Jellyfish

jellyfish

🙌 Hi web3 folks! ⚽️ Sorare sees over 585,000 new sign-ups over the World Cup The gamified sports NFT platform has seen a significant influx of users since the launch of its World Cup game on November 10th. . More 🌊 Aquarium de Paris launches educational NFT collection with real-world utility The 1234 NFTs are 1:1 replicas of real jellyfish at the world’s oldest public Aquarium. NFT holders receive unlimited free access to the aquarium, in-store discounts, and other perks. . More 🟠 Redditors have now minted over 5 million NFT avatars Reddit’s Polygon-based avatars launched in July. The initiative has led to over 5 million avatars being minted by over 4 million Reddit users in 6 months. . More 🏎️ The Tiny Digital Factory partners with Aston Martin to create NFTs for a blockchain-based racing game The 3,000 Aston Martin NFT cars will be playable in the Infinite Drive Racing game. . More 🛞 Mattel Creations releases new batch of Hot Wheels NFTs The Hot Wheels NFT Garage™ Series 4 Collection is available on the Mattel Creations website and offers fans a new way of experiencing the leading toy brand’s 75-year-long line of products. . More 🎶 Warner Music releases music-themed Sandbox experience The Warner Music Game Jam invites music fans to create music-themed games in the Sandbox for a chance to win SAND tokens. . More 👀 Donald Trump releases NFTs Trump Cards NFT holders get access to various Donald Trump-related benefits and experiences. . More 🦊 PayPal partners with MetaMask The partnership will enable MetaMask users to purchase ETH with PayPal, with plans to add more cryptocurrencies in the future. . More 🗞️ Time Magazine announces upcoming NFT collection The magazine’s web3 arm, TIMEpieces, is releasing another NFT collection in collaboration with author and founder Deepak Chopra. The collection will commemorate Deepak’s bestselling book, Seven Spiritual Laws of Success reaching its 25th anniversary year. . More 🖥️ Intel and Billboard collaborate on fourth Chartstars NFT collection Billboard’s NFT brand, Chartstars, celebrates global music fandom. The most recent NFT drop rewards loyalty and is only being made available to fans that bought into previous collections. . More ⚖️ New European Laws provide new hope for crypto and NFT mobile The EU Digital Markets Act offers a way to sidestep Apple’s restrictive NFT/crypto policies that restrict NFT utility, place a 30% fee on all transactions, and more. The new regulations will apply from May 2023. . More 👜 American accessories brand, Steel, looks to redefine luxury NFT experiences Purchasers of Steel products can scan their items to receive digital twin NFTs, which track authenticity and can be added to customers’ Apple wallets and used as membership passes. . More WAGMI!  See you next week!

Weekly Web3 Brand Tracker: NFT Jellyfishes, Donald Trump Joins In, and More

Rastreador semanal de marca Web3: medusas NFT, Donald Trump se une y más

Suivi hebdomadaire de la marque Web3 : NFT Jellyfishes, Donald Trump se joint à nous, et plus encore

साप्ताहिक वेब3 ब्रांड ट्रैकर: एनएफटी जेलिफ़िश, डोनाल्ड ट्रम्प शामिल हुए, और बहुत कुछ

Weekly Web3 Brand Tracker: NFT Jellyfishes、Donald Trump の参加など

Rastreador semanal de marcas Web3: NFT Jellyfishes, Donald Trump se junta a eles e muito mais

Công cụ theo dõi thương hiệu Web3 hàng tuần: NFT Jellyfishes, Donald Trump tham gia và hơn thế nữa

