Globally, infertility rates are increasing, with 2.5\% of all births being assisted by in vitro fertilisation (IVF) in 2022. Male infertility is the cause for approximately half of these cases. The quality of sperm DNA has substantial impact on the success of IVF. The assessment of sperm DNA is traditionally done through chemical assays which render sperm cells ineligible for IVF. Many compounding factors lead to the population crisis, with fertility rates dropping globally in recent history. As such assisted reproductive technologies (ART) have been the focus of recent research efforts. Simultaneously, artificial intelligence has grown ubiquitous and is permeating more aspects of modern life. With the advent of state-of-the-art machine learning and its exceptional performance in many sectors, this work builds on these successes and proposes a novel framework for the prediction of sperm cell DNA fragmentation from images of unstained sperm. Rendering a predictive model which preserves sperm integrity and allows for optimal selection of sperm for IVF.

Knowledge Graphs (KGs) have been used to organize large datasets into structured, interconnected information, enhancing data analytics across various fields. In the legislative context, one potential natural application of KGs is modeling the intricate set of interconnections that link laws and their articles with each other and the broader legislative context. At the same time, the rise of large language models (LLMs) such as GPT has opened new opportunities in legal applications, such as text generation and document drafting. Despite their potential, the use of LLMs in legislative contexts is critical since it requires the absence of hallucinations and reliance on up-to-date information, as new laws are published on a daily basis. This work investigates how Legislative Knowledge Graphs and LLMs can synergize and support legislative processes. We address three key questions: the benefits of using KGs for legislative systems, how LLM can support legislative activities by ensuring an accurate output, and how we can allow non-technical users to use such technologies in their activities. To this aim, we develop Legis AI Platform, an interactive platform focused on Italian legislation that enhances the possibility of conducting legislative analysis and that aims to support lawmaking activities.

Deep Neural Networks (DNNs) have achieved state of the art results and even outperformed human accuracy in many challenging tasks, leading to DNNs adoption in a variety of fields including natural language processing, pattern recognition, prediction, and control optimization. However, DNNs are accompanied by uncertainty about their results, causing them to predict an outcome that is either incorrect or outside of a certain level of confidence. These uncertainties stem from model or data constraints, which could be exacerbated by adversarial attacks. Adversarial attacks aim to provide perturbed input to DNNs, causing the DNN to make incorrect predictions or increase model uncertainty. In this review, we explore the relationship between DNN uncertainty and adversarial attacks, emphasizing how adversarial attacks might raise DNN uncertainty.

Environmental hazards place certain individuals at disproportionately higher risks. As these hazards increasingly endanger human health, precise identification of the most vulnerable population subgroups is critical for public health. Moderated multiple regression (MMR) offers a straightforward method for investigating this by adding interaction terms between the exposure to a hazard and other population characteristics to a linear regression model. However, when the vulnerabilities are hidden within a cross-section of many characteristics, MMR is often limited in its capabilities to find any meaningful discoveries. Here, we introduce a hybrid method, named regression-guided neural networks (ReGNN), which utilizes artificial neural networks (ANNs) to non-linearly combine predictors, generating a latent representation that interacts with a focal predictor (i.e. variable measuring exposure to an environmental hazard). We showcase the use of ReGNN for investigating the population heterogeneity in the health effects of exposure to air pollution (PM2.5) on cognitive functioning scores. We demonstrate that population heterogeneity that would otherwise be hidden using traditional MMR can be found using ReGNN by comparing its results to the fit results of the traditional MMR models. In essence, ReGNN is a novel tool that enhances traditional regression models by effectively summarizing and quantifying an individual's susceptibility to health risks.

Witnesses described unthinkable scenes of heavy flooding in northern Italy as Storm Boris continued its journey across Europe on Thursday. People were seen climbing on roofs to escape the water as buildings collapsed in Traversara di Bagnacavallo. The Italian emergency services carried out helicopter rescues after what one eyewitness said was 36 hours of rain. Storm Boris had earlier swept across Poland, the Czech Republic, Romania and Austria, killing at least 23 people. One of Kyiv's main government buildings was hit in overnight missile and drone strikes by Russia.

Surgeon'became robotic' to treat sheer volume of wounded Lebanese A Lebanese surgeon has described how the sheer volume of severe wounds from two days of exploding device attacks forced him to act robotic just to be able to keep working. Surgeon Elias Jaradeh said he treated women and children but most of the patients he saw were young men. The surgeon said a large proportion were "severely injured" and many had lost the sight in both eyes. The dead and injured in Lebanon include fighters from Hezbollah - the Iranian backed armed group which has been trading cross-border fire with Israel for months and is classed as a terrorist organisation by the UK and the US. But members of their families have also been killed or wounded, along with innocent bystanders.

