bluuebunny/crossref_metadata_2025 huggingface dataset:
A Plug Seedling Growth-Point Detection Method Based on Differential Evolution Extra-Green Algorithm
Authors: Xia Hongmei , Zhu Shicheng , Yang Teng , Huang Runxin , Ou Jianhua , Dong Lingjin , Tao Dewen , Zhen Wenbin
Published: January 2025

To produce plug seedlings with uniform growth and which are suitable for high-speed transplanting operations, it is essential to sow seeds precisely at the center of each plug-tray hole. For accurately determining the position of the seed covered by the substrate within individual plug-tray holes, a novel method for detecting the growth points of plug seedlings has been proposed. It employs an adaptive grayscale processing algorithm based on the differential evolution extra-green algorithm to extract the contour features of seedlings during the early stages of cotyledon emergence. The pixel overlay curve peak points within the binary image of the plug-tray’s background are utilized to delineate the boundaries of the plug-tray holes. Each plug-tray hole containing a single seedling is identified by analyzing the area and perimeter of the seedling’s contour connectivity domains. The midpoint of the shortest line between these domains is designated as the growth point of the individual seedling. For laboratory-grown plug seedlings of tomato, pepper, and Chinese kale, the highest detection accuracy was achieved on the third-, fourth-, and second-days’ post-cotyledon emergence, respectively. The identification rate of missing seedlings and single seedlings exceeded 97.57% and 99.25%, respectively, with a growth-point detection error of less than 0.98 mm. For tomato and broccoli plug seedlings cultivated in a nursery greenhouse three days after cotyledon emergence, the detection accuracy for missing seedlings and single seedlings was greater than 95.78%, with a growth-point detection error of less than 2.06 mm. These results validated the high detection accuracy and broad applicability of the proposed method for various seedling types at the appropriate growth stages.
Screening and Assessment of Genetic Diversity of Rice (Oryza sativa L.) Germplasm in Response to Soil Salinity Stress at Germination Stage
Authors: Anwar Alia , Tabassum Javaria , Ahmad Shakeel , Ashfaq Muhammad , Hussain Adil , Ullah Muhammad Asad , Saad Nur Shuhadah Binti Mohd , Ghazy Abdelhalim I. , Javed Muhammad Arshad
Published: January 2025

Salinity stress significantly affects rice yield, especially when it occurs during the germination stage. Direct seeding is an emerging method to conserve water in rice cultivation. However, to date, there have been limited efforts to screen rice germplasm for salt tolerance under this approach. In this study, 40 rice genotypes were evaluated for salt tolerance using a combination of germination and growth parameters. A total of 59 microsatellite markers were used to assess genetic diversity, revealing significant variation in both germination and growth traits. Based on germination parameters, IR36, Sri Malaysia 2, and MR185 performed well under saline conditions, while Hashemi Tarom and BAS2000 exhibited weak tolerance. MR219, MR211, and MR263 were identified as superior salt-tolerant genotypes against all growth parameters. BAS2000 and MCHKAB were identified as salt-sensitive, showing reduced growth in key traits, including root and shoot development. Marker-based genotyping identified a total of 287 alleles. The number of alleles per locus ranged from two to nine with an average of 4.86. The polymorphic information content (PIC) ranged from four to eight. The markers RM21, RM481 RM566, RM488, RM9, RM217, RM333, RM242, RM209, RM38, RM539, RM475, RM267, RM279, and RM430 were found highly polymorphic with PIC value > 0.7 and contain the highest number of alleles (≥6). Model- and distance-based population structures both inferred the presence of three clusters in the studied rice germplasm. Based on cluster analysis, Shiroodi, Hashemi Tarom, and BAS2000 were found as weak salt-tolerant varieties, whereas MR211 and MR219 are two Malaysian varieties found to be highly tolerant and have a high potential for direct seeding methods. An AMOVA test suggested that 95% genetic diversity was within the population, which implies that significant genetic variation was present in rice germplasm to be used to select parents for future breeding programs.
Healthy as a Horse? Characterising the UK and Ireland’s Horse Owners, Their Horses, and Owner-Reported Health and Behavioural Issues
Authors: Watson Wendy Leah , MacKay Jill R. D. , Dwyer Cathy M.
Published: January 2025

This study focuses on recreational horse owners in the UK and Ireland to explore the relationship between horse characteristics and welfare issues. An online questionnaire was distributed to 1501 horse owners to collect data on the owners, horses, and health/behavioural issues. Most respondents were female (98%), lived in England (56%), and did not insure their horses for veterinary costs (51%). Horses were typically over 5 years of age (96%), taller than 154 cm (55%), and mostly geldings (65%). Common welfare issues reported included lameness (26%), handling problems (11%), antisocial behaviours (9%), and abnormal oral behaviours (9%). Older horses were 4.23 times more likely to have lameness issues than younger horses (95% CI [2.17, 9.27], p < 0.001), while sport horse breeds were 3.12 times more likely to exhibit abnormal oral behaviours (95% CI [2.10, 4.73], p < 0.001) compared to other breed types. Whilst the study found a relatively low rate of welfare issues, the main problems reported were consistent with those seen in other studies. Age and breed appeared to influence the prevalence of these issues, although the relationships were weak. The study suggests that factors such as the owner’s attitudes, knowledge, and management practices may play a significant role in the incidence of welfare problems. Further research is needed to explore the impact of management on horse welfare.
Effect of Supplementation of Quercetagetin on the Antioxidant Function, Liver Mitochondrial Function and Gut Microbiota of Broilers at High Stocking Density
Authors: Yang Shuo , Su Zixuan , Huo Min , Zhong Cuihong , Wang Fangfang , Zhang Yongying , Song Yaqi , Shi Yuxiang
Published: January 2025

