bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mitigating Salinity Stress in Solanaceae: The Role of Nanoparticles in Seed Germination and Growth Development
Authors: mahmud chinur 
Published: January 2025

Abstract

Salinity is a major challenge affecting agricultural productivity in many regions worldwide. Various approaches have been implemented to mitigate its impact and enhance crop production. This study investigates the application of nanoparticles to improve the growth and development of crops from the Solanaceae family, both individually and in combination with salinity stress. The primary aim is to evaluate the effects of salinity and nanoparticles, specifically titanium dioxide (TiO₂NPs), copper oxide (CuONPs), and zinc oxide (ZnONPs) at 750, 1250, and 1500 mg/kg per seed, respectively, on seed germination and growth performance of tomato, eggplant and pepper plants. The results demonstrated that tomato plants grown under salinity conditions exhibited significant improvements in key traits when treated with CuONPs. The lowest number of aborted flowers was observed under the combined application of salinity and TiO₂NPs, which also enhanced seed production and increased the 1000-seed weight. For eggplants, the combination of salinity with CuONPs and ZnONPs positively influenced plant characteristics, with CuONPs applied individually also showing notable effects. In contrast, control plants displayed the lowest values for all measured attributes in both tomatoes and eggplants. For pepper plants, ZnO nanoparticles applied individually were the most effective in improving plant traits. The application of CuONPs significantly reduced the number of aborted flowers and enhanced seed and mean daily germination rates. However, under salinity stress, pepper plants recorded the lowest values for most growth parameters. These findings suggest that the strategic use of nanoparticles under salinity conditions can support sustainable agriculture by enhancing the growth and productivity of vegetable crops, offering valuable solutions for farmers and growers facing salinity challenges.
Association between sphericity and ventricular function in fetuses of diabetic mothers: A longitudinal study from the fetal to neonatal period.
Authors: Sabry Ayman F. , Evers Patrick D. , Madriago Erin J. 
Published: January 2025

Abstract

Background: The impact of maternal diabetes on the fetal heart is complex and not fully understood.
Objective: The study aimed to investigate how differenttypes and stages of maternal diabetes affect fetal heart function and ventricular remodeling during prenatal and postnatal periods.
Methods: The study included 45 pregnant women with diabetes and 15 with uncomplicated pregnancies. Fetal echocardiograms were performed between 28-32 weeks of gestation using different techniques to assess cardiac function. Measurements of ventricular transverse and longitudinal diameters, as well as the sphericity index, were determined. Postnatal follow-up echocardiograms were also performed.
Results: The diabetic pregnant group was divided into three subgroups: 15 with GDM and 30 with PGD, including 15 well-controlled and 15 uncontrolled cases. The E and E/A ratio values for the mitral and tricuspid valves were significantly lower in fetuses and neonates affected by diabetes compared to the healthy group. The Tei Doppler index for the left ventricle was significantly higher in pregnancies affected bydiabetes, affecting both fetuses and neonates. The right ventricle exhibited significant differences in all groups of diabetic pregnancies in fetuses and postnatally in cases of pregestational diabetes. The sphericity index differed significantly in all fetal diabetic groups and in neonates compared to controls, except for the LV in the GDM cohort. Postnatally, the sphericity index of the RV increased compared to fetal values, while the LV sphericity index remained unchanged.
Conclusion: Maternal diabetes mellitus affects fetal cardiac function and structure, which may continue into the early days of life.
Identification of pancreatic nonfunctional neuroendocrine tumors and solid pseudopapillary tumors via the construction of a consensus clustering model based on enhanced CT images
Authors: Zhang Wuyang , Cheng Peng , Cao Wei , Wang Min , Wang Bin , Shi Dan , Li Jingyu , Wei Wei 
Published: January 2025