Weekly Web3 Brand Tracker：NFT 水母、唐纳德·特朗普加入等等

HackerNoon Reporter: Please tell us briefly about your background. I was trained and started my career as an engineer, and over time grew into running a large engineering team. I saw many challenges in leading those teams, the influence of which is how I came to co-found a company like Jellyfish. I’m also a startup guy. I’ve been at or helped to start half a dozen startups, including as VP of Engineering at Endeca, Founder at Loopit, and Chief Strategy Officer at Nanigans before starting Jellyfish. It’s been super fun to see the team grow and make a difference for our customers. What's your startup called? And in a sentence or two, what does it do? Our startup is called Jellyfish - it’s a platform that gives engineering leaders visibility into what their teams are working on, how they’re operating, and how they can improve. I’ve been in the trenches as an engineer and leader, so I understand how difficult it is to lead technical teams without the right analytics. Our goal is to make the lives of engineering leaders easier and help them make better business decisions by providing them with access to insightful data about their organization. What is the origin story? Dave, Phil, and I met 21 years ago when we were all working together at Endeca. In 2016 we got the band back together and found that we had all faced a common challenge in growing our careers, and we realized that we could make a difference for a lot of folks out there. At the time, there was all this software that helped sales, marketing, and other leaders make data-driven decisions, but that didn’t really exist for engineering leaders. We thought that was a large part of the problem we had individually faced, so in 2017 we founded Jellyfish to build that tool and really help engineering leaders like ourselves evolve, help drive product strategy and company direction, and just make informed business decisions. What do you love about your team, and why are you the ones to solve this problem? What I love most about this team is that they teach me something new every day. We (Dave, Phil, and I) are inspired to wake up every day learning new things from them. And frankly, they are all just good people who we like spending time with. We all know that startups can be a challenge, so I think it’s important to have people you want to spend time with on those challenging days. This problem that we’re solving is near and dear to our hearts, and I think we’re the team to solve it because we’ve been through the challenges of leading engineering teams of 10 people, 50 people, 100 people, thousands of people. All of these are different challenges, but the tools today are not sufficient for solving any of them. More recently, we’ve sat on the other side of the proverbial table and have seen what engineering teams can do to help the business grow more. More than just code, it’s about understanding how the team, the code, and the business fit together - the trifecta of successful businesses. If you weren’t building your startup, what would you be doing? I’d have to say, barbecue chef or oyster farmer. As a hobby, I’m a KCBS certified judge and a bbq enthusiast, and harvesting oysters in the summer is one of my favorite things to do. At the moment, how do you measure success? What are your core metrics? There are all the SaaS metrics that you all know already from hundreds or thousands of blogs and books. I could list them all here, but I don’t think that defines success for me. To me, success is really about this: are we making a dent in the way that companies make engineering decisions, and are we changing the way that engineering leaders do their work? For our customers, I think the answer is yes, and so I’m excited to see that success. What’s most exciting about your traction to date? We’ve been super lucky in this challenging time to find resonance and acceleration despite all the tough things going on in the world. We’ve seen some really exciting growth over the past few years, and it’s only continued to accelerate. In January, we announced our Series B funding along with 5X growth in revenue. Things haven’t really slowed down since then. It’s been a crazy time for our business, but for me, the most exciting part is that it’s a testament to the fact that we’re solving a real problem out there. What technologies are you currently most excited about and most worried about? And why? This may seem tired, but it’s been amazing to watch the confluence of cloud and AI come to fruition. Yes, we’ve all been reading about these things for over a decade, but it’s finally here and actually happening now. I used to joke all the time that every company, even air conditioning companies, is becoming a software company. It was awesome when a few weeks ago, a literal air conditioning company came to us for help! What drew you to get published on HackerNoon? What do you like most about our platform? The community! HackerNoon is an amazing community of smart, boundary-pushing hackers. There are some world changers here, and that’s why we’re always stoked to be featured. What advice would you give to the 21-year-old version of yourself? Get out and do something, build something. Don’t spend your life reading blogs and interviews (except this one, of course!), but instead get going on something. Even if you aren’t working on your own startup, get out there and join one. You’ll learn a ton about the industry, companies, and yourself. You’ve got 40+ years to create the perfect startup - stop studying and worrying if the perfect idea isn’t coming to you right now. What is something surprising you've learned this year that your contemporaries would benefit from knowing? Pre-2020, I think we were all constantly on the go. As it turns out, I’m finding that having to sit on a pair of flights every week isn’t an experience I particularly miss! I love spending time with my family. My kids are young enough that they love spending time with us too. It’s a real blessing to be able to have dinner with them every night. So I’d say I’ve learned how important it is to me to take a step back to appreciate this time I get to spend with my family. Jellyfish is contending as the . startup of the year, Boston

