Research Highlights: Consuming more than half a tablespoon of olive oil daily was associated with a 15% lower risk of having any type of cardiovascular disease and a 21% lower risk of having coronary heart disease. Replacing one teaspoon of butter, ...

DALLAS and ARLINGTON, April 23, 2020 — As emerging science around COVID-19 highlights elevated danger for people with diabetes, heart disease and stroke[1], the American Heart Association and the American Diabetes Association urge people living with type...

DALLAS, May 4, 2020 — Tomorrow, on #GivingTuesdayNow, a global day of philanthropic action to address the COVID-19 pandemic, the American Heart Association – the leading global public health organization devoted to a world of longer healthier lives – is...

The business world has changed over the years and you’ll need to rely on digital methods of marketing your brand to succeed. One of the best ways to do that is through search engine optimization (SEO) to get better traffic for your business. When you use the right techniques and strategies, you can double your organic traffic.  If you’re in the business of helping people with their search engine optimization needs, here are some of the best ways to double your client’s organic traffic. Help Clients Work On Their Content You need to teach and advise your clients on how

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The Iowa high school softball season was supposed to start practice Monday. Instead, the coronavirus pandemic has everything delayed until June 1, or maybe longer. Or, perhaps, canceled. But since...

CEDAR RAPIDS — This was his alma mater, a place he had a ton of success at as a player. The future of the program is clearly bright. But Matt Lesan has a clear plan for his own future, which...

The Iowa Supreme Court approved a pilot program in the 4th Judicial District — Audubon, Cass, Fremont, Harrison, Mills, Montgomery, Pottawattamie, Page and Shelby counties — to develop...

A good idea when trying to get the most out of your blog is usging the meta tag to tell the web bots to search & index your site. But for good SEO you should apply this code in your header.php file of your WordPress blog. <?php if(is_search()) { ?> <meta name="robots" content="noindex, nofollow" /> […]

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Most all WordPress theme’s use a a simple search form to search your site. But what it you wanted to search your whole site and not just your posts. Search Unleashed comes into the picture. Search Unleashed performs searches across all data, including that added by plugins. Some features of this plugin are: Full text […]

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The Iowa Supreme Court approved a pilot program in the 4th Judicial District — Audubon, Cass, Fremont, Harrison, Mills, Montgomery, Pottawattamie, Page and Shelby counties — to develop procedures for the use of electronic search warrants.

Electronic search warrants will reduce the time required to obtain warrants, reduce travel time by law enforcement and make more effective use of judges’ time, according to the order. Paper warrants require law enforcement to fill out application forms and then leave the scene of the potential search and drive to find a judge, either at a courthouse during business hours or their home after hours. If the judge grants the warrant, then the officer has to drive back to the scene to execute it.

The electronic warrants can be submitted to a judge from a squad car computer, which is more efficient for law enforcement and the judges.

The pilot program will be evaluated by the court annually and will continue until further notice.

Fourth Judicial District Chief Judge Jeff Larson, who was on the advisory committee to develop recommendations for the new process, talked about the project, which will start in the next few weeks.

Page County Chief Deputy Charles McCalla, 6th Judicial Associate District Judge Nicholas Scott, Linn County Sheriff Capt. Greg McGivern and Marion police Lt. Scott Elam also provided their thoughts about electronic search warrants.

Q: Iowa courts started going paperless in 2010, so why did it take so long to get a pilot program for electronic search warrants?

A: Larson: It had been discussed at various levels since (the electronic document management system) started. We should take advantage of the electronic process because it will save us money. Most law enforcement agencies are now used to filing electronic citations from their patrol cars and offices. There may have been some pushback a few years ago because some counties or offices didn’t have computer scanners and needed technology. Now, the rural offices have that technology.

Q: As a task force member working on this program, what were the hurdles?

A: Larson: It was just working through the procedural issues to make sure there would be a safeguard throughout the process. When a search warrant is needed, law enforcement has to fill out the search warrant package, including the application with all the pertinent information, and submit it to a magistrate judge, associate or district judge in their judicial district. Then the officer or deputy can just call the judge to alert him/her to the warrant and the judge can ask for any additional information needed. The judge then administers the oath of office over the phone and signs off or denies the warrant. Law enforcement doesn’t have to leave the crime scene and can print off the warrant from their squad car computer.