This study investigates the effects of quercetagetin (QG) supplementation on the antioxidant capacity, liver mitochondrial function, and cecal microbiota of broilers raised under high-density conditions. A 2 × 2 factorial design with 144 one-day-old WOD168 broilers, which were allocated to two stocking densities (LD: 4 birds per cage, equivalent to 11.1 birds per square meter; HD: eight birds per cage, equivalent to 22.2 birds per square meter) and two levels of dietary supplementation of QG (0 and 20 mg/kg). At the conclusion of day 21, broilers of similar body weights were randomly allocated into four groups (22 to 42 d): control (CON), QG treatment (QG), high stocking density (HSD), and high stocking density with QG supplementation (H_QG). The results demonstrated that HD groups significantly reduced broiler growth performance, including body weight (BW), average daily gain (ADG), and average daily feed intake (ADFI) (p < 0.05). Additionally, HD groups increased serum stress hormone levels (CORT and ACTH), pro-inflammatory cytokines (IL-1β and IL-6) (p < 0.05), while decreasing liver antioxidant enzyme activities (GSH-Px, T-SOD), serum CAT and T-SOD activities, and mitochondrial function (GSH, complex I-III, ATP contents) (p < 0.05). However, dietary supplementation with 20 mg/kg QG significantly alleviated the negative effects induced by HSD, restoring growth performance, stress hormone levels, immune parameters, and liver antioxidant and mitochondrial function. Moreover, QG supplementation markedly improved cecal microbiota composition, enhancing gut health. Correlation analysis revealed a strong association between microbial composition and overall broiler health, indicating that gut microbiota plays a critical role in mediating these beneficial effects. In conclusion, QG exhibits protective effects against oxidative stress, mitochondrial dysfunction, and gut microbiota imbalance induced by high-density rearing, suggesting its potential as a functional feed additive to improve broiler health under intensive farming conditions.
No More Evasion: Redefining Conflict Behaviour in Human–Horse Interactions
Authors: O’Connell Emily , Dyson Sue , McLean Andrew , McGreevy Paul
Published: January 2025

Euphemisms, anthropomorphisms, and equivocation are established characteristics of traditional equestrian language. ‘Evasion’, ‘resistance’, and ‘disobedience’ are common labels assigned to unwelcome equine behaviours, implying that the horse is at fault for not complying with the human’s cues and expectations. These terms appear to overlook multiple motivations that may directly result in the horse offering unwelcome responses, which may then inadvertently be reinforced. This article revisits some of the anthropocentric inferences in these terms and explores the harmful consequences of such convenient but incorrect labels before proposing a redefinition of ‘conflict behaviour’ in human–horse interactions: Responses reflective of competing motivations for the horse that may exist on a continuum from subtle to overt, with frequencies that range from a singular momentary behavioural response to repetitive displays when motivational conflict is prolonged. Addressing how inadequate terms may mask pain, obscure the horse’s motivation, and deflect human culpability, this commentary highlights the merits of a multidisciplinary approach to terminology across equine research. Acknowledging that variables contributing to behaviour can be biological, environmental and anthropogenic, it emphasises the need for more investigation into the relationships between equicentric motivations reflecting equine telos and problematic horse behaviours.
Effects of Black Cumin Seed Extract on Pancreatic Islet β-Cell Proliferation and Hypoglycemic Activity in Streptozotocin-Induced Diabetic Rats
Authors: Kim Jongkyu , Chun Yoon-Seok , Yoon Namkyu , Kim Byungkwon , Choi Kiin , Ku Sae-Kwang , Lee Namju
Published: January 2025

Thymoquinone (TQ), a bioactive compound derived from black cumin seeds, is renowned for its potent anti-obesity and anti-diabetic properties. Due to the stability challenges of TQ, it has predominantly been utilized in oil formulations. This study aimed to enhance the stability of TQ and investigated the impact of consuming insoluble fiber from black cumin seeds on restoring antioxidant function compromised by diabetes and improving hyperglycemia management. We evaluated the restorative effects of a 35-day administration of black cumin seed extract (BCS) on antioxidant function impaired by streptozotocin (STZ)-induced diabetes, alongside structural and functional alterations in the pancreas, liver, and kidneys. The results demonstrated significant improvements in organ weight, particularly in pancreatic tissue. Moreover, BCS administration markedly suppressed the expression of key genes associated with pancreatic dysfunction and damage, including caspase-3, transforming growth factor-beta 1 (TGF-β1), and interleukin-1 beta (IL-1β). Through oral glucose tolerance tests (OGTTs), BCS was found to effectively regulate chronic hyperglycemia and exhibit potential for managing acute hyperglycemia. These findings suggest that BCS not only addresses both glycemic and non-glycemic complications of diabetes but also offers a safe, long-term solution. Consequently, BCS emerges as a promising therapeutic agent for hyperglycemia management, including in prediabetic stages.
Metal Recovery from Wastes: A Review of Recent Advances in the Use of Bioelectrochemical Systems
Authors: Pines Pozo María Teresa , Lopez Fernandez Ester , Villaseñor José , Leon-Fernandez Luis F. , Fernandez-Morales Francisco Jesus
Published: January 2025

