bluuebunny/crossref_metadata_2025 huggingface dataset:
Current Management of Aneurysmal Subarachnoid Hemorrhage
Authors: Findlay Jay Max
Published: February 2025

The diagnosis of aneurysmal subarachnoid hemorrhage (aSAH) is most difficult in patients who are in good clinical condition with a small hemorrhage, especially when a ruptured aneurysm might not be considered, or if a computed tomographic (CT) scan is not obtained, or if when a CT is obtained, the findings are subtle and missed by an inexperienced reviewer. All acute onset (thunderclap) headaches should be considered ruptured aneurysms until proven otherwise. Treatment begins with immediate control of pain and blood pressure, placement of an external ventricular drain (EVD) in poor-grade patients and those with acute hydrocephalus on CT scanning, administration of antifibrinolytic tranexamic acid, and then repair of the aneurysm with either surgical clipping or endovascular techniques as soon as the appropriate treatment team can be assembled. After securing the aneurysm, aSAH patient treatment is focused on maintaining euvolemia and a favorable systemic metabolic state for brain repair. A significant and aneurysm-specific threat after aSAH is delayed arterial vasospasm and resulting cerebral ischemia, which is detected by vigilant bedside examinations for new-onset focal deficits or neurological decline, assisted with daily transcranial Doppler examinations and the judicious use of vascular imaging and cerebral perfusion studies with CT. The management of diagnosed symptomatic vasospasm is the prompt induction of hypertension with vasopressors, but if this fails to reverse deficits quickly after reaching a target systolic blood pressure of 200 mmHg, endovascular angioplasty is indicated, providing CT scanning rules out an established cerebral infarction. Balloon angioplasty should be considered early for all patients found to have severe angiographic vasospasm, with or without detectable signs of ischemic neurological deterioration due to either sedation or a pre-existing deficit.
Associations Between Dietary Patterns and the Occurrence of Hospitalization and Gastrointestinal Disorders—A Retrospective Study of COVID-19 Patients
Authors: Hawryłkowicz Viktoria , Stasiewicz Beata , Korus Sebastian , Krauze Wiktoria , Rachubińska Kamila , Grochans Elżbieta , Stachowska Ewa
Published: February 2025

During the COVID-19 pandemic, dietary habits in the population changed and sometimes deviated from healthy eating patterns, such as the Mediterranean diet. Based on reports on the quality of the diet of respondents to studies conducted at the beginning of the pandemic, it could be concluded that these new dietary habits are unfavorable for a good prognosis and the course of any disease and its severity of symptoms. This study decided to confront these assumptions with the results of people who had COVID-19. Background/Objectives: This study aimed to assess the associations between dietary patterns and the occurrence of hospitalization and gastrointestinal disorders among patients diagnosed with COVID-19. Methods: This study included 550 respondents who completed a survey up to 8 months after being diagnosed with COVID-19. The survey included 62 items from the FFQ-6®, GSRS, PAC-SYM and FACT-G7 standardized questionnaires. Results: Two dietary patterns (DPs) were identified: ‘Processed high fat/sugar/salt/meat/dairy/potatoes’ and ‘Semi-vegetarian’. Higher adherence to the ‘Processed’ DP was associated with higher odds of hospitalization due to COVID-19, a more severe course of the disease, and the highest intensity of gastrointestinal symptoms. Higher adherence to the ‘Semi-vegetarian’ DP was associated with lower odds of hospitalization due to COVID-19, a less severe course of the disease, and the lowest intensity of gastrointestinal symptoms. Conclusions: This study showed a strong harmful effect of high adherence to a processed dietary pattern on an increased incidence of hospitalization and gastrointestinal disorders among northwestern Polish adults during the COVID-19 pandemic, emphasizing the importance of a healthy diet.
Anti-Tumor Strategies of Photothermal Therapy Combined with Other Therapies Using Nanoplatforms
Authors: Xu Rubing , Wang Shengmei , Guo Qiuyan , Zhong Ruqian , Chen Xi , Xia Xinhua
Published: February 2025

Conventional cancer treatments often have complications and serious side effects, with limited improvements in 5-year survival and quality of life. Photothermal therapy (PTT) employs materials that convert light to heat when exposed to near-infrared light to raise the temperature of the tumor site to directly ablate tumor cells, induce immunogenic cell death, and improve the tumor microenvironment. This therapy has several benefits, including minimal invasiveness, high efficacy, reduced side effects, and robust targeting capabilities. Beyond just photothermal conversion materials, nanoplatforms significantly contribute to PTT by supplying effective photothermal conversion materials and bolstering tumor targeting to amplify anti-tumor effects. However, the anti-tumor effects of PTT alone are ultimately limited and often need to be combined with other therapies. This narrative review describes the recent progress of PTT combined with chemotherapy, radiotherapy, photodynamic therapy, immunotherapy, gene therapy, gas therapy, chemodynamic therapy, photoacoustic imaging, starvation therapy, and multimodal therapy. Studies have shown that combining PTT with other treatments can improve efficacy, reduce side effects, and overcome drug resistance. Despite the encouraging results, challenges such as optimizing treatment protocols, addressing tumor heterogeneity, and overcoming biological barriers remain. This paper highlights the potential for personalized, multimodal approaches to improve cancer treatment outcomes.
Evaluating Physiological and Hormonal Responses of Two Distinct Rice Genotypes Under High Temperatures
Authors: Qi Xiaoyu , Jin Weicai , Zhong Wenhao , Han Jiatong , Afzal Muhammad , Yue Qiang , Wang Guoping , Jan Mehmood
Published: February 2025

