bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Fault Detection Technology for Circuit Breaker Operating Mechanism Combinations Based on Deep Residual Networks
Authors: Shao Hongping , Jiang Yizhe , Zhao Jianeng , Li Xueteng , Zhang Mingzhan , Yang Mingkun , Wang Xinyu , Yang Hao
Published: February 2025

Due to the complex mechanical structure of the spring-operated mechanism, its failure mechanisms often exhibit a multi-faceted nature, involving various potential failure sources. Therefore, conducting a failure mechanism analysis for multi-source faults in such systems is essential. This study focuses on the design of composite faults in combination operating mechanisms and develops simulation scenarios with varying levels of fault severity. Given the challenges of traditional simulation methods in performing quantitative analysis of core jamming faults and the susceptibility of the core’s motion trajectory to external interference, this paper innovatively installs a spring-damping device at the extended core position. This ensures that, during the simulation of core jamming faults, the motion trajectory remains stable and unaffected by external factors, while also enabling precise control over the degree of jamming. As a result, the simulation more accurately reflects real fault conditions, thereby enhancing the accuracy and practicality of diagnostic model outcomes. This study employs the Morlet wavelet transform to convert the current and displacement signals in the time series into time-frequency spectrograms. These spectrograms are then processed using the ResNet50 deep residual neural network for feature extraction and fault classification. The results demonstrate that, when addressing the diagnostic problem of small-sample data for operating mechanism faults, ResNet50, with its residual structure design, exhibits significant advantages. The convolutional layer strategy, which first performs dimensionality reduction followed by dimensionality expansion, combined with the use of the ReLU activation function, contributes to superior performance. This approach achieves a fault recognition accuracy of up to 91.67%.
Northward Expanding Variation of Neo-Chinese-Style Landscape Influenced by Bamboos in China Under Climate Change Based on MaxEnt Model
Authors: Zhao Ying , Liu Junxiang , Zhang Zhi , Zhao Yongbin , Cui Di , Zhou Yan , Fan Lei
Published: February 2025

Bamboos, as imperative vegetations in Chinese traditional gardens, also significantly influenced the recently originated Neo-Chinese-style landscape in China, and their habitat ranges have been profoundly impacted by global climate warming. Current studies on the distribution dynamics of bamboo reveal existent gaps in assessing the suitable distribution area of Neo-Chinese-style landscapes. In this study, we calculated the habitat ranges of two widely distributed bamboo genera (Phyllostachys and Bambusa) based on the optimal MaxEnt model, predicted their future (2050s, 2070s and 2090s) distributions under different climate scenarios (SSP1-2.6 and SSP5-8.5), and assessed the suitable distribution area of the Neo-Chinese-style landscape according to the distribution union of two bamboo genera. The results showed that the optimal MaxEnt model exhibited high evaluation indices (AUC > 0.90) for the two bamboo genera. The habitat ranges of bamboo genera were significantly influenced by the minimum temperature of the coldest month and would expand northwardly in the future. The suitable distribution area of Neo-Chinese-style landscapes covered about 71.3% cities of China, which would expand 5.9%–8.7% of cities and 10%–18.7% of cities under the SSP1-2.6 climate scenario and the SSP5-8.5 climate scenario, respectively. The suitable distributions are mainly located in the southeast part of China. This study advanced our understanding of the restriction of bamboo to the distribution of the Neo-Chinese-style landscape and provided valuable insights and a scientific basis for landscape construction in different areas of China.
Analysis of the Evolution of Shock Waves When a Muzzle Jet Impacts a Constrained Moving Body
Authors: Li Zijie , Wang Hao
Published: February 2025

The evolution form of the flow field generated via the impact of a muzzle jet on a constrained moving body changes from the state of fully free-spatial development to that of constrained development, and it involves the problem of interference, owing to the spatiotemporal coupling of various kinds of shock waves and vortices. Against this backdrop, the authors use the dynamic mesh method to establish two models for simulating the flow field and exploring the mechanism of development and the characteristics of propagation of disturbances induced via the shock waves as the muzzle jet impacts a constrained moving body. The results show that the muzzle jet exhibited a circumferentially asymmetric shape under the influence of the constrained track. The shock wave leaned towards the upper part of the muzzle, and its speed of propagation above the muzzle was higher than that below the muzzle. Meanwhile, the vortex that should have been present below the muzzle disappeared, and it was replaced with a separation line. Changes in the pressure of the flow field and important parameters of the moving body also became more complex due to the influence of the constrained track.
Hysteresis-Induced Onset and Progressive Decay of Periodic and Metastable Sheet Cavitation in a Chamfered Circular Orifice
Authors: Son Min , Börner Michael , Armbruster Wolfgang , Hardi Justin S.
Published: February 2025

