Search Results (17,308)

With the expansion of photovoltaic (PV) systems, failures of bypass diodes (BPDs) embedded in PV modules can degrade the power-generation performance and pose safety risks. When a BPD fails, current circulates within the module, leading to overheating and eventual burnout of the failed BPD. The heating characteristics of a BPD depend on its fault resistance, and although many modules are connected in series in actual PV systems, the heating risk at the module-string level has not been sufficiently evaluated to date. In this study, a numerical simulation model is constructed to reproduce the operation of PV modules and module strings containing failed BPDs, and its validity is verified through experiments. The validated numerical simulation results quantitatively illustrate how series-connected PV modules modify the fault-resistance dependence of BPD heating under maximum power-point operation. The results show that, under maximum power-point operation, the fault resistance at which BPD heating becomes critical shifts depending on the number of series-connected modules examined, while the magnitude of the maximum heating decreases as the string length increases. The heat generated in a BPD at the maximum power point decreases as the number of series-connected modules increases for the representative string configurations analyzed. However, under open-circuit conditions due to power-conditioner abnormalities, the power dissipated in the failed BPD increases significantly, posing a very high risk of burnout. Considering that lightning strikes are one of the major causes of BPD failure, adopting diodes with higher voltage and current ratings and improving the thermal design of junction boxes are effective measures to reduce BPD failures. The simulation model constructed in this study, which was experimentally validated for short PV strings, can reproduce the electrical characteristics and heating behaviors of PV modules and strings with BPD failures with accuracy sufficient for comparative and parametric trend analysis, and serves as a practical tool for system-level safety assessment, design considerations, and maintenance planning within the representative configurations analyzed. Full article

Early Onset Scoliosis (EOS), defined as presenting before 10 years of age, often has a significant adverse impact on pulmonary function, due to a complex interrelationship between the spine, chest, pulmonary structures and their development. Left untreated, EOS leads to premature death, with early fusion surgery to arrest curve progression making little impact on this. To date, the natural history has not been clearly established as compounded by the heterogeneity of pathologies, causing EOS and challenges in objective measurements of pulmonary function in this young age group. A desire to address this poor natural history has motivated interest in pursuing ‘growth friendly’ surgical strategies. The implants used have evolved with time, often to address compromises and poor results, with multiple options now available based on treatment principles (distraction, compression, or guided growth systems). The aims of such strategies are to control the structural spinal deformity, whilst allowing spinal and thoracic growth, with the seemingly reasonable expectation that this will result in improved pulmonary function and avoidance of premature death. Most studies have focused on radiological outcome measures such as Cobb angle and thoracic height to gauge the success of surgery, with these measures acting as surrogate markers of improved pulmonary outcome. This assumption, however, is not supported by more recent clinical data which has attempted to assess directly the pulmonary outcomes associated with growth-friendly surgical strategies. This literature review therefore sets out to characterise the effect of EOS on pulmonary function and to critically analyse the impact surgical treatment options will have while addressing this. Full article

Early life is a critical window for immune system development, during which the gut microbiome shapes innate immunity, antigen presentation, and adaptive immune maturation. Disruptions in microbial colonization—driven by factors such as cesarean delivery, antibiotic exposure, and formula feeding—deplete beneficial early-life taxa (e.g., Bifidobacterium, Bacteroides, and Enterococcus) and impair key microbial functions, including short-chain fatty acid (SCFA) production by these keystone species, alongside regulatory T cell induction. These dysbiosis patterns are associated with an increased risk of pediatric autoimmune diseases, notably type 1 diabetes, inflammatory bowel disease, celiac disease, and juvenile idiopathic arthritis. This review synthesizes current evidence on how the early-life microbiota influences immune maturation, with potential effects on the development of autoimmune diseases later in life. We specifically focus on human observational and intervention studies, where treatments with probiotics, synbiotics, vaginal microbial transfer, or maternal fecal microbiota transplantations have been shown to partially restore a disrupted microbiome. While restoration of the gut microbiome composition and function is the main reported outcome of these studies, to date, no reports have disclosed direct prevention of autoimmune disease development by targeting the early-life gut microbiome. In this regard, a better understanding of the early-life microbiome–immune axis is essential for developing targeted preventive strategies. Future research must prioritize longitudinal evaluation of autoimmune outcomes after microbiome modulation to reduce the burden of chronic immune-mediated diseases. Full article