The process of going to electronic warrants started in 2017, when the lawmakers amended the law to allow those to be submitted electronically, and then in 2018, the state court administrator’s office set up an advisory committee to develop recommendations.

Q: What has been the process to get a search warrant?

A: Larson: Law enforcement would have to leave the scene, fill out paperwork and then, many times, travel miles to go to the courthouse to have the judge sign it or if it’s after hours, go to a judge’s home. The officer may not be in the same county as the courthouse where the judge works or where the judge lives. (It) can take a lot of time. The process is way overdue.

Q: Page County Sheriff’s Chief Deputy Charles McCalla, what do you see as the biggest advantage for filing them electronically?

A: McCalla: The smaller counties have limited manpower, and some of the judges, like in Mills County, may be 60 to 70 miles away if a search warrant is needed after hours. Just traveling across the county can take time, depending where you are. At a minimum, we probably have to drive 30 minutes and up to an hour to get to a judge. This will save us time, money for travel and provide safety because we can stay at the scene to ensure the evidence hasn’t been tampered with.

Q: Is there a recent incident where an electronic search warrant may have helped?

A: McCalla: A few weeks ago, there was a theft report for a stolen chain saw and deputies went to the home and saw guns all over the house and they knew the guy who lived there had been convicted. They didn’t want to tip him off, so they just left the scene and went to get a search warrant. Luckily, the evidence was still there when they came back. They found about 90 guns.

Q: How do you feel about being the “guinea pigs” for the process?

A: McCalla: Happy to be. As law enforcement, we’re natural fixers. We find solutions. And this is an idea time to use the process during the COVID-19 pandemic to keep everyone safe. We won’t have to have any face-to-face contact with the judges.

Q: Is Linn County excited about the program, once it’s tested and used across the state?

A: Scott: I think many of us in the criminal justice system are eagerly awaiting the results of the pilot. They have the potential to make the system more efficient. It is in the interest of the police and the suspect, who is often detained pending a warrant, to get the search warrant application reviewed by a judge as soon as possible. A potential benefit is that officers could also use those more often, which protects citizens from unlawful search and seizures if a judge first reviews the evidence.

A: McGivern: I believe the implementation will be a much faster and efficient process for deputies. Like any new process, there may need to be some revisions that will have to be worked out, but I look forward to it.

A: Elam: We’ve done it this way for a long time, and it can be a bit of a haul for us, depending who’s on call (among the judges) — after hours. It’s nice to see there’s a pilot. The concern would be if something goes wrong in the process. If the internet is down or something else. Now, we have to go from Marion to the Linn County Courthouse. Then we go to the county attorney’s office to get a prosecutor to review the warrant and then find a judge (in courthouse during business hours). That takes some time. If you can type out the application from your car right at the scene, it would help with details on the warrant — describing the structure or property needing be searched. I just hope they work out all the bugs first.

Comments: (319) 398-8318; trish.mehaffey@thegazette.com

Seasonal Worker Programme and Pacific Labour Scheme workers can extend their stay for up to 12 months to work for approved employers as long as pastoral care and accommodation needs of workers are met to minimise health risks to visa holders and the community. Approved employers under the Seasonal Worker Programme and Pacific Labour Scheme […]

The post What can I do if I am on a working holiday or seasonal worker visa in the Coronavirus (COVID-19) crisis? appeared first on Visa Australia - Immigration Lawyers & Registered Migration Agents.

Refresh Seattle – February 2014 First off, what is Refresh? According to their website… Refresh Seattle is a community of designers and developers working to refresh the creative, technical, and professional culture of New Media endeavors in the Seattle/Puget Sound area. Promoting design, technology, usability, and standards, Refresh Seattle is a part of Refresh and […]

Suicide attempts common in post-concussion patients, says Dr. Charles Tator of the Canadian Concussion Centre

Patterns can be a powerful way to quickly add some real texture to your artwork with very minimal effort. In one-click you have beautiful texture overlays that will...