The rapid technological advancements and the shift towards clean energy have significantly increased the demand for metals, leading to an increasing metal pollution problem. This review explores recent advances in bioelectrochemical systems (BES) for metal recovery from waste, especially Acid Mine Drainage (AMD) and Electrical, Electronic Wastes (EEW) and waste from smelters, highlighting their potential as a sustainable and economically viable alternative to traditional methods. This study addresses the applications and limitations of current BES recovery techniques. BES, including microbial fuel cells (MFCs), microbial electrolytic cells (MECs), and Microbial Desalination Cells (MDCs), offer promising solutions by combining microbial processes with electrochemical reactions to recover valuable metals while reducing energy requirements. This review categorizes recent research into two main areas: pure BES applications and BES coupled with other technologies. Key findings include the efficiency of BES in recovering metals like copper, chromium, vanadium, iron, zinc, nickel, lead, silver, and gold and the potential for integrating BES with other systems to enhance performance. Despite significant progress in BES application for metal recovery, challenges such as high costs and slow kinetics remain, necessitating further research to optimize materials, configurations, and operational conditions. The work also includes an economic assessment and guidelines for BES development and upscale. This review underscores the critical role of BES in advancing sustainable metal recovery and mitigating the environmental impact of metal pollution.
An Analytical Benchmark of Feature Selection Techniques for Industrial Fault Classification Leveraging Time-Domain Features
Authors: Süpürtülü Meltem , Hatipoğlu Ayşenur , Yılmaz Ersen
Published: January 2025

The growing size and complexity of industrial datasets have intensified the need for efficient fault diagnostics tools. This study addresses the challenge of handling large-scale data by developing a data-driven architecture for fault classification in industrial systems. To extract meaningful insights, 15 time-domain features were combined with 5 Feature Selection Methods to optimize model performance by eliminating redundant features. The sensor data and selected features were analyzed using the Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) algorithms to enable accurate fault detection and prediction. The proposed framework was validated using publicly available datasets, namely the Case Western Reserve University (CWRU) bearing dataset and the National Aeronautics and Space Administration Ames Prognostics Center of Excellence (NASA PCoE) lithium-ion battery dataset. The results demonstrate the framework’s adaptability and high efficacy across diverse scenarios, achieving an average F1-score exceeding 98.40% using only 10 selected features. This finding highlights the effectiveness of embedded Feature Selection Methods in improving classification performance while reducing computational complexity. The study underscores the potential of the proposed framework as a foundational tool in intelligent manufacturing, offering a versatile solution to enhance fault diagnostics in diverse industrial applications.
Optimizing Cervical Cancer Diagnosis with Feature Selection and Deep Learning
Authors: Jeleń Łukasz , Stankiewicz-Antosz Izabela , Chosia Maria , Jeleń Michał
Published: January 2025

The main purpose of cervical cancer diagnosis is a correct and rapid detection of the disease and the determination of its histological type. This study investigates the effectiveness of combining handcrafted feature-based methods with convolutional neural networks for the determination of cancer histological type, emphasizing the role of feature selection in enhancing classification accuracy. Here, a data set of liquid-based cytology images was analyzed and a set of handcrafted morphological features was introduced. Furthermore, features were optimized through advanced selection techniques, including stepwise and significant feature selection, to reduce feature dimensionality while retaining critical diagnostic information. These reduced feature sets were evaluated using several classifiers including support vector machines and compared with CNN-based approach, highlighting differences in accuracy and precision. The results demonstrate that optimized feature sets, paired with SVM classifiers, achieve classification performance comparable to those of CNNs while significantly reducing computational complexity. This finding underscores the potential of feature reduction techniques in creating efficient diagnostic frameworks. The study concludes that while convolutional neural networks offer robust classification capabilities, optimized handcrafted features remain a viable and cost-effective alternative, particularly when the data count is limited. This work contributes to advancing automated diagnostic systems by balancing accuracy, efficiency, and interpretability.
Sustainability in Bio-Based Edible Films, Coatings, and Packaging for Small Fruits
Authors: Oliveira Ivo , Pinto Teresa , Afonso Sílvia , Karaś Monika , Szymanowska Urszula , Gonçalves Berta , Vilela Alice
Published: January 2025

Sustainability in bio-based edible films, coatings, and packaging integrates environmental, economic, and social sustainability using renewable resources. These materials offer an eco-friendly alternative to traditional petroleum-based plastics and can extend the shelf life of fruits. The wine industry’s by-products, rich in bioactive compounds, can create bio-based films and coatings. However, some challenges and limitations may occur. Producing bio-based films and coatings on a commercial scale can be challenging, requiring significant investment in research and development. While bio-based materials offer many benefits, they may not always match synthetic plastics’ mechanical strength and barrier properties. However, ongoing research is actively working to improve the functionality and durability of these materials, offering hope for the future. Bio-based materials can be more expensive to produce than conventional plastics, which may limit their widespread adoption without economic incentives or subsidies. Therefore, this review, which aims to provide a literature review about the benefits, challenges, and prospects of the sustainability offered using bio-based edible films, coatings, and packaging, particularly in small fruits and grapevine by-products, is important in the field.
Dynamic Online Label Distribution Feature Selection Based on Label Importance and Label Correlation
Authors: Chen Weiliang , Sun Xiao , Ren Fuji
Published: January 2025