This study investigates the onset and decay mechanisms of sheet cavitation within a chamfered orifice under turbulent conditions, using high-speed backlight imaging for detailed frame-by-frame analysis. A distinctive metastable sheet cavitation regime was identified, distinguished by its unique hysteresis behavior during onset conditions, with the ability to control periodicity through variations in cavitation numbers. This new sheet cavitation regime appears at high cavitation numbers, contrary to typical expectations of cavitation inception, highlighting a new potential risk within the range of safe operation for hydraulic systems equipped with control valves. Furthermore, linear growth and rapid collapse of the bubble sheet were observed, which differs from the conventional periodic behavior of sheet cavitation on hydrofoils. The new mechanism to intentionally initiate and control this sheet cavitation regime by manipulating the pressure drop across the orifice could potentially be adopted for industrial applications, particularly in the generation of controlled and dispersed bubbles. Future research should include quantifying bubble dynamics within this regime and assessing the effects of fluid properties and orifice geometries on cavitation characteristics. In summary, this study introduces a new perspective on metastable sheet cavitation, emphasizing its potential applications and importance in the design and operation of fluid systems.
Effects of Dietary Pretreatment with All-trans Lycopene on Lipopolysaccharide-Induced Jejunal Inflammation: A Multi-Pathway Phenomenon
Authors: Mou Daolin , Ding Dajiang , Pu Junning , Zhou Pan , Cao Enming , Zhang Xueyan , Lan Junrong , Ye Lu , Wen Wanxue
Published: February 2025

This study was conducted to investigate the effects and mechanisms of all-trans lycopene on intestinal health by establishing lipopolysaccharide-induced (LPS-induced) jejunal inflammation model. Dietary lycopene supplementation enhanced serum and jejunum antioxidant capacity. Lycopene significantly reduced LPS-induced upregulation of toll-like receptor-4 (TLR-4) and nuclear factor kappa-B (NF-κB), suggesting that lycopene reduced the activation of TLR-4/NF-κB signaling pathway induced by LPS challenge, and further protected mice from LPS induced jejunal inflammation. Furthermore, lycopene increased jejunal zonula occludens-1 (ZO-1) protein expression that was reduced by LPS challenge, and increased abundance of Rikenella, Lachnospiraceae_NK4A136_group and Mucispirillum potentially associated with reducing gut inflammation. Overall, these results showed that pretreatment with lycopene can improve jejunal inflammation and ensure intestinal health in mice by improving antioxidant capacity, intestinal barrier function, microorganisms potentially associated with anti-inflammatory effects and reducing the activation of TLR-4/NF-κB signaling pathway by LPS. We provided a new insight into lycopene prevented LPS-induced jejunal inflammation by corresponding alterations in serum metabolites and gut microbiota, improving antioxidant capacity and regulating the TLR-4/NF-κB signaling pathway in mice.
Development of a Magnetic Solid-Phase Extraction-Liquid Chromatography Targeted to Five Fluoroquinolones in Food Based on Aptamer Recognition
Authors: Zhou Haiyan , Yan Xiaofeng , Song Yaning , Yang Xiao , Chen Xianggui , Huang Yukun
Published: February 2025

Fluoroquinolones (FQs) are present in trace amounts in the environment, from where they enter animal- and plant-derived food products. Long-term exposure to low-dose drugs poses a risk to human health and increases the pressure on antibiotic selection. Based on previous aptamer screening with high FQs specificity, this study combined a new aptamer recognition probe with a metal–organic framework (MOF) to obtain a sample pretreatment composite material with strong FQs specificity for multi-target analysis. Residual FQs were extracted from the complex food matrix via magnetic dispersive solid-phase extraction and examined using high-performance liquid chromatography. The method showed good linearity in a range of 0.39 to 200 µg/kg for five FQs in milk and fish samples, with a detection limit of 0.04–0.10 µg/kg and a quantitative limit of 0.13–0.33 µg/kg. This study successfully developed an effective sample pretreatment material and methodology for trace FQs identification in complex animal-derived food matrices.
Improvement of Esterifying Power of Isolated Bacillus velezensis from Daqu by Atmospheric Pressure and Room Temperature Plasma Mutagenesis
Authors: Song Chuan , Guan Tongwei , Xiong Zhuang , Chen Xiaodie , Tu Wenying , Xu Yanping , Yan Xiyue , Li Qiang
Published: February 2025

Strong-flavor Baijiu, a widely popular distilled spirit in China, derives its characteristic aroma and quality largely from ethyl hexanoate, a key flavor compound. The concentration of ethyl hexanoate, influenced by its precursor hexanoic acid, is critical in defining the style and quality of this Baijiu variety. In this study, atmospheric and room temperature plasma (ARTP) mutagenesis technology was applied to strains isolated from Strong-flavor Daqu to enhance their acid and ester production capabilities. A hexanoic acid-producing strain, identified as Bacillus velezensis WY4 through morphological, physiological, biochemical, and molecular analyses, was used as the starting strain. Following 90 s of ARTP exposure, a mutant strain, WY4-3, was successfully developed, achieving a balance between high mutation diversity and moderate lethality. WY4-3 exhibited robust growth across a pH range of 4.2 to 5.0 and demonstrated high ethanol tolerance. After five days of fermentation, WY4-3 produced 0.36 g/L of total acid and 0.528 g/L of total ester, surpassing the wild-type strain. Enzymatic activity assays revealed significant enhancements in amylase (9.13%), saccharifying enzyme (101.72%), and esterification (573.71%) activities in WY4-3. Validation in multiple artificial esterification systems further confirmed the superior ester production capacity of this mutant strain. These findings enrich the microbial germplasm resources for Baijiu brewing and provide a solid foundation for strain selection and genetic improvement in Baijiu production processes. This study highlights the potential of ARTP mutagenesis in optimizing brewing microorganisms and improving the quality and consistency of Strong-flavor Baijiu.
A New Approach Based on Metaheuristic Optimization Using Chaotic Functional Connectivity Matrices and Fractal Dimension Analysis for AI-Driven Detection of Orthodontic Growth and Development Stage
Authors: Cicek Orhan , Özçelik Yusuf Bahri , Altan Aytaç
Published: February 2025