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Having too many WordPress themes to choose among is of course better than having too few. But there are times when searching for what you really need is like looking for the proverbial needle in the haystack. If you’ve been looking for a top-of-the-line multipurpose theme you will probably find it right here. We’ve listed […]

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By Lauren McCauley Common Dreams Even scientists who question findings say ‘we ignore James Hansen at our peril.’ Dr. James Hansen, the former NASA scientist who is widely credited with being one of the first to raise concerns about human-caused … Continue reading →

Video by NASA’s Goddard Space Flight Center / Jefferson Beck Arctic sea ice has not only been shrinking in surface area in recent years, it’s becoming younger and thinner as well. In this animation, where the ice cover almost looks … Continue reading →

By Hannah Hickey UWNEWS While winter sea ice in the Arctic is declining so dramatically that ships can now navigate those waters without any icebreaker escort, the scene in the Southern Hemisphere is very different. Sea ice area around Antarctica … Continue reading →

By David Suzuki David Suzuki Foundation The fossil fuel era must end, or it will spell humanity’s end. The threat isn’t just from pollution and accelerating climate change. Rapid, wasteful exploitation of these valuable resources has also led to a … Continue reading →

Some of the problems we work on as UX researchers are simple and are easily solved by getting users in front of our product. But other problems can be complex and it's hard to know how to start solving them. In situations like that, a simple 2x2 diagram can cut through the 'what ifs', the 'how abouts' and the edge cases and provide a simple way of looking at the problem. Here are 10 examples of 2x2 diagrams to simplify UX research discussions.

If you compare the UX research methods we use today with the methods we used 16 years ago, something interesting emerges. We see that UX research is becoming increasingly remote and increasingly unmoderated. In other words, we're moving to a world where UX research is becoming automated. We can learn a lot from automated research. But it comes at the price of understanding our users.

When carried out in a lab, user experience research is gear heavy. You need technology to record audio, video and the screen of the device under test. In contrast, when carried out in the field, user experience research is more lightweight. Even so, there are a few non-obvious items of kit that I find essential on a field visit.

Doing UX research in a university is very different to doing UX research in a business setting. If you're an academic making the leap, what are the main differences you need to keep in mind?

Whether you call it a field visit, a contextual inquiry or a customer discovery interview, the goal of early stage research is the same: to uncover users' needs. Here are 5 mistakes I've seen crop up time and again in this kind of research.

So many of us are going along on the path that we think we want, only to realize that something is missing. The same was true for today’s guest, Chelsea Yamase (@chelseakauai) who found herself heading into a potential career that was slowly killing her soul. Through a winding path of architecture, graphic design, journalism, and a myriad of side hustles, she found herself faced with the big question: pursue the unconventional life of your dreams or stick to a “real job”. She lept. Today, Chelsea is a sought after model, photographer, influencer and movement enthusiast from Hawaii with a focus on mindful living. She’s been featured in Travel and Leisure, Cosmopolitan, Condé Nast Traveler, to name a few, and and worked with numerous brands such as Canon USA, Adidas, Google, Athleta, GoPro, DJI Global and The National Parks Foundation. In this episode: How to give yourself structure that can help you take a leap into an unconventional lifestyle What can you make with what’s around you? Constraints are a path to creativity and a key gaining new perspectives As money and opportunities come in, how do you stay in alignment with your values and the work you really want […]

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Today on the show, I’m chatting with New York Times bestselling author Mark Manson. He is the #1 New York Times Bestselling author of Everything is F*cked and The Subtle Art of Not Giving a F*ck, the mega-bestseller that reached #1 in fourteen different countries. Mark also runs one of the largest personal growth websites in the world, MarkManson.net, a blog with more than two million monthly readers and half a million subscribers, making him one of the largest and most successful independent publishers in the world. In this episode, we take a deep dive into the creative process. How to spend your time when you’re trying get comfortable with being uncomfortable. Mark helps bring into focus the up-side that this moment has created for us while also sharing some of the tactics he while quarantined. Enjoy! FOLLOW MARK: instagram | twitter | website Listen to the Podcast Subscribe   This podcast is brought to you by CreativeLive. CreativeLive is the world’s largest hub for online creative education in photo/video, art/design, music/audio, craft/maker, money/life and the ability to make a living in any of those disciplines. They are high quality, highly curated classes taught by the world’s top experts — Pulitzer, Oscar, […]