High-resolution NMR spectroscopy is the leading method for determining nuclear magnetic moments. It is designed to measure stable nuclei, which can be investigated in macroscopic samples. In this work, we discuss the progress in research into light nuclei from the first three periods of the Periodic Table and several selected heavy nuclides. The ¹H and ³He nuclear magnetic moments, established using the new double Penning trap facility, are also considered. Both nuclei can be used as references in gaseous mixtures. Gas-phase NMR spectroscopy enables precise measurements of the frequencies and shielding constants of isolated single molecules. They can be used to determine new, accurate nuclear magnetic moments of nuclides in stable, gaseous substances. Particular attention is paid to the importance of diamagnetic corrections for obtaining accurate results. Finding precise diamagnetic corrections—shielding factors —even for light nuclei in molecules is a significant challenge. To date, nuclear moments have been obtained primarily from experimental data. The theoretical approach is mostly unable to predict these values accurately. Some remarks are also made on pure theoretical treatments of nuclear moments. Full article

Apple breeding programs focus on enhancing yield, quality, and disease resistance, with a strong emphasis on evaluating phenological traits like flowering time and pomological traits such as fruit size and flavour, which are crucial for commercial success and consumer preference. Twenty-four families were obtained by crossing six apple varieties selected as pollen receptors and four apple genotypes resistant to scab selected as pollen donors. Data related to bud burst date, flowering date, harvest date, lengths of the periods between bud burst and flowering and from flowering to harvest (developmental period), fruit equatorial and polar diameter, fruit polar/diameter ratio, soluble solid content (SSC) and flesh firmness were analysed as a genetic partial diallel design. The study’s ANOVA on 24 fruit families across two years revealed significant genotype–environment interactions affecting flowering date, harvest date, and developmental periods, with some variables like fruit weight and soluble solids showing consistent variation. During each year, temperature influenced phenological phases, with earlier budbreak and flowering in warmer, less variable conditions in 2019. Analysis of genetic effects indicated high heritability for phenological traits and moderate heritability for fruit morphology and quality, with parental genetic contributions varying over years. Principal component and Procrustes analyses identified key variable groupings and parent profiles, highlighting genotypes such as ‘Granny Smith’, ‘McIntosh’, and ‘HM100’ with consistent additive effects, and certain families with notable heterotic performance. Overall, genetic and environmental interactions significantly shape phenological and fruit quality traits, guiding breeding strategies. Full article

Insect pollination, a critical ecological process, pre-dates the emergence of angiosperms by nearly 200 million years, with fossil evidence indicating pollination interactions between insects and non-angiosperm seed plants during the Late Paleozoic. This review examines the symbiotic relationships between insects and gymnosperms in pre-angiosperm ecosystems, highlighting the complexity of these interactions. Fossil records suggest that the mutualistic relationships between insects and gymnosperms, which facilitated plant reproduction, were as intricate and diverse as the modern interactions between angiosperms and their pollinators, particularly bees. These early pollination systems likely involved specialized behaviors and plant adaptations, reflecting a sophisticated evolutionary dynamic long before the advent of flowering plants. The Anthropocene presents a dichotomy: while climate change and anthropogenic pressures threaten insect biodiversity and risk disrupting angiosperm reproduction, such upheaval may simultaneously generate opportunities for novel plant–insect interactions as ecological niches are vacated. Understanding the deep evolutionary history of pollination offers critical insight into the mechanisms underlying the resilience and adaptability of these mutualisms. The evolutionary trajectory of bees—originating from predatory wasps, diversifying alongside angiosperms, and reorganizing after mass extinctions—exemplifies this dynamic, demonstrating how pollination networks persist and reorganize under environmental stress and underscoring the enduring health, resilience, and adaptability of these essential ecological systems. Full article