Startup Interview with Andrew Lau, Co-founder and CEO of Jellyfish 

Authors:
(1) Michael Sorochan Armstrong, Computational Data Science (CoDaS) Lab in the Department of Signal Theory, Telematics, and Communications at the University of Granada;
(2) Jose Carlos P´erez-Gir´on, part of the Interuniversity Institute for Research on the Earth System in Andalucia through the University of Granada;
(3) Jos´e Camacho, Computational Data Science (CoDaS) Lab in the Department of Signal Theory, Telematics, and Communications at the University of Granada;
(4) Regino Zamora, part of the Interuniversity Institute for Research on the Earth System in Andalucia through the University of Granada. Table of Links Abstract & Introduction Optimization of the Optical Interpolation Materials and Methods Results and Discussion Conclusion Appendix A: Proof of Hermitian Self-Adjoint product identity for Equidistant Time-Domain Measurements Appendix B: AAH ̸= MIN I in the Non-Equidistant Case Acknowledgments & References 3 MATERIALS AND METHODS 3.0.1 Remote Sensor Data Soil temperature data were collected in the Sierra Nevada National Park in Andaluc´ıa, Spain, as part of the Smart EcoMountains program through the Lifewatch ERIC Program, from solar-powered remote multi-parametric micro-stations located within different environments (shrub, rock, and bare-earth) and altitudes (from 1500m to 2300m) from 29- 07-2020 until 04-05-2023. Measurements were continuously collected at a nominal 10 minute interval with micro-sensors (ibuttons, thermochron-type; Maxim integrated) connected to a network that transmits the collected information when connectivity is available. All the collected data were visually inspected for extreme values outside the normal ranges of the variable in the time series due to sensor failures, identifying a single sensor reporting erroneous values that were reported as NaNs. 3.0.2 Computational information All calculations were run with a B550 AORUS ELITE AX V2 motherboard with 128 GiB DDR4 RAM, an AMD Ryzen 9 5950x 32 core processor with an NVIDIA GeForce RTX 3080 graphics processor, and a 2 TB NVMe Samsung SSD 980. Software was installed on Ubuntu 22.04.3 LTS 64-bit operating system “Jammy Jellyfish”. Graphical inspections and data cleaning were conducted with the tidyverse 2.0.0 package [13] implemented in the R 4.3.1 software environment [14]. Calculations were performed using Python 3.10. Data was parsed and cleaned from the original .csv values using Pandas 2.0.3. Various numerical operations were performed using the vectorized functions available in NumPy 1.25 [15], with additional statistical functionality from SciPy 1.11 [16]. Graphics were created using Matplotlib 3.7.1 [17]. This paper is available on arxiv under CC 4.0 license. Authors: (1) Michael Sorochan Armstrong, Computational Data Science (CoDaS) Lab in the Department of Signal Theory, Telematics, and Communications at the University of Granada; (2) Jose Carlos P´erez-Gir´on, part of the Interuniversity Institute for Research on the Earth System in Andalucia through the University of Granada; (3) Jos´e Camacho, Computational Data Science (CoDaS) Lab in the Department of Signal Theory, Telematics, and Communications at the University of Granada; (4) Regino Zamora, part of the Interuniversity Institute for Research on the Earth System in Andalucia through the University of Granada. Authors: Authors: (1) Michael Sorochan Armstrong, Computational Data Science (CoDaS) Lab in the Department of Signal Theory, Telematics, and Communications at the University of Granada; (2) Jose Carlos P´erez-Gir´on, part of the Interuniversity Institute for Research on the Earth System in Andalucia through the University of Granada; (3) Jos´e Camacho, Computational Data Science (CoDaS) Lab in the Department of Signal Theory, Telematics, and Communications at the University of Granada; (4) Regino Zamora, part of the Interuniversity Institute for Research on the Earth System in Andalucia through the University of Granada. Table of Links Abstract & Introduction Abstract & Introduction Optimization of the Optical Interpolation Optimization of the Optical Interpolation Materials and Methods Materials and Methods Results and Discussion Results and Discussion Conclusion Conclusion Appendix A: Proof of Hermitian Self-Adjoint product identity for Equidistant Time-Domain Measurements Appendix A: Proof of Hermitian Self-Adjoint product identity for Equidistant Time-Domain Measurements Appendix B: AAH ̸= MIN I in the Non-Equidistant Case Appendix B: AAH ̸= MIN I in the Non-Equidistant Case Acknowledgments & References Acknowledgments & References 3 MATERIALS AND METHODS 3.0.1 Remote Sensor Data Soil temperature data were collected in the Sierra Nevada National Park in Andaluc´ıa, Spain, as part of the Smart EcoMountains program through the Lifewatch ERIC Program, from solar-powered remote multi-parametric micro-stations located within different environments (shrub, rock, and bare-earth) and altitudes (from 1500m to 2300m) from 29- 07-2020 until 04-05-2023. Measurements were continuously collected at a nominal 10 minute interval with micro-sensors (ibuttons, thermochron-type; Maxim integrated) connected to a network that transmits the collected information when connectivity is available. All the collected data were visually inspected for extreme values outside the normal ranges of the variable in the time series due to sensor failures, identifying a single sensor reporting erroneous values that were reported as NaNs. 3.0.2 Computational information All calculations were run with a B550 AORUS ELITE AX V2 motherboard with 128 GiB DDR4 RAM, an AMD Ryzen 9 5950x 32 core processor with an NVIDIA GeForce RTX 3080 graphics processor, and a 2 TB NVMe Samsung SSD 980. Software was installed on Ubuntu 22.04.3 LTS 64-bit operating system “Jammy Jellyfish”. Graphical inspections and data cleaning were conducted with the tidyverse 2.0.0 package [13] implemented in the R 4.3.1 software environment [14]. Calculations were performed using Python 3.10. Data was parsed and cleaned from the original .csv values using Pandas 2.0.3. Various numerical operations were performed using the vectorized functions available in NumPy 1.25 [15], with additional statistical functionality from SciPy 1.11 [16]. Graphics were created using Matplotlib 3.7.1 [17]. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Remote Sensor Data Collection: Insights from Sierra Nevada National Park