Things to Do in L.A. Tap to enable a layout that focuses on the article. Gabriel Zendejas Chavez leaves the federal courthouse in downtown Los Angeles. Indicted in 2018 in an investigation of the Mexican Mafia's rackets in L.A. County jails, Chavez pleaded guilty in federal court to a rarely filed charge called "misprision of a felony." A lawyer accused of helping members of the Mexican Mafia traffic drugs, collect extortion money and expose government informants pleaded guilty Thursday in a deal with prosecutors that may spare him prison time. Gabriel Zendejas Chavez, who was indicted in 2018 in an investigation of the Mexican Mafia's rackets in L.A. County jails, told U.S. District Judge George Wu he was guilty of a rarely filed charge of "misprision of a felony."

Prince Harry says his father King Charles is'great' following their first meeting in 19 months... which was over a cup of tea and just 55 minutes long A DEI mayor, an inconvenient crime and video they never wanted you to see: MAUREEN CALLAHAN knows why the Left has sympathy for that killer... but none for his victim Tragedy as Charlie Kirk's wife left behind with two young children after conservative activist is fatally shot Sweater weather starts here - the cozy, chic pieces from Soft Surroundings you'll actually wear all season Fox News reveals new lineup and elevates star White House reporter who's sparred with Trump I tried the 30 cent'miracle chill pill' before a big event.. now I'm taking it for everything Carlos Alcaraz's new girlfriend revealed after US Open triumph... amid Emma Raducanu rumors Kimberly Guilfoyle urged to'stop with the lips' as she shows off drastic new look Knifeman accused of stabbing Ukrainian refugee to death gives chilling reason for the attack... as he speaks for the first time from jail on the murder that shocked America We only had one symptom we dismissed... but then we were diagnosed with the rarest form of melanoma MSNBC sparks outrage for'disgusting' Charlie Kirk comments following Utah shooting I was thrilled to finally sit in the cuck chair... now I fear my fantasy has destroyed my marriage: DEAR JANE READ MORE: Top brain surgeon who says he went to heaven reveals what it's like A baffling new theory to explain human consciousness has suggested it comes from hidden dimensions and is not just brain activity. A physicist claimed that we plug in to these invisible planes of the universe when making art, practicing science, pondering philosophy or dreaming, and this could explain the phenomenon that has evaded scientific understanding for centuries. Michael Pravica, a professor of physics at the University of Nevada, Las Vegas, has based the wild idea on hyperdimensionality, the idea that the universe is made up of more dimensions than just the four we perceive: height, length width and time. But his theory is highly controversial, with one scientist saying that the cornerstone of Pravica's theory'borders on science fiction.' 'The sheer fact that we can conceive of higher dimensions than four within our mind, within our mathematics, is a gift... it's something that transcends biology,' Pravica told Popular Mechanics . Scientists have been attempting to explain human consciousness and its origins for hundreds of years - and the theories run the gamut.

Things to Do in L.A. Tap to enable a layout that focuses on the article. Commuters wait for a train against dark skies at the MTA's Expo/Bundy station in Culver City on Thursday. An unseasonable shift in weather is bringing the chance of showers and thunderstorms across Southern California, prompting some concerns about flooding as temperatures also drop well below average for mid-September. In much of the Los Angeles area, the system is expected to bring only light rain or drizzling Thursday and Friday, but there is a possibility for pockets of thunderstorms that could bring heavier rain. The greatest chance for thunderstorms is in the mountains, including along the Interstate 5 corridor and across the San Gabriels, according to Bryan Lewis, a National Weather Service meteorologist in Oxnard. "We're looking at mostly less than a tenth of an inch, maybe up to a quarter of an inch in the mountains," Lewis said.

Things to Do in L.A. Tap to enable a layout that focuses on the article. Long Beach's Backyard Builders Program uses one-time funding that will provide as many as 10 homeowners low-to zero-interest loans of up to $250,000 to build Accessory Dwelling Units, or ADUs, on their lots. Eager to boost the supply of affordable housing, city officials in Long Beach devised a program that could help a limited number of homeowners build an extra unit on their land. But before they could launch it, they had to decide what to call it. "We've been playing with a name for a while," Mayor Rex Richardson said, noting that a news release touting the program had been delayed days because of christening purposes.