Climate change poses a major threat to rice productivity, particularly due to high-temperature stress during anthesis, which severely impacts the grain yield. Understanding the physiological and biochemical responses of different rice genotypes to high-temperature stress is critical for breeding resilient varieties. In this study, we assessed two contrasting rice genotypes, high-temperature-tolerant-1 (HTR-1) and high-temperature-sensitive (HTS-5), to confirm previously established physiological and hormonal mechanisms associated with high-temperature tolerance. The study evaluated morphological, physiological, and biochemical markers at the anthesis stage under control (29/24 °C) and high-temperature stress (38 °C for six hours) conditions. Our results confirmed that HTR-1 exhibits superior tolerance through better antioxidant enzyme activity, higher anther dehiscence, and lower oxidative damage. The genotype HTS-5 exhibited a substantial rise in hydrogen peroxide (1.9-fold) and malondialdehyde (1.74-fold) levels, accompanied by the reduced activity of antioxidant enzymes. Furthermore, the high transcript level of cytosolic APX (OsAPX1, OsAPX2), peroxisomal APX (OsAPX3 and OsAPX4), OsCATA, and OsCATB confirmed high antioxidant activity in HTR-1. Moreover, the GA and IAA levels were reduced in both genotypes, while the ABA concentration was increased significantly in the anthers of HTS-5 as compared to those of HTR-1. This suggests that higher ABA production, along with higher reactive oxygen species (ROS) in the anthers, could lead to sterility in rice under high-temperature scenarios. These findings confirmed HTR-1 as a promising genetic resource for breeding heat-tolerant rice, by validating physiological and biochemical mechanisms of high-temperature resilience. This study also provides practical insights for selecting suitable genotypes to improve rice production under the challenges of climate change.
Advances in the Preservation of Plant-Based Pigments via Spray Drying—A Systematic Review
Authors: Díaz-Montes Elsa
Published: February 2025

Natural pigments derived from plant sources are notable not only for their vibrant colors but also for their nutritional value and proven biological activities. Spray drying has emerged as an efficient and cost-effective encapsulation technique, offering significant advantages such as enhanced stability, improved handling properties, and protection against degradation. The diverse range of natural wall materials (e.g., polysaccharides, proteins, and lipids) and the variability in spray drying operating conditions provide numerous possibilities to optimize encapsulation processes. The aim of this systematic review was to evaluate and compare the key factors influencing spray drying encapsulation of plant-based pigments. ResearchGate, Scopus, and Google Scholar were searched between July and December 2024. Data extraction was performed manually using a standardized form to collect information on plant source, pigment type, wall materials (type and concentration), spray drying conditions (in-let/outlet temperatures and feed flow rate), and process results (encapsulation efficiency, process yield, and total pigment content). Future advances in spray drying should focus on the optimization of spray drying conditions. Furthermore, innovations in spray drying formulations, such as customized combinations of polysaccharides and proteins or the incorporation of emulsifiers, could lead to more effective and scalable encapsulation processes, supporting the development of high-performance stable pigments for food, cosmetic, and pharmaceutical applications.
Long-Term Follow-Up of a Patient with Ankylosis of a Primary Incisor Caused by Trauma: A Case Report
Authors: Akitomo Tatsuya , Hamaguchi Shuma , Mitsuhata Chieko , Nomura Ryota
Published: February 2025

Introduction and Clinical Significance: Tooth ankylosis is a serious complication that can occur because of the replantation of an avulsed tooth. However, few reports have investigated the follow-up of replanted or ankylosed primary incisors because the replantation of primary teeth is not recommended in the guidelines of the International Association of Dental Traumatology. Case Presentation: A boy aged 4 years and 8 months was referred to hospital for further evaluation of the maxillary right primary central incisor. It had been avulsed and replanted 2 years earlier. The tooth was positioned higher than the central incisor on the left side, and a metallic percussion sound was noted, leading to a diagnosis of tooth ankylosis. Long-term follow-up revealed the progression of ankylosis, and the tooth was finally extracted. At the age of 7 years and 6 months, permanent tooth eruption was detected, and no pathological finding was observed. Conclusions: In this case, root resorption of the replanted primary incisor was observed with age, but tooth ankylosis progressed, and natural exfoliation was difficult. The authors extracted the primary incisor appropriately, which aided the eruption of a successor permanent tooth. This report suggests the importance of patients visiting the dentist regularly after trauma to primary teeth and appropriate treatment by dentists to erupt the permanent teeth.
AS-YOLO: Enhanced YOLO Using Ghost Bottleneck and Global Attention Mechanism for Apple Stem Segmentation
Authors: Baek Na Rae , Lee Yeongwook , Noh Dong-hee , Lee Hea-Min , Cho Se Woon
Published: February 2025