Accurate identification of growth and development stages is critical for orthodontic diagnosis, treatment planning, and post-treatment retention. While hand–wrist radiographs are the traditional gold standard, the associated radiation exposure necessitates alternative imaging methods. Lateral cephalometric radiographs, particularly the maturation stages of the second, third, and fourth cervical vertebrae (C2, C3, and C4), have emerged as a promising alternative. However, the nonlinear dynamics of these images pose significant challenges for reliable detection. This study presents a novel approach that integrates chaotic functional connectivity (FC) matrices and fractal dimension analysis to address these challenges. The fractal dimensions of C2, C3, and C4 vertebrae were calculated from 945 lateral cephalometric radiographs using three methods: fast Fourier transform (FFT), box counting, and a pre-processed FFT variant. These results were used to construct chaotic FC matrices based on correlations between the calculated fractal dimensions. To effectively model the nonlinear dynamics, chaotic maps were generated, representing a significant advance over traditional methods. Feature selection was performed using a wrapper-based approach combining k-nearest neighbors (kNN) and the Puma optimization algorithm, which efficiently handles the chaotic and computationally complex nature of cervical vertebrae images. This selection minimized the number of features while maintaining high classification performance. The resulting AI-driven model was validated with 10-fold cross-validation and demonstrated high accuracy in identifying growth stages. Our results highlight the effectiveness of integrating chaotic FC matrices and AI in orthodontic practice. The proposed model, with its low computational complexity, successfully handles the nonlinear dynamics in C2, C3, and C4 vertebral images, enabling accurate detection of growth and developmental stages. This work represents a significant step in the detection of growth and development stages and provides a practical and effective solution for future orthodontic diagnosis.
Hybrid Systems of Gels and Nanoparticles for Cancer Therapy: Advances in Multifunctional Therapeutic Platforms
Authors: Kim Kibeom
Published: February 2025

Cancer is a global health concern. Various therapeutic approaches, including chemotherapy, photodynamic therapy, and immunotherapy, have been developed for cancer treatment. Silica nanoparticles, quantum dots, and metal–organic framework (MOF)-based nanomedicines have gained interest in cancer therapy because of their selective accumulation in tumors via the enhanced permeability and retention (EPR) effect. However, bare nanoparticles face challenges including poor biocompatibility, low stability, limited drug-loading capacity, and rapid clearance by the reticuloendothelial system (RES). Gels with unique three-dimensional network structures formed through various interactions such as covalent and hydrogen bonds are emerging as promising materials for addressing these challenges. Gel hybridization enhances biocompatibility, facilitates controlled drug release, and confers cancer-targeting abilities to nanoparticles. This review discusses gel–nanoparticle hybrid systems for cancer treatment developed in the past five years and analyzes the roles of gels in these systems.
A Comparative Study of Dormex® and Biostimulant Effects on Dormancy Release, Productivity, and Quality in ‘Royal Tioga®’ Sweet Cherry Trees (Prunus avium L.)
Authors: İmrak Burhanettin , Kafkas Nesibe Ebru , Çömlekçioğlu Songül , Bilgin Ömer Faruk , Gölcü Ayşegül Esra , Burgut Ayşegül , Attar Şule Hilal , Küçükyumuk Cenk , Küçükyumuk Zeliha
Published: February 2025

Dormancy breakers are widely employed in regions with an insufficient chill accumulation to enhance floral bud break in sweet cherry production. Dormex (HC) has not been authorized in Europe and many other countries due to its detrimental effects on human health (carcinogenic) and the environment. This situation has increased the demand for alternative chemicals to HC. The current study was conducted in an orchard of 5-year-old ‘Royal Tioga®’ sweet cherry trees (Prunus avium L.) grafted on MaxMa 14 rootstocks in the Karayusuflu Village (at an altitude of 50 m), Adana, a Mediterranean city in Türkiye. Levante (LV) and HC were applied approximately 30 days before the anticipated dormancy break of the buds. Chill accumulation was quantified monthly during the 2023–2024 winter season using the chilling hours below 7.2 °C (467 h) and chill units (280 CUs). This study evaluated the effects of dormancy breakers on hormonal changes in floral buds, focusing specifically on gibberellic acid (GA3) and abscisic acid (ABA). Also, their impact on fruit set and quality parameters was assessed. The findings revealed that the LV and HC applications reduced the ABA content in flower buds during the dormancy period compared to the control. LV significantly improved bud break rates (56.8%) and fruit set (85.2%) while positively influencing the fruit quality parameters and yield. No significant differences between the LV and HC treatments were observed regarding average fruit weight (8.8–8.4 g) and yield values (3.7–3.5 kg tree−1). These results suggest LV as an alternative to HC for early-season cherry production in warm climates.
Nitrogen Use Efficiency of Microbial and Amino Acid Treatments for Organic Broccoli (Brassica oleracea L. var. italica Plenk) Seed Production
Authors: Garcia Gresheen , Treccarichi Simone , Calì Riccardo , Arena Donata , Tribulato Alessandro , Branca Ferdinando
Published: February 2025