Abstract

Background: Unsupervised clustering has played a greater role in the diagnosis and differential diagnosis of pancreatic tumors in recent years. This study aimed to investigate the value of constructing a c[1]lustering model for unsupervised learning based on enhanced CT to identify pancreatic nonfunctional neuroendocrine tumors (NF-pNETs) and solid pseudopapillary tumors (SPTs).
Methods: 45 patients with SPTs and 47 patients with NF-psNETs were retrospectively analyzed. The data were randomly divided into a training set and a validation set at a ratio of 7:3. One-way logistic regression was performed for each clinical variable to assess its relationship with the clustered labels, and a logistic regression model was fitted with the clustered labels as the dependent variable and the clinical variables as independent variables. Variables with P values <0.1 were selected for further analysis. Multifactorial logistic regression models were fitted via the clinical variables selected in the univariate analysis, ridge regularization (L2 penalty) was used to prevent overfitting and address potential multicollinearity, with the strength of regularization (alpha) set to a default value of 1. Clinical variables that were meaningful in the multifactorial logistic regression analyses were used to construct the final logistic regression model, which was used to predict individual clinical-based group labeling on the basis of individual clinical characteristics. For imaging, the optimal number of clusters k selected by the covariance coefficient was used to build the clustering model via unsupervised classification of the lesions through consensus clustering analysis fusing the imaging histological features of arterial-phase, venous-phase, and delayed-phase images. The clinical factors with a final p value < 0.2 were subsequently combined with the clustering model to perform stepwise multivariate logistic regression analyses, thereby establishing a joint model. The performance of the three models was assessed via AUC values, and column line plots were generated to visualize the models. Finally, the clinical validity of the models was assessed via decision curve analysis (DCA).
Results: The AUCs of the clustered and clinical models were 0.70 and 0.74 (95% CI: 0.66–0.81) in the training set and 0.65 and 0.75 (95% CI: 0.64–0.87) in the validation set, and the AUCs of the training and test sets in the joint model were 0.88 (95% CI: 0.81–0.94) and 0.85 (95% CI: 0.71–0.96), respectively. Decision curve analysis revealed that the joint clinical-clustering model had a greater net benefit when the high-risk threshold probability was in the range of 0--1.
Conclusions: Unsupervised clustering models based on enhanced CT have potential for discriminating between SPTs and NF-PNETs, which can inform clinical decision-making.
Higher aphid infestation in the alleys of organic apple orchards compared to IPM during fruit setting in eastern Germany
Authors: Niyibizi Ingrid Aline Bapfubusa , Schnerch Benjamin , Djoudi El Aziz , Birkhofer Klaus 
Published: January 2025

Abstract

Apple is a major fruit crop worldwide and the most produced fruit in Germany. However, apple orchards face persistent threats from aphid infestations, which can severely compromise fruit yields. In this study we compared aphid infestation levels in commercial apple orchards under organic and Integrated Pest Management (IPM) at three stages of the apple growing season: fruit-setting, fruit-growing and post-harvest, and in two habitats. We sampled eight organic and eight IPM apple orchards in eastern Germany using standardised canopy beating of apple trees and suction sampling in the orchard alleys. Our results indicate no significant differences in canopy aphid infestation between organic and IPM orchards. However, aphid communities in the tree canopy of organic orchards exhibited greater evenness across species compared to IPM orchards. Eriosoma lanigerum consistently dominated the aphid community of the tree canopies in both management systems, highlighting the need for targeted management practices for this pest. Aphid community structure varied significantly across sampling periods in the canopy and orchard alleys. Differences between organic and IPM orchards were observed during the fruit-setting phase in orchard alleys, with higher levels of infestation in organic orchards. Species such as Macrosiphum euphorbiae, Dysaphis spp., Aphis spiraecola, and Rhopalosiphum insertum contributed to these differences. Our findings provide a better understanding of the temporal dynamics of aphid communities in commercial apple orchards and highlight the importance of pest management strategies that consider different habitats and periods.
A Hybrid Prediction Method for Conducted EMI in AC-DC Power Converter
Authors: Xu Zhoujiang , Shu Liang , Jiang Min , Deng Yijian , Wang Chuanqi , Zhou Yongxing 
Published: January 2025

