you want to skip it and hop on a call, just go on try it! It’s a Hack question for a reason It helps recall vs reimagine: We’re terrible at reimagining others’ worlds. “If I cooked up some tapioca balls and put them in tea would you drink it?” Err… sure! It’s open vs close-ended: Asking close-ended questions isn’t useful. It allows the easy way out. “How is everything?” Great! It’s non-leading vs leading: Leading questions make it easy for someone to lie. “This recipe is from my grandmother, isn’t it amazing” Yes! It forces detail: Building products is a high detail activity. Simply knowing “world hunger is a problem” doesn’t help you decide what to cook next. It uncovers jobs to be done: Every successful product solves some job. This question forces the user to recall jobs they need to do to accomplish a goal. Meeting bookends You naturally don’t want to start and finish the call with a Hack question. So, what do bookends look like? Smile, thank, and welcome your guest. Let them know it isn’t an inquisition. You’re just trying to understand better. Ok to record? Intro: Ask exactly what your product intends to solve. Remember we’re going for detail. Kickoff: “Tell me about the last time you bought steak at a food truck”. Depending on their response, adjust, but . They may be further up the buyer journey. That’s ok, you’ll get different information from this audience. Like how to acquire them. settle into HQ asap Speak from the heart. Big thank you, it was a valuable conversation and meant a lot. Finish: a BANTer s you get better at it You’ve overcome the initial fear. Now learn to BANTer between HQs as they describe pain points. Budget: Have you spent money on solving that? Authority: Did you need to get an ok from someone else first? Need: Do you really need to solve it, how many hrs/week do you get back? Timing: When was the last time you faced this, how often do you face it? It’s a sales discovery technique but applies to feature discovery too. Not every pain point is worth solving. Uncover the one to focus on. Don’t panic, and good luck! 😅

Hack Calmer Conversations and Get Reliable Feedback from Users

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Andrea Roncoli, Department of Computer, Science (University of Pisa);
(2) Aleksandra Ciprijanovi´c´, Computational Science and AI Directorate (Fermi National Accelerator Laboratory) and Department of Astronomy and Astrophysics (University of Chicago);
(3) Maggie Voetberg, Computational Science and AI Directorate, (Fermi National Accelerator Laboratory);
(4) Francisco Villaescusa-Navarro, Center for Computational Astrophysics (Flatiron Institute);
(5) Brian Nord, Computational Science and AI Directorate, Fermi National Accelerator Laboratory, Department of Astronomy and Astrophysics (University of Chicago) and Kavli Institute for Cosmological Physics (University of Chicago). Table of Links Abstract and Intro Data and Methods Results Conclusions Acknowledgments and Disclosure of Funding, and References Additional Plots 2 Data and Methods 2.1 Domain Adaptation Optimization and Computing Resources We performed experiments on NVIDIA A100 40GB GPU. For each of the models, implemented using PyTorch Geometric [19], we perform a hyperparameter search using the Optuna library [1], with 50 trials per model. More details on code performance, model implementations, and selected hyperparameters can be found in the publicly available code[4]. 2.2 Evaluation [1] https://arepo-code.org/ [2] http://www.tapir.caltech.edu/~phopkins/Site/GIZMO.html [3] CAMELS dataset documentation: https://camels.readthedocs.io/en/latest/index.html [4] GitHub repository will be added after the anonymous review stage. This paper is available on arxiv under CC 4.0 license. Authors: (1) Andrea Roncoli, Department of Computer, Science (University of Pisa); (2) Aleksandra Ciprijanovi´c´, Computational Science and AI Directorate (Fermi National Accelerator Laboratory) and Department of Astronomy and Astrophysics (University of Chicago); (3) Maggie Voetberg, Computational Science and AI Directorate, (Fermi National Accelerator Laboratory); (4) Francisco Villaescusa-Navarro, Center for Computational Astrophysics (Flatiron Institute); (5) Brian Nord, Computational Science and AI Directorate, Fermi National Accelerator Laboratory, Department of Astronomy and Astrophysics (University of Chicago) and Kavli Institute for Cosmological Physics (University of Chicago). This paper is available on arxiv under CC 4.0 license. available on arxiv Authors: Authors: (1) Andrea Roncoli, Department of Computer, Science (University of Pisa); (2) Aleksandra Ciprijanovi´c´, Computational Science and AI Directorate (Fermi National Accelerator Laboratory) and Department of Astronomy and Astrophysics (University of Chicago); (3) Maggie Voetberg, Computational Science and AI Directorate, (Fermi National Accelerator Laboratory); (4) Francisco Villaescusa-Navarro, Center for Computational Astrophysics (Flatiron Institute); (5) Brian Nord, Computational Science and AI Directorate, Fermi National Accelerator Laboratory, Department of Astronomy and Astrophysics (University of Chicago) and Kavli Institute for Cosmological Physics (University of Chicago). Table of Links Abstract and Intro Abstract and Intro Data and Methods Data and Methods Results Results Conclusions Conclusions Acknowledgments and Disclosure of Funding, and References Acknowledgments and Disclosure of Funding, and References Additional Plots Additional Plots 2 Data and Methods 2.1 Domain Adaptation Optimization and Computing Resources We performed experiments on NVIDIA A100 40GB GPU. For each of the models, implemented using PyTorch Geometric [19], we perform a hyperparameter search using the Optuna library [1], with 50 trials per model. More details on code performance, model implementations, and selected hyperparameters can be found in the publicly available code[4]. Optimization and Computing Resources 2.2 Evaluation [1] https://arepo-code.org/ [2] http://www.tapir.caltech.edu/~phopkins/Site/GIZMO.html [3] CAMELS dataset documentation: https://camels.readthedocs.io/en/latest/index.html [4] GitHub repository will be added after the anonymous review stage.

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