bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy-Based Adaptive Control for Variable-Rope-Length Double-Pendulum Ship-Borne Cranes: A Disturbance Rejection Stabilization Controller Without Overshoot
Authors: Zhong Ken , Qian Yuzhe , Chen He , Wu Shujie
Published: January 2025

The operation process of double-pendulum ship-borne cranes with variable rope lengths is frequently complex, with numerous unpredictable circumstances, such as the swing of the load and external environmental interferences, which undoubtedly make the analysis of the swing characteristics of the system and the controller design more difficult. On this basis, an active disturbance rejection controller based on an energy coupling method is proposed to inhibit the double-pendulum swing angle. The controller can suppress the swing of the hook and load within 0.5 degrees under the conditions of continuous sea wave disturbances and external disturbances. Firstly, the energy function of the system is constructed by analyzing the dynamic model of the system. Then, an adaptive control method is designed by analyzing the energy function of the system. In addition, an overshoot limit term and an anti-swing term are added to limit the overshoot and swing of underactuated parts of the system. Then, the stability of the closed-loop system is strictly proven by using Lyapunov analysis. Finally, the simulation and experimental results indicate that the proposed controller ensures the accurate positioning of the jib and rope length without overshoot. Additionally, it effectively reduces the double-pendulum swing angle when there is an external interference such as waves, demonstrating strong robustness.
Optimizing High-Power Performance of [001]-Oriented Pb(Mg1/3Nb2/3)-PbTiO3 Through Combined DC and AC Polarization Above Curie Temperature
Authors: Zhu Yuliang , Wang Xiaobo , Xue Wenchao , Wen Xinran , Luo Chengtao
Published: January 2025

Pb(Mg1/3Nb2/3)O3-PbTiO3 single crystals (PMN-PT SCs) are widely utilized in high-performance piezoelectric devices due to their exceptional piezoelectric properties. Among the various post-processing techniques for domain engineering in PMN-PT SCs, alternating current polarization (ACP) has become a widely adopted method for enhancing piezoelectric performance. This study proposes a new ultrahigh-temperature field-cooling polarization (UFCP) technique, combining direct current polarization (DCP) and ACP with field cooling above the Curie temperature. Dielectric spectra indicate that the UFCP method promotes electric field-induced phase transitions above the Curie point, forming a stable multiphase configuration. The transverse piezoelectric coefficient d31 of UFCP SCs is 1126 pC/N, and the electromechanical coupling factor k31 is 0.559. Compared with traditional DCP, UFCP increases d31 by 68.6%, the mechanical quality factor Qm by 16.7%, and the piezoelectric figure of merit (FOM) by 98.3%. Furthermore, under high-power excitation with a root-mean-square voltage of 15 V, UFCP achieves a 343% increase in power and a 130.5% improvement in the FOM compared with DCP, demonstrating its potential for enhancing high-power performance in practical applications.
Implications of Output Impedance Mask Stability on Power Bus Architectures Used in Space Platforms
Authors: Carrasco José A. , Ejea Juan B. , Garrigós Ausias , Sanchis Esteban , Blanes José M. , Ferreres Agustín , Marroquí David , Gilabert David
Published: January 2025

The European Power Standard, used when designing and implementing spacecraft power buses, imposes stringent impedance requirements for high reliability and robustness, unlike other standards such as those from the American Institute for Aeronautics and Astronautics, SAE International, or the International Deep Space Interoperability Standard. These strict requirements, however, may limit innovations leveraging new technologies resulting from recent component advancements. This work examines the implications of the European Power Standard’s output impedance criteria for stability and its impact on payload power supplies, focusing on the potential to increase operational frequencies in power supply topologies to reduce system volume and mass, which are key factors in space technology.
Ablation Mechanism and Process of Low-Density Needled Quartz Felt/Phenolic Resin Thermal Protection Materials Under Long-Term Low–Medium Heat Flow
Authors: Huang Xiaoyu , Zhao Yuwen , Wang Kaining , Wang Yifan , Ding Chen , Wang Yichun , Liu Xianlong , Duan Xiuhui
Published: January 2025

In the aerospace industry, low-density quartz fiber/phenolic resin composites offer advantages such as low cost, low density, high thermal insulation, and excellent thermal resistance, making them a promising candidate when exposed to a long-term low–medium heat flow environment. However, there is currently a lack of understanding regarding the ablation evolution and mechanisms of these materials under this environment, which hampers the enhancement of material performance. Additionally, there is insufficient quantification of their pyrolysis processes, which is detrimental to the development of subsequent mathematical models for ablation thermal response. Therefore, this work focuses on the study of the ablation process of low-density needled quartz felt/phenolic resin (PR/NQF) under long-term low–medium heat flow. Ablation samples of PR/NQF with varying densities were obtained by treating them with a quartz lamp at different temperatures. The differences in the carbonization of the PR/NQF ablation surface were analyzed through SEM, microCT, FTIR, XRD, and XPS experiments, revealing the influence of ablation temperature and composite density. Subsequently, the pyrolysis mechanism of PR/NQF was analyzed using Py-GC-MS, resulting in insights into the evolution and component ratio of pyrolysis gases and their temperature correlations. To further describe the pyrolysis process of low-density PR/NQF, a pyrolysis kinetics model was developed based on the TGA experimental results, and the consistency between the fitted results and theoretical values was validated. The conclusions of this study provide support for analyzing the ablation mechanisms and evolution processes of low-density PR/NQF under long-term low–medium heat flow. Furthermore, the conclusions offered a certain degree of basic data support of mathematical models for ablation processes and the development of new thermal protection materials.
Balancing Tradition and Innovation: The Role of Environmental Conservation Agriculture in the Sustainability of the Ifugao Rice Terraces
Authors: Maharjan Keshav Lall , Gonzalvo Clarisse Mendoza , Baggo Jude Cadingpal
Published: January 2025

