The emergence of vehicular networks integrated with Artificial Intelligence (AI) technologies has created new promising opportunities for intelligent transportation systems. One of the newly adapted AI techniques is Generative Artificial Intelligence (GenAI), which provides significant capabilities in addressing numerous challenges in vehicular networks. We review the challenges associated with vehicular networks and explore how GenAI models can solve them. The specific challenges that we focus on include efficient data communication, enhanced network security, and intelligent data management for driving applications, as well as data generation and augmentation for rare and complex driving scenarios. Moreover, we discuss future research directions, such as adopting federated learning, 6G-enabled communications, synthetic data generation for rare events, intelligent resource management, and secure vehicular communications. We hope that the results of this work will provide a useful reference for researchers planning to leverage GenAI technology in developing intelligent, secure, and data-efficient vehicular networks.
The term 'endometrosis', coined in 1992 to describe chronic degenerative changes of the equine endometrium, is descriptively imprecise and readily confused with 'endometritis' and the human gynaecological condition 'endometriosis'. A modified four-round electronic Delphi (e-Delphi) process was conducted with an international panel of eight specialists to achieve consensus on a replacement term. Fifteen candidate terms were evaluated in Round 1 using a 7-point Likert scale and preference rankings; terms were retained if >50% of respondents scored >= 4/7. Round 2 (Refinement) evaluated shortlisted terms plus five panel-proposed new terms against a >= 75% threshold. Round 3 (Consensus Vote) presented six retained terms and four variants for a forced-choice ranking. The primary criterion (>= 75% scoring >= 6/7) was not met by any individual term, therefore a pre-specified Round 4 binary vote resolved the outcome. 'Endometrosis' (proposed for retention by one panel member) was near-unanimously rejected in Round 2 (median 1/7; IQR 1-3). In Round 3, Chronic Endometrial Degeneration (CED) achieved the highest support (median 6/7; IQR 5-7; 71.4% scoring >= 6/7) and all seven respondents placed CED or its variant Chronic Equine Endometrial Degeneration (CEED) as their first preference. In Round 4, five of eight panel members (62.5%) selected CED. Chronic Endometrial Degeneration (CED) is recommended as the replacement term for 'endometrosis' in equine endometrial biopsy reporting, clinical practice and scientific publication. CED is well-suited as a consensus term; it is concise, broad and generates a memorable acronym. CEED is an accepted alternative where species specificity is required.
Wire Arc Additive Manufacturing (WAAM) has emerged as one of the most practical and scalable technologies for fabricating large metal components. With high deposition rate and cost efficiency, WAAM is increasingly used in aerospace, marine, and other high-value industries. Conventional WAAM systems, based on commercial welding equipment and industrial robots, are limited in controlling material microstructure, mechanical properties, and geometric accuracy. As the demands for higher performance in fabricated parts continue to rise, process-oriented system innovations have become a key development trend. These modifications directly manipulate arc behaviour, wire feeding, thermal fields, and in-situ deformation, providing more effective regulation of molten pool dynamics and solidification patterns. Approaches such as multi-wire feeding, hybrid arc-laser configurations, external field assistance, and in-situ thermal or mechanical treatments have achieved improved structural uniformity, reduced defects, and higher deposition efficiency. Despite this rapid progress, the diversity and complexity of independently developed systems have led to a fragmented research landscape. This review synthesizes these innovations, evaluates their mechanisms and effectiveness, and maps them to key research objectives. It then provides critical insights of current research, discusses existing issues and highlights future opportunities to guide the development of high-performance, structurally reliable, and industrially deployable WAAM systems.
Limbic-predominant age-related TDP-43 encephalopathy (LATE) is a neurodegenerative disease marked by TDP-43 proteinopathy, affecting approximately one-third of individuals aged 80 and above. LATE neuropathological change (LATE-NC) is characterized by the accumulation of phosphorylated TDP-43 preferentially in the limbic system, with potential extension to the neocortex and other brain regions. Notably, the anatomic pattern of LATE-NC differs from that seen in frontotemporal lobar degeneration with TDP-43-immunoreactive inclusions (FTLD-TDP). LATE-NC can occur in a “pure” form but more commonly exists alongside other dementia-related comorbidities, including both degenerative and vascular pathologies. When those “mixed” pathologies are factored in, LATE contributes significantly to cognitive decline in human populations. However, LATE currently lacks a molecular-specific diagnostic method for definitive diagnosis in living people. There are new consensus-based guidelines for predicting the presence of either pure LATE-NC or LATE-NC combined with Alzheimer’s disease neuropathologic change (ADNC). Aimed at developing more specific diagnostic methods, recent research efforts have been directed toward identifying unique features on neuroimaging and molecular signatures in biological fluids such as blood and cerebrospinal fluid to facilitate clinical diagnosis for LATE. This review discusses current progress in molecular understanding of LATE-NC, the search for biomarkers for LATE, and highlights key gaps that need to be addressed to advance early detection and improve patient management and clinical trial stratification.