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Robots operating in household environments must find objects on shelves, under tables, and in cupboards. Previous work often formulate the object search problem as a POMDP (Partially Observable Markov Decision Process), yet constrain the search space in 2D. We propose a new approach that enables the robot to efficiently search for objects in 3D, taking occlusions into account. We model the problem as an object-oriented POMDP, where the robot receives a volumetric observation from a viewing frustum and must produce a policy to efficiently search for objects. To address the challenge of large state and observation spaces, we first propose a per-voxel observation model which drastically reduces the observation size necessary for planning. Then, we present a novel octree-based belief representation which captures beliefs at different resolutions and supports efficient exact belief update. Finally, we design an online multi-resolution planning algorithm that leverages the resolution layers in the octree structure as levels of abstractions to the original POMDP problem. Our evaluation in a simulated 3D domain shows that, as the problem scales, our approach significantly outperforms baselines without resolution hierarchy by 25%-35% in cumulative reward. We demonstrate the practicality of our approach on a torso-actuated mobile robot searching for objects in areas of a cluttered lab environment where objects appear on surfaces at different heights.

Deep neural networks have exhibited promising performance in image super-resolution (SR). Most SR models follow a hierarchical architecture that contains both the cell-level design of computational blocks and the network-level design of the positions of upsampling blocks. However, designing SR models heavily relies on human expertise and is very labor-intensive. More critically, these SR models often contain a huge number of parameters and may not meet the requirements of computation resources in real-world applications. To address the above issues, we propose a Hierarchical Neural Architecture Search (HNAS) method to automatically design promising architectures with different requirements of computation cost. To this end, we design a hierarchical SR search space and propose a hierarchical controller for architecture search. Such a hierarchical controller is able to simultaneously find promising cell-level blocks and network-level positions of upsampling layers. Moreover, to design compact architectures with promising performance, we build a joint reward by considering both the performance and computation cost to guide the search process. Extensive experiments on five benchmark datasets demonstrate the superiority of our method over existing methods.

For safety-critical black-box optimization tasks, observations of the constraints and the objective are often noisy and available only for the feasible points. We propose an approach based on log barriers to find a local solution of a non-convex non-smooth black-box optimization problem $min f^0(x)$ subject to $f^i(x)leq 0,~ i = 1,ldots, m$, at the same time, guaranteeing constraint satisfaction while learning an optimal solution with high probability. Our proposed algorithm exploits noisy observations to iteratively improve on an initial safe point until convergence. We derive the convergence rate and prove safety of our algorithm. We demonstrate its performance in an application to an iterative control design problem.

Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digital Twin is defined extensively but is best described as the effortless integration of data between a physical and virtual machine in either direction. The challenges, applications, and enabling technologies for Artificial Intelligence, Internet of Things (IoT) and Digital Twins are presented. A review of publications relating to Digital Twins is performed, producing a categorical review of recent papers. The review has categorised them by research areas: manufacturing, healthcare and smart cities, discussing a range of papers that reflect these areas and the current state of research. The paper provides an assessment of the enabling technologies, challenges and open research for Digital Twins.

Showing items that do not match search query intent degrades customer experience in e-commerce. These mismatches result from counterfactual biases of the ranking algorithms toward noisy behavioral signals such as clicks and purchases in the search logs. Mitigating the problem requires a large labeled dataset, which is expensive and time-consuming to obtain. In this paper, we develop a deep, end-to-end model that learns to effectively classify mismatches and to generate hard mismatched examples to improve the classifier. We train the model end-to-end by introducing a latent variable into the cross-entropy loss that alternates between using the real and generated samples. This not only makes the classifier more robust but also boosts the overall ranking performance. Our model achieves a relative gain compared to baselines by over 26% in F-score, and over 17% in Area Under PR curve. On live search traffic, our model gains significant improvement in multiple countries.