This study investigates the continuation of Environmental Conservation Agriculture (ECA) practices among farmers in the Ifugao Rice Terraces, a Globally Important Agricultural Heritage System (GIAHS) in the Philippines. Through a cross-sectional survey of ECA farmers in the municipality of Banaue, this research explores the socio-demographic, environmental, and economic factors influencing the adoption and persistence of ECA. The findings reveal that while access to resources such as high-yielding seeds, modern farming equipment, and financial support is important for the adoption of ECA, the shift toward high-yielding varieties has contributed to a decline in the cultivation of Tinawon rice, which is vital for maintaining the ecological balance and cultural heritage of the terraces. This study underscores the importance of balancing modern agricultural practices with the continued cultivation of Tinawon rice to preserve biodiversity, soil health, and cultural identity, while also enhancing agricultural productivity. Additionally, the roles of community-based support systems, market access, and financial incentives are highlighted as key factors in sustaining ECA practices. Climate change presents both challenges and opportunities for adaptation, making it essential to integrate traditional knowledge with modern techniques to build resilience. Understanding the factors that shape ECA continuation is crucial for refining initiatives that address both the economic and cultural contexts. By emphasizing the importance of tailored, community-driven interventions, this study provides critical insights for enhancing ECA adoption in the Ifugao Rice Terraces, contributing to climate resilience and the long-term sustainability of this significant agricultural heritage system.
Evaluation of Salt Tolerance in Four Self-Rooted Almond Genotypes for Super-High-Density Orchards Under Varying Salinity Levels
Authors: Rius-García Xavier , Videgain-Marco María , Casanova-Gascón José , Acuña-Rello Luis , Zufiaurre-Galarza Raquel , Martín-Ramos Pablo
Published: January 2025

Increasing soil salinity threatens almond production globally, driving the need for the development of salt-tolerant cultivars. This study investigated the salt tolerance mechanisms of four self-rooted almond genotypes (Vialfas, Guara, Penta, and Avijor) under controlled conditions. Young plants were exposed to four salinity levels (0, 25, 50, and 75 mM NaCl) for 5 months. Growth parameters (trunk diameter, shoot length, fresh and dry weights), physiological responses (chlorophyll fluorescence, gas exchange, Soil–Plant Analysis Development (SPAD)), and mineral content were analyzed. Results show significant genotype-specific responses at the critical salinity threshold of 50 mM NaCl. Under these conditions, Guara and Vialfas maintained higher stem fresh weights (31.4 g and 37 g, respectively), while Avijor showed significant declines. Trunk diameter measurements revealed Vialfas’ superior performance (7 mm) compared to Guara and Penta (both around 6 mm), while Avijor exhibited the most significant reduction (5 mm). Chlorophyll fluorescence parameters indicated stress impact, with Fv/Fm values decreasing to 0.84 compared to control values of 0.87. Guara maintained higher K+/Na+ ratios in leaves (3.05) compared to Avijor (1.95), while Penta showed better Na+ exclusion ability with the lowest leaf Na+ content (0.57%). Cl− accumulation patterns also differed among genotypes, with Avijor and Vialfas showing higher leaf Cl− concentrations (0.74% and 0.73%, respectively) compared to Penta (0.44%). Genotype responses across all salinity levels revealed distinct tolerance patterns: Guara maintained growth and physiological functions across treatments, while Penta showed remarkable stability under high salinity. Vialfas exhibited vigor at low salinity but declined sharply at 75 mM NaCl. Avijor demonstrated the highest salt sensitivity. These findings highlight the genetic variability in salt tolerance among almond cultivars and identify potential sources of salt-tolerant traits for breeding programs. The study also provides insights for optimizing genotype selection and management strategies in salt-affected orchards, contributing to more sustainable almond production in challenging environments.
A Method for the Rapid Identification of Rice Seed Blast Using Deep Learning and Hyperspectral Imagery
Authors: Yin Yanling , Wang Ruidong , Jiang Yang , Suo Yuting , Li Yang , Wang Zhentao , Shen Xihui
Published: January 2025

