bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring Machine Learning Algorithms for Predicting Early Antenatal Care Initiation at First Trimester among Reproductive Women in Nigeria
Authors: Sani Jamilu , Ahmed Mohamed Mustaf , Oluyomi Alabi Olatunji 
Published: November 2024

Abstract

Background
Early antenatal care (ANC) initiation during the first trimester is crucial for maternal and child health outcomes. However, in Nigeria, early ANC uptake remains low due to socioeconomic and cultural barriers. Traditional statistical models used to predict ANC initiation often fail to capture the complex nonlinear interactions between predictors. This study applies machine learning (ML) algorithms to predict early ANC initiation using data from Nigeria’s 2018 Demographic and Health Survey (NDHS).
Methods
This cross-sectional study utilized NDHS 2018 data and six ML algorithms: Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree, Random Forest (RF), and XGBoost. The synthetic minority oversampling technique (SMOTE) was used to address data imbalance. The models were evaluated using metrics, such as accuracy, precision, recall, and AUROC values. Feature importance was assessed using the permutation importance and Gini impurity methods.
Results
The Random Forest model demonstrated the best performance, achieving the highest accuracy (77%), precision (75%), recall (80%), and AUROC value of 0.77. This model effectively identified key predictors of early ANC, including education level, wealth index, and place of delivery, with educated and wealthier women being more likely to seek early care. Feature importance analysis revealed significant sociodemographic and geographic disparities, highlighting the critical role of economic resources and healthcare accessibility in influencing ANC behavior.
Conclusion
ML models, particularly Random Forest, provide an effective approach for predicting early ANC initiation, offering comprehensive insights beyond traditional methods. These findings underscore the need for targeted interventions focusing on education, economic empowerment, and healthcare access to enhance early ANC uptake among Nigerian women.
Milligan–Morgan hemorrhoidectomy combined with rubber band ligation and polidocanol foam sclerotherapy for the management of grade III/IV hemorrhoids: A retrospective study
Authors: Long Qing , Wen Yong , Li Jun 
Published: November 2024

Abstract

Background
Hemorrhoids are one of the most common and annoying benign diseases in the field of colorectal surgery. A Milligan–Morgan hemorrhoidectomy (MMH) is the most frequently applied surgical technique due to its clear efficacy and high success rate, but the reported postoperative complications remain a major problem. This study aimed to retrospectively evaluate the efficacy and safety of a MMH combined with rubber band ligation and polidocanol foam sclerotherapy (MMH + RBL + PFS) for the management of grade III/IV hemorrhoids.
Methods
This was a single-center retrospective study. A total of 255 patients with grade III/IV hemorrhoids who underwent MMH + RBL + PFS (n = 128) or MMH (n = 127) between May 2022 and June 2023 were included in the study. The primary outcomes included recurrence rates, hemorrhoid severity score (HSS), and patient satisfaction 12 months after surgery. Secondary outcomes included intraoperative outcomes and postoperative outcomes.
Results
Follow-up was conducted by telephone or outpatient visit 12 months after surgery. The recurrence rate was lower in the MMH + RBL + PFS group than in the MMH group (p < 0.05). The patient satisfaction score was higher in the MMH + RBL + PFS group than in the MMH group (p < 0.05), and there was no significant difference in the HSS between the two groups (p > 0.05). The median operation time in the two groups was similar (16 min (15–20 min) vs.16 min (15–18 min), p > 0.05). The median number of incisions in the the MMH + RBL + PFS group was 3 (2–3), while that in the MMH group was 3 (3–4) (p < 0.05). There was no significant difference in intraoperative blood loss between the two groups (p > 0.05). Visual analog scale pain scores were lower in the MMH + RBL + PFS group than in the MMH group at the first postoperative defecation at 12 h and at 1, 3, and 7 days (all p < 0.05). The wound healing time was shorter in the MMH + RBL + PFS group than in the MMH group (27.62 ± 3.74 vs. 28.73 ± 4.48 days, respectively, p < 0.05). The incidence of urinary retention was lower in the MMH + RBL + PFS group than in the MMH group (5.47% vs. 12.60, respectively, p < 0.05). Nine patients (one case in the MMH + RBL + PFS group and eight cases in the MMH group (p < 0.05)) had delayed bleeding and were successfully controlled with manual compression or surgical hemostasis. No cases had anal stenosis in the MMH + RBL + PFS group, and six cases had it in the MMH group, all with mild anal stenosis and successfully treated by dilatation alone (p < 0.01). No incision infection or anal incontinence occurred in either group.
Conclusions
Compared with the MMH, the MMH + RBL + PFS surgical procedure is safe and effective for grade III/IV hemorrhoids, which is associated with a lower recurrence rate, a higher patient satisfaction score, a lower postoperative pain score, fewer postoperative complications, and a shorter wound healing time.
Success of salivary gland fine-needle aspiration cytology is depending on various lesion- and sampling-related factors
Authors: Mayer Marcel , Alfarra Mohammad Marwan , Möllenhoff Kathrin , Engels Marianne , Arolt Christoph , Quaas Alexander , Wolber Philipp , Jansen Louis , Nachtsheim Lisa , Grosheva Maria , Klussmann Jens Peter , Shabli Sami 
Published: November 2024

