It's been hard recently to think about anything other than the wars and humanitarian crises raging around the world. Climate change has left its mark in what was almost certainly the hottest year in human history--there were unprecedented heat waves, intensified forest fires, torrential rain, and floods like those in Libya that caused devastation after two dams burst. But this has not stopped scientists, innovators, and decisionmakers from working on solutions to our biggest societal challenges--with success. Here is a collection of uplifting news to come out of 2023. In an instant, millions of volts can damage buildings, spark fires, and harm people--unless the lightning can be redirected.

The United States and China explore the lunar presence of critical minerals. Mexico will launch its first lunar mission next month, a historic step for the country and Latin America as a whole, according to officials. "This project will make history and is the first of its kind in Latin America, which elevates the name of our country, confirming once again that Mexican engineering is at the level of the best in the world," Salvador Landeros, director of the Mexican Space Agency (AEM), said in a press release. A team of scientists and nearly 250 university students developed five microrobots that the AEM will launch from Cape Canaveral, Florida, between Jan. 8 and Jan. 11 as part of project Colmena. Each robot weighs 60 grams -- a little over one-tenth of a pound -- and measures just under 5 inches in diameter.

Russia says it has targeted Ukrainian military sites in the capital Kyiv and Kharkiv in a new wave of drone and missile attacks in days, in retaliation for a deadly attack a day earlier on the city of Belgorod. The Russian defence ministry said on Sunday it had struck "decision-making centres and military installations" in the northeastern city of Kharkhiv, after Kyiv said that residential buildings, a hotel and cafes had been hit. In the first wave of overnight attacks, at least six missiles hit Kharkiv, Ukraine's National Police said on Sunday, injuring at least 22 people and hitting 12 apartment buildings, 13 residential houses and a kindergarten. Most drones were aimed at Ukraine's first line of defence as well as at civilian, military and infrastructure in the Kharkiv, Kherson, Mykolaiv and Zaporizhia regions, the Ukrainian Air Force said, adding that it destroyed 21 out of 49 attack drones. Earlier, Ukrainian officials said that among those injured in Kharkiv were two boys aged 14 and 16 and a security adviser for a team of German journalists.

From a Taylor Swift takeover to Capitol Hill chaos and everything in between, Fox News' Digital Originals takes a look back on the biggest headlines of 2023. As history books close the chapter on 2023, Fox News Digital takes a look at the biggest news headlines of the year. Another trip around the sun brought unprecedented political plays, a Hollywood holdout, war in the Middle East and an economic boom from a world-famous pop singer. California Rep. Kevin McCarthy, a Republican, was elected speaker of the House of Representatives Jan. 7, 2023, after 15 floor votes. The fight to elect the speaker was unprecedented.

The real estate market has slowed a little, but property remains one of the best investments you can make. With Mashvisor, it's even easier to make smart investments and get a big discount now through January 1. Mashvisor offers comprehensive coverage of 95% of US markets with up-to-date real estate data sourced from some of the best sources in the country. With data from the MLS, Zillow, Rentometer, Airbnb, and the US Census Bureau and powerful machine learning algorithms, Mashvisor assesses properties and neighborhoods to identify short- and long-term potential. You can search properties depending on your preferred market, property type, size, budget, and more to start building a real estate portfolio from scratch. Find out why Mashvisor has earned an excellent Trustpilot rating.

Fashion and lifestyle have a knack for the surprise. The out-of-the-blue rise of butter moulding, say, or the sudden coolness of a shoe with a cloven toe. Divergence and disparateness are the mood music for 2024. What this means for fashion is yet more extreme luxury, both of the stealth wealth and exhibitionist varieties. But there will also be more emphasis than ever on thrifting, textile recycling, and the development of new materials, especially in the luxury market. Expect more seaweed yarns, plastic-free sequins and grape leathers like those shown by designer Stella McCartney at Cop28. With several elections set for 2024, slogan T-shirts will be used once more for political statements and to pledge allegiance rather than for more personal messages. Expect Maga caps and merch in the vein of Keir Starmer's Sparkle With Starmer tee, turned around at speed after he was glitter-bombed at Labour conference.

