Subcutaneous vascularization has become a new solution for identification management over the past few years. Systems based on dorsal hand veins are particularly promising for high-security settings. The dorsal hand vein recognition system comprises the following steps: acquiring images from the database and preprocessing them, locating the region of interest, and extracting and recognizing information from the dorsal hand vein pattern. This paper reviewed several techniques for obtaining the dorsal hand vein area and identifying a person. Therefore, this study just provides a comprehensive review of existing previous theories. This model aims to offer the improvement in the accuracy rate of the system that was shown in previous studies and

A growing and pressing need for Speech Enhancement Algorithms (SEAs) has emerged with the proliferation of hearing devices and mobile devices that aim to improve speech intelligibility without sacrificing speech quality. Recently, a tremendous number of studies have been conducted in the field of speech enhancement. This study aims to map the field of speech enhancement by conducting a systematic literature review to provide comprehensive details of recently proposed SEAs. This systematic review aims to highlight research trends in SEAs and direct researchers to the most important topics published between 2015 and 2024. It attempts to address seven key research questions related to this topic. Moreover, it covers articles available

Any harm done to genetic material, whether directly interacting with DNA or indirectly through biological systems, is referred to as genotoxicity. Such harm poses major risks to the health of people, animals, and plants as it is a primary source of carcinogenesis, mutagenesis, and teratogenesis. Because of their medicinal qualities, alkaloids—a family of naturally occurring phytochemicals made by plants from amino acids—are frequently utilized to treat ailments such newborn apnea, gout, and asthma. Recent research has sparked worries about their possible genotoxic consequences despite their therapeutic advantages. Through a variety of processes, including as the creation of DNA adducts, DNA–DNA cross-links, and DNA–protein c

Chronic cancer pain results from the complex interaction of nociceptive, neuropathic, and neuroimmune mechanisms, which vary according to tumor type, location, stage, and treatment history. Recent advances in cancer neuroscience have reframed pain as a dynamic manifestation of reciprocal tumor–nerve–immune interactions, rather than a mere consequence of tissue damage. In this model, malignant, stromal, and immune cells remodel nociceptive circuits at peripheral and central levels. This narrative review, conducted in accordance with SANRA criteria, synthesizes current mechanistic insights into the neurobiology of cancer pain. At the peripheral level, tumor-derived mediators such as prostaglandins, cytokines, chemokines, glutamate

In this research, we highlight the most important research related to the mixed ligand complexes of the drug trimethoprim (TMP), and for the past 7 years where this drug has been used as a chelating ligand and gives stability to the complexes with ions of metal elements where these complexes, prepared and diagnosed, and for some research the bacterial activity was studied against different types of bacteria

This paper explores VANET topics: architecture, characteristics, security, routing protocols, applications, simulators, and 5G integration. We update, edit, and summarize some of the published data as we analyze each notion. For ease of comprehension and clarity, we give part of the data as tables and figures. This survey also raises issues for potential future research topics, such as how to integrate VANET with a 5G cellular network and how to use trust mechanisms to enhance security, scalability, effectiveness, and other VANET features and services. In short, this review may aid academics and developers in choosing the key VANET characteristics for their objectives in a single document.

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing