On a Thursday morning in early February, Kartik Sivakumar realized that he would have to leave America. He was sitting in his dorm room, at the University of Iowa, where he was a senior majoring in neuroscience. He was also a resident adviser, a leader of the university's hospital student-volunteer corps, and an organizer of the Indian Student Alliance's annual dance competition. Sivakumar had lived in Iowa for half his life. That morning, he received an e-mail from U.S. Citizenship and Immigration Services (U.S.C.I.S.), saying that action had been taken on his change-of-status application for a student visa.

The mortgage industry has been talking about ending its'Paper-Palooza' for at least 20 years as we linger behind other industries like healthcare and insurance. Digital technology opportunities span the entire ecosystem, bound only by the willingness of its participants. Artificial intelligence (AI) and machine learning (ML) are the most understood and deployed, thereby leading the way in these early stages. Blockchain, on the other hand, is more "fuzzy" to many, yet has a persuasive cast of evangelists. There are companies, and even countries, being built on blockchain tech, such as Figure and Liquid Mortgage.

One of the boons of cryptocurrency is meant to be that no particular company, central bank or government has control. That might not be true. Researchers for a report commissioned by the Defense Advanced Research Projects Agency (DARPA) found there can be "unintended centralities" in these supposed decentralized systems. Cryptocurrency power is concentrated among people or organizations with a large chunk of the pie. "Unintended centralities" was the term used, defined as circumstances where an entity has sway over a so-called decentralized system.

Millions of shipments of nuclear and other radiological materials are moved in the U.S. every year for good reasons, including health care, power generation, research and manufacturing. But there remains the threat that bad actors in possession of stolen or illegally produced nuclear materials or weapons will try to smuggle them across borders for nefarious purposes. Texas A&M University researchers are making it harder for them to succeed. If border agents intercept illicit nuclear materials, investigators need to know who produced them and where they came from. Fortunately, nuclear materials carry certain forensic markers that can reveal valuable information, much like fingerprints can identify criminals.

One of the significant challenges that smart grid networks face is cyber-security. Several studies have been conducted to highlight those security challenges. However, the majority of these surveys classify attacks based on the security requirements, confidentiality, integrity, and availability, without taking into consideration the accountability requirement. In addition, some of these surveys focused on the Transmission Control Protocol/Internet Protocol (TCP/IP) model, which does not differentiate between the application, session, and presentation and the data link and physical layers of the Open System Interconnection (OSI) model. In this survey paper, we provide a classification of attacks based on the OSI model and discuss in more detail the cyber-attacks that can target the different layers of smart grid networks communication. We also propose new classifications for the detection and countermeasure techniques and describe existing techniques under each category. Finally, we discuss challenges and future research directions.

ABSTRACT Coronal mass ejections (CMEs) are the most geoeffective space weather phenomena, being associated with large geomagnetic storms, having the potential to cause disturbances to telecommunication, satellite network disruptions, power grid damages and failures. Thus, considering these storms' potential effects on human activities, accurate forecasts of the geoeffectiveness of CMEs are paramount. This work focuses on experimenting with different machine learning methods trained on white-light coronagraph datasets of close to sun CMEs, to estimate whether such a newly erupting ejection has the potential to induce geomagnetic activity. We developed binary classification models using logistic regression, K-Nearest Neighbors, Support Vector Machines, feed forward artificial neural networks, as well as ensemble models. At this time, we limited our forecast to exclusively use solar onset parameters, to ensure extended warning times. We discuss the main challenges of this task, namely the extreme imbalance between the number of geoeffective and ineffective events in our dataset, along with their numerous similarities and the limited number of available variables. We show that even in such conditions, adequate hit rates can be achieved with these models. INTRODUCTION The purpose of this work is to develop a machine learning (ML) based model that can predict whether a coronal mass ejection (CME) will be geoeffective, using only numerical solar parameters as input. Coronal mass ejections are solar eruptive events whose magnetically charged particles can, directly or indirectly, under certain circumstances, reach Earth and cause geomagnetic storms (GSs), i.e., be geoeffective. These storms represent perturbations in the Earth's magnetic field, which have the potential to lead to electrical systems and grids failure and/or damage, power outages, navigation errors, radio signal perturbations, significant exposure to dangerous radiations for astronauts during space missions, etc. Given the potential negative impacts of such storms, predicting their occurrence is paramount for enabling safeguarding of human technology (Schwenn 2006; Pulkkinen 2007; Council 2013; Vourlidas et al. 2019; Temmer 2021). The intensity of the storms can be measured by various geomagnetic indices such as Ap, Kp, AE, PC or Dst (see Lockwood 2013, and references therein). Herein, we have chosen to use the values of the Dst index (Sugiura 1964) to establish whether the magnetic field perturbations do, in fact, manifest as storms. This is an index that is calculated using four geomagnetic stations situated at low latitudes. Depending on the value of this index, it can be established whether these perturbations are associated with geomagnetic storms or not. In terms of storm intensity, one of the most popular classifications that takes into consideration the minimum value of the Dst index is that of Gonzalez et al. (1994).