Rice seeds’ infection with rice blast will directly lead to rice yield reduction or even crop failure in the next year. Therefore, it is very important accurately identify infected rice seeds. In this study, deep learning and hyperspectral imaging techniques were used for that purpose. First, hyperspectral image data were collected. Then, the UeAMNet (unsupervised extraction attention-based mixed CNN) model—designed in this study—was used to analyze these data and the results compared with the 2DCNN, 3DCNN, A2DCNN, A3DCNN, Ue2DCNN, Ue3DCNN, UeA2DCNN, UeA3DCNN, MNet, AMNet and UeMNet models using different training set (Tr) sizes. The results showed that the new UeAMNet model was superior to the comparison models when using different Tr sizes, and the accuracy could reach 100%. Notably, when Tr was only 0.05, the accuracy of this model still reached 96.85%. This showed that the proposed method could successfully identify infected rice seeds. Therefore, this study provides an approach for rice germplasm management and also for the development of crop disease identification methods in other parts of the world.
Effects of Hexanal Supplementation on Volatile Compound Profiles and Quality Parameters of ‘Fuji Kiku’ Apples During Cold Storage and Shelf Life
Authors: Jesenko Erika , Vidrih Rajko , Zlatić Emil
Published: January 2025

The effects of hexanal supplementation in the storage atmosphere of ‘Fuji Kiku’ apples were investigated. The contents of volatile compounds (VOCs) in the headspace emitted by apple fruit during cold storage and in the headspace of apple fruit and juice during shelf life were determined. Hexanal treatment during storage significantly affected the VOC profile by stimulating the production or retention of key esters, including hexyl acetate, ethyl acetate, and butyl 2-methylbutanoate, during cold storage. Supplementation of hexanal also increased the production of linear esters, especially hexyl acetate, and promoted the formation of branched esters such as ethyl 2-methylbutanoate and hexyl 2-methylbutanoate during shelf life. Hexanal also increased the alcohol concentrations, with a significant increase in hexanol and 2-pentanol. Partial least squares discriminant analysis showed clear separation between control and hexanal-treated samples, with compounds like butyl hexanoate and 2-methyl-1-butanol being the most influential. Apple juice extracted from the flesh of hexanal-treated apples exhibited higher concentrations of key VOCs, including 2-methylbutyl acetate, hexyl acetate, and 2-methyl-1-butanol. No significant differences in firmness were observed; however, hexanal showed an inhibitory effect on the colour development of fruit. This study highlights the potential of hexanal in influencing aroma-related compounds and provides insight into strategies to improve postharvest aroma in apples.
Data Integration and Analytics in the Dairy Industry: Challenges and Pathways Forward
Authors: Cabrera Victor E. , Bewley Jeffrey , Breunig Mitch , Breunig Tom , Cooley Walt , De Vries Albert , Fourdraine Robert , Giordano Julio O. , Gong Yijing , Greenfield Randall , Hu Haowen , Lenkaitis Andy , Niu Mutian , Noronha Eduardo A. F. , Sullivan Michael
Published: January 2025

The dairy industry faces significant challenges in data integration and analysis, which are critical for informed decision-making, operational optimization, and sustainability. Data integration—combining data from diverse sources, such as herd management systems, sensors, and diagnostics—remains difficult due to the lack of standardization, infrastructure barriers, and proprietary concerns. This commentary explores these issues based on insights from a multidisciplinary group of stakeholders, including industry experts, researchers, and practitioners. Key challenges discussed include the absence of a national animal identification system in the US, high IT resource costs, reluctance to share data due to competitive disadvantages, and differences in global data handling practices. Proposed pathways forward include developing comprehensive data integration guidelines, enhancing farmer awareness through training programs, and fostering collaboration across industry, academia, and technology providers. Additional recommendations involve improving data exchange standards, addressing interoperability issues, and leveraging advanced technologies, such as artificial intelligence and cloud computing. Emphasis is placed on localized data integration solutions for farm-level benefits and broader research applications to advance sustainability, traceability, and profitability within the dairy supply chain. These outcomes provide a foundation for achieving streamlined data systems, enabling actionable insights, and fostering innovation in the dairy industry.
Alpha and Betacoronavirus Detection in Neotropical Bats from Northeast Brazil Suggests Wide Geographical Distribution and Persistence in Natural Populations
Authors: Figueiroa Thays , Galvão Bueno Marina , Bento Moura Patricia Emilia , de Oliveira Marcione Brito , Passos Cordeiro José Luís , Santos-Cavalcante Nádia , Camacho Antevere Mazzarotto Giovanny A. , Wallau Gabriel Luz , Corrêa da Silva Junior Leonardo , Resende Paola Cristina , Siqueira Marilda M. Mendonça , Ogrzewalska Maria
Published: January 2025