Stem removal from harvested fruits remains one of the most labor-intensive tasks in fruit harvesting, directly affecting the fruit quality and marketability. Accurate and rapid fruit and stem segmentation techniques are essential for automating this process. This study proposes an enhanced You Only Look Once (YOLO) model, AppleStem (AS)-YOLO, which uses a ghost bottleneck and global attention mechanism to segment apple stems. The proposed model reduces the number of parameters and enhances the computational efficiency using the ghost bottleneck while improving feature extraction capabilities using the global attention mechanism. The model was evaluated using both a custom-built and an open dataset, which will be later released to ensure reproducibility. Experimental results demonstrated that the AS-YOLO model achieved high accuracy, with a mean average precision (mAP)@50 of 0.956 and mAP@50–95 of 0.782 across all classes, along with a real-time inference speed of 129.8 frames per second (FPS). Compared with state-of-the-art segmentation models, AS-YOLO exhibited superior performance. The proposed AS-YOLO model demonstrates the potential for real-time application in automated fruit-harvesting systems, contributing to the advancement of agricultural automation.
Subspace-Based Two-Step Iterative Shrinkage/Thresholding Algorithm for Microwave Tomography Breast Imaging
Authors: Wu Ji , Yang Fan , Zheng Jinchuan , Nguyen Hung T. , Chai Rifai
Published: February 2025

Microwave tomography serves as a promising non-invasive technique for breast imaging, yet accurate reconstruction in noisy environments remains challenging. We propose an adaptive subspace-based two-step iterative shrinkage/thresholding (S-TwIST) algorithm that enhances reconstruction accuracy through two key innovations: a singular value decomposition (SVD) approach for extracting deterministic contrast sources, and an adaptive strategy for optimal singular value selection. Unlike conventional DBIM methods that rely solely on secondary incident fields, S-TwIST incorporates deterministic induced currents to achieve more accurate total field approximation. The algorithm’s performance is validated using both synthetic “Austria” profiles and 45 digital breast phantoms derived from the UWCEM repository. The results demonstrate robust reconstruction capabilities across varying noise levels (0–20 dB SNR), achieving average relative errors of 0.4847% in breast tissue reconstruction without requiring prior noise level knowledge. The algorithm successfully recovers complex tissue structures and density distributions, showing potential for clinical breast imaging applications.
Experimental Study on Monitoring Equipment for the Scouring and Sedimentation of Wharf Bank Slopes Based on Heat Transfer Principles
Authors: Yin Jilong , Zhang Huaqing , Liu Mengmeng , Ma Qian
Published: February 2025

The scouring and sedimentation of wharf bank slopes significantly impact port safety and efficiency. To overcome the limitations of existing monitoring technologies in real-time capability, adaptability, and precision, this study introduces an innovative device based on distributed fiber optic sensing technology. By analyzing changes in the temperature gradient at the water–soil interface, the device enables dynamic monitoring of the results of scouring and sedimentation processes. It employs a modular design, integrating a linear heat source with fiber optic temperature sensing to capture high-resolution changes. Laboratory experiments evaluated variables such as heating duration, pipe material, pipe diameter, and fiber winding pitch. Results show optimal performance with a 20-min heating duration, with PVC sensors offering higher sensitivity and steel sensors providing greater stability. This study presents a high-precision, real-time solution for monitoring wharf bank slopes, offering insights for equipment optimization and engineering applications.
Displacement-Sensing Method Based on Residual Scaling for One-Shot MMF Specklegram Prediction
Authors: Shen Bohao , Li Jianzhi
Published: February 2025

A high-resolution and wide measurement range displacement sensing method based on multimode fiber (MMF) is proposed. To achieve a high-resolution displacement detection model, a one-shot dataset was constructed by collecting MMF specklegram images for 1801 displacements with resolution of 0.01 mm. This work modifies the fully connected layer of a residual network (ResNet) to achieve displacement prediction and applies residual scaling to reduce prediction errors in the one-shot learning task. Under stable environmental conditions, experimental results show that this method achieves an average error as low as 0.0083 mm in displacement prediction with resolution of 0.01 mm; meanwhile, the measurement range reaches 18 mm. Additionally, the model trained on a 0.01 mm resolution dataset was evaluated on a specklegram dataset with a resolution of 0.005 mm for its generalization ability, yielding an average error of 0.0138 mm. Regression evaluation metrics demonstrate that the proposed model has a significant improvement over other displacement-sensing methods based on MMF specklegrams, with prediction errors approximately three times lower than ResNet. Additionally, temperature immunity was studied within an 18 mm measurement range under a temperature range from 21.25 °C to 22.35 °C; the MMF displacement sensor demonstrates a dispersion of 5.08%, an average nonlinearity of 7.71% and a hysteresis of 6.13%. These findings demonstrate the potential of this method for high-performance displacement-sensing in practical applications.
Exposing Face Manipulation Based on Generative Adversarial Network–Transformer and Fake Frequency Noise Traces
Authors: Man Qiaoyue , Cho Young-Im
Published: February 2025

In recent years, with the application of GANs and diffusion generative network algorithms, many highly realistic synthetic images are emerging, greatly increasing the potential for misuse, and deepfakes have become a serious social concern. To cope with indistinguishable deep forgery face images, this paper proposes a novel detection network with a generative adversarial network (GAN) and transformer as the main architectures. It adds frequency domain analysis and noise detection prediction modules. In the proposed model in which GAN is used to capture local forgery, artifacts and transformers are used to model global dependencies and predict anomalies in the forged images using frequency domain and noise information; the framework enhances the detection of subtle and diverse deep forgery patterns. Experiments on benchmark datasets show that the proposed method achieves higher accuracy and robustness compared to existing methods.
Comparison of Cervical Spine Kinematics and Clinical Neck Symptoms Between Mobile Device and Desktop Computer Use
Authors: Park Myung Woo , Seong Min Yong , Song Young Seop , Youn Kibum , Yang Kyung Yong , Lee Jehee , Chung Sun Gun , Kim Keewon
Published: February 2025