Existing feature selection methods mainly target single-label learning and multi-label learning, and only a few algorithms are optimized for label distribution learning. In label distribution learning, the associated labels of each sample have different levels of importance. Therefore, multi-label feature selection algorithms cannot be directly applied to label distribution learning. Discretizing label distribution data into multi-label data will cause part of the supervision information to be lost. In most practical applications of label distribution learning, the feature space is undefined, and the features are in the form of flow features. To solve this problem, this paper applies fuzzy rough set theory and applies the flow feature framework to propose a dynamic label distribution feature selection algorithm that handles flow features. Experimental results show that the proposed method is more effective than six state-of-the-art feature selection algorithms on 12 datasets with respect to six representative evaluation metrics.
DAPONet: A Dual Attention and Partially Overparameterized Network for Real-Time Road Damage Detection
Authors: Pan Weichao , Lei Jianmei , Wang Xu , Lv Chengze , Wang Gongrui , Li Chong
Published: January 2025

Existing methods for detecting road damage mainly depend on manual inspections or sensor-equipped vehicles, which are inefficient, have limited coverage, and are susceptible to errors and delays. These traditional methods also struggle with detecting minor damage, such as small cracks and initial potholes, making real-time road monitoring challenging. To address these issues and improve the performance for real-time road damage detection using Street View Image Data (SVRDD), this study propose DAPONet, a new deep learning model. DAPONet proposes three main innovations: (1) a dual attention mechanism that combines global context and local attention, (2) a multi-scale partial overparameterization module (CPDA), and (3) an efficient downsampling module (MCD). Experimental results on the SVRDD public dataset show that DAPONet reaches a mAP50 of 70.1%, surpassing YOLOv10n (an optimized version of YOLO) by 10.4%, while reducing the model’s size to 1.6 M parameters and cutting FLOPs to 1.7 G, resulting in a 41% and 80% decrease, respectively. Furthermore, the model’s mAP50-95 of 33.4% on the MS COCO2017 dataset demonstrates its superior performance, with a 0.8% improvement over EfficientDet-D1, while reducing parameters and FLOPs by 74%.
Monitoring of Cropland Non-Agriculturalization Based on Google Earth Engine and Multi-Source Data
Authors: Yang Liuming , Sun Qian , Gui Rong , Hu Jun
Published: January 2025

Cropland is fundamental to food security, and monitoring cropland non-agriculturalization through satellite enforcement can effectively manage and protect cropland. However, existing research primarily focuses on optical imagery, and there are problems such as low data processing efficiency and long updating cycles, which make it difficult to meet the needs of large-scale rapid monitoring. To comprehensively and accurately obtain cropland change information, this paper proposes a method based on the Google Earth Engine (GEE) cloud platform, combining optical imagery and synthetic aperture radar (SAR) data for quick and accurate detection of cropland non-agriculturalization. The method uses existing land-use/land cover (LULC) products to quickly update cropland mapping, employs change vector analysis (CVA) for detecting non-agricultural changes in cropland, and introduces vegetation indices to remove pseudo-changes. Using Shanwei City, Guangdong Province, as a case study, the results show that (1) the cropland map generated in this study aligns well with the actual distribution of cropland, achieving an accuracy of 90.8%; (2) compared to using optical imagery alone, the combined optical and SAR data improves monitoring accuracy by 22.7%, with an overall accuracy of 73.65%; (3) in the past five years, cropland changes in Shanwei followed a pattern of an initial increase followed by a decrease. The research in this paper can provide technical reference for the rapid monitoring of cropland non-agriculturalization on a large scale, so as to promote cropland protection and rational utilization of cropland.
Raman Spectroscopy and Imaging Techniques Applied to Neolithic Artefacts as a Valuable Contribution to the Archaeological Research on Piacentine Sites
Authors: Fracasetti Laura , Pescio Sara , Maffi Maria , Mazzieri Paola , Fumagalli Patrizia , Zucali Michele , Trombino Luca
Published: January 2025

Archaeologists and conservation scientists join interdisciplinary projects aiming at the in-depth analysis of artefacts and the resolution of new archaeological issues, overcoming the common limits of mesoscopic observation. The aim of this research is to perform multidisciplinary research, adapting imaging techniques (RTI imaging and 3D photogrammetry) and Raman spectroscopy from their conventional field of application to study and valorise neolithic archaeological findings from Piacentine sites (Emilia-Romagna, Italy). RTI images enable the detection of a comprehensive framework of anthropic and natural traces on the object surfaces to support the hypothesis of the intended usage of artefacts. Combining qualitative and quantitative Raman spectra analysis, the specific lithological characterisation of each fragment is conducted, thereby the understanding of their probable geographic provenance is enhanced. This contributes to the identification of the External Ligurian Units as a possible primary supply area, along with the already known outcrops in the Mont Viso Massif and Voltri Group. Their potential as a powerful instrument for conservation and valorisation has been revealed by 3D models. In fact, they may enrich museum exhibits, enhancing visitors’ experience through interactive engagement and guarantee the examination of artefacts by experts across the globe through online sharing, without the need for transportation and excessive manipulation.
Assessing Risk of Emissions Generated During Illegal Waste Burning: Phytotoxicity and Bioaccumulation
Authors: Tumurbaatar Selenge , Kováts Nora , Eck-Varanka Bettina , Teke Gábor , Hubai Katalin
Published: January 2025