Abstract

This paper proposes a hybrid prediction method for the conducted electromagnetic interference (EMI) of AC-DC power converter. Under this method, the equivalent EMI model of AC-DC converter system is established to separate interference source and conduction path in the converter. For the front stage rectifier with T type topology, a topology simplification method is applied to develop a time-domain model of the interference source with consideration given to variable slope characteristics and ringing effects. When modeling DC-DC converter stage, main interference source in time domain is built from the perspective of capacitor charging and discharging. Experimental verification is performed to obtain the results that are consistent with the analytical results obtained by using the proposed modeling method. Furthermore, frequency-domain prediction techniques are applied to forecast the conducted EMI of the converter. Finally, a comprehensive comparison is performed with other prediction method to demonstrate the advantage of this hybrid prediction method in accuracy, simulation speed and convergence.
A New Classification Method of Surrounding Rock Quality for Phyllite Tunnels under the Condition of Layer Orientation Parallel to the orientation of tunnel Axis
Authors: Yang Jing , Wu Chengfeng , Zeng Rui , Wang Ping , Lu Yupeng , Man Hao , Wang Jingyong , Ji Feng 
Published: January 2025

Abstract

Surrounding rock classification is a critical factor in evaluating tunnel stability, determining construction methods, and selecting support parameters. Various engineering sectors utilize different methods for grading tunnel surrounding rock quality. The HC method iswidely adopted in the hydropower industry for this purpose. However, due to the anisotropy of layered phyllite, the classification results obtained using the HC method for phyllite tunnels—when the layer orientation is parallel to the tunnel axis-differ significantly from those based on actual field investigations. This study conducted uniaxial compression tests on rocks, revealing that layered phyllite exhibits notable anisotropy at bedding angles of 0°, 45°, and 90°. The compressive strength follows a V-shaped trend as the angle between the bedding and loading orientations changes, while the deformation modulus decreases linearly with increasing angular deviation between the loading orientation and tunnel axis. Numerical simulations were performed to observe tunnel deformation at various bedding-to-tunnel axis angles. Results showed that, as the bedding angle decreases, deformation of the tunnel wall and crown increases progressively. At angles of 0°, 30°, 45°, 60°, and 90°, the deformation ratios for the tunnel wall were 1:3.7:3:4.74:5.44:7.7, and for the tunnel crown, the ratios were 1:1.3:1.94:4.7:6.7. When the traditional HC method was used to classify the surrounding rock in tunnels with parallel phyllite layers, the agreement rate was only 13.33%, indicating low accuracy. By modifying the occurrence score for major structural joints and incorporating the weight ratios derived from numerical simulations, the HC method’s accuracy improved, achieving an agreement rate of 100%. This study enhances the precision and applicability of surrounding rock classification and offers valuable insights for tunnel construction.
Efficacy and safety of endoscopic versus robotic axillary lymph node dissection in patients with node-positive breast cancer: a comparative retrospective study
Authors: Wu Zhijie , Li Zongyan , Chen Zuxiao , Fu Xiaoyan , Huang Ze , Luo Yunxiang , Liu Qiwen , Li Haiyan 
Published: January 2025

Abstract

Background.
Robotic surgery for breast cancer is increasingly being adopted, but the evidence on its effectiveness and safety remains limited. This study aimed to compare the surgical quality and short-term outcomes of robotic and endoscopic axillary lymph node dissection in patients with node-positive breast cancer. Here we report the short-term outcomes of this trial.
Methods.
This single-center retrospective study compared the short-term efficacy and safety of endoscopic (E-ALND) and robotic (R-ALND) axillary lymph node dissection in patients with node-positive breast cancer. Patients were recruited from those who underwent surgery at the Sixth Affiliated Hospital of Sun Yat-sen University between January 2022 and October 2024. Clinical and pathological characteristics, surgical outcomes, and postoperative complications were analyzed.
Results
The study included 56 patients, with 29 undergoing E-ALND and 27 undergoing R-ALND. The R-ALND group had significantly shorter surgical times (43.37 ± 12.40 min vs. 60.10 ± 19.37 min, p < 0.001) and lower mean blood loss (3.26 ± 2.40 ml vs. 9.24 ± 4.29 ml, p < 0.001). Postoperatively, the R-ALND group had better upper limb function and sensation, with significantly lower DASH scores at 1-month (10.87 ± 1.35 vs. 14.64 ± 3.49, p < 0.001) and 3-month (6.68 ± 1.86 vs. 9.24 ± 2.74, p < 0.001) follow-ups. The R-ALND group also had fewer postoperative complications, including a lower incidence of reduced sensation, burning sensation, and numbness in the upper limb.
Conclusion
Compared with E-ALND, R-ALND significantly reduces intraoperative bleeding and postoperative complications, resulting in better upper limb function and sensation. These findings suggest that R-ALND may offer superior clinical outcomes for patients undergoing axillary lymph node dissection for breast cancer.
The Effect of Neuromuscular Combined with Biomechanical Scapular Stabilizer Muscle Corrective Exercises on Upper Crossed Syndrome in Chinese Secondary School Students: A Randomized Controlled Trial
Authors: Hu Xuanming , Bao Guiying , Quan Xi , Wang Kai 
Published: January 2025