The chronology of the Petralona hominid remains a key issue in European Middle Pleistocene paleoanthropology. The recent study by Falguères et al., which reports new U-series ages of approximately 300 ka for travertines associated with the Petralona cranium, provides an important opportunity to reassess this long-standing debate. This commentary critically evaluates the strengths and limitations of that contribution, with particular attention to the treatment of analytical precision, geological uncertainties, and stratigraphic constraints inherent to speleothem dating. While the new data represent a valuable analytical advance and independently support a Middle Pleistocene age, the reported narrow error margins warrant cautious interpretation. When broader sources of uncertainty are considered, the results are best viewed as a confirmation rather than a fundamental revision of the established chronological framework. Overall, this commentary situates the findings of the new study within their broader methodological and historical context and underscores their significance for refining, but not redefining, the age and evolutionary placement of the Petralona hominid. Full article

Constructed wetlands (CWs) are signified as green, self-sustaining systems for wastewater treatment. To date, their conventional designs struggle with slow kinetics and poor removal of refractory pollutants. This review redefines CWs as photo-reactive engineered systems, integrating near-neutral Fenton and photo-Fenton processes and in-situ oxidant generation to overcome diffusion limits, acid dosing, and sludge formation. By coupling catalytic fillers, solar utilization, and plant–microbe–radical (ROS) synergies, the approach enables intensified pollutant degradation while preserving the low-energy nature of CWs. Bibliometric trends indicate a sharp rise in studies linking CWs with advanced oxidation and renewable energy integration, confirming the emergence of a circular treatment paradigm. A decision framework is proposed that aligns material selection, reactor hydrodynamics, and solar light management with sustainability indicators such as energy efficiency, Fe-leach budget, and ROS-to-photon yield. This synthesis bridges environmental biotechnology with solar-driven catalysis, paving the way for next-generation eco-engineered wetlands capable of operating efficiently beyond the classical Fenton constraints. This work introduces the concept of “Constructed Wetlands Beyond the Fenton Limit”, where CWs are reimagined as photo-reactive circular systems that unify catalytic, biological, and solar processes under near-neutral conditions. It provides the first integrated decision matrix and performance metrics connecting catalyst design, ROS efficiency, and circular sustainability that offers a scalable blueprint for real-world hybrid wetland applications. Full article

The Archaic period in the Maya lowlands of Mesoamerica emerged around 8000 BCE and likely lasted until about 1000 BCE; however, both the development and complex cultural adaptations representative of Archaic peoples present challenges for archaeologists. In central Belize, archaeological evidence for Archaic people is limited, especially when compared to northern and southern Belize. Nevertheless, our knowledge of Archaic lifestyles in this part of the world has substantially increased over the last twenty years or so. This paper reviews the current understanding of the Archaic period in central Belize based primarily on radiocarbon dates from stratigraphic excavations, diagnostic lithic artifacts, and both faunal and floral remains recovered from excavations, and compares these data to archaeological evidence from northern and southern Belize for regional contextualization and synthesis. Although some aspects of Archaic lifestyles in central Belize appear quite clear based on the available archaeological evidence, others remain elusive. More regional surveys to find sites and an increased number of excavations with datable stratigraphic contexts are needed to more accurately reconstruct the lives of the people who initially inhabited central Belize prior to the emergence of the first culturally recognizable Maya. Full article

A rapid decline of coral reefs is taking place around the world, with climate warming being the biggest driver behind this deterioration. Efforts to increase coral climate resilience via bioengineering methods have thus become urgent, and there is hope that such interventions can help corals and coral reefs survive until a time when no further climate warming occurs and perhaps a future of climate cooling is imaginable. The manipulation of coral-associated bacterial communities is among the less advanced interventions currently being explored. Nevertheless, early findings provide confidence that some level of thermal enhancement can be achieved via the inoculation of corals with beneficial bacteria. The small number of studies available, however, is limited in terms of the traits used to select candidate bacteria and their ability to ascribe host enhancement to specific bacterial taxa and functions. Further, findings to date are unable to decipher whether candidate bacteria integrate stably within the coral microbiome. These shortcomings prevent assessment of the efficacy of bacterial manipulation to enhance the long-term thermal resilience of corals on the reef. Here we summarise the state-of-play of the field and provide recommendations to fast-track this approach via fine-tuning experimental designs and methods. Full article