Open burning of agricultural waste is a common practice in both developed and developing regions of the world, and the emissions pose serious inputs for ambient concentrations of atmospheric particulate matter (PM). In addition, when agricultural waste burning is combined with open-air burning of domestic waste such as plastic, rags, or tires, the potential risk of generating toxic emissions increases. PM samples produced via controlled burning of selected waste types were tested in our laboratory using the No. 227 OECD Guideline for the Testing of Chemicals: Terrestrial Plant Test. Comparing two recommended test species, lettuce (Lactuca sativa) and mustard (Sinapis alba), L. sativa showed significantly higher sensitivity, as treatment elucidated biomass reduction (Df = 1, F = 16.43, p = 0.000385), the biomass of the treated plants was 61.4-91.7% of the control plants. In our investigation inhibition in photosynthetic pigment activity chlorophyll-b in lettuce (Df = 1, F = 3.609, p = 0.0701) was found. The levels of the stress enzyme peroxidase increased significantly in the case of both test species (L. sativa: Df = 1, F = 6.76, p = 0.0112; S. alba: Df = 1, F = 49.99, p = 1.63 × 10−9), indicating that peroxidase could be regarded as the most sensitive indicator of air pollution. The bioaccumulation pattern was also assessed, proving the risk of significant bioaccumulation of potentially toxic compounds in edible parts of the vegetables tested. Both test plants accumulated higher molecular weight PAHs in significant quantities, as the concentration of 5-ring PAHs was 43.2 μg/kg in mustard and 49.35 μg/kg in lettuce.
Fine-Grained Air Pollution Inference at Large-Scale Region Level via 3D Spatiotemporal Attention Super-Resolution Model
Authors: Li Changqun , Tang Shan , Liu Jing , Pan Kai , Xu Zhenyi , Zhao Yunbo , Yang Shuchen
Published: January 2025

Air pollution presents a serious hazard to human health and the environment for the global rise in industrialization and urbanization. While fine-grained monitoring is crucial for understanding the formation and control of air pollution and their effects on human health, existing macro-regional level or ground-level methods make air pollution inference in the same spatial scale and fail to address the spatiotemporal correlations between cross-grained air pollution distribution. In this paper, we propose a 3D spatiotemporal attention super-resolution model (AirSTFM) for fine-grained air pollution inference at a large-scale region level. Firstly, we design a 3D-patch-wise self-attention convolutional module to extract the spatiotemporal features of air pollution, which aggregates both spatial and temporal information of coarse-grained air pollution and employs a sliding window to add spatial local features. Then, we propose a bidirectional optical flow feed-forward layer to extract the short-term air pollution diffusion characteristics, which can learn the temporal correlation contaminant diffusion between closeness time intervals. Finally, we construct a spatiotemporal super-resolution upsampling pretext task to model the higher-level dispersion features mapping between the coarse-grained and fined-grained air pollution distribution. The proposed method is tested on the PM2.5 pollution datatset of the Yangtze River Delta region. Our model outperforms the second best model in RMSE, MAE, and MAPE by 2.6%, 3.05%, and 6.36% in the 100% division, and our model also outperforms the second best model in RMSE, MAE, and MAPE by 3.86%, 3.76%, and 12.18% in the 40% division, which demonstrates the applicability of our model for different data sizes. Furthermore, the comprehensive experiment results show that our proposed AirSTFM outperforms the state-of-the-art models.
Spherical Fuzzy Credibility Dombi Aggregation Operators and Their Application in Artificial Intelligence
Authors: Khan Neelam , Qiyas Muhammad , Karabasevic Darjan , Ramzan Muhammad , Ali Mubashir , Dugonjic Igor , Stanujkic Dragisa
Published: January 2025

It was recently proposed to extend the spherical fuzzy set to spherical fuzzy credibility sets (SFCSs). In this paper, we define the concept of SFCSs. We then define new operational laws for SFCSs using Dombi operational laws. Various spherical fuzzy credibility aggregation operators such as spherical fuzzy credibility Dombi weighted averaging (SFCDWA), spherical fuzzy credibility Dombi ordered weighted averaging (SFCDOWA), spherical fuzzy credibility Dombi weighted geometric (SFCDWG), and spherical fuzzy credibility Dombi ordered weighted geometric (SFCDOWG) are defined. We also show the boundedness, monotonicity, and idempotency aspects of the suggested operators. We proposed the spherical fuzzy credibility entropy to find the unknown weight information of the attributes. Symmetry analysis is a useful and important tool in artificial intelligence that may be used in a variety of fields. To calculate the significant factor, we determine the multi-attribute decision-making (MADM) method using the suggested operators for SFCSs to increase the value of the assessed operators. To demonstrate the effectiveness and superiority of the suggested approach, we compare our findings to those of many other approaches.
HIF-1α Promotes Luteinization via NDRG1 Induction in the Human Ovary
Authors: Nishigaki Akemi , Ishida Mitsuaki , Tsubokura Hiroaki , Hisamatsu Yoji , Hirose Yoshinobu , Okada Hidetaka
Published: January 2025

