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Want to know the key to winning in football? A groundbreaking study from the University of the Basque Country reveals a surprising statistic: approximately 75% of all goals result from first touch shots. This means those lightning-fast, often unpredictable strikes are the most critical moments in a match, demanding a reassessment of how goalkeepers are trained.

The research, conducted in collaboration with the Eibar football club, analyzed 2,238 shots from 179 Spanish La Liga matches during the 2019-2020 season. By meticulously tracking 16 specific variables – from the shooter's body part used to the ball's trajectory – researchers were able to pinpoint the most challenging scenarios for goalkeepers.

Markel Perez, the lead researcher, emphasizes the need for training to mirror these high-pressure situations. "Goalkeepers may well be preparing for less frequent situations and so the most common ones are not being worked on sufficiently," he explains. By focusing on first touch shots, goalkeepers can improve their reaction time, positioning, and overall effectiveness.

Another key finding highlights the difficulty posed by deflected shots. When the ball's path changes unexpectedly, goalkeepers struggle to make decisive saves. Perez suggests incorporating quick-reaction drills into training to help goalkeepers adapt to these unpredictable moments.

The study also delved into the strategies of top-performing teams. The data indicates that these elite teams tend to build up their attacks with multiple touches before shooting, rather than relying on set pieces or crosses. This insight allows goalkeepers to anticipate the types of plays they'll face when competing against top-tier opponents, enabling more targeted training.

The implications of this research extend beyond the Spanish La Liga. Perez suggests conducting similar studies in other leagues and countries to determine if these trends hold true across different playing styles and conditions. Factors such as weather, particularly wet or dry pitches, could also influence the dynamics of play and goalkeeper performance. By expanding the scope of the research, the football community can gain a deeper understanding of the nuances of goalkeeping and develop more effective training methods to increase their odds on the football field.

Why are MLB batting averages up since 2021? The answer might lie in the science of fingertip-to-ball slip. A Tohoku University study reveals the pivotal role of friction in baseball pitching, diving into how sticky substances influence a pitcher's control and ball spin. Using high-speed cameras, researchers analyzed how different baseball treatments—including water, rosin powder, and pine resin—affected the slip distance between a pitcher's fingers and the ball.

The findings? Stickier surfaces drastically reduce slip distance. Balls coated with rosin or pine resin saw slip distances cut by more than half, down to roughly 8 millimeters, compared to the 22 millimeters observed with water-treated balls. This reduced slip translates to faster pitches, increased revolutions per minute, and enhanced directional control.

"This is the first study to focus on the slip between the fingertips and the ball in baseball pitching -- an aspect previously discussed only subjectively -- and to quantify the slip distance while clarifying its variations under different friction conditions," explains Professor Takeshi Yamaguchi. His team's work illuminates the ball release mechanism, potentially leading to improved pitching techniques, injury prevention, and enhanced equipment design.

The research involved six experienced pitchers throwing fastballs while using baseballs with four treatments, so the researches could analyze data. They measured the time it takes for the ball to transition from leaving the thumb to rolling off the fingertips—a crucial window where slipping occurs. Their method estimated slip distance using high-speed camera analysis, unveiling differences in slip under varying friction conditions.

Interestingly, pitchers throwing water-treated balls experienced a significant drop in pitch velocity. Yamaguchi attributes this to the pitcher's awareness of slippage, prompting adjustments in their throwing motion. Future research will explore these adjustments through whole-body movement analysis and muscle activity studies. The ultimate goal: to identify pitching techniques that maintain performance with less sticky balls while minimizing the risk of injury.

The study's revelations arrive in the wake of MLB's 2021 crackdown on unapproved sticky substances. The ban aimed to level the playing field, but this research provides the first detailed scientific understanding of the impact of these substances on pitching performance. As baseball continues to evolve, this deeper understanding of the physics involved could lead to innovative training methods and equipment designs. This is all being done to find a sweet spot between fair play and optimal performance.