The emergence of zoonotic viral diseases, notably exemplified by the recent coronavirus disease pandemic in 2019 (COVID-19), underscores the critical need to understand the dynamics of viruses circulating in wildlife populations. This study aimed to investigate the diversity of coronaviruses in bat populations from northeastern Brazil, particularly in the state of Ceará, where little research on bat pathogens has been conducted previously. Bat sampling was performed between March 2021 and March 2022 across three municipalities, resulting in the collection of oral and rectal swabs from 298 captured individuals. Molecular analyses revealed alphacoronaviruses in multiple bat species. Additionally, a novel Betacoronavirus was identified in Artibeus planirostris, which did not fall within an established subgenus. Phylogenetic placement of these new coronavirus sequences suggests that closely related coronavirus lineages can infect a wide range of bat species sampled in distantly related Brazilian states and biomes. No SARS-CoV-2 and influenza A viruses were found in the sampled bats. These findings expand our understanding of coronavirus diversity in Brazilian bats. The detection of coronaviruses in various bat species underscores the importance of bats as reservoirs for these viruses. The absence of SARS-CoV-2 in the sampled bats indicates a lack of spillback events from human or environmental sources. However, the potential for future transmission events underscores the importance of ongoing surveillance and transmission mitigation protocols in wildlife management practices.
Integrating Metabolomics and Genomics to Uncover Antimicrobial Compounds in Lactiplantibacillus plantarum UTNGt2, a Cacao-Originating Probiotic from Ecuador
Authors: Molina Diana , Angamarca Evelyn , Marinescu George Cătălin , Popescu Roua Gabriela , Tenea Gabriela N.
Published: January 2025

Background/Objectives: Lactic acid bacteria (LAB) produce several diverse metabolites during fermentation that play key roles in enhancing health and food quality. These metabolites include peptides, organic acids, exopolysaccharides, and antimicrobial compounds, which contribute to gut health, immune system modulation, and pathogen inhibition. This study analyzed the intracellular (Met-Int) and extracellular metabolites (Met-Ext-CFS; cell-free supernatant) of Lactiplantibacillus plantarum UTNGt2, a probiotic strain isolated from Theobroma grandiflorum. Methods: The assessment was performed using capillary LC-MS/MS metabolomics with a SWATH-based data-independent acquisition approach to identify molecules associated with antimicrobial activity. Results: The integration of metabolomic data with whole-genome annotation enabled the identification of several key metabolites, including amino acids, nucleotides, organic acids, oligopeptides, terpenes, and flavonoids, many of which were associated with the antimicrobial activity of UTNGt2. Pathway analysis reveals critical processes such as secondary metabolite biosynthesis, nucleotide and galactose metabolism, and cofactor biosynthesis. By integrating RiPP (ribosomally synthesized and post-translationally modified peptide) cluster gene predictions with LC-MS data, this study validates the production of specific RiPPs and uncovers novel bioactive compounds encoded within the UTNGt2 genome. The oligopeptide val-leu-pro-val-pro-gln found in both Met-Int (ESI+) and Met-Ext-CFS (ESI+) may contribute to the strain’s antimicrobial strength. It could also enhance probiotic and fermentation-related functions. Conclusions: While genome-based predictions highlight the strain’s biosynthetic potential, the actual metabolite profile is influenced by factors like transcriptional regulation, post-transcriptional and post-translational modifications, and environmental conditions. These findings emphasize the value of multi-omics approaches in providing a holistic understanding of metabolite production and its role in antimicrobial activity.
Prospective Observational Study of De-Escalation of Empirical Antibiotics in Fiji’s National Hospital
Authors: Young-Sharma Tracey , Wati Shitanjni , Sharma Vikash , Naidu Ravi , Tong Deborah , Jenney Adam
Published: January 2025

Background: Antimicrobial resistance is a global health threat and Fiji is not exempt. The appropriate prescribing and timely de-escalation of antibiotics as an integral component of antimicrobial stewardship has been recently introduced in Fiji to help curb antimicrobial resistance through de-escalation, leading to a reduced opportunity for the induction of resistance. Objectives: To assess whether empirical antibiotics are being adjusted in a timely fashion in patients admitted with a diagnosis of suspected infection in the Colonial War Memorial Hospital( CMWH) over three months. Method: The study was undertaken on patients admitted to the acute medical ward and intensive care unit of the CWMH in Suva (Fiji’s largest hospital). A total of 474 patients were prospectively enrolled at admission when prescribed empiric antibiotic therapy for suspected infections between February and April 2019. Results: A total of 356 patients admitted to the Acute Medical Ward and 118 admitted to the Intensive Care Unit were prescribed empiricalantibiotics. These 474 patients were prospectively observed to determine the factors influencing the extent and the timing of antibiotic de-escalation. Only 137 (29%) patients had their antibiotic regimen de-escalated in the first 72 h post-admission based on their microbiological results, whereas, 207 (42%) were de-escalated more than 72 h after admission (OR = 0.5, 95% CI 0.3–0.89; p < 0.016). Conclusions: At CWMH, antibiotic de-escalation is slow and may be improved by quicker laboratory reporting, greater access to laboratory results for prescribers, and the availability of a wider range of narrow-spectrum antibiotics to assist de-escalation.
Oral Administration of Lactobacillus gasseri and Lacticaseibacillus rhamnosus Ameliorates Amyloid Beta (Aβ)-Induced Cognitive Impairment by Improving Synaptic Function Through Regulation of TLR4/Akt Pathway
Authors: Choi Hye Ji , Lee Hyo Lim , Kim In Young , Ju Yeong Hyeon , Heo Yu Mi , Na Hwa Rang , Lee Ji Yeon , Choi Soo-Im , Heo Ho Jin
Published: January 2025