The availability and quality of organic seeds are critical challenges for organic farming, with nitrogen use efficiency (NUE) being crucial for improving productivity. This study, part of the H2020 BRESOV project, assessed the effects of three nutritional protocols (NPs) on eight broccoli genotypes (GEs), comprising two commercial F1 hybrids and six Sicilian landraces. The tested NPs included formulations containing Trichoderma species, organic nitrogen, and essential micronutrients such as iron, zinc, carbon, boron, manganese, molybdenum, and zinc. This trial was conducted on an organic farm in Adrano (CT). Plants were evaluated for key traits related to growth, development, and seed production. NUE was analyzed to measure the efficiency of nitrogen conversion from soil into seed production. Significant interactions between NPs and GEs were observed for all seed yield components and most morphometric traits, except for secondary branches and root width, varying significantly only among the tested genotypes. The Sicilian landraces Broccolo nero and Sparaceddi showed the highest seed yield, overcoming the productive performances of the commercial hybrids F1 Marathon and Gentleman. Broccolo nero, grown using amino acid microbial consortia applied solely via fertigation (NP1), exhibited the highest NUE, indicating a positive nitrogen balance relative to seed yield and soil nitrogen content. Principal component analysis (PCA) grouped the genotypes into five distinct clusters based on the analyzed bio-morphometric traits and on the effect of the treatment. The Broccolo nero and Sparaceddi genotypes formed two distinct groups, clearly differentiated by their unique morphological traits related to plant biomass and seed production. Additionally, both genotypes exhibited distinct responses to the applied nutrition protocols, with positive results compared to the control condition. These results underscore the potential of the broccoli landraces for organic farming and breeding due to their adaptability, resilience, and superior NUE.
Utilizing an Educational Intervention to Enhance Influenza Vaccine Literacy and Acceptance Among Minoritized Adults in Southern Californian Vulnerable Communities in the Post-COVID-19 Era
Authors: Abdul-Mutakabbir Jacinda C. , Abdul-Mutakabbir Raheem , Casey Samuel J.
Published: February 2025

Background/Objectives: Since the COVID-19 pandemic began, vaccination rates for preventable diseases, including influenza, have significantly dropped among racially and ethnically minoritized (REM) individuals in the United States. This study explored the effects of a community-based educational intervention designed to improve influenza vaccine literacy and acceptance among vulnerable REM individuals. Methods: The intervention included four 45 min interactive educational sessions on the influenza vaccine. The session attendees (18+) were invited to participate in a pre-/post-intervention study where an anonymous survey measured their post-COVID-19 pandemic attitudes, knowledge, and behaviors regarding the influenza virus and vaccine. To assess the effect of the intervention on vaccine literacy, we used a Mann–Whitney U test to test for differences between the pre-/post-intervention survey responses to seven knowledge-based questions. Descriptive statistics were employed to assess the impact of intervention on vaccine acceptance. Results: A total of 116 participants completed the pre-intervention survey, and 90 (78%) completed the post-intervention survey. All (100%) identified as REM, and 99% lived in highly vulnerable areas. Only 43% believed they were at risk for viral infection before the intervention, but 60% said the intervention helped them reassess their risk. We found significant differences in vaccine literacy when comparing the pre-/post-intervention survey responses, particularly regarding guideline-based vaccine recommendations (p < 0.05). Before the intervention, 65% of the participants indicated a high likelihood of receiving the influenza vaccine. In contrast, after the intervention, 81% of respondents indicated a high likelihood of being vaccinated, and 72% indicated that they were “extremely likely” to receive the immunization. Conclusions: Community-based educational interventions can have a positive impact on influenza vaccine literacy and acceptance among vulnerable REM populations in the post-COVID-19 era.
Using Machine Learning to Improve Readmission Risk in Surgical Patients in South Africa
Authors: Tokac Umit , Chipps Jennifer , Brysiewicz Petra , Bruce John , Clarke Damian
Published: February 2025

Unplanned readmission within 30 days is a major challenge both globally and in South Africa. The aim of this study was to develop a machine learning model to predict unplanned surgical and trauma readmission to a public hospital in South Africa from unstructured text data. A retrospective cohort of records of patients was subjected to random forest analysis, using natural language processing and sentiment analysis to deal with data in free text in an electronic registry. Our findings were within the range of global studies, with reported AUC values between 0.54 and 0.92. For trauma unplanned readmissions, the discharge plan score was the most important predictor in the model, and for surgical unplanned readmissions, the problem score was the most important predictor in the model. The use of machine learning and natural language processing improved the accuracy of predicting readmissions.
CXCR4 Inhibition Enhances the Efficacy of CD19 Monoclonal Antibody-Mediated Extermination of B-Cell Lymphoma
Authors: Khunti Nupur , Kumar Manish , Datta Moumita , Harelimana Jean de Dieu , Harms Mirja , Albers Dan , Kirchhoff Frank , Münch Jan , Stenger Steffen , Buske Christian , Maity Palash Chandra
Published: February 2025

CD19 and CXCR4 are pivotal regulators of B-cell activation and migration, respectively. Specifically, CXCR4 signaling critically influences the dissemination of various malignant B cells through constitutive activation and aberrant expression. This study explores the interaction between CD19 and CXCR4 signaling in the context of B-cell lymphomas, particularly focusing on diffuse large B-cell lymphoma (DLBCL) and Waldenström Macroglobulinemia (WM). We assessed the roles of CD19 in survival and CXCL12-induced migration by using knockout (KO) cells of DLBCL and WM origin alongside evaluating the impact of CD19 monoclonal antibodies (mAbs) on antibody-dependent cell-mediated cytotoxicity (ADCC). Our results highlight that CD19 is important for survival and CXCL12-induced migration, and mAbs variably increase CXCL12-induced migration and enhance ADCC. Additionally, we demonstrate that the endogenous peptide inhibitor of the CXCR4 (EPI-X4) derivative JM#21 effectively inhibits CD19-mediated migration enhancement and promotes ADCC, thereby augmenting the therapeutic efficacy of CD19 mAb-based immunotherapy in lymphoma models. Our study underscores the potential of targeting both CD19 and CXCR4 to refine therapeutic strategies for treating B-cell malignancies, suggesting a synergistic approach could improve clinical outcomes in WM treatment.
Special Issue: “Microbial Enzymes for Biotechnological Applications”
Authors: Fusco Salvatore , Aulitto Martina
Published: February 2025