240 Stories To Learn About Startups Of The Year

90 Stories To Learn About Startup Strategy

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Alice in Wonderland by Lewis Carroll, is part of the HackerNoon Books Series. You can jump to any chapter in this book . The Lobster Quadrille here CHAPTER X. The Lobster Quadrille The Mock Turtle sighed deeply, and drew the back of one flapper across his eyes. He looked at Alice, and tried to speak, but for a minute or two sobs choked his voice. “Same as if he had a bone in his throat,” said the Gryphon: and it set to work shaking him and punching him in the back. At last the Mock Turtle recovered his voice, and, with tears running down his cheeks, he went on again:— “You may not have lived much under the sea—” (“I haven’t,” said Alice)—“and perhaps you were never even introduced to a lobster—” (Alice began to say “I once tasted—” but checked herself hastily, and said “No, never”) “—so you can have no idea what a delightful thing a Lobster Quadrille is!” “No, indeed,” said Alice. “What sort of a dance is it?” “Why,” said the Gryphon, “you first form into a line along the sea-shore—” “Two lines!” cried the Mock Turtle. “Seals, turtles, salmon, and so on; then, when you’ve cleared all the jelly-fish out of the way—” “ generally takes some time,” interrupted the Gryphon. That “—you advance twice—” “Each with a lobster as a partner!” cried the Gryphon. “Of course,” the Mock Turtle said: “advance twice, set to partners—” “—change lobsters, and retire in same order,” continued the Gryphon. “Then, you know,” the Mock Turtle went on, “you throw the—” “The lobsters!” shouted the Gryphon, with a bound into the air. “—as far out to sea as you can—” “Swim after them!” screamed the Gryphon. “Turn a somersault in the sea!” cried the Mock Turtle, capering wildly about. “Change lobsters again!” yelled the Gryphon at the top of its voice. “Back to land again, and that’s all the first figure,” said the Mock Turtle, suddenly dropping his voice; and the two creatures, who had been jumping about like mad things all this time, sat down again very sadly and quietly, and looked at Alice. “It must be a very pretty dance,” said Alice timidly. “Would you like to see a little of it?” said the Mock Turtle. “Very much indeed,” said Alice. “Come, let’s try the first figure!” said the Mock Turtle to the Gryphon. “We can do without lobsters, you know. Which shall sing?” “Oh, sing,” said the Gryphon. “I’ve forgotten the words.” you So they began solemnly dancing round and round Alice, every now and then treading on her toes when they passed too close, and waving their forepaws to mark the time, while the Mock Turtle sang this, very slowly and sadly:— “Will you walk a little faster?” said a whiting to a snail. “There’s a porpoise close behind us, and he’s treading on my tail. See how eagerly the lobsters and the turtles all advance! They are waiting on the shingle—will you come and join the dance? Will you, won’t you, will you, won’t you, will you join the dance? Will you, won’t you, will you, won’t you, won’t you join the dance? “You can really have no notion how delightful it will be When they take us up and throw us, with the lobsters, out to sea!” But the snail replied “Too far, too far!” and gave a look askance— Said he thanked the whiting kindly, but he would not join the dance. Would not, could not, would not, could not, would not join the dance. Would not, could not, would not, could not, could not join the dance. “What matters it how far we go?” his scaly friend replied. “There is another shore, you know, upon the other side. The further off from England the nearer is to France— Then turn not pale, beloved snail, but come and join the dance. Will you, won’t you, will you, won’t you, will you join the dance? Will you, won’t you, will you, won’t you, won’t you join the dance?” “Thank you, it’s a very interesting dance to watch,” said Alice, feeling very glad that it was over at last: “and I do so like that curious song about the whiting!” “Oh, as to the whiting,” said the Mock Turtle, “they—you’ve seen them, of course?” “Yes,” said Alice, “I’ve often seen them at dinn—” she checked herself hastily. “I don’t know where Dinn may be,” said the Mock Turtle, “but if you’ve seen them so often, of course you know what they’re like.” “I believe so,” Alice replied thoughtfully. “They have their tails in their mouths—and they’re all over crumbs.” “You’re wrong about the crumbs,” said the Mock Turtle: “crumbs would all wash off in the sea. But they their tails in their mouths; and the reason is—” here the Mock Turtle yawned and shut his eyes.—“Tell her about the reason and all that,” he said to the Gryphon. have “The reason is,” said the Gryphon, “that they go with the lobsters to the dance. So they got thrown out to sea. So they had to fall a long way. So they got their tails fast in their mouths. So they couldn’t get them out again. That’s all.” would “Thank you,” said Alice, “it’s very interesting. I never knew so much about a whiting before.” “I can tell you more than that, if you like,” said the Gryphon. “Do you know why it’s called a whiting?” “I never thought about it,” said Alice. “Why?” “ ,” the Gryphon replied very solemnly. It does the boots and shoes Alice was thoroughly puzzled. “Does the boots and shoes!” she repeated in a wondering tone. “Why, what are shoes done with?” said the Gryphon. “I mean, what makes them so shiny?” your Alice looked down at them, and considered a little before she gave her answer. “They’re done with blacking, I believe.” “Boots and shoes under the sea,” the Gryphon went on in a deep voice, “are done with a whiting. Now you know.” “And what are they made of?” Alice asked in a tone of great curiosity. “Soles and eels, of course,” the Gryphon replied rather impatiently: “any shrimp could have told you that.” “If I’d been the whiting,” said