This paper proposes a faceted information exploration model that supports coarse-grained and fine-grained focusing of geographic maps by offering a graphical representation of data attributes within interactive widgets. The proposed approach enables (i) a multi-category projection of long-lasting geographic maps, based on the proposal of efficient facets for data exploration in sparse and noisy datasets, and (ii) an interactive representation of the search context based on widgets that support data visualization, faceted exploration, category-based information hiding and transparency of results at the same time. The integration of our model with a semantic representation of geographical knowledge supports the exploration of information retrieved from heterogeneous data sources, such as Public Open Data and OpenStreetMap. We evaluated our model with users in the OnToMap collaborative Web GIS. The experimental results show that, when working on geographic maps populated with multiple data categories, it outperforms simple category-based map projection and traditional faceted search tools, such as checkboxes, in both user performance and experience.

With the continued digitalization of societal processes, we are seeing an explosion in available data. This is referred to as big data. In a research setting, three aspects of the data are often viewed as the main sources of challenges when attempting to enable value creation from big data: volume, velocity and variety. Many studies address volume or velocity, while much fewer studies concern the variety. Metric space is ideal for addressing variety because it can accommodate any type of data as long as its associated distance notion satisfies the triangle inequality. To accelerate search in metric space, a collection of indexing techniques for metric data have been proposed. However, existing surveys each offers only a narrow coverage, and no comprehensive empirical study of those techniques exists. We offer a survey of all the existing metric indexes that can support exact similarity search, by i) summarizing all the existing partitioning, pruning and validation techniques used for metric indexes, ii) providing the time and storage complexity analysis on the index construction, and iii) report on a comprehensive empirical comparison of their similarity query processing performance. Here, empirical comparisons are used to evaluate the index performance during search as it is hard to see the complexity analysis differences on the similarity query processing and the query performance depends on the pruning and validation abilities related to the data distribution. This article aims at revealing different strengths and weaknesses of different indexing techniques in order to offer guidance on selecting an appropriate indexing technique for a given setting, and directing the future research for metric indexes.

Rescue vessels are the main actors in maritime safety and rescue operations. At the same time, aerial drones bring a significant advantage into this scenario. This paper presents the research directions of the AutoSOS project, where we work in the development of an autonomous multi-robot search and rescue assistance platform capable of sensor fusion and object detection in embedded devices using novel lightweight AI models. The platform is meant to perform reconnaissance missions for initial assessment of the environment using novel adaptive deep learning algorithms that efficiently use the available sensors and computational resources on drones and rescue vessel. When drones find potential objects, they will send their sensor data to the vessel to verity the findings with increased accuracy. The actual rescue and treatment operation are left as the responsibility of the rescue personnel. The drones will autonomously reconfigure their spatial distribution to enable multi-hop communication, when a direct connection between a drone transmitting information and the vessel is unavailable.

Recently, the outbreak of Coronavirus Disease 2019 (COVID-19) has spread rapidly across the world. Due to the large number of affected patients and heavy labor for doctors, computer-aided diagnosis with machine learning algorithm is urgently needed, and could largely reduce the efforts of clinicians and accelerate the diagnosis process. Chest computed tomography (CT) has been recognized as an informative tool for diagnosis of the disease. In this study, we propose to conduct the diagnosis of COVID-19 with a series of features extracted from CT images. To fully explore multiple features describing CT images from different views, a unified latent representation is learned which can completely encode information from different aspects of features and is endowed with promising class structure for separability. Specifically, the completeness is guaranteed with a group of backward neural networks (each for one type of features), while by using class labels the representation is enforced to be compact within COVID-19/community-acquired pneumonia (CAP) and also a large margin is guaranteed between different types of pneumonia. In this way, our model can well avoid overfitting compared to the case of directly projecting highdimensional features into classes. Extensive experimental results show that the proposed method outperforms all comparison methods, and rather stable performances are observed when varying the numbers of training data.