Microbial biocatalysts are at the forefront of modern biotechnology, offering sustainable solutions to some of the world’s most pressing environmental and industrial challenges [...]
Effects of Deoxynivalenol Detoxifier on Growth Performance, Blood Biochemical Indices, and Microbiota Composition of Piglets
Authors: Zhang Luyao , Wang Yongwei , Wang Weiwei , Wang Li , Shi Jingjing , Cheng Junlin , Zhang Jing , Li Aike , He Beibei , Fan Zhiyong
Published: February 2025

Deoxynivalenol (DON), also known as vomitoxin, has a high detection and exceeding rate in feed and is prone to causing symptoms such as loss of appetite, weight loss, vomiting, and diarrhoea in animals, which brings great harm to the aquaculture industry. The common mycotoxin adsorbents have low adsorption rates for DON, and the use of biological methods to remove DON in feeds has gradually become a research trend. One hundred and twenty crossbred barrows were randomly divided into four groups, which included the normal diet group (CON), normal diet + detoxifier group (Det), DON-polluted diet group (DON), and DON-polluted diet + DON detoxifier group (DON + Det); the experiment lasted for 28 d. The results showed that, compared with piglets fed a normal diet, those piglets fed DON-polluted diets significantly decreased their average daily gain (ADG) and average daily feed intake (ADFI) during the 1–14 d and 1–28 d periods; the content of immunoglobulin G (IgG), catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GSH-PX), interleukin-4 (IL-4), and interleukin-10 (IL-10) in serum was decreased; and the content of aminotransferase (AST), alanine aminotransferase (ALT), malondialdehyde (MDA), diamine oxidase (DAO), and endotoxin (LPS) was increased in pigs fed DON-polluted diets; meanwhile, feeding piglets DON-polluted diets significantly reduced the levels of acetic acid, propionic acid, and total short-chain fatty acids (SCFAs) as well as gut microbiota health index (GMHI) in piglet faeces, but increased the relative abundance of Treponema, Prevotellaceae_UGG-001, Lachnospiraceae_XPB1014_group, Frisingicoccus and Sphaerochaeta. In contrast, the addition of a composite detoxifier effectively ameliorated the reduction in ADG and ADFI in piglets caused by DON-polluted diets. It suppressed the reduction in CAT, SOD, GSH-PX, IL-4, and IL-10 and the elevation of TNF-α, IL-2, IL-6, IL-12, MDA, LPS, and DAO in serum; the composite detoxifier also restrained the decrease in SCFA in piglet faeces and increased the relative abundance of Ruminococcus, Lachnospiraceae_NK4A136_group, Lachnospiraceae_AC2044_group, UCG-009, and Eubacterium_siraeum_group bacteria. The composite detoxifier effectively mitigated the adverse effects of a DON-polluted diet on piglet growth performance, blood biochemical indices, and gut microbiota composition.
NRAP-RCNN: A Pseudo Point Cloud 3D Object Detection Method Based on Noise-Reduction Sparse Convolution and Attention Mechanism
Authors: Zhou Ziyue , Jia Yongqing , Zhu Tao , Wan Yaping
Published: February 2025

In recent years, pseudo point clouds generated from depth completion of RGB images and LiDAR data have provided a robust foundation for multimodal 3D object detection. However, the generation process often introduces noise, reducing data quality and detection accuracy. Moreover, existing methods fail to effectively capture channel correlations and global contextual information during the 2D feature extraction stage after the 3D backbone network, limiting detection performance. To address these challenges, this paper proposes NRAP-RCNN, a pseudo point cloud-based 3D object detection method with two key innovations: (1) A noise-reduction sparse convolution network (NRConvNet), comprising NRConv (noise-resistant submanifold sparse convolution), SRB (sparse convolution residual block), and MHSA (multi-head self-attention). NRConv suppresses pseudo point cloud noise by jointly encoding 2D and 3D features, SRB enhances feature extraction depth and robustness, and MHSA optimizes global feature representation. (2) An attention fusion module (ECA_GCA) is introduced to enhance the feature representation of the 2D backbone network by combining channel and global contextual information. The experimental results demonstrate that NRAP-RCNN achieves 88.4% car AP (R40) on the KITTI validation set and 85.1% on the test set, significantly outperforming advanced 3D detection methods, showcasing its effectiveness in improving detection performance.
SynergyAI: A Human–AI Pair Programming Tool Based on Dataflow
Authors: Jiang Le , Yamaguchi Shingo , Bin Ahmadon Mohd Anuaruddin
Published: February 2025