Alice, whose thoughts were still running on the song, “I’d have said to the porpoise, ‘Keep back, please: we don’t want with us!’” you “They were obliged to have him with them,” the Mock Turtle said: “no wise fish would go anywhere without a porpoise.” “Wouldn’t it really?” said Alice in a tone of great surprise. “Of course not,” said the Mock Turtle: “why, if a fish came to , and told me he was going a journey, I should say ‘With what porpoise?’” me “Don’t you mean ‘purpose’?” said Alice. “I mean what I say,” the Mock Turtle replied in an offended tone. And the Gryphon added “Come, let’s hear some of adventures.” your “I could tell you my adventures—beginning from this morning,” said Alice a little timidly: “but it’s no use going back to yesterday, because I was a different person then.” “Explain all that,” said the Mock Turtle. “No, no! The adventures first,” said the Gryphon in an impatient tone: “explanations take such a dreadful time.” So Alice began telling them her adventures from the time when she first saw the White Rabbit. She was a little nervous about it just at first, the two creatures got so close to her, one on each side, and opened their eyes and mouths so wide, but she gained courage as she went on. Her listeners were perfectly quiet till she got to the part about her repeating “ ,” to the Caterpillar, and the words all coming different, and then the Mock Turtle drew a long breath, and said “That’s very curious.” very You are old, Father William “It’s all about as curious as it can be,” said the Gryphon. “It all came different!” the Mock Turtle repeated thoughtfully. “I should like to hear her try and repeat something now. Tell her to begin.” He looked at the Gryphon as if he thought it had some kind of authority over Alice. “Stand up and repeat ‘’ ,’” said the Gryphon. Tis the voice of the sluggard “How the creatures order one about, and make one repeat lessons!” thought Alice; “I might as well be at school at once.” However, she got up, and began to repeat it, but her head was so full of the Lobster Quadrille, that she hardly knew what she was saying, and the words came very queer indeed:— “’Tis the voice of the Lobster; I heard him declare, “You have baked me too brown, I must sugar my hair.” As a duck with its eyelids, so he with his nose Trims his belt and his buttons, and turns out his toes.” [later editions continued as follows When the sands are all dry, he is gay as a lark, And will talk in contemptuous tones of the Shark, But, when the tide rises and sharks are around, His voice has a timid and tremulous sound.] “That’s different from what used to say when I was a child,” said the Gryphon. I “Well, I never heard it before,” said the Mock Turtle; “but it sounds uncommon nonsense.” Alice said nothing; she had sat down with her face in her hands, wondering if anything would happen in a natural way again. ever “I should like to have it explained,” said the Mock Turtle. “She can’t explain it,” said the Gryphon hastily. “Go on with the next verse.” “But about his toes?” the Mock Turtle persisted. “How he turn them out with his nose, you know?” could “It’s the first position in dancing.” Alice said; but was dreadfully puzzled by the whole thing, and longed to change the subject. “Go on with the next verse,” the Gryphon repeated impatiently: “it begins ‘ .’” I passed by his garden Alice did not dare to disobey, though she felt sure it would all come wrong, and she went on in a trembling voice:— “I passed by his garden, and marked, with one eye, How the Owl and the Panther were sharing a pie—” [later editions continued as follows The Panther took pie-crust, and gravy, and meat, While the Owl had the dish as its share of the treat. When the pie was all finished, the Owl, as a boon, Was kindly permitted to pocket the spoon: While the Panther received knife and fork with a growl, And concluded the banquet—] “What the use of repeating all that stuff,” the Mock Turtle interrupted, “if you don’t explain it as you go on? It’s by far the most confusing thing ever heard!” is I “Yes, I think you’d better leave off,” said the Gryphon: and Alice was only too glad to do so. “Shall we try another figure of the Lobster Quadrille?” the Gryphon went on. “Or would you like the Mock Turtle to sing you a song?” “Oh, a song, please, if the Mock Turtle would be so kind,” Alice replied, so eagerly that the Gryphon said, in a rather offended tone, “Hm! No accounting for tastes! Sing her ‘ ,’ will you, old fellow?” Turtle Soup The Mock Turtle sighed deeply, and began, in a voice sometimes choked with sobs, to sing this:— “Beautiful Soup, so rich and green, Waiting in a hot tureen! Who for such dainties would not stoop? Soup of the evening, beautiful Soup! Soup of the evening, beautiful Soup! Beau—ootiful Soo—oop! Beau—ootiful Soo—oop! Soo—oop of the e—e—evening, Beautiful, beautiful Soup! “Beautiful Soup! Who cares for fish, Game, or any other dish? Who would not give all else for two p ennyworth only of beautiful Soup? Pennyworth only of beautiful Soup? Beau—ootiful Soo—oop! Beau—ootiful Soo—oop! Soo—oop of the e—e—evening, Beautiful, beauti—FUL SOUP!” “Chorus again!” cried the Gryphon, and the Mock Turtle had just begun to repeat it, when a cry of “The trial’s beginning!” was heard in the distance. “Come on!” cried the Gryphon, and, taking Alice by the hand, it hurried off, without waiting for the end of the song. “What trial is it?” Alice panted as she ran; but the Gryphon only answered “Come on!” and ran the faster, while more and more faintly came, carried on the breeze that followed them, the melancholy words:— “Soo—oop of the e—e—evening, Beautiful, beautiful Soup!” 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. Lewis Carroll (2008). Alice in Wonderland. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/11/pg11-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.