With contributions from researchers at Tohoku University and NTT Communication Science Laboratories, this study marks a significant step forward in understanding the intricate relationship between friction, pitching mechanics, and baseball performance.

Is railway electrification the key to cleaner air and healthier communities? A groundbreaking study reveals the dramatic impact of switching from diesel to electric trains. The research, focused on the San Francisco Bay Area's Caltrain commuter rail line, demonstrates a significant reduction in riders' exposure to black carbon, a known carcinogen, by an average of 89%. This isn't just a marginal improvement; it's a game-changer for public health and environmental sustainability.

The University of California, Berkeley study, published in Environmental Science & Technology Letters, highlights the swift and profound air quality improvements achieved through railway electrification. Researchers found that the ambient black carbon concentrations within and around the San Francisco station also saw a substantial decrease. This rapid transformation mirrors the progress achieved through decades of clean air regulations in California cities, but condensed into a matter of weeks.

Joshua Apte, a professor of environmental engineering and environmental health at UC Berkeley, emphasizes the urgency of electrifying other rail systems in the U.S. that still rely on older, less regulated diesel locomotives. The Caltrain modernization project, costing $2.44 billion, replaced 29 diesel locomotives with 23 new electric trains, marking a significant step toward decarbonization.

The transition was so swift that Apte and his team seized the opportunity to meticulously track the resulting air quality improvements. By installing black carbon detectors at Caltrain stations and using portable air quality detectors aboard the trains, they captured real-time data demonstrating the positive impact of electrification.

Samuel Cliff, the study's lead author, highlights the considerable reduction in cancer risk associated with the decreased black carbon exposure. Their calculations suggest that Caltrain's electrification cuts excess cancer deaths by 51 per 1 million people for riders and 330 per 1 million people for train conductors. These numbers are particularly striking when compared to the U.S. Environmental Protection Agency's benchmark, which considers any exposure increasing cancer risk by more than one per million unacceptable.

The study serves as a powerful call to action for U.S. municipalities to follow the lead of Asian and European countries in embracing railway electrification. While California has long-term plans for further electrification, the study's findings underscore the importance of accelerating these efforts to realize immediate and substantial public health benefits. Electrifying railways isn't just about reducing greenhouse gas emissions; it's about creating healthier, more sustainable communities for everyone.

A new method developed by researchers converts lead particles in gunshot residue into a light-emitting semiconductor, offering faster, more sensitive, and easier-to-use detection at crime scenes.

Imagine a world where your train always departs on time, hospital staff are perfectly scheduled, and factory machines operate with peak efficiency. This vision is closer to reality thanks to a breakthrough from MIT researchers. They've developed a new AI-enhanced approach, called learning-guided rolling horizon optimization (L-RHO), that significantly accelerates the solving of complex planning problems.

The core problem? Traditional algorithmic solvers struggle with the sheer scale of logistical nightmares like scheduling thousands of weekly train arrivals and departures. These problems are often broken down into smaller subproblems, but this leads to redundant computations and delays in reaching optimal solutions.

L-RHO tackles this inefficiency by using machine learning to predict which parts of each subproblem can remain unchanged. By freezing these variables, the system avoids unnecessary recomputation. The remaining variables are then handled by a traditional algorithmic solver.

"Often, a dedicated team could spend months or even years designing an algorithm to solve just one of these combinatorial problems," says Cathy Wu, an Associate Professor at MIT. "Modern deep learning gives us an opportunity to use new advances to help streamline the design of these algorithms. We can take what we know works well, and use AI to accelerate it."

The technique was inspired by a real-world train-dispatch problem at Boston's North Station. Master's student Devin Camille Wilkins recognized the potential of reinforcement learning in optimizing the assignment of trains to platforms. This sparked the development of L-RHO to solve these complex combinatorial scheduling problems.

