Recent Results on the Use of Artificial Intelligence Techniques Applied to Wireless Power Transfer Systems by Federico Amadei, Michele Quercio, Francesco Riganti Fulginei

“…The article discusses various approaches, including supervised learning, regression models, and Q-learning algorithms, highlighting their ability to reduce design time, improving system efficiency, and mitigate risks associated with misalignment and object interference. …”
Get full text

The Potential of Artificial Intelligence in Pharmaceutical Innovation: From Drug Discovery to Clinical Trials by Vera Malheiro, Beatriz Santos, Ana Figueiras, Filipa Mascarenhas-Melo

“…Artificial intelligence (AI) is a subfield of computer science focused on developing systems that can execute tasks traditionally associated with human intelligence. AI systems work through algorithms based on rules or instructions that enable the machine to make decisions. …”
Get full text

Analyzing Digital Political Campaigning Through Machine Learning: An Exploratory Study for the Italian Campaign for European Union Parliament Election in 2024 by Paolo Sernani, Angela Cossiri, Giovanni Di Cosimo, Emanuele Frontoni

“…Our findings highlight the significance of micro-targeting practices, the role of algorithmic biases, and the risks associated with disinformation in shaping public opinion. …”
Get full text

Ocean Response Along the East Antarctic Coastal Margin to the Southern Annular Mode by K. Mizobata, D. Hirano, K. Kusahara, S. Aoki, J. Inoue, S. Takao, R. Makabe

“…Abstract Ocean circulation around the Antarctic coastal margins plays a critical role in heat delivery to Antarctica, melting ice shelves. …”
Get full text

Identification of m5C RNA modification-related gene signature for predicting prognosis and immune microenvironment-related characteristics of heart failure by Zirui Liu, Rui Feng, Ying Xu, Meili Liu, Haocheng Wang, Yu Lu, Weiqi Wang, Jikai Wang, Cao Zou

“…Abstract Background Methylation of RNA is involved in many pathophysiological processes. The roles of N6-methyladenosine (m6A) and N7-methylguanosine (m7G) in heart failure (HF) have been established. …”
Get full text

Lipids as key biomarkers in unravelling the pathophysiology of obesity-related metabolic dysregulation by Anis Adibah Osman, Siok-Fong Chin, Lay-Kek Teh, Noraidatulakma Abdullah, Nor Azian Abdul Murad, Rahman Jamal

“…Metabolites were identified using a molecular feature and chemical formula algorithm, followed by a differential analysis using MetaboAnalyst 5.0. …”
Get full text

Cognitive function changes and DTI-ALPS index in postmenopausal women by Ningning Liu, Yue Zhang, Weiqing Fu, Huijun Liu

“…BackgroundCognitive decline in postmenopausal women is a growing public health concern, with estrogen deficiency linked to brain aging. However, the role of the brain's lymphatic-like system—assessed via the diffusion tensor imaging along the perivascular space (DTI-ALPS) index—in mediating estrogen-cognitive associations remains unclear. …”
Get full text

The contribution of X to youth environmental movements addressing climate change: Effective impact or distorting noise? by Ángela Alonso-Jurnet, Ainara Larrondo Ureta, Jordi Morales-i-Gras

“…Through an algorithmic analysis of nearly 280,000 tweets, the research characterises the main communities that have shaped the digital debate surrounding these ecological protest actions. …”
Get full text

A Review of Emerging Techniques for Power Quality Improvement in Renewable Energy Integration by Kumar P. Rajesh, Shravani Chapala, Rajitha M., Lokeshwar Reddy Ch.