The widespread use of mobile devices and desktop computers has been associated with mechanical neck symptoms, yet few studies have compared cervical kinematics and clinical symptoms between them. In this study, 15 participants (27.7 ± 4.4 years, 12 male) performed four randomly ordered 20 min tasks: two mobile (smartphone and tablet) and two desktop computer (keyboard and mouse) tasks. Kinematic variables, including neck flexion, lateral bending, axial rotation, anterior translation, and total distance moved, were measured using an optical motion capture system, while clinical symptoms, including discomfort, pain, tension, and fatigue, were assessed using a visual analog scale. Paired t-tests and linear mixed models were used for analysis. Results showed that mobile device users exhibited greater neck flexion (38.9° [32.1–45.6°] vs. −0.2° [−4.3–3.9°], p < 0.001) and anterior translation (21.0 cm [12.0–30.1] vs. 1.6 cm [−4.4–7.7], p < 0.001) compared to desktop users. All clinical symptoms were significantly higher during mobile device use (p < 0.05), with neck flexion and anterior translation strongly correlating with symptom severity. In conclusion, mobile device use leads to more severe neck symptoms compared to desktop computer use, which is associated with increased flexion and forward head posture. To reduce neck symptoms, avoiding sustained flexion and forward head positions during mobile device use is recommended.
Research on Emergency Rescue Scheme Based on Multi-Objective Material Dispatching of Heavy-Haul Railway
Authors: Zhang Xiaolei , Zhao Kaigong , Zhang Xingkai , Gao Shang , Meng Ting
Published: February 2025

It is particularly important to improve the emergency rescue response ability of heavy-haul railways to ensure the safety of personnel and the efficiency of material transportation. The current research has achieved some results for multi-objective material dispatching, but it does not consider the impact of accident response level and material type on material dispatching scheme. In this study, a heavy-haul railway in China was selected as the research object. By designing a dual-objective material scheduling model, an optimal material scheduling scheme was obtained, and the optimal solution was solved by a non-dominated sorting genetic algorithm (NSGA-II). Under the condition of keeping the station unchanged and ensuring that the total amount of materials remained unchanged, an optimization scheme of relief material reserves that match the risk characteristics of the line is proposed. The results show that, based on the utility theory, the minimum distance of the improved dual-objective material dispatching is reduced by 34.8% (single accident point) and 62.99% (multiple accident points), and the total distance of material dispatching is reduced by 37.92% and 70.57%, respectively, indicating that the optimized reserve scheme can effectively shorten the response time and improve the rescue efficiency. The material reserve optimization scheme for emergency rescue stations proposed in this study has important reference value for improving the emergency rescue efficiency of heavy-haul railways.
Development of Sustainable Artificial Lightweight Aggregates with Binary Mixtures of Waste Rich in Aluminosilicate and Carbonate in Kaolinitic Clay
Authors: da Silva Neto José Anselmo , dos Anjos Marcos Alyssandro Soares , Dutra Ricardo Peixoto Suassuna , Mendonça de Souza Maelson , Pederneiras Cinthia Maia
Published: February 2025

In Brazil, artificial lightweight aggregates (LWAs) are predominantly produced in the Southeast Region using clay as the primary raw material. However, clay extraction has significant environmental impacts and limits access to LWAs in the North and Northeast regions, resulting in high costs and hindering sustainable construction solutions. This study addresses these challenges by developing sustainable LWAs in the Northeast Region using raw materials from the metropolitan area of João Pessoa, Paraíba, namely chamotte (CHT), which is rich in aluminosilicates, and eucalyptus firewood ash (EFA), which is rich in carbonates, combined with kaolinitic clay (KC). Sixty-four binary mixtures were produced, demonstrating diverse properties in density, water absorption, and compressive strength. EFA-rich mixtures achieved the highest expansion (80%) and lowest density (1.20 g/cm3), while CHT-rich mixtures provided superior strength (>10 MPa) and deformation (>20 GPa). These properties highlight their suitability for diverse applications, from structural uses to landscaping, enhanced by distinct color variations. Statistical optimization identified the residue content and sintering temperature as key factors, confirming the technical viability of incorporating up to 80% industrial waste into sustainable LWA production. Therefore, the results confirm the technical feasibility of producing LWAs using CHT and EFA in the metropolitan region of João Pessoa/Paraíba, achieving properties comparable to commercial LWAs. By incorporating up to 80% industrial waste, this study reduces dependence on non-renewable resources, decreases CO2 emissions and transportation costs, and promotes sustainable practices. The findings offer a scalable, eco-friendly solution to resource-limited regions’ material scarcity.
Characterization of Sustainable Food Initiatives: Preliminary Study
Authors: Florença Sofia G. , Amaral Ana Luísa , Costa Filipa , Guiné Raquel P. F. , Costa Cristina A.
Published: February 2025