Background/Objectives: Hypoxia-inducible factor-1α (HIF-1α) is a transcription factor that plays a crucial role in various physiological and pathological processes of the ovary. However, the timing of HIF-1α expression and its specific biological function in the follicular development of the human ovary remain unclear. Therefore, in this study, we aimed to examine whether HIF-1α and its downstream gene, N-myc downstream-regulated gene 1 (NDRG1), exhibit stage-specific expression during the follicular development process in the human ovary. Methods: We used ovarian tissues from eight women with regular menstrual cycles who were not undergoing hormonal treatment. We investigated HIF-1α and NDRG1 expression and localization using immunohistochemistry. Further, we transfected human ovarian granulosa (KGN) cells with HIF-1α small interfering RNA (siRNA) to investigate the influence of HIF-1α on NDRG1 expression and progesterone synthesis. Results: The immunohistochemical analysis of human ovarian tissues revealed that HIF-1α was localized in the cytoplasm of granulosa cells (GCs) at both the primary and secondary follicular stages. Conversely, in tertiary and later developmental stages, HIF-1α was observed exclusively in the nucleus of GCs. Furthermore, while NDRG1 was not detected in primary follicles, it was present in all GCs beyond the tertiary stage. Notably, transfection of KGN cells with HIF-1α siRNA significantly decreased NDRG1 expression, at both the mRNA and protein levels, and in progesterone synthesis. Conclusion: Our results indicate that HIF-1α and NDRG1 are integral to follicular development and the early luteinization of pre-ovulatory follicles.
Energy-Saving and Decarbonization Design Optimization for School Canteen Buildings: A Case Study in Nanjing
Authors: Zhang Yuhan , Hu Kai , Yang Yankai , Li Depeng , Deng Tao , Hu Zhongping , Xu Yizhe
Published: January 2025

In light of global climate change and China’s commitment to carbon neutrality by 2060, this study explores energy-saving and decarbonization design optimization for educational buildings, with a specific focus on a high school canteen in Nanjing. Through a comparative analysis of optimal energy-saving and lifecycle decarbonization retrofit schemes, the study aims to identify the performance differences and provide practical guidance for retrofitting educational buildings. The optimization process involves two separate single-objective optimizations: one aimed at minimizing annual total primary energy consumption (TES) and the other at minimizing lifecycle carbon emissions (E). Energy performance is simulated using EnergyPlus 23.1.0, while the Strengthened Elitist Genetic Algorithm (SEGA) is applied to optimize design variables such as insulation materials, window types, window-to-wall ratios (WWRs), and photovoltaic (PV) system configurations. The results reveal that the optimal energy-saving scheme achieves zero net energy consumption annually, generating a surplus of 20,625.2 kWh (15.05 kWh/m2). Conversely, the optimal decarbonization scheme achieves zero lifecycle carbon emissions, contributing a carbon reduction of 386,926.4 kg, albeit with a 28.83% higher lifecycle TES compared to the energy-saving scheme. This study underscores the distinctions between energy-saving and decarbonization retrofits and offers valuable insights for sustainable retrofitting of educational buildings in China.
Validation of the Barcelona Magnetic Resonance Imaging Predictive Model for Significant Prostate Cancer Detection in Men Undergoing Mapping per 0.5 Mm-Core Targeted Biopsies of Suspicious Lesions and Perilesional Areas
Authors: Paesano Nahuel , Catalá Violeta , Tcholakian Larisa , Alomar Xavier , Barranco Miguel Ángel , Hernández-Mancera Jonathan , Miró Berta , Trilla Enrique , Morote Juan
Published: January 2025

Background/Objectives: Validation of predictive models (PMs) is crucial to be implemented in new populations or when advances in diagnostic approaches occurred. The aim of this study is to validate the BCN-MRI PM for sPCa when a highly effective prostate biopsy protocol is used. Methods: A prospective cohort of 457 men suspected of having PCa, for whom MRI results were reported with the Prostate Imaging-Reporting and Data System (PI-RADS) v 2.1, underwent a per 0.5 mm-core mapping targeted biopsy of suspicious lesions and perilesional areas, followed by a 12-core-systematic biopsy. These procedures took place between 1 February 2022, and 29 February 2024, at a reference center for prostate biopsy. The individual likelihood of sPCa was assessed through the BCN-MRI risk calculator. Results: The overall sPCa detection rate was 58.3%. The calibration curve of the BCN-MRI PM showed an appropriate accuracy between expected and observed probabilities with a discrimination ability for sPCa yielding an area under the curve (AUC) of 0.862 (95% CI 0.828–0.896) comparable to the AUC of 0.858 (95% CI 0.833–0.883) observed in the development cohort. The application of the BCN-MRI PM provided a net benefit over performing biopsies on all men, avoiding 24.9% of prostate biopsies at 95% sensitivity for sPCa, compared to the 23.7% reduction observed in the development cohort. Conclusions: We conclude that the BCN-MRI PM is ready to be implemented when this biopsy protocol is employed.
The Diverse Pathways for Cell Surface MT1-MMP Localization in Migratory Cells
Authors: Kelly Hannah , Inada Masaki , Itoh Yoshifumi
Published: January 2025