“…Special emphasis is placed on the role of modern technologies, such as artificial intelligence (AI) and machine learning (ML), in enhancing the adaptability and robustness of PQ solutions. …”
Get full text

SIGMAR1 screened by a GPCR-related classifier regulates endoplasmic reticulum stress in bladder cancer by Jingming Zhuang, Yang Wang, Xinyong Wu, Zijing Peng, Zhengnan Huang, Chao Zhao, Bing Shen

“…The sigma-1 receptor (SIGMAR1), although not a classical GPCR, has similar functions and is associated with the regulation of ER stress. However, its specific role and mechanism in bladder cancer are still unclear. …”
Get full text

Using actigraphy to assess sleep characteristics by G. A. Trusov, A. V. Korobeinikova, L. V. Getmantseva, S. Yu. Bakoev, A. N. Lomov, A. A. Keskinov, V. S. Yudin

“…The importance of accurate methodology and validated algorithms for  actigraphy data analysis is  emphasized through a  review of various sleep assessment algorithms and their application in clinical and research settings. …”
Get full text

Predicting Firefighter Injury and Entrapment in Urban Firefighting Operations: An Investigation Into the Effectiveness of Modified Fire Time Stages and Machine Learning by Mohammad Mahdi Barati Jozan, Hamed Khosravi, Aynaz Lotfata, Krzysztof J. Cios, Hamed Tabesh

“…Firefighters play an important role in managing these incidents, so their safety is a top priority for fire departments and emergency responders. …”
Get full text

Large Language Models in Medicine: Clinical Applications, Technical Challenges, and Ethical Considerations by Kyu-Hwan Jung

“…Objectives This study presents a comprehensive review of the clinical applications, technical challenges, and ethical considerations associated with using large language models (LLMs) in medicine. …”
Get full text

The Transition To Artificial Intelligence -Based Solutions For Improving Energy Efficiency In Urban Environments by Ikram MENAI, Hana SALAH SALAH, Sara KHELIL, Amina AIDAOUI, Fatima Zahra DJOUAD

“…It examines the implementation of AIbased energy networks, smart energy storage solutions and the integration of renewable energy into urban planning, and also looks at the potential challenges and ethical considerations associated with its adoption. It addresses issues such as data privacy, algorithmic biases and the need for transparent decision-making processes. …”
Get full text

Construction of Diagnostic Model for Regulatory T Cell-Related Genes in Sepsis Based on Machine Learning by Xuesong Wang, Zhe Guo, Xinrui Wang, Zhong Wang

“…Thus, we utilized multiple machine learning algorithms to screen and extract Treg-related genes associated with sepsis diagnosis. …”
Get full text

A Novel Logarithmic Approach to General Relativistic Hydrodynamics in Dynamical Spacetimes by Mario Imbrogno, Rita Megale, Luca Del Zanna, Sergio Servidio

“…A key innovation of our work is the logarithmic transformation applied to critical variables such as rest-mass density, energy density, and pressure, thus preserving physical positivity and mitigating numerical issues associated with extreme variations. Our formulation is fully compatible with advanced numerical techniques, including spectral methods and Fourier-based algorithms, and it is particularly suited for simulating highly nonlinear regimes in which gravitational fields play a significant role. …”
Get full text

On the strength and failure mechanism of confined pre-holed jointed rock mass via DIC by Wei Wang, Wei Wang, Yundong Bi, Shuo Yang, Shuo Yang

“…In this paper, characteristics of strength and failure mechanism of pre-holed jointed rock mass is experimentally investigated by adopting the digital image correlation and acoustic emission methods. The role of buried depth is considered with confining boundary applied during experiments. …”
Get full text

Mir-494-3p enhances aggressive phenotype of non-small cell lung cancer cells by regulating SET/I2PP2A by Yuwen Du, Taisuke Kajino, Yukako Shimada, Takashi Takahashi, Ayumu Taguchi

“…However, its role in NSCLC development and progression remains elusive. …”
Get full text

A combined immune and exosome-related risk signature as prognostic biomakers in acute myeloid leukemia by Zenghui Fang, Jiali Fu, Xin Chen

“…In addition, we performed KEGG and GO enrichment analyses to investigate the role played by these genes in AML. The variations in immune cell infiltrations among risk groups were assessed through four algorithms. …”
Get full text

CTSS in the tumor microenvironment links immune escape and immunotherapy sensitivity in kidney renal clear cell carcinoma by Hanjing Zhou, Jun Ying, Xuchun Xu, Jian Huang

“…Employing advanced machine learning (ML) algorithms, we identified Cathepsin S (CTSS) as the most pivotal tumor suppressor, with elevated CTSS expression consistently predicting improved survival across multiple independent cohorts. …”
Get full text