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![]() Instead of *just* having the option of buying storage, Wuala gives you the option to _share_ a bit of my local drive space as a way to earn more Wuala storage. * A pro account gives you automated backups, sync, and file versioning.īy far my favourite feature of Wuala is the '()' model for getting extra storage space. In groups, the sharing is a bit like a poor man's Basecamp, as comments are enabled on everything and there's a nifty little notification when a new comment is posted. * Sharing is super-simple and can be done through sharing links or groups. * Even though the desktop application is written in Java, it's responsive, full-featured, and actually kind of fun to use because of the way that sharing works. Having used Wuala for a week now, here's what I really like: Git or Gitorious storage open source software The runner-ups, IMHO, would be SpiderOak and SparkleShare (h/t to for the later). Many thanks to Elijah for the introduction to Wuala. Feel free to let me know if I’ve got something wrong, or if I’ve missed a service entirely. I have not personally confirmed the claims around security, or encryption on mobile devices, for example. Some I’ve tried in the past, some I tried this week, and with some I just simply reviewed their FAQs and support forums for answers to my questions. Basic iOS and Android clients: nothing fancy, just access to the files (ideally read/write) and using the same kind of encryption as the desktop client.Īdmittedly, I’ve done a very, very cursory review of the following services.Priced reasonably for storage: ideally with an invite code, referral program, or other ways to ‘earn’ storage.Finder / OS integration: It has to be easy to use, and work like any other folder or mounted drive.Share: I must admit, I don’t use the share stuff as much as I could, but being able to share a folder or a file with a person, or a team, is a great feature.I don’t want to have to remember to move things in or out of something. If you want “real” security, encrypt your own files or don’t store them in the cloud.) And, if you don’t use the Web site, theoretically there’s no copy of they key. (Some will say that most services need to cache the key if you sign-in through a Web site, but at least they might not keep it kicking around. Encryption in transit and on the remote disk. ![]()
Carter and Scoggins reach the control panel, but the largest shark storms in, ripping Scoggins apart and wrecking the controls. Carter and Scoggins go to the flooded laboratory to activate a control panel that drains a stairway to the surface, while Susan heads to her room to collect her research material. The rest of the group moves on, encountering Preacher. Despite Carter's attempt to save her, a shark drags Janice under and eats her. As they climb, explosive tremors cause the ladder to break, and Janice loses her grip and falls into the water. The remaining crew opt to climb up the elevator shaft at the risk of destabilizing the pool. While delivering a monologue emphasizing the need for group unity, Franklin is dragged into the submersible pool by a shark and devoured. When the group reaches the wet entry, they discover that the submersible has been damaged. In the facility's kitchen, which has been partially flooded, cook Sherman "Preacher" Dudley, whose parrot is eaten by a shark, manages to kill the big fish by setting off an explosion. Susan confesses to the others that she and Jim genetically engineered the sharks to increase their brain size, as they were not large enough to harvest sufficient amounts of the protein complex this broke protocol and made the sharks smarter and more deadly. The group goes to the facility's wet entry, where they plan to take a submersible to escape. In the laboratory, Susan, Franklin, wrangler Carter Blake, marine biologist Janice Higgins, and engineer Tom Scoggins witness the shark smash the stretcher against the laboratory's main window, which then shatters, drowning Jim and flooding the facility. The largest shark grabs the stretcher and pulls the helicopter into the tower, killing Brenda and the pilots, as well as causing massive explosions that severely damage the facility. As Jim is being lifted the cable jams, dropping Jim and his stretcher into the shark pen. Brenda Kerns, the tower's operator, calls a helicopter that braves heavy rain and strong winds to evacuate Jim. ![]() Susan and Jim prove their research is working by testing a certain protein complex that was removed from the brain tissue of their largest shark, which bites off Jim's right arm upon awakening in the laboratory. After one of the sharks escapes the facility and attempts to attack a boat full of young adults, financial backers send corporate executive Russell Franklin to investigate the facility. In a remote underwater facility, doctors Susan McCallister and Jim Whitlock are conducting research on mako sharks to help in the re-activation of dormant human brain cells like those found in Alzheimer's disease patients. A third film, Deep Blue Sea 3, was released on July 28, 2020. A direct-to-video sequel, Deep Blue Sea 2, was released in 2018. Retrospectively, Deep Blue Sea has been regarded as a successful shark film, especially within a limited genre that has been dominated by Steven Spielberg's 1975 thriller Jaws. ![]() It received generally mixed reviews from critics, who praised its suspense, pacing, and action sequences, but criticized its unoriginality and B movie conventions. Released in theaters during the summer season, Deep Blue Sea grossed over $165 million worldwide. Trevor Rabin composed the film score LL Cool J contributed two songs to the film: "Deepest Bluest (Shark's Fin)" and " Say What". Although Deep Blue Sea features some shots of real sharks, most of the sharks used in the film were either animatronic or computer generated. The film was primarily shot at Fox Baja Studios in Rosarito, Mexico, where the production team constructed sets above the large water tanks that had been built for James Cameron's 1997 film Titanic. The situation plunges into chaos when multiple genetically engineered sharks go on a rampage and flood the facility.