Traditional academic peer review is plagued by systemic issues including significant delays, reviewer bias, and prohibitive costs. This paper introduces a novel operational model for scholarly publishing that leverages multiple large language models to conduct rapid, transparent, and unbiased peer review. We describe the architecture of our AI-augmented system, which requires consensus from at least two out of three different AI models, with all reviews published alongside manuscripts. Initial data from the first year demonstrates significant reduction in time-to-publication and successful evaluation of highly interdisciplinary research.

Forensic identification commonly rests on estimation of biological sex, age at death, stature, and postmortem interval. This paper proposes a principled, end-to-end, multi-task probabilistic machine learning framework that fuses skeletal and dental measurements, radiographic descriptors, taphonomic variables, and entomological evidence to infer joint posterior distributions. The framework foregrounds calibrated probabilities and explicitly models uncertainty, offering a comprehensive approach to forensic anthropological identification.

DNA microarrays and next-generation sequencing technologies have revolutionized genomics research by enabling high-throughput analysis of nucleic acids at unprecedented scales. This comprehensive examination explores fundamental principles, methodological frameworks, and practical applications of both platforms. The analysis includes detailed mathematical formulations, comprehensive Python implementation for data visualization, and extensive discussion of technological trade-offs for researchers, clinicians, and students in genomics and molecular biology.

Biological membranes represent one of the most sophisticated and evolutionarily conserved molecular assemblies in living systems, serving as dynamic interfaces that regulate selective passage of substances whilst maintaining cellular integrity. This comprehensive analysis examines the intricate structural organisation of biological membranes within the fluid mosaic model framework, providing rigorous quantitative exploration of diverse mechanisms governing molecular transport across these barriers. The investigation includes mathematical formalisms governing transport phenomena, from Fick's Laws to Michaelis-Menten kinetics.

This article examines the profound impact of international migration on human capital accumulation and economic development from the late 19th century to modern times. Drawing upon extensive historical data spanning 1850-2024, this research analyses migration volumes, demographic patterns, economic impacts, and policy transformations across multiple continents. The study demonstrates how immigration has consistently served as a catalyst for economic growth, cultural enrichment, and social transformation, with particular focus on the Brazilian experience following the abolition of slavery in 1888.