This study investigated the anti-amnesic effects of Lactobacillus gasseri (L. gasseri) MG4247 and Lacticaseibacillus rhamnosus (L. rhamnosus) MG4644 in amyloid beta (Aβ)-induced mice. We confirmed that oral administration of L. gasseri MG4247 and L. rhamnosus MG4644 ameliorated cognitive impairment in Aβ-induced mice using Y-maze, passive avoidance, and Morris water maze tests. Oral administration of L. gasseri MG4247 and L. rhamnosus MG4644 protected the antioxidant system by regulating superoxide dismutase levels, reduced glutathione levels, and reduced malondialdehyde contents. Similarly, they attenuated mitochondrial function by decreasing mitochondrial reactive oxygen species levels and increasing mitochondrial membrane potential and ATP levels. In addition, they regulated neuroinflammation and neurotoxicity by modulating the Toll-like receptor 4 (TLR4)/protein kinase B (Akt) pathway. As a result, they enhanced synaptic function by regulating acetylcholine contents, acetylcholinesterase activity, and the expression of synaptic-function-related proteins such as AChE, ChAT, SYP, PSD-95, and GAP-43. Furthermore, the administration of L. gasseri MG4247 and L. rhamnosus MG4644 improved dysbiosis by promoting the growth of beneficial bacteria while suppressing the growth of harmful bacteria. Therefore, these results suggest that L. gasseri MG4247 and L. rhamnosus MG4644 may be used as probiotics to prevent cognitive impairment.
Deep Learning-Based Optimization for Maritime Relay Networks
Authors: Guo Nianci , Wang Xiaowei
Published: January 2025

The complexity and uncertainty of the marine environment pose significant challenges to the stability and coverage of communication links. Due to the limited coverage range of traditional onshore base stations (BSs) in marine environments, relay technology has become an essential approach to extending communication coverage. However, the rapid variations in marine wireless channels and the complexity of hydrological conditions make it extremely difficult to obtain accurate channel state information (CSI). In particular, dynamic environmental factors such as waves, tides and wind speed cause channel parameters to fluctuate significantly over time. To address these challenges, this paper proposes a cooperative communication strategy based on ships and designs a novel channel modeling method to accurately capture the characteristics of marine wireless channels. Furthermore, a deep learning-based optimization scheme is proposed, which formulates the relay selection problem as a spatiotemporal classification task. By integrating the spatial positions of candidate relays and their communication conditions, the proposed scheme enables real-time selection of the optimal relay while evaluating link connectivity probabilities under hydrological influences. Simulation results confirm that the proposed method achieves high accuracy even in rapidly changing marine environments.
Automated System for Evaluating Alternatives for Developing Innovative IT Projects
Authors: Pikh Iryna , Senkivskyy Vsevolod , Sikora Liubomyr , Lysa Nataliia , Kudriashova Alona
Published: January 2025

Software engineering occupies a prominent place in the theory and practice of simulation modeling, which necessitates scientific research in the field of methodological principles for forming software product quality. The problem of determining the optimal option for software development is one of the key ones in the field of information technology because it determines the quality of the final product and the efficiency of project management. The article considers the concept of developing an automated system, the basis of which is the software for assessing alternatives in the process of creating innovative IT projects. The main goal of the study is to model alternatives and select the optimal option for the process of creating an IT project using modern methodological approaches. For this purpose, the methods of ontological analysis, expert evaluation, multi-criteria optimization, pairwise comparisons and multi-factor selection of alternatives are applied. In the course of the research, a subset of Pareto factors is singled out and alternative development options are formed based on the method of linear convolution of criteria. The proposed methodology allows for assessing the importance of key factors and selecting the optimal option for the software development process. As a result, the developed approach contributes to strategic planning and increases the transparency of the decision-making process. The key result of the research is the created software product that allows one to automate the procedure for selecting the optimal solution for the IT project development process, providing reliable support for simulation modeling and increasing the efficiency of project management. The proposed methodology creates a new paradigm for making informed decisions regarding systems for creating complex software complexes.
Combining Higher-Order Statistics and Array Techniques to Pick Low-Energy P-Seismic Arrivals
Authors: Messuti Giovanni , Palo Mauro , Scarpetta Silvia , Napolitano Ferdinando , Scotto di Uccio Francesco , Capuano Paolo , Amoroso Ortensia
Published: January 2025