This paper proposes SynergyAI, an AI–human pair programming tool that represents predictive models as dataflows composed of AI, input, and output nodes. By visualizing decision tree models and integrating them with dataflow diagrams, SynergyAI effectively addresses the machine learning black-box problem. Additionally, the tool leverages comprehensive prediction algorithms and ensemble learning to simplify the operation of complex dataflows and mitigate overfitting risks. SynergyAI also features an AI assistant that utilizes scatter plot matrices and data correlation analysis to help programmers select data and optimize model structures. Experimental results demonstrate that, through human–AI collaboration, SynergyAI achieved an accuracy of 85% in predicting mechanical failures in a chocolate factory, providing an efficient and powerful tool for programming and data analysis.
Coordination Polymers Constructed from Polycarboxylic Acids and Semi-Rigid Bis-pyridyl-bis-imide Ligands: Synthesis, Structures and Iodine Adsorption
Authors: Chen Yi-Wun , Chen Zhi-Ling , Wang Song-Wei , Chen Jhy-Der
Published: February 2025

Reactions of N,N′-bis(3-pyridylmethyl)-pyromellitic diimide (L1) or N,N’-bis(3-pyridyl)bicyclo(2,2,2,)oct-7-ene-2,3,5,6-tetracarboxylic diimide (L2) with 1,3,5-benzenetricarboxylic acid (1,3,5-H3BTC), 4,4′-sulfonyldibenzoic acid (H2SDA), or 4,4′-oxybisbenzoic acid (H2OBA) and divalent metal salts afforded {[Co(1,3,5-HBTC)(H2O)2(L1)]·H2O}n, 1, {[Co(1,3,5-HBTC)(H2O)3(L1)0.5]·H2O}n, 2, {[Co(SDA)(L1)0.5]·H2O}n, 3, {[Co(1,3,5-HBTC)(H2O(L2))]·H2O}n, 4, {[Ni(1,3,5-HBTC)(H2O)(L2)]·H2O}n, 5, [Ni(SDA)(L2)]n, 6, and [Ni(OBA)(L2)]n, 7, which were structurally characterized by using single-crystal X-ray diffraction. Complexes 1 and 2 are 1D chains with the 2,4C6 and 2,3C2 topologies, respectively, and 3 is a 2D layer with the 4,5L51 topology, whereas 4 and 5 are 1D chains with the 2,4C6 topology and 6 and 7 are 2D layers with the 2,4L2 topology. Complex 3 shows a better iodine-adsorption factor of 133.77 mg g−1 at 75 °C for 24 h than 5–7, revealing that the pi-pi conjugation of the dipyridyl ligand may govern the iodine adsorption capacity.
Cross-Cultural Ageism: Perspectives from Nursing Students in the USA and Japan
Authors: Doan Therese , Brennan Sumiyo , Seo Jongmi , Osada Hisao , Bando Michiyo
Published: February 2025

Age discrimination in nursing may result in judgmental care and compromise the quality of care offered to older adults. While geriatric–gerontological education can address ageism among nursing students, cross-cultural perspectives on aging remain understudied. This study describes the characteristics of nursing students in the USA and Japan and explores their perspectives on aging after completing a life review assignment, both personally and professionally. A mixed-methods study using quantitative surveys and an exploratory–descriptive qualitative design was conducted at two nursing schools (one each in the USA and Japan). Students participated voluntarily with strict anonymity and confidentiality. There were significant differences between American and Japanese nursing students in both demographics and perceived impact of the life review assignment. The American students were predominantly older and had more experience in caregiving for older adults, whereas the Japanese students were younger and lacked such experience. The qualitative analysis revealed an increased awareness of patient-centered care for older adults as a major professional theme across both groups. The life review assignment proved effective in providing meaningful experiential learning opportunities for future nurses across different cultural contexts. This method appears promising in addressing ageism through personalized engagement with older adults.
Computer-Aided Decision Support and 3D Models in Pancreatic Cancer Surgery: A Pilot Study
Authors: Rasenberg Diederik W. M. , Ramaekers Mark , Jacobs Igor , Pluyter Jon R. , Geurts Luc J. F. , Yu Bin , van der Ven John C. P. , Nederend Joost , de Hingh Ignace H. J. T. , Bonsing Bert A. , Vahrmeijer Alexander L. , van der Harst Erwin , den Dulk Marcel , van Dam Ronald M. , Groot Koerkamp Bas , Erdmann Joris I. , Daams Freek , Busch Olivier R. , Besselink Marc G. , te Riele Wouter W. , Reinhard Rinze , Jansen Frank Willem , Dankelman Jenny , Mieog J. Sven D. , Luyer Misha D. P.
Published: February 2025

Background: Preoperative planning of patients diagnosed with pancreatic head cancer is difficult and requires specific expertise. This pilot study assesses the added value of three-dimensional (3D) patient models and computer-aided detection (CAD) algorithms in determining the resectability of pancreatic head tumors. Methods: This study included 14 hepatopancreatobiliary experts from eight hospitals. The participants assessed three radiologically resectable and three radiologically borderline resectable cases in a simulated setting via crossover design. Groups were divided in controls (using a CT scan), a 3D group (using a CT scan and 3D models), and a CAD group (using a CT scan, 3D and CAD). For the perceived fulfillment of preoperative needs, the quality and confidence of clinical decision-making were evaluated. Results: A higher perceived ability to determine degrees and the length of tumor–vessel contact was reported in the CAD group compared to controls (p = 0.022 and p = 0.003, respectively). Lower degrees of tumor–vessel contact were predicted for radiologically borderline resectable tumors in the CAD group compared to controls (p = 0.037). Higher confidence levels were observed in predicting the need for vascular resection in the 3D group compared to controls (p = 0.033) for all cases combined. Conclusions: “CAD (including 3D) improved experts’ perceived ability to accurately assess vessel involvement and supports the development of evolving techniques that may enhance the diagnosis and treatment of pancreatic cancer”.
Obesity as a Risk Factor in Pediatric Sepsis: A Retrospective Comparative Study Under the Phoenix Definition
Authors: Yuki Koichi , Koutsogiannaki Sophia
Published: February 2025