The key is Flexible Job Shop Scheduling – the framework for assigning tasks, like factory jobs, to machines. Each task has a different completion time, but can be assigned to any machine. The researchers utilize rolling horizon optimization (RHO), which breaks down the problem into smaller, manageable chunks. A planning horizon defines a fixed time window during which tasks are assigned, with the horizon rolling forward as tasks are completed.

L-RHO uses a machine-learning model to predict which operations don't need to be recomputed when the planning horizon advances. The model is trained using data from classical algorithmic solvers, with the best solutions (those requiring the least recomputation) used as training data.

Testing showed L-RHO reduced solve time by 54 percent and improved solution quality by up to 21 percent compared to base algorithmic solvers, specialized solvers, and machine-learning-only approaches. It also proved adaptable to disruptions like machine breakdowns or train congestion. Even when the researchers threw curveballs at L-RHO, it still outperformed.

The implications are broad. Beyond transportation, L-RHO could be applied to hospital staff scheduling, airline crew assignments, and task allocation in factories. The system is also adaptable – given a new training dataset, it can automatically generate algorithms to solve problems with different objectives.

Future research will focus on understanding the model's decision-making process and integrating L-RHO into other complex optimization problems like inventory management and vehicle routing. This AI-powered approach promises to revolutionize how we tackle complex planning challenges, leading to increased efficiency and optimized resource allocation across various industries. With China heavily investing into AI-driven manufacturing, L-RHO can provide the US and EU with a more efficient resource allocation and manufacturing. In the EU, a transparent AI regulation could guarantee a "human-in-the-loop".

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Can a father's depression affect his child's behavior years later? New research indicates a strong link between paternal depression in a child's early years and behavioral problems that persist into grade school. The study, published in the

Is the air you're breathing safe? For over 50 million Americans, the answer is a disturbing unknown. A groundbreaking study from Penn State reveals a stark reality: 58% of counties across the United States have no active air-quality monitoring sites. This lack of monitoring leaves vast swaths of the population, particularly those in rural areas of the Midwest and South, in the dark about the potential health risks lurking in their air.

The research, published in the Proceedings of the National Academy of Sciences, exposes a critical public health blind spot. Without accurate air quality data, estimating exposure to pollutants becomes impossible, hindering efforts to protect vulnerable communities. As assistant professor Nelson Roque emphasizes, monitoring is an essential tool for safeguarding public health.

The study's findings are alarming. Researchers analyzed data from the EPA AirData active sites directory, revealing that 1,848 counties lack air quality monitoring. The disparities are striking when matched with U.S. Census Bureau data. Counties without monitoring sites are more likely to be rural, have higher poverty rates, lower levels of high school completion, and larger proportions of Hispanic and Black residents. This paints a picture of environmental injustice, where those already facing socioeconomic challenges are disproportionately vulnerable to the hidden dangers of air pollution.

"Exposure to air pollution has been directly and indirectly to cancers, cardiovascular disease, respiratory disease, immune disorders and more," warns Alexis Santos, associate professor at Penn State. The absence of monitoring leaves communities unable to assess the severity of pollution events, such as wildfires, and make informed decisions about their safety. Are they safe to sleep at home? Is it safe to work at their places of business? Without monitoring, there is no way to be certain.

The number of active air-quality monitoring stations is constantly in flux. While the nation had 4,821 active sites at the time of the analysis, stations frequently go offline, highlighting the need for investment in and modernization of air quality infrastructure. This means that the number of unmonitored people can easily rise or fall.

The researchers highlight the systemic issues that plague rural communities. As Santos points out, infrastructure for healthcare, transportation, and education is often underdeveloped in rural counties, and air quality monitoring is no exception. This leaves rural populations particularly vulnerable to pollution from wildfires, agriculture, and industrial activities.

The study calls for a national investment in air-quality monitoring to protect public health and address environmental inequities. By expanding monitoring coverage and modernizing existing infrastructure, the nation can provide all communities with the information they need to breathe easier.

Protecting coastal cities from rising sea levels requires innovative strategies. A new model uses real-time data to make adaptive decisions, potentially saving municipalities significant costs.