A sustainable food system can be described as a system that ensures economic, social, and environmental sustainability to secure food and nutrition for current and future generations. The present research aimed to identify and characterize sustainable food initiatives to understand the governance framework, the motivations, the reasons for success, the typology of actors involved, and future prospects. Semi-structured interviews were conducted for seven initiatives between June and August 2024. The interviews were performed online, recorded, transcribed, and analyzed. The results showed that the main drivers of the initiatives relate to food, sustainability, and economic and social dimensions. Moreover, one of the reasons for the success of the initiatives is the availability and commitment of the people involved. These initiatives were created to meet local needs and promote sustainability as well as to encourage economic circularity, knowledge sharing, rural and local valorization, and waste management.
Lightweight Leather Surface Defect Inspection Model Design for Fast Classification and Segmentation
Authors: Lee Chin-Feng , Chen Yu-Chuan , Shen Jau-Ji , Rehman Anis Ur
Published: February 2025

Automated inspection of leather surface defects is critical in evaluating product quality, yet manual inspection is still time-consuming and error-prone. Conventional automated methods, on the other hand, exhibit high computational complexities, are rigid in dealing with varied defects, and often require extensive manual parameter tuning. To counter these challenges, we propose a lightweight model integrated with symmetry for efficient defect classification and segmentation. The model consists of a streamlined semantic segmentation network that uses depthwise separable convolution and symmetric padding to preserve edge features while eliminating deconvolution layers, thus considerably reducing computational overhead. Moreover, a discrimination network automates defect detection without requiring manual thresholds, and a segmentation suggestion stage refines defect masks for practical cutting recommendations. Experimental results demonstrate a 96.75% detection accuracy and 89.41% mean pixel accuracy, achieving performance comparable to state-of-the-art models (e.g., KMDNet, U-Net) while reducing training time by 40% and model size by 60%. The symmetry-driven architecture enhances computational efficiency (0.05 s/img) and robustness across multiple defect types. Furthermore, the modular design enables independent updates for new defect types without requiring full retraining, addressing a major limitation of prior methods. These findings highlight the potential of symmetry-based architectures in industrial quality control, offering a scalable and efficient solution for automated defect detection.
A Hybrid AI Framework for Enhanced Stock Movement Prediction: Integrating ARIMA, RNN, and LightGBM Models
Authors: Alarbi Adel , Khalifa Wagdi , Alzubi Ahmad
Published: February 2025

Forecasting stock market movements is a critical yet challenging endeavor due to the inherent nonlinearity, chaotic behavior, and dynamic nature of financial markets. This study proposes the Autoregressive Integrated Moving Average Ensemble Recurrent Light Gradient Boosting Machine (AR-ERLM), an innovative model designed to enhance the precision and reliability of stock movement predictions. The AR-ERLM integrates ARIMA for identifying linear dependencies, RNN for capturing temporal dynamics, and LightGBM for managing large-scale datasets and non-linear relationships. Using datasets from Netflix, Amazon, and Meta platforms, the model incorporates technical indicators and Google Trends data to construct a comprehensive feature space. Experimental results reveal that the AR-ERLM outperforms benchmark models such as GA-XGBoost, Conv-LSTM, and ANN. For the Netflix dataset, the AR-ERLM achieved an RMSE of 2.35, MSE of 5.54, and MAE of 1.58, surpassing other models in minimizing prediction errors. Moreover, the model demonstrates robust adaptability to real-time data and consistently superior performance across multiple metrics. The findings emphasize AR-ERLM’s potential to enhance predictive accuracy, mitigating overfitting and reducing computational overhead. These implications are crucial for financial institutions and investors seeking reliable tools for risk assessment and decision-making. The study sets the foundation for integrating advanced AI models into financial forecasting, encouraging future exploration of hybrid optimization techniques to further refine predictive capabilities.
Inhibition Effects of Infrared Radiation Prior to Cold Storage Against Alternaria alternata on Yellow Peach (Amygdalus persica)
Authors: Liu Longxiao , Fan Kai , Huang Qingwen , Wang Xinyi , Nie Dongxia , Han Zheng , Li Zhizhong , Zhao Zhihui
Published: February 2025

During postharvest storage, the yellow peach (Amygdalus persica) is susceptible to infection by Alternaria alternata, which causes fruit decay and produces multiple Alternaria toxins (ATs), leading to economic losses and potential health risks. The present study investigated the inhibitory effects of infrared radiation treatment against A. alternata on yellow peaches. Our in vitro experimental results indicated that infrared radiation at 50 °C for 30 min could completely inhibit fungal growth and AT production. Furthermore, infrared treatments prior to cold storage effectively delayed the onset of decay and significantly reduced the lesion diameter, decay rate, and AT levels in the yellow peaches inoculated with A. alternata. After the peaches underwent infrared radiation at 50 °C for 30 min and then cold storage for 60 days, the levels of tenuazonic acid, alternariol, alternariol methyl ether, and altenuene in the yellow peaches decreased by 95.1%, 98.6%, 76.1%, and 100.0%, respectively. Additionally, infrared radiation caused slight changes in their firmness, total soluble solids, and concentrations of sugar and organic acids, indicating minor negative impacts on the quality of the yellow peaches. Therefore, the present work provides a novel strategy for controlling A. alternata and AT contamination, thereby extending the shelf-life of yellow peaches, and improving food safety administration.
AFAR-WQS: A Quick and Simple Toolbox for Water Quality Simulation
Authors: Rogéliz-Prada Carlos A. , Nogales Jonathan
Published: February 2025