North Korea has said it will launch three more military spy satellites, build military drones and boost its nuclear arsenal in 2024, continuing a military modernisation programme that saw a record number of weapons tests this year. Pyongyang put a spy satellite into orbit in November at its third attempt and this month, again launched its most powerful intercontinental ballistic missile (ICBM), which is seen as having the range to deliver a nuclear warhead to anywhere in the United States. "The task of launching three additional reconnaissance satellites in 2024 was declared" as one of the key policy decisions for 2024 at the end of a five-day party meeting chaired by leader Kim Jong Un, the official Korean Central News Agency (KCNA) reported. Kim wrapped up the meeting on Saturday, lashing out at the US, which he blamed for making war inevitable. "Because of reckless moves by the enemies to invade us, it is a fait accompli that a war can break out at any time on the Korean Peninsula," Kim said, according to KCNA.

This study developed a generative adversarial network (GAN)-based defense method for traffic sign classification in an autonomous vehicle (AV), referred to as the attack-resilient GAN (AR-GAN). The novelty of the AR-GAN lies in (i) assuming zero knowledge of adversarial attack models and samples and (ii) providing consistently high traffic sign classification performance under various adversarial attack types. The AR-GAN classification system consists of a generator that denoises an image by reconstruction, and a classifier that classifies the reconstructed image. The authors have tested the AR-GAN under no-attack and under various adversarial attacks, such as Fast Gradient Sign Method (FGSM), DeepFool, Carlini and Wagner (C&W), and Projected Gradient Descent (PGD). The authors considered two forms of these attacks, i.e., (i) black-box attacks (assuming the attackers possess no prior knowledge of the classifier), and (ii) white-box attacks (assuming the attackers possess full knowledge of the classifier). The classification performance of the AR-GAN was compared with several benchmark adversarial defense methods. The results showed that both the AR-GAN and the benchmark defense methods are resilient against black-box attacks and could achieve similar classification performance to that of the unperturbed images. However, for all the white-box attacks considered in this study, the AR-GAN method outperformed the benchmark defense methods. In addition, the AR-GAN was able to maintain its high classification performance under varied white-box adversarial perturbation magnitudes, whereas the performance of the other defense methods dropped abruptly at increased perturbation magnitudes.

This paper uses the MIMIC-IV dataset to examine the fairness and bias in an XGBoost binary classification model predicting the Intensive Care Unit (ICU) length of stay (LOS). Highlighting the critical role of the ICU in managing critically ill patients, the study addresses the growing strain on ICU capacity. It emphasizes the significance of LOS prediction for resource allocation. The research reveals class imbalances in the dataset across demographic attributes and employs data preprocessing and feature extraction. While the XGBoost model performs well overall, disparities across race and insurance attributes reflect the need for tailored assessments and continuous monitoring. The paper concludes with recommendations for fairness-aware machine learning techniques for mitigating biases and the need for collaborative efforts among healthcare professionals and data scientists.

The proliferation of social network data has unlocked unprecedented opportunities for extensive, data-driven exploration of human behavior. The structural intricacies of social networks offer insights into various computational social science issues, particularly concerning social influence and information diffusion. However, modeling large-scale social network data comes with computational challenges. Though large language models make it easier than ever to model textual content, any advanced network representation methods struggle with scalability and efficient deployment to out-of-sample users. In response, we introduce a novel approach tailored for modeling social network data in user detection tasks. This innovative method integrates localized social network interactions with the capabilities of large language models. Operating under the premise of social network homophily, which posits that socially connected users share similarities, our approach is designed to address these challenges. We conduct a thorough evaluation of our method across seven real-world social network datasets, spanning a diverse range of topics and detection tasks, showcasing its applicability to advance research in computational social science.