We propose the HOSA algorithm to pick P-wave arrival times on seismic arrays. HOSA comprises two stages: a single-trace stage (STS) and a multi-channel stage (MCS). STS seeks deviations in higher-order statistics from background noise to identify sets of potential onsets on each trace. STS employs various thresholds and identifies an onset only for solutions that are gently variable with the threshold. Uncertainty is assigned to onsets based on their variation with the threshold. MCS verifies that detected onsets are consistent with the array geometry. It groups onsets within an array by hierarchical agglomerative clustering and selects only groups whose maximum differential times are consistent with the P-wave travel time across the array. HOSA needs a set of P-onsets to be calibrated. These sets may be already available (e.g., preliminary catalogs) or retrieved from picking (manually/automatically) a subset of traces in the target area. We tested HOSA on 226 microearthquakes recorded by 20 temporary arrays of 10 stations each, deployed in the Irpinia region (Southern Italy), which, in 1980, experienced a devastating 6.9 Ms earthquake. HOSA parameters were calibrated using a preliminary catalog of onsets obtained using an automatic template-matching approach. HOSA solutions are more reliable, less prone to false detection, and show higher inter-array consistency than template-matching solutions.
Photovoltaic Power Plants with Horizontal Single-Axis Trackers: Influence of the Movement Limit on Incident Solar Irradiance
Authors: Barbón Arsenio , Martínez-Suárez Jaime , Bayón Luis , Bayón-Cueli Covadonga
Published: January 2025

This paper presents an energy analysis of the influence of the movement limit of a horizontal single-axis tracker on the incident energy on the photovoltaic field. The procedure used comprises the following steps: (i) the determination of the periods of operation of a horizontal single-axis tracking; (ii) the analytical determination of the annual, daily, and hourly incident solar irradiance on the photovoltaic field; (iii) the validation of the model; and (iv) the definition of the evaluation indicators. The study focused on three photovoltaic power plants in Spain (Miraflores PV power plant, Basir PV power plant, and Canredondo PV power plant). Four evaluation indicators (annual energy loss, daily energy loss, beam component, and diffuse component) and ten movement limits, ranging from ±50 (°) to ±60 (°), were analysed. In Spain, photovoltaic power plants usually have a movement limit of ±60 (°), which is why it has been called the current scenario. According to this study, the following conclusions can be drawn: (i) It is necessary to calculate the optimal movement limit for each site under study at the design stage of the PV power plant. Although the energy loss per square metre for not using the optimal boundary movement is small, due to the large surface of the photovoltaic field, these energy losses cannot be neglected. For example, in the Canredondo photovoltaic power plant, the limit movement is not optimised and the annual energy loss is 18.49 (MWh). (ii) The higher the range of the limiting movement, the shorter the duration of the static operating period. Therefore, when the current scenario starts the normal tracking mode (where the beam component is maximised), the other scenarios remain in the static mode of operation in a horizontal position, which impairs the incidence of the beam component and favours the diffuse component. (iii) The type of day, in terms of cloudiness index, prevailing at a given location affects the choice of the movement limit. If the beam component is predominant, it favours the performance of the current scenario. In contrast, if the diffuse component is predominant, it favours scenarios other than the current scenario.
Deformation and Failure Mechanism and Control of Water-Rich Sandstone Roadways in the Huaibei Mining Area
Authors: Zhang Zhisen , Fan Yukuan , Xu Qiang , Li Kai , Han Minkang , Fei Lixiang
Published: January 2025

The sandstone roof rock in the Huaibei mining area contains abundant water at depths of 2–3 m. Water–rock interactions in the rock-surrounding roadway can cause significant deformation, seriously threatening the safety of mine operations. Investigating the deformation and failure mechanisms of water-rich sandstone is therefore of critical importance. In this study, X-ray diffraction and scanning electron microscopy were used to analyze the composition and microstructure of water-rich sandstone. Based on the stress state during the roadway excavation, a true triaxial loading scheme with four different stress paths was designed to study the effects of different moisture contents and loading methods on the mechanical properties of the sandstone. The results show that the deviatoric stress decreased for all stress paths. Acoustic emission (AE) characteristics during the deformation and failure processes were also studied, which indicated that the AE b-value decreased, increased, and then decreased again corresponding to the primary compaction, elastic deformation, and plastic deformation evolutionary processes in the internal microstructure of the rock. The variation in the b-value reflected the development and expansion of internal fractures. These findings provide useful insights for controlling the stability of the surrounding rock in water-rich roadways in coal mines.
Deep Learning for Risky Cardiovascular and Cerebrovascular Event Prediction in Hypertensive Patients
Authors: Goretti Francesco , Salman Ali , Cartocci Alessandra , Luschi Alessio , Pecchia Leandro , Milli Massimo , Iadanza Ernesto
Published: January 2025

In this comprehensive study, we employed a versatile approach to tackle the prediction challenges associated with atrial fibrillation (AF) and cardiovascular events (CE). Exploiting the Gaussian copula synthesizer technique for data generation, we created high-quality synthetic data to overcome the limitations posed by scarce patient records. Heart rate variability (HRV), known to be an efficient indicator of cardiac health often used with artificial intelligence (AI), was used to train and optimize custom-built deep learning (DL) models. Additionally, we explored transfer learning (TL) to enhance the model capabilities by adapting our AF classification model to address CE classification challenges, effectively transferring learned features and patterns, without extensive retraining. As a result, our models achieved accuracy rates of 77% for AF and 82% for CEs, with high sensitivity, highlighting the efficacy of synthetic data generation and transfer learning in improving classification performance across diverse medical datasets. These findings hold significant promise for enhancing diagnostic and predictive capabilities in clinical settings, ultimately contributing to improved patient care and outcomes.
DSpix2pix: A New Dual-Style Controlled Reconstruction Network for Remote Sensing Image Super-Resolution
Authors: Wang Zhouyi , Wang Changcheng
Published: January 2025