In this paper, we continue our prior work on using imitation learning (IL) and model free reinforcement learning (RL) to learn driving policies for autonomous driving in urban scenarios, by introducing a model based RL method to drive the autonomous vehicle in the Carla urban driving simulator. Although IL and model free RL methods have been proved to be capable of solving lots of challenging tasks, including playing video games, robots, and, in our prior work, urban driving, the low sample efficiency of such methods greatly limits their applications on actual autonomous driving. In this work, we developed a model based RL algorithm of guided policy search (GPS) for urban driving tasks. The algorithm iteratively learns a parameterized dynamic model to approximate the complex and interactive driving task, and optimizes the driving policy under the nonlinear approximate dynamic model. As a model based RL approach, when applied in urban autonomous driving, the GPS has the advantages of higher sample efficiency, better interpretability, and greater stability. We provide extensive experiments validating the effectiveness of the proposed method to learn robust driving policy for urban driving in Carla. We also compare the proposed method with other policy search and model free RL baselines, showing 100x better sample efficiency of the GPS based RL method, and also that the GPS based method can learn policies for harder tasks that the baseline methods can hardly learn.

Making changes to a program to optimize its performance is an unscalable task that relies entirely upon human intuition and experience. In addition, companies operating at large scale are at a stage where no single individual understands the code controlling its systems, and for this reason, making changes to improve performance can become intractably difficult. In this paper, a learning system is introduced that provides AI assistance for finding recommended changes to a program. Specifically, it is shown how the evaluative feedback, delayed-reward performance programming domain can be effectively formulated via the Monte Carlo tree search (MCTS) framework. It is then shown that established methods from computational games for using learning to expedite tree-search computation can be adapted to speed up computing recommended program alterations. Estimates of expected utility from MCTS trees built for previous problems are used to learn a sampling policy that remains effective across new problems, thus demonstrating transferability of optimization knowledge. This formulation is applied to the Apache Spark distributed computing environment, and a preliminary result is observed that the time required to build a search tree for finding recommendations is reduced by up to a factor of 10x.

You'll be forgiven if, during the daily deluge of COVID-19-related updates, you didn't notice that some seriously great musicians recently booked shows in and around Spokane for later in the year.…

We've known that Hamilton was going to be part of the 2020-21 STCU Best of Broadway season for a while, but now we finally know the exact dates, as well as the rest of the featured shows for the season. Granted, the whole world has changed since WestCoast Entertainment announced Hamilton was coming to town back when they announced their 2019-20 season — a season that's been roiled, along with the rest of our lives, by the coronavirus pandemic.…

A catastrophic loss in biodiversity, reckless destruction of wildland and warming temperatures have allowed disease to explode. Ignoring the connection between climate change and pandemics would be “dangerous delusion,” one scientist said. The scientists who study how diseases emerge in a changing environment knew this moment was coming.…

It’s March. The regular season is now in the rearview mirror.…

Methods and arrangements for conducting a search using query logs. A query log is consulted and query rewrite rules are learned automatically based on data in the query log. The learning includes obtaining click-through data present in the query log.

Methods, systems, and computer-readable media for providing topical search suggestions are provided. Topical search suggestions allow a user to receive search results related to the designated topic or subject matter. The present invention may generate multiple topics based on search input provided by a user. The search input may be a search prefix that includes one or more words entered into the search query box before the completed search query is submitted to the search engine. A search interface then presents the topics derived from the search prefix to a user before the user submits the query. In another embodiment, the user designates multiple search inputs. The present invention generates search results based on the search inputs and then presents topics extracted from the search results. In one embodiment, the topics are extracted by performing a natural language analysis of search result metadata.

The present invention pertains to an additive combination comprising at least two sterically hindered amines, at least one further stabilizer, a dispersing agent and a plasticizer. The present invention also pertains to a composition comprising an organic material susceptible to degradation by light, oxygen and/or heat, and the additive combination and to the use and the process for stabilizing organic material against degradation by light, oxygen and/or heat by the additive combination.

A coating/sealant system that includes a coating and a sealant deposited over at least a portion of the coating, in which the coating includes a reaction product formed from reactants comprising a phosphated epoxy resin and a curing agent, and the sealant includes a sulfur-containing polymer.