Water quality management in large basins demands tools that balance scientific rigor with computational efficiency to avoid paralysis by analysis. While traditional models offer detailed insights, their complexity and resource intensity hinder timely decision-making. To address this gap, we present AFAR-WQS, an open-source MATLAB™ toolbox that introduces a novel integration of assimilation factors with graph theory and a Depth-First Search (DFS) algorithm to rapidly simulate 13 water quality determinants across complex topological networks. AFAR-WQS resolves cumulative processes in networks of up to 30,000 segments in just 163 s on standard hardware, enabling real-time scenario evaluations. Its object-oriented architecture ensures scalability, allowing customization for urban drainage systems or macro-basin studies while maintaining computational efficiency. Case studies demonstrate its utility in prioritizing sanitation investments, assessing water quality at the national scale and fostering stakeholder collaboration through participatory workshops. By bridging the gap between simplified and complex models, AFAR-WQS supports adaptive management in contexts of hydrological uncertainty, regulatory compliance, and climate change. The toolbox is freely available at GitHub, offering a transformative approach for integrated water resource management.
Changes in Sea Level, Storm and Wave Conditions, and Ice Cover—Over 70 Years of Observation in the Southern Baltic Sea
Authors: Zalewska Tamara , Kowalska Beata , Krzysztofik Katarzyna , Sapiega Patryk
Published: February 2025

This study demonstrates changes in the hydrodynamic regime associated with climate change in the southern Baltic over more than 70 years. The analysis of long-term data about sea level, the occurrence of ice cover, waves, and storm surges in the southern Baltic enabled the identification of spatiotemporal variability, including the detection of changes in intensity, frequency, and repeatability of these phenomena. The sea level in the southern Baltic rose by approximately 1 cm/decade from 1886 to 1955. Then, from 1956 to 2019, intensification was observed, and the sea level rose by 1.6 cm/decade and 1.9 cm in the western and eastern parts, respectively. The most intense decadal sea level change in 1955–2019 occurred in March (3.1 cm) and January (2.5 cm), while from July to December, it was at 0.8–1.3 cm. Statistical direct correlation analyses using Spearman’s rank method showed a weak but statistically significant relationship between the mean daily sea level with water temperature and air temperature measured at the same stations. An increase in the frequency of storms in individual decades and a decrease in the number of days with ice was demonstrated. There was no clear trend in the wave conditions regime during the period covered by the analysis in 1980–2021.
Optimizing Nitrogen Removal Through Coupled Simultaneous Nitrification-Denitrification and Sulfur Autotrophic Denitrification: Microbial Community Dynamics and Functional Pathways in Mariculture Tailwater Treatment
Authors: Jiang Shuaifeng , Huang Haoran , Chen Yongli , Xiong Jianhua , Lin Ziyuan , Wang Shuangfei
Published: February 2025

This study investigates the nitrogen removal pathways and microbial community dynamics in a novel system coupling simultaneous nitrification and denitrification (SND) with sulfur autotrophic denitrification (SAD) for the treatment of mariculture tailwater. High-throughput sequencing and predictive functional analysis were employed to examine microbial compositions and their functional roles across varying carbon-to-nitrogen (C/N) ratios. The results revealed that SND occurred in the aerobic stage, with Nitrosomonas and Nitrospira facilitating nitrification, while Denitromonas and Paracoccus drove denitrification. In the anaerobic stage, SAD was the primary nitrogen removal process, with sulfur metabolism supported by Thiobacillus and Desulfobacteria. Increasing C/N ratios enriched denitrifying bacteria, enhancing nitrogen removal performance, but reduced nitrifying activity. Functional gene analysis demonstrated the upregulation of denitrification genes (napAB, nirS, norBC, nosZ) with higher carbon inputs, while sulfur metabolism genes (sqr, soxB, dsrAB) confirmed the critical role of sulfur cycling in SAD. The integration of SND and SAD pathways, supported by carbon addition, achieved efficient nitrogen removal, while promoting sulfur bioavailability. Under C/N ratios of 1.2, the nitrate nitrogen (NO3−-N) removal efficiencies reached 93.48%, respectively, while the total nitrogen (TN) removal efficiencies were 95.06%. Ammonia nitrogen (NH4+-N) removal efficiency consistently exceeded 95%, stabilizing at 99.00% in the steady-state operation. This research provides a comprehensive understanding of the microbial and functional mechanisms underlying SND–SAD systems, offering an innovative solution for sustainable mariculture tailwater management.
Comparison of Satellite-Derived Vegetation Indices for Assessing Vegetation Dynamics in Central Asia
Authors: Li Qian , Cheng Junhui , Yan Junjie , Zhang Guangpeng , Ling Hongbo
Published: February 2025