The US Supreme Court on Tuesday declined an appeal from Bayer-owned Monsanto that aimed to challenge thousands of lawsuits claiming its weedkiller Roundup causes cancer -- a potentially costly ruling. The high court did not explain its decision not to take the case, which left intact a $25 million ruling in favor of a California man who alleged he developed cancer after using the chemical for years. The decision marks a major blow to the German conglomerate's legal fight against some 31,000 Roundup-related cases. "Bayer respectfully disagrees with the Supreme Court's decision," the company said in a statement. "The company believes that the decision undermines the ability of companies to rely on official actions taken by expert regulatory agencies," it added, referring to a 2020 federal finding that Roundup's active ingredient is not risky.

Meta Platforms Inc. will change its ad delivery system to address concerns that it violates the Fair Housing Act by discriminating against users, as part of a settlement with a federal regulator. The accord resolves a lawsuit by the US Department of Housing and Urban Development alleging that the algorithms used in Meta's advertising systems allowed marketers to violate fair housing laws by limiting or blocking certain groups of people from seeing housing ads on the service. "Because of this ground-breaking lawsuit, Meta will--for the first time--change its ad delivery system to address algorithmic discrimination," Manhattan US Attorney Damian Williams said in a statement. Meta said Tuesday that it built machine learning technology to ensure that ads reach people that reflect the overall potential audience for a particular ad, and not just a subset of that group. In a blog post, Meta wrote that it will "work to ensure the age, gender and estimated race or ethnicity of a housing ad's overall audience matches the age, gender, and estimated race or ethnicity mix of the population eligible to see that ad."

From cyber operations to disinformation, artificial intelligence extends the reach of national security threats that can target individuals and whole societies with precision, speed, and scale. As the US competes to stay ahead, the intelligence community is grappling with the fits and starts of the impending revolution brought on by AI. The US intelligence community has launched initiatives to grapple with AI's implications and ethical uses, and analysts have begun to conceptualize how AI will revolutionize their discipline, yet these approaches and other practical applications of such technologies by the IC have been largely fragmented. As experts sound the alarm that the US is not prepared to defend itself against AI by its strategic rival, China, Congress has called for the IC to produce a plan for integration of such technologies into workflows to create an "AI digital ecosystem" in the 2022 Intelligence Authorization Act. The term AI is used for a group of technologies that solve problems or perform tasks that mimic humanlike perception, cognition, learning, planning, communication, or actions.

Imagine a world where wars are fought by AI-powered tanks, allowing soldiers to stay at a safe distance from the battlefield and yet, still demolish their enemies. Although this sounds like something out of a sci-fi film, the scenario is exactly what Milrem Robotics and Kongsberg Defense & Aerospace have shown in a first live fire of the PROTECTOR Remote Turret from the Type-X Robotic Combat Vehicle (RCV). The unmanned tank, dubbed Type-X,' features navigation and obstacle detection systems powered by AI and a range of weapons including 50 mm cannons, anti-tank missiles, and even a tethered drone. Milrem plans to sell its killer robotic tank to Nordic and Western European countries, but the US has also showed interest in the technology. And at least ten countries have already placed orders for the Type-X platform, including seven NATO members.