Background: The relationship between sepsis outcomes and obesity has attracted significant interest in the medical community. However, this association has not been tested under Phoenix criteria, which represent the new pediatric sepsis definition, defining sepsis as life-threatening organ dysfunction in the setting of infection. Methods: A single-center, observational, retrospective study of pediatric sepsis patients from January 2014 to December 2019. The PICU was located within a tertiary pediatric center in the United States. Children more than one month old, but less than 18 years old, with a diagnosis of sepsis were included. Results: Six hundred and twenty-seven patients with a diagnosis of sepsis based on the Sepsis-2 definition were identified. Within the cohort, 554 patients met the definition of sepsis under the Phoenix criteria. Patients were classified based on the body habitus as underweight, normal, overweight, and obese. Obese patients had significantly higher mortality compared to the normal weight group (p = 0.033). More renal dysfunction was also seen in the obesity group (p = 0.0007). No difference in the frequency of identified Gram-positive, Gram-negative bacterial, viral, or fungal sepsis was observed between normal-weight and obese patients. Conclusions: In our cohort of pediatric sepsis, obesity was significantly associated with a higher degree of organ dysfunction and mortality. However, no difference in the incidence of identified bacterial, fungal, or viral sepsis was observed.
Neutrophil Gelatinase-Associated Lipocalin: Biological Aspects and Potential Diagnostic Use in Acute Kidney Injury
Authors: Virzì Grazia Maria , Morisi Niccolò , Oliveira Paulo Catarina , Clementi Anna , Ronco Claudio , Zanella Monica
Published: February 2025

Acute kidney injury (AKI) is a syndrome characterized by a rise in creatinine or a decrease in urinary flow, according to the Kidney Disease Improving Global Outcomes (KDIGO) definition. It is diagnosed in 15% of inpatients and 50% of patients in the intensive care unit (ICU), and it is related to increased mortality. As part of a global effort aimed at the elimination of preventable deaths from AKI, there is a growing interest in identifying biomarkers that can be point-of-care and that are not influenced by the variability in patient characteristics in a relevant way. Neutrophil gelatinase-associated lipocalin (NGAL), particularly in its 25 kDa form, which is exclusively released by renal tubules, has emerged as a promising biomarker with potential use in the diagnosis of AKI in the critically ill, including its use in guiding the initiation and/or weaning of renal replacement therapy (RRT). The objective of this review is to summarize the current understanding of NGAL in acute settings, emphasizing biological and genomic insights.
Individualized Algorithm-Based Intermittent Hypoxia Improves Quality of Life in Patients Suffering from Long-Term Sequelae After COVID-19 Infection
Authors: Kapel Josephine Schultz , Stokholm Rasmus , Elmengaard Brian , Nochi Zahra , Olsen Rikke Jentoft , Foldager Casper Bindzus
Published: February 2025

Background/Objectives: Post-COVID-19 condition (PCC), also known as long COVID, has emerged as a recognized syndrome affecting millions of people worldwide, significantly impairing their quality of life. Currently, no effective therapeutic options are available to manage this condition. The objective of the present study was to evaluate the long-term effects of personalized, algorithm-based intermittent hypoxia–hyperoxia conditioning (IHHC) on quality of life and pain in patients with PCC. Methods: This open-label cohort study included 199 PCC patients, aged 11–87 years (female-to-male ratio: 67:33) and experiencing moderate-to-severe fatigue, between 1 January 2020 and 31 December 2023. Each patient received an algorithm-based treatment plan tailored to their demographics, symptom duration, and baseline pain (NRS) and quality of life (SF-36) scores. Patients received an average of six treatment sessions (range: 2–21), each consisting of intermittent hypoxic–hyperoxic cycles, with hypoxia (9–13% O2) lasting 3–8 min and hyperoxia (34–36% O2) lasting 1–3 min. The primary outcomes were changes in the NRS and SF-36 scores at the 6-week and 6-month follow-ups. Results: At the 6-week follow-up after treatment initiation, the SF-36 scores increased by 102 points (p < 0.001, 95% CI: 78.4–127), and this improvement persisted at the 6-month follow-up (Δ106, p < 0.001, 95% CI: 57.0–154). Pain was reduced by 28–32% at both follow-up time points, exceeding the clinically relevant threshold. Health transition scores indicated a patient-perceived improvement in health status. Conclusions: In this study, a personalized, algorithm-based IHHC alleviated pain and improved quality of life in patients suffering from persistent long-term sequelae after COVID-19 infection. The effects were sustained for up to six months. Further research is warranted to elucidate the mechanisms underlying IHHC’s therapeutic effects in this patient population.
Sex Differences and the Relationship Between Athlete Anthropometrics and Long Jump Performance at National Elite Level
Authors: Uzomba Godwin Chinedu , Fuchs Philip X. , Cortis Cristina , Fusco Andrea
Published: February 2025