Controlled cell migration is an essential biological process in health, while uncontrolled cell migration contributes to disease progression. For cells to migrate through tissue, they must first degrade the extracellular matrix (ECM), which acts as a physical barrier to cell migration. A type I transmembrane-type matrix metalloproteinase, MT1-MMP, is the key enzyme involved in this process. It has been extensively shown that MT1-MMP promotes the migration of different cell types in tissue, including fibroblasts, epithelial cells, endothelial cells, macrophages, mesenchymal stem cells, and cancer cells. MT1-MMP is tightly regulated at different levels, and its localization to leading-edge membrane structures is an essential process for MT1-MMP to promote cellular invasion. Different cells display different motility-associated membrane structures, which contribute to their invasive ability, and there are diverse mechanisms of MT1-MMP localization to these structures. In this article, we will discuss the current understanding of MT1-MMP regulation, in particular, localization mechanisms to these different motility-associated membrane structures.
Health Preferences in Transition: Differences from Pandemic to Post-Pandemic in Valuation of COVID-19 and RSV Illness in Children and Adults
Authors: Mercon Kerra R. , Rose Angela M. , Cadham Christopher J. , Gebremariam Acham , Pike Jamison , Wittenberg Eve , Prosser Lisa A.
Published: January 2025

Objective: This study aimed to measure changes in preferences regarding health-related quality of life associated with COVID-19 and RSV illness in children and adults from 2021 (during the COVID-19 pandemic) to 2023 (post-pandemic). Methods: A stated-preference survey elicited time trade-off (TTO) values from US adults in spring 2021 (n = 1014) and summer 2023 (n = 1186). Respondents were asked to indicate how much time they would hypothetically be willing to trade from the end of their life to avoid the effects of varying severities of COVID-19 and RSV illness for: (1) children; (2) parents of an ill child (family spillover); and (3) adults. Attitudes relating to COVID-19 vaccination and data on experience with COVID-19 or RSV illness were also collected. The primary outcome measure was the loss in quality-adjusted life years (QALYs). Changes in preferences over the time period from 2021 to 2023 were evaluated using regression analysis. Results: QALY losses increased with disease severity and were highest for Long COVID. Across all COVID-19 and RSV health states, QALY losses associated with child health states were higher than family spillover or adult health states. In the regression analysis, QALY losses reported in the 2023 survey were significantly lower than 2021 QALY losses for COVID-19, but not RSV. Conclusions: Preferences may change over time in a pandemic context and therefore, economic analyses of pandemic interventions should consider the timeframe of health preference data collection to determine whether they are suitable to include in an economic evaluation. Even with the impacts on health-related quality of life attenuated over time, childhood illnesses still had a measurable impact on caregivers’ quality of life.
Implementation of COVID-19 Vaccination in Makwanpur District of Nepal: Readiness and Challenges of a Restructured Health System
Authors: Dahal Aashma , Bhat Neeti , Poudel Bishal , Poudel Safal , Shrestha Roshan
Published: January 2025

This research study explores the readiness, strengths, and challenges of the district health system and local bodies during Nepal’s COVID-19 vaccination program. The primary aim of this study is to identify gaps in the current health system and provide actionable insights for the effective implementation and management of large-scale health programs in the future. A qualitative approach was employed, gathering perspectives of key stakeholders through twelve key informant interviews of stakeholders involved in the planning, management, and execution of the vaccination program in Makwanpur district, the district with the administrative headquarters of Bagmati Province. The study was conducted in the context of Nepal’s transitioning health system following federalization. The qualitative data were analyzed using thematic analysis, guided by the VIRAT2.0 framework for vaccine readiness provided by the WHO. Seven domains from the framework were used to assess readiness and challenges faced by the newly formed health system. The challenges identified by key informants included insufficient logistics and supply chain management, poor coordination between local and higher levels of government, limited awareness about vaccination among the public, vaccine hesitancy, and lack of a robust system for data management and reporting. These findings highlight critical areas for improvement and can be useful evidence to inform the design and implementation of future health programs and policies.
Additive Manufacturing of High-Performance Ti-Mo Alloys Used on a Puncture Needle: The Role of Linear Energy Density in Microstructure Evolution and Mechanical Properties
Authors: Dai Xuesong , Sun Yue , Han Jitai
Published: January 2025

This study involved the preparation of dense Ti-10wt.%Mo alloys using selective laser melting (SLM) with a powder combination of pure titanium (Ti) and pure molybdenum (Mo). Integrating temperature stress numerical simulations and actual data elucidates the correlation between linear laser energy density and residual stress. The impact of linear energy density on the surface roughness, densification behavior, microstructural development, and mechanical properties of SLM-processed Ti-10Mo components was also examined. As linear energy density diminished from 0.125 J/mm to 0.233 J/mm, surface roughness reduced from 18.2 μm to 4.4 μm, while relative compactness increased from 94.9% to 99.8%, respectively. It is necessary to reduce the friction between the puncture needle or implant needle and human tissue, enhancing comfort and precision. The microstructural investigation revealed that SLM-processed Ti-10Mo alloys consist of a phase combination of hexagonal tight-packed (hcp) α-Ti and body-centered cubic (bcc) β-Ti, with heterogeneous conchoidal microstructures found in the samples. Furthermore, as the laser energy input increased, Mo powder particles were mostly fully melted, leading to a significant rise in the microhardness value. The as-built Ti-10Mo alloys exhibited a high ultimate tensile strength of 860 MPa and an elongation of 32.9% at a linear laser energy density of 0.15 J/mm, with the fracture morphology indicating a mixed fracture mode mostly characterized by ductile fracture. This research can enhance the prospective bio-application of Ti-Mo alloys.
Effectiveness of Double Balloon Enteroscopy in the Diagnosis and Treatment of Small Bowel Varices
Authors: Dolu Suleyman , Arayici Mehmet Emin , Onem Soner , Buyuktorun Ilker , Dongelli Huseyin , Bengi Goksel , Akarsu Mesut
Published: January 2025