Background: Large language models (LLMs) are increasingly used in clinical medicine, yet their ability to interpret advanced intraoperative hemodynamic monitoring—particularly in the context of liver transplantation—remains largely unexplored. In this proof-of-concept study, we evaluated ChatGPT’s capacity to interpret multimodal hemodynamic data derived from both standard anesthesia monitoring and the PiCCO system. The study also employed a structured assessment instrument (ARQuAT), adapted through a Delphi-based process to evaluate LLM-generated clinical interpretations. Methods: Ten key surgical–hemodynamic phases of liver transplantation were identified using a modified Delphi approach to capture the major physiological transitions of the procedure. Sequential screenshots representing these phases were obtained from five liver transplant recipients, yielding a total of 50 images. Each screenshot, along with standardized clinical background information, was submitted to ChatGPT. Five expert anesthesiologists independently assessed the model’s responses using the modified ARQuAT tool, which includes six content-quality domains (Accuracy, Up-to-dateness, Contextual Consistency, Clinical Usability, Trustworthiness, Clarity) and a separate catastrophic Risk item. Descriptive statistics were calculated for domain-level performance. Inter-rater reliability (Kendall’s W) and internal consistency (Cronbach’s alpha, McDonald’s omega) were also analyzed. All statistical analyses and visualizations were performed using NumIQO. Results: ChatGPT demonstrated consistently high performance across all content-quality domains, with median scores ranging from 4.6 to 4.8 and more than 90% of all ratings classified as satisfactory. Lower scores appeared only in a small subset of frames associated with abrupt hemodynamic changes and did not indicate a recurring weakness in any specific domain. Catastrophic Risk exhibited a pronounced floor effect, with 86% of ratings scored as 0 and only three isolated high-risk assessments across the dataset. Internal consistency of the six ARQuAT content domains was excellent, while inter-rater agreement was modest, reflecting ceiling effects and tied ratings among evaluators. Conclusions: ChatGPT generated clinically acceptable, contextually aligned interpretations of complex intraoperative hemodynamic data in liver transplant recipients, with minimal evidence of unsafe recommendations. These findings suggest preliminary promise for LLM-assisted interpretation of advanced monitoring, while underscoring the need for future studies involving larger datasets, dynamic physiological inputs, and expanded evaluator groups. The reliability characteristics observed also provide initial support for further refinement and broader validation of the Delphi-derived ARQuAT framework. Full article

With the increasing complexity of cyber threats and the inefficiency of traditional vulnerability management, artificial intelligence has been increasingly integrated into cybersecurity. This review provides a comprehensive evaluation of AI-powered strategies including machine learning, deep learning, and large language models for identifying cybersecurity vulnerabilities and supporting automated patching. In this review, we conducted a synthesis and appraisal of 29 peer-reviewed studies published between 2019 and 2024. Our results indicate that AI methods substantially improve the precision of detection, scalability, and response speed compared with human-driven and rule-based approaches. We detail the transition from conventional ML categorization to using deep learning for source code analysis and dynamic network detection. Moreover, we identify advanced mitigation strategies such as AI-powered prioritization, neuro-symbolic AI, deep reinforcement learning and the generative abilities of LLMs which are used for automated patch suggestions. To strengthen methodological rigor, this review followed a registered protocol and PRISMA-based study selection, and it reports reproducible database searches (exact queries and search dates) and transparent screening decisions. We additionally assessed the quality and risk of bias of included studies using criteria tailored to AI-driven vulnerability research (dataset transparency, leakage control, evaluation rigor, reproducibility, and external validation), and we used these quality results to contextualize the synthesis. Our critical evaluation indicates that this area remains at an early stage and is characterized by significant gaps. The absence of standard benchmarks, limited generalizability of the models to various domains, and lack of adversarial testing are the obstacles that prevent adoption of these methods in real-world scenarios. Furthermore, the research suggests that the black-box nature of most models poses a serious problem in terms of trust. Thus, XAI is quite pertinent in this context. This paper serves as a thorough guide for the evolution of AI-driven vulnerability management and indicates that next-generation AI systems should not only be more accurate but also transparent, robust, and generalizable. Full article