The Lobster Quadrille

Anne of Avonlea by L. M. Montgomery, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . Odds and Ends Chapter XXII - Odds and Ends “So you had tea at the stone house with Lavendar Lewis?” said Marilla at the breakfast table next morning. “What is she like now? It’s over fifteen years since I saw her last . . . it was one Sunday in Grafton church. I suppose she has changed a great deal. Davy Keith, when you want something you can’t reach, ask to have it passed and don’t spread yourself over the table in that fashion. Did you ever see Paul Irving doing that when he was here to meals?” “But Paul’s arms are longer’n mine,” brumbled Davy. “They’ve had eleven years to grow and mine’ve only had seven. ‘Sides, I did ask, but you and Anne was so busy talking you didn’t pay any ‘tention. ‘Sides, Paul’s never been here to any meal escept tea, and it’s easier to be p’lite at tea than at breakfast. You ain’t half as hungry. It’s an awful long while between supper and breakfast. Now, Anne, that spoonful ain’t any bigger than it was last year and I’m ever so much bigger.” “Of course, I don’t know what Miss Lavendar used to look like but I don’t fancy somehow that she has changed a great deal,” said Anne, after she had helped Davy to maple syrup, giving him two spoonfuls to pacify him. “Her hair is snow-white but her face is fresh and almost girlish, and she has the sweetest brown eyes . . . such a pretty shade of wood-brown with little golden glints in them . . . and her voice makes you think of white satin and tinkling water and fairy bells all mixed up together.” “She was reckoned a great beauty when she was a girl,” said Marilla. “I never knew her very well but I liked her as far as I did know her. Some folks thought her peculiar even then. Davy, if ever I catch you at such a trick again you’ll be made to wait for your meals till everyone else is done, like the French.” Most conversations between Anne and Marilla in the presence of the twins, were punctuated by these rebukes Davy-ward. In this instance, Davy, sad to relate, not being able to scoop up the last drops of his syrup with his spoon, had solved the difficulty by lifting his plate in both hands and applying his small pink tongue to it. Anne looked at him with such horrified eyes that the little sinner turned red and said, half shamefacedly, half defiantly, “There ain’t any wasted that way.” “People who are different from other people are always called peculiar,” said Anne. “And Miss Lavendar is certainly different, though it’s hard to say just where the difference comes in. Perhaps it is because she is one of those people who never grow old.” “One might as well grow old when all your generation do,” said Marilla, rather reckless of her pronouns. “If you don’t, you don’t fit in anywhere. Far as I can learn Lavendar Lewis has just dropped out of everything. She’s lived in that out of the way place until everybody has forgotten her. That stone house is one of the oldest on the Island. Old Mr. Lewis built it eighty years ago when he came out from England. Davy, stop joggling Dora’s elbow. Oh, I saw you! You needn’t try to look innocent. What does make you behave so this morning?” “Maybe I got out of the wrong side of the bed,” suggested Davy. “Milty Boulter says if you do that things are bound to go wrong with you all day. His grandmother told him. But which is the right side? And what are you to do when your bed’s against the wall? I want to know.” “I’ve always wondered what went wrong between Stephen Irving and Lavendar Lewis,” continued Marilla, ignoring Davy. “They were certainly engaged twenty-five years ago and then all at once it was broken off. I don’t know what the trouble was but it must have been something terrible, for he went away to the States and never come home since.” “Perhaps it was nothing very dreadful after all. I think the little things in life often make more trouble than the big things,” said Anne, with one of those flashes of insight which experience could not have bettered. “Marilla, please don’t say anything about my being at Miss Lavendar’s to Mrs. Lynde. She’d be sure to ask a hundred questions and somehow I wouldn’t like it . . . nor Miss Lavendar either if she knew, I feel sure.” “I daresay Rachel would be curious,” admitted Marilla, “though she hasn’t as much time as she used to have for looking after other people’s affairs. She’s tied home now on account of Thomas; and she’s feeling pretty downhearted, for I think she’s beginning to lose hope of his ever getting better. Rachel