Background/Aims: Double balloon enteroscopy (DBE) is an innovative method for the diagnosis and management of small bowel (SB) diseases. SB varices are rare disorders, and their diagnosis and treatment can be challenging for clinicians. This study evaluates the use of double balloon enteroscopy (DBE) in diagnosing and treating small bowel varices. Materials and Methods: SB varices were detected in 28 out of 900 double balloon enteroscopy procedures over an 18-year period. Eleven cases of SB varices of various etiologies, diagnosed via DBE, are described. The characteristics of SB varices and endoscopic procedural details were evaluated. Results: A retrospective investigation of 750 patients identified eleven patients (eight males and three females; median age 59 years, range 40–80 years) with small bowel varices. The most common site of SB varices was the jejunum. At least one abdominopelvic surgical procedure had been previously performed on five patients. Endotherapy by DBE was administered to nine patients (seven emergent and two prophylactic). Post-endotherapy, three patients experienced bleeding that required re-endotherapy. Endoscopic therapy for small bowel varices included injection sclerotherapy in eight cases (six with cyanoacrylate and two with polidocanol) and injection sclerotherapy plus hemoclipping in one case. Conclusions: SB varices can present a diagnostic challenge for clinicians. DBE is a valuable tool for both the diagnosis and management of small bowel varices.
Occupational and Physical Therapy Interventions for Young Children with Developmental Central Hypotonia: An Overview of Systematic Reviews
Authors: Paleg Ginny S. , Hidalgo Robles Álvaro , Govender Pragashnie , Livingstone Roslyn W.
Published: January 2025

Developmental central hypotonia describes children with decreased muscle tone due to non-progressive central damage, and includes many genetic conditions (e.g., Down, Prader–Willi or Joubert syndromes etc.), cerebral palsy with hypotonia as the main motor type, developmental delays and congenital hypotonia with favorable outcome. This umbrella review aims to systematically describe the best available evidence for interventions that may be used by early intervention therapists in home and community settings. We conducted electronic searches in PubMed, Medline, CINAHL, EMBASE, EBM Reviews and PEDro during August 2024. Methodological quality and risk-of-bias were rated by all authors, and included reviews were compared and contrasted. Eight systematic reviews (SRs) and two overviews of interventions for children with developmental central hypotonia under 6 years of age were identified through databases and other search methods. Four SRs and one overview evaluated treadmill training, one SR evaluated use of orthotics, another evaluated therapeutic exercise, and two SRs and one overview evaluated a range of occupational and physical therapy interventions. Methodological quality and risk-of-bias of included reviews were variable. Most evidence is related to children with Down syndrome, with few studies addressing children with central hypotonia from other causes. Low-quality (GRADE) evidence supports treadmill training to promote walking onset in children with Down syndrome. Motor, sensorimotor, orthotics, positioning, mobility and infant massage interventions are supported by positive but low- or very-low-quality evidence, and recommendations in favor are all conditional. Primary research on effectiveness of all occupational and physical therapy early interventions for children with developmental central hypotonia from all causes is warranted.
The Spectrum of Cognitive Impairment in Atypical Parkinsonism Syndromes: A Comprehensive Review of Current Understanding and Research
Authors: Jellinger Kurt A.
Published: January 2025

Multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD) are the most common atypical parkinsonism (AP) syndromes. They are clinically characterized by varying combinations of levodopa-poorly responsive parkinsonism, motor, cerebellar, and other signs. They are associated with a wide spectrum of non-motor symptoms, including prominent cognitive impairment such as global cognitive deficits, memory, executive, attentional, visuospatial, language, and non-verbal reasoning dysfunctions. Within the APs, their cognitive functioning is distributed along a continuum from MSA with the least impaired cognitive profile (similar to Parkinson’s disease) to PSP and CBD with the greatest decline in global cognitive and executive domains. Although their pathological hallmarks are different—MSA α-synucleinopathy, CBD, and PSP 4-repeat tauopathies—cognitive dysfunctions in APs show both overlaps and dissimilarities. They are often preceding and anticipate motor dysfunctions, finally contributing to reduced quality of life of patients and caregivers. The present paper will review the current evidence of the prevalence and type of cognitive impairment in these AP syndromes, their neuroimaging, pathogenic backgrounds, and current management options based on extensive literature research. Cognitive dysfunctions in APs are due to disruption of prefronto-subcortical and striato-thalamo-cortical circuitries and multiple essential brain networks. This supports the concept that they are brain network disorders due to complex pathogenic mechanisms related to the basic proteinopathies that are still poorly understood. Therefore, the pathophysiology and pathogenesis of cognitive impairment in APs deserve further elucidation as a basis for early diagnosis and adequate treatment of these debilitating comorbidities.