Super-resolution reconstruction is a critical task in remote sensing image classification, and generative adversarial networks (GANs) have emerged as a dominant approach in this field. Traditional generative networks often produce low-quality images at resolutions like 256 × 256, and current research on single-image super-resolution typically focuses on resolution enhancement factors of two to four (2×–4×), which do not meet practical application demands. Building upon the framework of StyleGAN, this study introduces a dual-style controlled super-resolution reconstruction network referred to as DSpix2pix. It uses a fixed style vector (Style 1) from StyleGAN-v2, generated through its mapping network and applied to each layer in the generator. And an additional style vector (Style 2) is extracted from example images and injected into the decoder using AdIn, enhancing the balance of styles in the generated images. DSpix2pix is capable of generating high-quality, smoother, noise-reduced, and more realistic super-resolution remote sensing images at 512 × 512 and 1024 × 1024 resolutions. In terms of visual metrics such as RMSE, PSNR, SSIM, and LPIPS, it outperforms traditional super-resolution networks like SRGAN and UNIT, with RMSE consistently exceeding 10. The network excels in 2× and 4× super-resolution tasks, demonstrating potential for remote sensing image interpretation, and shows promising results in 8x super-resolution tasks.
Context Is King: Large Language Models’ Interpretability in Divergent Knowledge Scenarios
Authors: Piñeiro-Martín Andrés , Santos-Criado Francisco-Javier , García-Mateo Carmen , Docío-Fernández Laura , López-Pérez María del Carmen
Published: January 2025

Large language models (LLMs) have revolutionized the field of artificial intelligence in both academia and industry, transforming how we communicate, search for information, and create content. However, these models face knowledge cutoffs and costly updates, driving a new ecosystem for LLM-based applications that leverage interaction techniques to extend capabilities and facilitate knowledge updates. As these models grow more complex, understanding their internal workings becomes increasingly challenging, posing significant issues for transparency, interpretability, and explainability. This paper proposes a novel approach to interpretability by shifting the focus to understanding the model’s functionality within specific contexts through interaction techniques. Rather than dissecting the LLM itself, we explore how contextual information and interaction techniques can elucidate the model’s thought processes. To this end, we introduce the Context-Driven Divergent Knowledge Evaluation (CDK-E) methodology, along with the Divergent Knowledge Dataset (DKD), for evaluating the interpretability of LLMs in context-specific scenarios that diverge from the model’s inherent knowledge. The empirical results demonstrate that advanced LLMs achieve high alignment with divergent contexts, validating our hypothesis that contextual information significantly enhances interpretability. Moreover, the strong correlation between LLM-based metrics and semantic metrics confirms the reliability of our evaluation framework.
Numerical Analysis of Temperature Distribution During Charging Process of Vertically Installed Hydrogen Tanks
Authors: Lee Yeseung , Hur Deog-Jae , Noh Jung-Hun
Published: January 2025

Recent advancements in hydrogen tank technology have favored the use of composites over metals for weight reduction, although at the cost of a narrower operating temperature range. Therefore, this study aims to establish safety standards for charging tube skids—large tanks positioned vertically within hydrogen transport vehicles—by examining the variations in temperature distribution under different charging environments through numerical analysis. A two-dimensional axisymmetric model was developed based on ANSYS Fluent to incorporate the effect of buoyancy by applying gravitational conditions along the axial direction. The study analyzed the impact of various charging and environmental conditions (charging time (0~240 min), inlet temperature, ambient temperature, initial temperature (−20 °C~40 °C), and initial pressure (5~20 bar)) on temperature distribution, ultimately deriving a regression equation to predict the tank’s maximum temperature. The findings indicate that the initial temperature has the most significant correlation with the tank’s temperature, followed by charging time and ambient temperature. Inlet temperature and initial pressure demonstrated minimal influence within the study’s scope. The derivation of predictive formulas for the maximum temperatures of the tank’s three regions, all showing an R2 value of 0.99 or higher, highlights the practicality of these results. This study’s insights are expected to contribute to further research aimed at optimizing charging conditions for tube skids and other hydrogen tanks.
End-of-Life Scenarios for Mass Timber: Assumptions, Limitations and Potentials—A Literature Review
Authors: Lin Lu , Trabucco Dario , Perrucci Giovanni
Published: January 2025