will be left pretty lonely if anything happens to him, with all her children settled out west, except Eliza in town; and she doesn’t like her husband.” Marilla’s pronouns slandered Eliza, who was very fond of her husband. “Rachel says if he’d only brace up and exert his will power he’d get better. But what is the use of asking a jellyfish to sit up straight?” continued Marilla. “Thomas Lynde never had any will power to exert. His mother ruled him till he married and then Rachel carried it on. It’s a wonder he dared to get sick without asking her permission. But there, I shouldn’t talk so. Rachel has been a good wife to him. He’d never have amounted to anything without her, that’s certain. He was born to be ruled; and it’s well he fell into the hands of a clever, capable manager like Rachel. He didn’t mind her way. It saved him the bother of ever making up his own mind about anything. Davy, do stop squirming like an eel.” “I’ve nothing else to do,” protested Davy. “I can’t eat any more, and it’s no fun watching you and Anne eat.” “Well, you and Dora go out and give the hens their wheat,” said Marilla. “And don’t you try to pull any more feathers out of the white rooster’s tail either.” “I wanted some feathers for an Injun headdress,” said Davy sulkily. “Milty Boulter has a dandy one, made out of the feathers his mother give him when she killed their old white gobbler. You might let me have some. That rooster’s got ever so many more’n he wants.” “You may have the old feather duster in the garret,” said Anne, “and I’ll dye them green and red and yellow for you.” “You do spoil that boy dreadfully,” said Marilla, when Davy, with a radiant face, had followed prim Dora out. Marilla’s education had made great strides in the past six years; but she had not yet been able to rid herself of the idea that it was very bad for a child to have too many of its wishes indulged. “All the boys of his class have Indian headdresses, and Davy wants one too,” said Anne. “I know how it feels . . . I’ll never forget how I used to long for puffed sleeves when all the other girls had them. And Davy isn’t being spoiled. He is improving every day. Think what a difference there is in him since he came here a year ago.” “He certainly doesn’t get into as much mischief since he began to go to school,” acknowledged Marilla. “I suppose he works off the tendency with the other boys. But it’s a wonder to me we haven’t heard from Richard Keith before this. Never a word since last May.” “I’ll be afraid to hear from him,” sighed Anne, beginning to clear away the dishes. “If a letter should come I’d dread opening it, for fear it would tell us to send the twins to him.” A month later a letter did come. But it was not from Richard Keith. A friend of his wrote to say that Richard Keith had died of consumption a fortnight previously. The writer of the letter was the executor of his will and by that will the sum of two thousand dollars was left to Miss Marilla Cuthbert in trust for David and Dora Keith until they came of age or married. In the meantime the interest was to be used for their maintenance. “It seems dreadful to be glad of anything in connection with a death,” said Anne soberly. “I’m sorry for poor Mr. Keith; but I am glad that we can keep the twins.” “It’s a very good thing about the money,” said Marilla practically. “I wanted to keep them but I really didn’t see how I could afford to do it, especially when they grew older. The rent of the farm doesn’t do any more than keep the house and I was bound that not a cent of your money should be spent on them. You do far too much for them as it is. Dora didn’t need that new hat you bought her any more than a cat needs two tails. But now the way is made clear and they are provided for.” Davy and Dora were delighted when they heard that they were to live at Green Gables, “for good.” The death of an uncle whom they had never seen could not weigh a moment in the balance against that. But Dora had one misgiving. “Was Uncle Richard buried?” she whispered to Anne. “Yes, dear, of course.” “He . . . he . . . isn’t like Mirabel Cotton’s uncle, is he?” in a still more agitated whisper. “He won’t walk about houses after being buried, will he, Anne?” 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. L. M. Montgomery (2022). Anne of Avonlea. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/47/pg47-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 lead image was generated using HackerNoon's Stable Disffusion Al Image Generator feature, via the prompt "Anne of Avonlea".