In this paper, a two-phase spatio-temporal point process (STPP) defined on a countable metric space and characterized by a conditional intensity function is introduced. In the first phase, the process is memoryless, generating completely random point patterns. In the second phase, the location and occurrence time of each event depend on the spatial configuration of previous events, thereby inducing spatio-temporal correlation. Theoretical results that characterize the distributional properties of the process are established, enabling both efficient numerical simulation and Bayesian inference. A statistical inference framework is developed, for the setting in which the STPP is observed at discrete calendar dates while the spatial locations of events are recorded, their exact occurrence times are unobserved, i.e., interval-censored. This partial observation scheme commonly arises in ecological and epidemiological applications, such as the monitoring of plant disease or insect pest spread across a spatial grid over time. The methodology is illustrated through an analysis of the spatio-temporal spread of sugarcane yellow leaf virus (SCYLV) in an initially disease-free sugarcane plot in Guadeloupe, FrenchWest Indies. Full article

An accurate DNA clock can strengthen cross-disciplinary inputs in the study of genealogies and ancient migrations. New Y-chromosome sequence data gathered from a Lotli Pai Kaundinya (LPK) Brahmin cohort whose staged migration from the Pontic Steppe to the West Coast of India was previously reported, are used here to generate a more precise DNA clock. The formula distinguishes Y-mutation rates for transitions and transversions and corrects for dropped mutations in sequence reads. The formula is validated against a baptismal tree covering over four centuries (0–704 YBP interval), a published STR-based chronology for this same cohort (704–5200 YBP) and a comparison to Y-Full formation times for mutations older than 3000 YBP. Using this more precise clock, we support a proposed “founder effect” expansion in Khorasan during 4300–3800 YBP using a novel phylogenetic branching metric; and use archeological, numismatic, toponymic, climate reconstruction and ancient textual data to explore religious and professional dimensions of cultural kinship with other communities believed to have interacted with the LPK during their long migration. The availability of more precise dating facilitates the integration of such secondary data types, resulting in an enriched and more plausible migration narrative. Full article

Accurate nearshore bathymetry is essential for various marine applications, including navigation, resource management, and the protection of coastal ecosystems and the services they provide. This study presents an approach to enhance the accuracy of bathymetric estimates derived from high-spatial- and high-temporal-resolution optical satellite imagery. The proposed technique is particularly suited for multispectral sensors that acquire spectral bands sequentially rather than simultaneously. PlanetScope SuperDove imagery was employed and validated against bathymetric data collected using a multibeam echosounder. The study area is the Gulf of Sciacca, located along the southwestern coast of Sicily in the Mediterranean Sea. Here, multibeam data were acquired along transects that are subparallel to the shoreline, covering depths ranging from approximately 7 m to 50 m. Satellite imagery was radiometrically and atmospherically corrected and then processed using a simplified radiative transfer transformation to generate a continuous bathymetric map extending over the entire gulf. The resulting satellite-derived bathymetry achieved reliable accuracy between approximately 5 m and 25 m depth. Beyond these limits, excessive signal attenuation for higher depths and increased water turbidity close to shore introduced significant uncertainties. The innovative aspect of this approach lies in the combined use of spectral averaging among the most water-penetrating bands, temporal averaging across multiple acquisitions, and a liquid-facets noise reduction technique. The integration of these multi-layer inputs led to improved accuracy compared to using single-date or single-band imagery alone. Results show a strong correlation between the satellite-derived bathymetry and multibeam measurements over sandy substrates, with an estimated error of ±6% at a 95% confidence interval. Some discrepancies, however, were observed in the presence of mixed pixels (e.g., submerged vegetation or rocky substrates) or surface artifacts. Full article