ĭeep Blue Sea had a production budget of $60–82 million and represented a test for Harlin, who had not made a commercially successful film since Cliffhanger in 1993. Set in an isolated underwater facility, the film follows a team of scientists and their research on mako sharks to help fight Alzheimer's disease. Jackson, Michael Rapaport, and LL Cool J. ![]() ![]() Deep Blue Sea is a 1999 American science fiction horror film directed by Renny Harlin and starring Saffron Burrows, Thomas Jane, Samuel L. ![]() We also study the trade-off between domain adaptation and task adaptation with respect to the amount of labeled data from the healthcare domain, and show that leveraging pre-trained models from other (seemingly unrelated) domains can be useful in scenarios where task adaptation may be ineffective, e.g., when labeled data for the target task as well as its related tasks within the healthcare domain is scarce. More specifically, we consider two scenarios: (i) extract features from a pre-trained network and use them to build models for target task and (ii) initialize deep network for target task using parameters of a pre-trained network and then fine-tune using labeled training data for target task. In this work, we consider two simple yet effective approaches to transfer the knowledge captured in pre-trained deep RNNs for new target tasks in healthcare domain. However, fine-tuning a large number of parameters with a small-labeled dataset may still result in overfitting, and requires careful regularization (as we show in Section 9 through empirical evaluation). Transfer learning via fine-tuning parameters of pre-trained models for end tasks has been recently considered for medical applications as well. Also, it has been argued that transferring weights even from distant tasks can be better than using random initial weights in neural networks. It has been shown that pre-trained networks can learn to extract a rich set of generic features that can then be applied to a wide range of other similar tasks. Moreover, fine-tuning a pre-trained network for the target task is often faster and easier than constructing and training a new network from scratch. For example, training a deep network on a diverse set of images can provide useful features for images from unseen domains. Transfer learning is known to mitigate this: It enables knowledge transfer from neural networks trained on a source task (domain) with sufficient training instances to a related target task (domain) with few training instances. However, like most deep learning approaches, RNNs are prone to overfitting when labeled training data is scarce, and often require careful and computationally expensive hyper-parameter tuning effort. With various medical parameters being recorded over a period of time in EHR databases, recurrent neural networks (RNNs) can be an effective way to model the sequential aspects of EHR data and, in turn, enable applications in diagnoses, mortality prediction, and estimating length of stay. As a result, there has been a rapid growth in the applications of deep learning to various clinical prediction tasks from electronic health records, e.g., Doctor AI for medical diagnosis, Deep Patient to predict future diseases in patients, and DeepR to predict unplanned readmission after discharge. On the other hand, deep learning approaches enable end-to-end learning without the need of hand-crafted and domain-specific features, and have recently produced promising results for various clinical prediction tasks. Traditional machine learning approaches often require careful domain-specific feature engineering to achieve good prediction performance. ![]() ![]() Electronic health records (EHR) consisting of the medical history of patients are useful in various clinical applications such as diagnosis and recommending medicine. ![]() However, the look has to be soft so using a stroke of soft matte brown shadow for the upper and lower lids would make the eyes look soft and sultry. For the lower lash line, use brown or white pencil or the two together and smudge with an angular brush. From the mid section you shall use bronze metallic tones and blend it into the eyelids to form a perfect gradient. Start with the inner corner of the eyes with a light shade of copper till the mid section of the lids. To emulate the 70’s pastel twiggy eyes, we shall use bronze and copper shimmer shadows for the natural gorgeous look to come through and for a sultry effect as well.Remember to keep the cheeks healthy and flushed with three strokes of blush. Choose colors such as warm browns, peaches and pinks, apricots to blend in well with the bronze look. For the cheeks, we would stick to the warm tone family again.Now with a buffer brush, we shall with light feather strokes apply the bronze shimmer mix only once, and with the same buffer brush in circular motions blend the rest away.With the of a damp sponge, we shall set the base well on the skin and allow the blending to come as clean. ![]() Next, we shall now with light feather strokes add a little yellow shimmer powder (just a pinch) to a large bowl of bronzer powder and mix them well. ![]()
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The larger ones resemble hollow jack-o-lanterns, but breaking them reveals them to be shadowy. Two small variants resembles crude scarecrows, and they're capable of teleporting the Child to each other if he gets too close. Botanical Abomination: The Pumpkins in the third nightmare.Other occasions include cutting bunnies into two new ones, the heads of the Elk exposed on sinew, and a smiley face creature having arms poke out of its face orifices. Body Horror: Unlike the games beforehand, Happy Game dabbles into this frequently, especially during the final sequence of the second nightmare, which depicts mutilated, still-living bodies of the previous characters littered throughout the abyss.Heck, a warning before the gameplay starts directly clarifies that Happy Game is not a happy game. Blatant Lies: The title Happy Game doesn't really bring to mind a violent, psychoactive horror game that is definitely not happy.Big Bad: The Smiling Demon is the one responsible for giving the Child deadly nightmares which he must escape.Balloon Belly: Feeding a rabbit a carrot will have it gain one, but it loses it if they're cut apart.Animate Inanimate Object: You'll encounter some from time to time, including but not limited to living toys, guillotines, rocks, and so forth.The Child and his dog end up riding a Pumpkin to get past some scarecrows, only for it to stampede along with other Pumpkins across a white void. Animal Stampede: A possible variant with "plants" instead of animals.Amusing Injuries: One puzzle has a Ripper seeing his own eyes pop out and starts smiling at it.Ambiguous Situation: Is everything in the game real and the Child really is being tormented by an Eldritch Abomination for its own sick amusement or is everything part of a Dying Dream as the Child, now an adult, dies of what might be an antidepressant overdose? Neither sound particularly pleasant, so it's probably best not to dwell on it.Ambiguously Absent Parent: The main character's parents never appear onscreen. ![]() The Demon is present in the flashbacks showing how the Child lost his toys and dog, and in the second flashback the Child seams to actually be able to see the Demon. While most of the events really are nightmares, it's heavily implied the Demon is real and created the nightmares the Child is having.
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