Each of the NDVI, EVI, NIRv, and kNDVI has varying strengths and weaknesses in terms of representing vegetation dynamics. Identifying the comparative advantages of these indices is crucial to objectively determine the dynamics of vegetation in dryland. In this study, Central Asia was selected as the research area, which is a typical drought-sensitive and ecologically fragile region. The Mann–Kendall trend test, coefficient of variation, and partial correlation analyses were used to compare the ability of these indices to express the spatiotemporal dynamics of vegetation, its heterogeneity, and its relationships with temperature and precipitation. Moreover, the composite vegetation index (CVI) was constructed by using the entropy weighting method and its relative advantage was identified. The results showed that the kNDVI exhibited a stronger capacity to express the relationship between the vegetation and the temperature and precipitation, compared with the other three indices. The NIRv best represented the spatiotemporal heterogeneity of vegetation in areas with a high vegetation coverage, while the kNDVI had the strongest expressive capability in areas with a low vegetation coverage. The critical value for distinguishing between areas with a high and low vegetation coverage was NDVI = 0.54 for temporal heterogeneity and NDVI = 0.50 for spatial heterogeneity. The CVI had no apparent comparative advantage over the other four indices in expressing the trends of changes in vegetation coverage and their correlations with the temperature and precipitation. However, it enjoyed a prominent advantage over these indices in terms of expressing the spatiotemporal heterogeneity of vegetation coverage in Central Asia.
A Study on the Design of a Fault-Tolerant Consequent-Pole Hybrid Excited Machine for Electric Vehicles
Authors: Qu Guangyu , Yu Jinyi , Li Zhenghan , Liu Wei
Published: February 2025

In this paper, a new fault-tolerant consequent-pole hybrid excited (FTCPHE) machine with toroidal winding (TW) is designed for electric vehicles (EVs). In this proposed machine, U-type permanent magnets (PMs) are adopted in the consequent-pole rotor with the sequence of PM–iron–PM–iron. The stator tooth placed in the stator is classified into two groups to achieve hybrid excitation. The TW is positioned on the stator yoke to achieve the simple structure and excellent fault-tolerant ability. First, the topology of this proposed FTCPHE machine with the TW is briefly introduced and compared to that with the traditional combined winding. Second, the operation principle, the magnetic circuit, and the design procedure of the FTCPHE machine are analyzed and illustrated. Third, several key structural parameters of the proposed FTCPHE machine are discussed and designed to improve electromagnetic performances. Next, some electromagnetic properties, including the flux distribution, the no-load back-EMF, the electromagnetic torque, the cogging torque, and the fault-tolerant ability, are discussed in detail. Finally, a prototype of this proposed FTCPHE machine is manufactured to validate the simulated results.
Kražių kolegijoje mirusių jėzuitų nekrologų korpusas: statistika, tekstų genezė ir koreliacija, redagavimas, autorystė ir vertė
Authors: Antanavičius Darius , Nedzinskaitė Živilė
Published: February 2025

In 2024, publication of the Fontes collegii Crosensis, qui in Archivo Romano Societatis Iesu asservantur was finally completed. Its final part contains, along with the so-called first and second catalogues (catalogus primus, secundus), all the extant necrologies of persons deceased in Kražiai College (collegium Crosense) and the Tilžė and Varniai missions (missio Tilsensis, Vornensis). The latter texts are the scope of the present article.
GRID MAP OF POLTAVA REGION AS A BASIS FOR BIODIVERSITY MONITORING IN THE REGION
Authors: Budzhak V. , Raida O. , Homlia L. , Dyachenko-Bohun M. , Shkura T.
Published: February 2025

The biodiversity preservation is a crucial task of modern ecology, as it reflects the state of ecosystems and natural processes. Effective monitoring of biodiversity requires the application of innovative approaches, particularly grid mapping. This method allows the systematization and analysis of spatial information on species diversity, facilitating more precise planning of conservation measures.Poltava Region, located in the forest-steppe zone of Ukraine, is characterized by diverse natural landscapes significantly impacted by anthropogenic activities. Despite the relatively comprehensive study of biodiversity in the region, challenges persist due to the limitations of mapping methods and the absence of a unified system for chorological data analysis.To create a grid map of Poltava Region, MapInfo and QGIS software was employed, applying electronic multi-layered maps at a scale of 1:200,000. Within the UTM grid system of the “Atlas Florae Europaeae” (1972), the region was divided into 50×50 km squares, which were further subdivided into smaller 5×5 km units for greater accuracy. Each square was assigned a unique identifier (ID), enabling the storage and analysis of attribute data on species.The resulting grid map identifies biodiversity “hotspots” – areas with the highest concentration of rare and endangered species. This methodology aids in evaluating the effectiveness of natural area conservation, analyzing the dynamics of species distribution and abundance, and planning measures for their study and preservation. Identifying such areas ensures the rational allocation of conservation resources and improves ecological monitoring efficiency.The application of grid mapping in Poltava Region is a significant step toward developing a systematic database on the flora and fauna of the region, contributing to ecosystem conservation and future research planning. The proposed methodology can be adapted for other regions to enhance natural resource monitoring across Ukraine.
HEALTH CONDITION OF TREES UNDER VARIOUS ANTHROPOGENIC INFLUENCES IN PLANTATIONS OF POLTAVA
Authors: Orlovskyi O. , Derevyanko T.
Published: February 2025