Abstract

Background and Objectives
Upper crossed syndrome (UCS), characterized by poor posture, neck pain and Functional disability, is a prevalent issue among youth. This study aims to evaluate the effects of neuromuscular combined with biomechanical exercise (NCBE) on UCS among secondary school students and compares its outcomes with biomechanical exercise (BE) alone.
Methods
Forty-five male secondary school students (aged 15–18) were divided into three groups: NCBE (n=15), BE (n=15), and a control group (n=15). The NCBE group underwent combined neuromuscular and biomechanical exercise, the BE group performed biomechanical exercise only, and the control group participated in regular physical activities. Interventions were conducted three times a week for eight weeks. Outcome measures, including Forward Head Angle (FHA), Rounded Shoulder Distance (RSD), Neck Disability Index (NDI), Visual Analog Scale (VAS) scores, and scapular muscle strength (Middle Trapezius (MT), Lower Trapezius (LT), Serratus Anterior (SA) ), were assessed at baseline, week 4, and week 8.
Results
Within-group comparisons: Both BE and NCBE groups showed significant improvements in all measures by week 4 compared to baseline (p<0.05), with further improvements by week 8 (p<0.05), while the control group showed no significant changes (p>0.05).
Between the group comparisons: Both BE and NCBE groups had better outcomes than the control group at weeks 4 and 8 (p<0.05). NCBE group showed superior results compared to the BE group only in the strength of MT, LT and SA (p<0.05) in week 4. NCBE group showed superior results compared to BE in FHA, NDI, VAS and the strength of MT, LT and SA (p<0.05), except for RSD (p>0.05) at week 8.
Conclusion
Both NCBE and BE are effective in alleviating UCS symptoms in Chinese secondary school students. However, NCBE demonstrates superior treatment effects compared to BE across multiple outcome measures, offering a promising and cost-effective therapeutic option. Additionally, regular physical activity is ineffective in treating UCS.
Optimal Planning and Decision-Making for Hybrid Microgrids: Integrating Diverse Renewable Sources with Battery Systems
Authors: Alyahya Saleh , Zaky Alaa A. , Yousif Bedir , Dawoud Samir M. 
Published: January 2025