Objectives: Anthropometric characteristics influence performance and development in athletic activities such as long jumping. This study aimed to analyze sex differences in anthropometrics among high-level long jumpers and investigate the relationship between anthropometrics and long jump distance. Methods: During the national championships, body height, mass, segment lengths, and circumferences of 39 male and 22 female competitors were obtained via a stadiometer, weight scale, and non-stretchable tape. Officials measured jump distances during the competition. ANOVA, correlation, and stepwise-forward regression analysis were conducted at a significance level of p < 0.05. The half-split method was used to cross-validate the final regression model. Results: Height, mass, and more than 50% of the measured segment lengths and circumferences differed between sexes (η2 = 0.053–0.422, p < 0.05). Jump distance correlated with sex, mass, height, arm span, shank and leg length, and upper arm and chest circumference (r = 0.264–0.686, p < 0.05). The final regression model identified sex and chest circumference as predictors of jump distance (adjusted R2 = 0.519, p < 0.001). Conclusions: This study enhances the understanding of key anthropometric features influencing long jump performance at an elite level. Recognizing the importance of these characteristics has practical implications for talent identification, athlete assessment, and strength program development.
Antarctic Sea Ice Extraction for Remote Sensing Images via Modified U-Net Based on Feature Enhancement Driven by Graph Convolution Network
Authors: Feng Wu , Geng Xiulin , He Xiaoyu , Hu Miao , Luo Jie , Bi Meihua
Published: February 2025

Antarctic true-color imagery synthesized using multispectral remote sensing data is effective in reflecting sea ice conditions, which is crucial for monitoring. Deep learning has been explored for sea ice extraction, but traditional convolutional neural network models are constrained by a limited perceptual field, making it difficult to obtain global contextual information from remote sensing images. A novel model named GEFU-Net, a modification of U-Net, is presented. The self-established graph reconstruction module is employed to convert features into graph data and construct the adjacency matrix using a global adaptive average similarity threshold. Graph convolutional networks are utilized to aggregate the features at each pixel, enabling the rapid capture of global context, enhancing the semantic richness of the features, and improving the accuracy of sea ice extraction through graph reconstruction. Experimental results using the sea ice dataset of the Ross Sea in the Antarctic, produced by Sentinel-2, demonstrate that our GEFU-Net achieves the best performance compared to other commonly used segmentation models. Specifically, it achieves an accuracy of 97.52%, an Intersection over Union of 95.66%, and an F1-Score of 97.78%. Additionally, fewer model parameters and good inference speed are demonstrated, indicating strong potential for practical ice mapping applications.
The Distribution of Dissolved Copper and Natural Organic Ligands in Tropical Coastal Waters Under Seasonal Variation
Authors: Ng Li Qing , Mohamed Khairul Nizam , Amiruddin Abd Muhaimin , Yusuff Ferdaus Mohamat , Mustaffa Nur Ili Hamizah
Published: February 2025

The bioavailability of dissolved copper (Cu) in seawater is influenced by the presence of natural organic matter. Changes in physicochemical conditions, such as pH, temperature, and salinity, can significantly affect the solubility and speciation of copper, thereby impacting the complexation of Cu(II)-binding organic ligands. The concentration of dissolved Cu in the coastal water of Mersing, Malaysia, was detected by anodic stripping voltammetry (ASV). The natural organic copper(II)-binding ligands (CuL) and their conditional stability constants (log K′) were determined by using the competitive ligand exchange–adsorptive cathodic stripping voltammetry method (CLE–AdCSV) in our samples. The in situ parameters, such as pH, temperature, salinity, and dissolved oxygen (DO), were found to be significantly different between sampling periods and indicated the different physical chemical conditions between the sampling periods. However, we found a consistent concentration of dissolved Cu throughout the water column between sampling periods. This suggests that the presence of a strong class of natural organic ligands (L1) in Mersing’s coastal water maintains the dissolved Cu(II) ions in the water column and prevents the scavenging and precipitation processes under the seasonal variations.
Association of Aspirin Use in Primary Prevention and Cardiovascular Events: A Retrospective Analysis of the VITAL Cohort
Authors: Caldeira Daniel , Alves Mariana , Gonçalves Nilza , Costa João , Ferreira Joaquim J. , Pinto Fausto J.
Published: February 2025

Background: Aspirin is part of the therapeutic antithrombotic armamentarium for the management of patients with established clinically relevant atherosclerosis or thrombotic cardiovascular disease. Personalized medicine identifies those who benefit most or face fewer risks from aspirin. The role of aspirin in primary prevention is still debatable. We aimed to assess the risks and benefits of aspirin in this setting, using the data of the prospective VITAL (VITamins and Lifestyle) study. Methods: We conducted a retrospective evaluation of the VITAL cohort. In this analysis, participants were split according to aspirin usage. Aspirin use was evaluated regarding all-cause mortality, CV mortality, major cardiovascular event (MACE), myocardial infarction, coronary heart disease, total stroke, and hemorrhagic stroke. The hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated to explore the association between cardiovascular events and aspirin usage. The estimates were adjusted for demographic and clinical variables. Results: The aspirin users (n = 11,570) were older, more frequently men, the body mass index was higher, and the proportion of smokers was smaller compared with non-users (n = 13,927). After adjusting for demographic and clinical variables, aspirin was not identified as a predictor of cardiovascular death (HR 1.17, 95%CI 0.89 to 1.55), major cardiovascular events (HR 1.04, 95%CI 0.89 to 1.22), coronary heart disease (HR 1.16, 95%CI 0.98 to 1.37), nor stroke (HR 1.01, 95%CI 0.77 to 1.31). Conclusion: In this retrospective analysis of the VITAL cohort, aspirin was not associated with a reduced risk of cardiovascular mortality or events.