Trump administration'unlocks' 140MILLION barrels of precious Iranian oil with major policy change to fight back against'hoarding' China... here's what it means for your wallet Buffy the Vampire Slayer star Nicholas Brendon dead at 54 as'heartbroken' family reveal cause of death Joseph Duggar's wife Kendra is arrested for allegedly endangering welfare of a minor as he faces new charges Behind closed doors, the Duggar family's next nightmare began long before Joseph's arrest: Insiders reveal what they knew and how they plan to recover America is about to be torn apart by a financial tsunami - and it's not just an oil crisis to fear. However, it seems not every corner of Britain is quite so beautiful - as a survey has revealed the least scenic locations. Voters on the Scenic Or Not survey awarded the top spot to Basingstoke's Newbury Road. This unappealing location received the lowest possible score, with just one out of 10 for'scenicness'. And while Cornwall might be renowned for its beautiful scenery, a rather less attractive part of the county - the Electricity Station in Landulph - joins Basingstoke at the bottom of the pile.

Will Gulf states join war? One police officer has been killed in a drone strike by "outlaw groups" on the headquarters of the Iraqi National Intelligence Service in the heart of capital Baghdad. "A drone targeted the headquarters of the Iraqi National Intelligence Service in the Mansour district" at about 10am local time (07:00 GMT), General Saad Maan, head of the Iraqi government's security media unit, said in a brief statement on Saturday. Another drone, filming the operation, crashed into a private members ' sports club popular with the Iraqi elite and foreign diplomats, according to the same source. The drone attack on the headquarters of the National Intelligence Service came hours after another attack on the US military complex.

Two people were killed in a Russian drone attack on a home in the Ukrainian city of Zaporizhzhia, local authorities say. Two children, 11 and 15, were also injured in the attack which took place on the eve of new talks between Ukrainian and American negotiators in the US. Negotiations on ending the war have been on hold since the start of the latest conflict in Iran. President Volodymy Zelensky wants his negotiators to discuss the US decision to ease sanctions on Russian oil - implemented by Washington to help keep down global energy prices. Talks mediated by the US have so far failed to stop the fighting in Ukraine or change Russia's demands, and there is little hope of a breakthrough.

The Amazon Prime prank series amplifies the hijinks of workplace dynamics, while showing how people find purpose--and community--in their jobs despite impossible situations. Anthony Norman is your typical Gen Z worker: 25, a little wayward, and struggling to find a full time job. Unemployment rates are high . AI is creating a crisis for young people trying to enter the workforce. And several companies--including Amazon, Block, and Meta --have embraced tech's latest era of layoffmaxxing, with some cutting their staff by 20 percent.

The Chinese automaker is racing ahead of global competitors--but don't expect to see those gains in the US anytime soon. Somehow, the whole thing got even faster. Earlier this month, Chinese automaker BYD announced that its Flash Chargers, first rolled out a year ago, can now charge some electric vehicle batteries from around 10 to 70 percent in five minutes, and from 10 to full in about nine. That's more than 600 miles of range in the time it takes to order a cappuccino and leave a nice tip. The new BYD chargers can add miles super quickly because they deliver up to 1,500 kilowatts (kW) per charge.

In recent years, indoor air pollution has posed a significant threat to our society, claiming over 3.2 million lives annually. Developing nations, such as India, are most affected since lack of knowledge, inadequate regulation, and outdoor air pollution lead to severe daily exposure to pollutants. However, only a limited number of studies have attempted to understand how indoor air pollution affects developing countries like India. To address this gap, we present spatiotemporal measurements of air quality from 30 indoor sites over six months during summer and winter seasons. The sites are geographically located across four regions of type: rural, suburban, and urban, covering the typical low to middle-income population in India. The dataset contains various types of indoor environments (e.g., studio apartments, classrooms, research laboratories, food canteens, and residential households), and can provide the basis for data-driven learning model research aimed at coping with unique pollution patterns in developing countries. This unique dataset demands advanced data cleaning and imputation techniques for handling missing data due to power failure or network outages during data collection. Furthermore, through a simple speech-to-text application, we provide real-time indoor activity labels annotated by occupants. Therefore, environmentalists and ML enthusiasts can utilize this dataset to understand the complex patterns of the pollutants under different indoor activities, identify recurring sources of pollution, forecast exposure, improve floor plans and room structures of modern indoor designs, develop pollution-aware recommender systems, etc.

Machine learning models are increasingly being deployed in real-world contexts. However, systematic studies on their transferability to specific and critical applications are underrepresented in the research literature. An important example is visual anomaly detection (VAD) for robotic power line inspection. While existing VAD methods perform well in controlled environments, real-world scenarios present diverse and unexpected anomalies that current datasets fail to capture. To address this gap, we introduce CableInspect-AD, a high-quality, publicly available dataset created and annotated by domain experts from Hydro-Québec, a Canadian public utility.

We introduce One-Shot Label-Only (OSLO) membership inference attacks (MIAs), which accurately infer a given sample's membership in a target model's training set with high precision using just a single query, where the target model only returns the predicted hard label. This is in contrast to state-of-the-art label-only attacks which require $\sim6000$ queries, yet get attack precisions lower than OSLO's.

Binary statistical decision making involves choosing between two states based on statistical evidence. The optimal decision strategy is typically formulated through a constrained optimization problem, where both the objective and constraints are expressed as integrals involving two Lebesgue measurable functions, one of which represents the strategy being optimized. In this work, we present a comprehensive formulation of the binary decision making problem and provide a detailed characterization of the optimal solution. Our framework encompasses a wide range of well-known and recently proposed decision making problems as specific cases. We demonstrate how our generic approach can be used to derive the optimal decision strategies for these diverse instances. Our results offer a robust mathematical tool that simplifies the process of solving both existing and novel formulations of binary decision making problems which are in the core of many Machine Learning algorithms.

Vision-Language Models (VLMs) excel in generating textual responses from visual inputs, but their versatility raises security concerns. This study takes the first step in exposing VLMs' susceptibility to data poisoning attacks that can manipulate responses to innocuous, everyday prompts. We introduce Shadowcast, a stealthy data poisoning attack where poison samples are visually indistinguishable from benign images with matching texts. Shadowcast demonstrates effectiveness in two attack types. The first is a traditional Label Attack, tricking VLMs into misidentifying class labels, such as confusing Donald Trump for Joe Biden.