This paper presents a literature review exploring the end-of-life (EoL) scenarios for mass timber, focusing on Life Cycle Assessment (LCA), Environmental Product Declarations (EPDs), and circular principles. Despite its claimed environmental benefits, significant gaps exist in standardising LCA methodologies, including inconsistent system boundaries, challenges with time-dependent emissions, and limited integration of circular strategies. The literature review evaluates four primary EoL scenarios: reuse, recycling, energy recovery, and landfill. Reuse is identified as the most sustainable option, extending material lifespans and minimising environmental impacts, followed by recycling. Energy recovery is considered a fallback, while landfill remains the least desirable. Design for Disassembly and Reuse (DfD&R) is highlighted as critical for promoting circularity, though economic, market, and regulatory barriers hinder widespread adoption. The conclusion of this literature review calls for several thematic topics including harmonised LCA practices, policy reforms, and industry awareness to optimise EoL strategies for mass timber. By addressing these challenges, the building sector can better align with circular economy goals, reducing environmental burdens and supporting global climate targets.
Estimation of Fuel Cell Power Demand on Commercial Vehicles Based on Improved Multiple Grey Prediction Method Considering Dynamic Time Window
Authors: Wang Yuan , Li Yingjia , Lu Jianshan , Zhou Hongbo
Published: January 2025

A frequently large variation in load conditions is of great impact on the service life of fuel cells during the operation of fuel cell vehicles and further increases the maintenance cost of the system. This study proposed a method of power demand prediction of the proton exchange membrane fuel cell (PEMFC) on vehicles in the actual traffic environment. The hybrid power system topology of fuel cells and power battery on commercial vehicles is selected to build a fuel cell model, and the accuracy of the fuel cell model is verified. An improved multiple grey prediction method is then proposed to predict the power demand during the sampling period of the fuel cell while considering a dynamic time window in the prediction period. Comparisons were made between this proposed model and the other two prediction models as a single-step prediction and multi-step prediction. Data of CHTC-HT and field testing working conditions were used to evaluate these three prediction models in fuel cell power demand. Results showed that the multiple grey method showed a better prediction performance than the other models, indicated by the lowest error value of 16.944% under the CHTC-HT condition, the lowest error value of 2.169% under stable conditions with less variable load and 1.930% under dynamic conditions with frequent load changes in field testing. This study of the demand power prediction can be devoted to pre-tuning the fuel cell system to avoid performance degradation caused by unanticipated power fluctuation.
Assessing Visual Pollution: The Impact of Urban Outdoor Advertisements in Addis Ababa, Ethiopia
Authors: Gelan Eshetu
Published: January 2025

Urban visual pollution, mainly driven by outdoor advertisements, is becoming increasingly prevalent in built environments. While urban visual pollution and outdoor advertising have been thoroughly examined in the Global North, less is known about these issues in the Global South. Therefore, this study examines the prevalence and impact of outdoor advertising in Addis Ababa, Ethiopia, focusing on both its forms and the perceptions of residents and commuters. The study employed key informant interviews, field observations, and surveys. The results show a significant increase in outdoor advertisements with 78% of respondents noting a recent rise and 62% feeling overwhelmed by their abundance. Additionally, the study reveals the negative effects of outdoor advertisements on urban aesthetics, as 82% of respondents believe these advertisements diminish the visual appeal of the city. The study underscores the perception of visual pollution, particularly in densely populated areas, where advertising clutter compromises the urban environment. Key contributing factors include a lack of regulation, poorly placed outdoor advertisements, inconsistent design, excessive size and brightness, and overcrowding. This study suggests the need for improved regulatory frameworks and community engagement in outdoor advertising to enhance the visual quality of urban spaces in developing countries like Ethiopia.
Early Intervention for Hearing-Impaired Children—From Policy to Practice: An Integrative Review
Authors: Petrocchi-Bartal Luisa , Khoza-Shangase Katijah , Kanji Amisha
Published: January 2025

Background/Objectives: Globally, many countries have endorsed the World Health Organisation’s (WHO) early intervention (EI) guidelines through their legislation with contextual variations. Sensitive evaluation of gaps within EI-recommended systems is essential, especially in the translation of policy into practice across high-income and low- to middle-income country (LMIC) contexts, including South Africa. The main objective was to explore and identify the current evidence reflecting the application of hearing-specific government policy regarding EI and early education (EE) for hearing-impaired/d/Deaf/hard-of-hearing (HI/D/HH) children aged six and below. Method: An integrative review was conducted on peer-reviewed articles that examined policy in practice regarding EI for HI/D/HH children aged six and below. Studies were accessed via four databases (Ebscohost, Sabinet, Scopus, and ScienceDirect) and one search engine (Google Scholar) between 2014 and 2024. Qualitative evaluation ensued of themes identified deductively. Results: Twenty-six peer-reviewed studies were included. Deductive thematic analysis revealed six derived themes: EI timing, early hearing detection and intervention (EHDI)/EI mechanisms; EI services, EE, family considerations, and policy. Five of the 26 directly scrutinised government policy in its EI/EE practical application. Articles reflected the need for consideration of the complex processes that allow for policy actualisation, such as adequate infrastructure and family considerations. Conclusions: A bottom-up approach to policy actualisation, with grass-roots contextual considerations such as EI access and caregiver concerns, may improve policy application. Current findings have implications, particularly for LMIC contexts including South Africa, where EI and EE policy scrutiny regarding hearing impairment/deafness specificity is imperative for understanding its application alignment.