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THE HARMAS

This article is created by students Edward Mercado, Marina Ghosh, and Monica Tartau to polish our skills in creating and marketing developer content. DevRel University changes the way we access and monetize data in a decentralized world. The data that sellers list on Ocean Protocol marketplaces spans many domains, and NFTs is one of them. NFT data harbors particular value for investors, traders, and NFT-based financial derivative builders alike. Web3-curious scientists are in a unique position to extract valuable forecasts from this data and use it to assess risks, to transform how we understand and evaluate these digital assets together with Ocean. Ocean Protocol NFT Price Analysis Data Challenge A recent collaboration between Ocean Protocol and blockchain data provider Transpose has made possible the NFT Price Analysis Data Challenge. This challenge looks for innovative submissions in  NFT price analysis, prediction, and valuation using the wealth of data available through the Ocean ecosystem. Ocean Protocol is committed to continue driving data innovation, and we are excited to support NFT data professionals and enthusiasts as they push data insights forward. The NFT Price Analysis Data Challenge invites data scientists, developers, and enthusiasts to leverage the power of Ocean Protocol's decentralized data infrastructure – and win prizes! All participants can access a curated dataset from Transpose containing information on over 300,000 NFTs from various platforms, such as OpenSea, Rarible, and Foundation. Top submissions will use this dataset as well as any other data sources, from Ocean or elsewhere, to provide insights into chosen NFT collections, look back at what historically drove their prices, and build a machine learning model that forecasts the NFT collection floor price. Bonus points are in store for those participants who post their NFT data insights on the Ocean Market on Polygon, contributing to the decentralized data value ecosystem. Be part of a new generation of data By enabling data-driven decision-making in the world of NFTs, Ocean Protocol is helping users and investors make informed choices when buying, selling, or trading these unique digital assets. It also allows the builders of NFT-based financial products to create better investment opportunities for web3 degens, by using data to assess risks. As the NFT market continues to expand, the importance of accurate and comprehensive data analysis, as well as informed forecasting, cannot be overstated. The NFT Price Analysis Data Challenge is Ocean Protocol’s way to empower individuals and organizations to harness the full potential of data in this rapidly growing sector. Ocean Protocol is thrilled to enable new ways for everyone in web3 to interact with and understand digital assets. In the NFT Price Analysis Data Challenge, Ocean’s data sharing and monetization capabilities come together with the expertise of data scientists to unlock decision-making value for all ecosystem participants. The community of data builders, dataset and data stream owners, and data-driven web3 enthusiasts has formed around Ocean Protocol to unlock new value creation loops. Together with this community, Ocean continues to realize its forward-looking vision of decentralized ownership and value borne from data. Featured image generated using Kadinsky 2 using the following prompt: “jelly fish floating from left to right in a deep vast ocean, viewpoint from below”

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