The article presents the results of the analysis of the distribution and health condition of trees of six tree species (Acer platanoides, A. negundo, Aesculus hippocastanum, Tilia cordata, Betula pendula, and Robinia pseudoacacia) in the plantations of Poltava. These trees are affected by restriction of root growth, pruning, vehicle emissions, and a combination of these effects. The prevalence of trees of each species in the absence of anthropogenic impact and with anthropogenic impact was determined as the proportion of trees in percentage of all recorded trees of this species that are exposed to a certain impact. The health index was calculated for groups of trees of each species exposed to the effects of one or more anthropogenic factors. It was found that the most widespread trees are: with restricted root growth – B. pendula, with signs of pruning – R. pseudoacacia; with simultaneous impact on roots and crowns – Aes. hippocastanum and T. cordata; under the influence of vehicle emissions – B. pendula and Aes. hippocastanum; under the simultaneous influence of all these factors – T. cordata and Aes. hippocastanum. About half of the A. platanoides and A. negundo trees showed no signs of influence from anthropogenic factors, slightly more than a third of the R. pseudoacacia and B. pendula, and less than 20% of the T. cordata and Aes. hippocastanum specimens. Most of the trees are weakened (index above 1.5). Aes. hippocastanum trees are significantly weakened by long-term defoliation caused by Cameraria ohridella. With increasing anthropogenic impact, the health index of all species tends to increase. At the same time, it is necessary to consider the age of trees and the effect of biotic factors specific to individual species.
Religião e espiritualidade: seus impactos em pacientes em cuidados paliativos: uma revisão integrativa
Authors: Lemos Carolina Teles , Souza Ramos Rodrigo
Published: February 2025

As doenças crônicas passam por um processo de aumento em escala mundial, o que torna necessário a implementação de um modelo de assistência que contemple todo o processo de adoecimento, a morte e o morrer. Nessa ótica, os cuidados paliativos fazem parte de uma modalidade emergente da assistência integral e multidisciplinar, contemplando, inclusive, a espiritualidade do paciente com doença avançada e terminal. Nosso objetivo é apresentar uma revisão bibliográfica feita para identificar o impacto da religião e da espiritualidade no seguimento de pacientes em cuidados paliativos. Como metodologia, realizamos uma Revisão Bibliográfica Integrativa de artigos científicos publicados nas principais bases de dados atuais – PubMed, Scielo e Biblioteca Virtual em Saúde (BVS). Os critérios de inclusão foram trabalhos publicados nos últimos dez anos (entre 2013 e 2023).   O universo do estudo foi constituído por 376 artigos relacionados ao tema abordado, dos quais 15 compuseram à amostra por se adequarem aos critérios de inclusão. Como resultados, percebemos que os estudos analisados apontaram para a compreensão que no caso de pacientes em cuidados paliativos, essas ferramentas se configuram como um caminho para que esses indivíduos possam lidar com a terminalidade, sem angústia, reduzindo o sofrimento e a dor provocados pelas doenças incuráveis.
O pórtico Northumberland: interconexões neoclássicas entre Rio de Janeiro e Roma a partir do traço de Robert Adam
Authors: Rodrigues Angela Rosch
Published: February 2025

O objetivo desta contribuição é verificar algumas influências para Robert Adam conceber o pórtico dito Lion Gate em Syon, House nos arredores de Londres, dentre as quais a de G. B. Piranesi. Esse mesmo desenho foi utilizado para a confecção do pórtico Northumberland, instalado no início do século XIX na entrada do Paço Imperial de São Cristovão (RJ). Considerando as conexões entre Roma e o Reino Unido, é possível constatar a difusão do neoclássico de matriz inglesa no Brasil a partir da chegada da família Real Portuguesa. Evidencia-se o valor de uma linguagem arquitetônica proposta por Robert Adam como um campo de experimentação deflagrado a partir do antigo.
Fuzzy Speech Recognition Algorithm Based on Continuous Density Hidden Markov Model and Self Organizing Feature Map
Authors: Zhang Yanning , Ma Lei , Li Yunwei
Published: February 2025

Speech recognition refers to the process of receiving and understanding human speech input through a computer, converting it into readable text or instructions. In order to improve the denoising effect and speech recognition effect of fuzzy speech, a fuzzy speech recognition algorithm based on continuous density hidden markov model and self-organizing feature map is proposed. Firstly, the conventional Wiener filtering algorithm is improved by using the dynamic estimation algorithm of noise power spectrum, and the endpoint detection of noisy speech signal is performed by using spectral entropy, and the noise power spectrum of the silent segment is dynamically updated according to the detection results to obtain a more ideal priori signal to noise ratio; Secondly, the fuzzy speech is input into the Wiener filter to eliminate the noise in the speech signal; Then, Mel-frequency cepstrum coefficient of speech signal is extracted as speech feature; Finally, combined with the continuous hidden Markov model and the self-organizing feature neural network in the artificial intelligence algorithm, through the process of adjusting parameters, Viterbi decoding, and the time adjustment of the voice signal in the same state, the speech classification and recognition are realized according to the speech characteristics. In the experiment, comparative experiments were conducted on the LibriSpeech dataset using speech recognition algorithms based on convolutional neural networks and recurrent neural networks, speech recognition algorithms based on residual networks and gated convolutional networks, speech recognition algorithms based on multi-scale mel domain feature map extraction. The experimental results show that the algorithm has good denoising performance. With the increase of added environmental noise intensity, the algorithm can maintain the Signal-to-Noise Ratio (SNR) of speech signals between 88dB-98dB; This algorithm can accurately detect the sound areas in the signal, and the endpoint detection accuracy is high; The accuracy and recall of the Continuous Density Hidden Markov Model-Self-Organizing Feature Neural Network (CDHMM-SOFM) designed in the algorithm increase with the number of iterations, and the highest levels of accuracy and recall can reach 0.89, respectively; The minimum recognition time of this algorithm is only 8.2 seconds, and the highest recognition rate can reach 98.7%; after applying this algorithm, the user’s error rate ranges from 0.0031 to 0.0084. The above results indicate that the algorithm has good application performance