Abstract

Microgrids as modern power system facilities must be optimally designed to secure their efficient techno-economic feasibility. The uncertainty in renewable energy and electricity demand growth which can be managed by appropriate design and demand-side management methods. In this research work, a hybrid microgrid comprising 3rd generation Perovskite Solar Cells / Wind Turbines / Micro turbines and battery system is modeled in Homer Pro software 3.14.2 to determine the optimal decisions for different demand-side management cases. Furthermore, the Perovskite Solar Cells devices were fabricated and experimentally examined and integrated to microgrid under investigation. This paper investigates the techno-economic modeling and optimization-based demand-side management of microgrids to maintain the load demand of a rural community on the coast of Aswan, Egypt. Various load demand scenarios involving baseloads without demand-side management, with loads shifting-based demand-side management, and with combined loads shifting and peak clipping-based demand-side management, are implemented, including their impacts on the microgrids' cost, reliability, and emissions are evaluated and compared. The design objective is to minimize the levelized cost of energy subject to various operational constraints based on Homer Pro software. The results have indicated a significant reduction in the Perovskite Solar Cells output power (89.0 kW) with Case-1(base load). While applying Case-2 (demand-side management based on loads shifting technique) the power reduced to 78.9 KW. Added to that the implementing of Case-3 (demand-side management based on loads shifting and loads clipping techniques) the power reduced to 77.6 KW. The results revealed that at Case-2 the demand side management was able to attain an attractive reduction of cost of energy by 14% in comparison with Case-1. Moreover, emissions at Case-3 decreased by 15% in comparison with Case-1. Finally, the proposed approach is to assist decision-makers to provide costs- effective and emissions-conscious planning for microgrids efficiently.
MH-YOLO: A Lightweight Traffic Sign Detection Method Based on YOLOv10n with Hybrid Attention Transformer and Multi-Scale Dilated Attention
Authors: Zhang Yifeng , Ma Haifei , Zhang Canlong , Wang Zhiwen , Li Zhixin 
Published: January 2025

Abstract

In intelligent transportation systems, the accurate and real-time detection and recognition of traffic signs are crucial for autonomous and assisted driving. Despite improvements in efficiency and accuracy of existing deep learning object detection algorithms, challenges remain in detecting small objects, handling multi-scale targets, and achieving real-time detection in low computational resource environments. To address these challenges, we propose a lightweight YOLOv10n-based method that incorporates a Hybrid Attention Transformer (HAT) to enhance the super-resolution reconstruction of small targets, thereby improving detection accuracy. Additionally, we introduce a Multi-Scale Dilated Attention mechanism (MDA), embedded within the YOLOv10n model to capture multi-scale semantic information through self-attention mechanisms, effectively enhancing the model's detection performance. The proposed method, termed MH-YOLO, significantly improves detection effectiveness while maintaining low computational complexity. Furthermore, to address the lack of nighttime traffic sign data and region-specific sign data in existing datasets, we constructed the Chinese Traffic Sign Dataset (CTSDB), covering all time periods and various complex scenarios. Experimental results show that MH-YOLO achieves detection accuracy comparable to more complex models while maintaining model lightweightness.
Knowledge, Attitudes, and Practices of Women and Men Towards Infertility: A Scoping Review
Authors: Mabitsela Vangile Naney , Musie Maurine Rofhiwa , Sepeng Nombulelo Veronica 
Published: January 2025

Background
Infertility is a serious concern with emotional and medical implications, affecting millions of couples worldwide. Despite its prevalence, there are still misconceptions and a lack of knowledge and awareness surrounding infertility.

Objectives
The objective of this review is to synthesize the existing literature on knowledge, attitudes, and practices of men and women towards infertility.

Methods
The scoping literature review followed the Arksey and O’Malley’s framework, which included formulating the research question, locating relevant studies, selecting studies, charting data, and synthesizing the results. The databases used were MEDLINE, Africa-Wide Information, Academic Search Complete, Family & Society Studies Worldwide, CINAHL, APA PsycInfo and Google Scholar. Thematic analysis was utilized to analyse the findings of this review.

Results
Twelve studies were included in this scoping review. The analysis of these studies produced six themes: women’s concerns regarding infertility, lack of knowledge and awareness regarding infertility, different types of educational information on reproductive health, attitudes towards infertility, practices related to infertility and gender-based treatment, responsibilities, and consequences of infertility.

Conclusion
The review revealed that men and women consulting in healthcare facilities reported several misunderstandings and information gaps regarding infertility. Regarding attitude, the review found that most men and women demonstrate a positive attitude towards infertility as a disease and regarding the use of fertility drugs for conception. Furthermore, the review found that most men were willing to adopt necessary lifestyle and health practices to enhance or improve their fertility. The use of alternative therapy was also a prominent healthcare option amongst most men and women. Lastly, infertility has been known to cause marriages into divorce or polygamy.
The results highlight the need for better healthcare to properly treat infertility. Furthermore, the review identified the need for education programs to address the stigma and misconceptions associated with infertility.