Abstract

Purpose. Ultrasound-guided fine-needle aspiration cytology (FNAC) is a widely used diagnostic procedure which facilitates the differentiation of salivary gland lesions. Although the performance of salivary gland FNAC (SG-FNAC) has improved since the introduction of the Milan System for Reporting Salivary Gland Cytopathology (MSRSGC), the range of the reported performance is still wide. Therefore, the aim of this study was to determine lesion- and sampling-related factors that influence the success of SG-FNAC.
Methods. All SG-FNAC cases performed in a tertiary referral hospital between September 1st, 2011, and August 31st, 2022, were retrospectively identified. Demographic, histopathological, lesion-specific, and sampling-related data were retrieved from the clinical charts. Cytopathological reports were categorized according to the MSRSGC. The risk of malignancy (ROM), the performance measures, and factors influencing the success of SG‑FNAC were calculated.
Results. Overall, 1,289 cases with histopathological follow-up diagnosis (out of 1,952 SG-FNACs) were included. The ROM was: non-diagnostic = 23.9%, non-neoplastic = 4.4%, atypia of undetermined significance (AUS) = 34.5%, neoplasm-benign = 1.0%, neoplasm‑salivary gland neoplasm of uncertain malignant potential (SUMP) = 15.3%, suspicious for malignancy = 74.1%, malignant = 96.2%. The sensitivity, specificity, accuracy, positive, and negative predictive value for differentiating benign from malignant lesions (excluding lesions categorized as AUS and SUMP) were 87.5%, 97.7%, 96.3%, 85.0%, and 98.1%, respectively. A larger lesion size (OR (95% CI) =1.21 (1.06-1.39), p = 0.004), a higher number of obtained slides (OR (95% CI) = 1.31 (1.17-1.46), p < 0.001), and the physician performing the FNAC (p = 0.047) were independent predictors for a higher success, while localization of the lesion within the submandibular compared to the parotid gland (OR (95% CI) = 0.38 (0.19-0.77), p = 0.008) was an independent predictor for lower success of SG-FNAC.
Conclusion. This is the largest single-center study evaluating SG-FNAC performance to date. It identified independent lesion- and sampling-related factors influencing the success of SG‑FNAC. Knowledge of those can improve performance of the procedure.
Experimental study of extracorporeal shock wave therapy for periprosthetic osteolysis induced by wear particles
Authors: Zhao Fengnian , Chen Yufei , Dong Ao , Song Keguan 
Published: November 2024

Abstract

Extracorporeal shock wave therapy (ESWT) is a conservative orthopedic treatment that has been shown to be effective in a variety of orthopedic diseases; however, its effectiveness in addressing sterile prosthesis loosening remains uncertain. This study aimed to establish a model of periprosthetic osteolysis and to assess the impact of ESWT on osteolysis induced by wear particles. The findings indicated that the group receiving ESWT exhibited an increase in bone mineral density, alongside a reduction in the extent of osteolysis, the quantity of osteoclasts, and serum levels of IL-1β. Consequently, we conclude that ESWT significantly diminishes inflammatory factor levels, inhibits the development of periprosthetic osteoclasts, and effectively slows the progression of osteolysis, thereby presenting substantial clinical relevance.
Mangroves and their services are at risk from tropical cyclones and sea level rise under climate change
Authors: Hülsen Sarah , Dee Laura , Kropf Chahan , Meiler Simona , Bresch David 
Published: November 2024

Abstract

Climate change is expected to alter the frequency and intensity of extreme events, modifying the natural disturbance regimes to which ecosystems are currently adapted. Here, we present a spatially explicit risk index for mangroves and their associated biodiversity and ecosystem services based on projected frequency changes of tropical cyclone wind speeds and rates of relative sea level rise under SSPs 245, 370 and 585 by 2100. Globally, approximately half of the total mangrove area (40-56% depending on the SSP) will be at high to severe levels of risk due to climate-modified tropical cyclone disturbance regimes. Further, we find mangrove areas with high levels of biodiversity and ecosystem services provision, including coastal protection for people and assets, carbon sequestration, and fishery benefits, are at proportionally higher levels of risk than mangrove forests generally. Our findings emphasize the need to anticipate changes in natural disturbance regimes and to adapt ecosystem management to sustain ecosystem services in the future.
Analysis of clinical audiology characteristics in children with Williams syndrome in China
Authors: LI Fangfang , XU Bin , SHEN Jiyang , CHEN Weijun , GUO Junxia , YAO Dan , SHAO Jie , JI Chai 
Published: November 2024

Abstract

Background
Williams Syndrome (WS) is a neurodevelopmental disorder caused by microdeletion on chromosome 7. Hearing loss (HL) is common in this population but is rarely taken seriously. Previous studies had small sample sizes and mixed conclusions, and few studies have investigated HL in children with WS.
Objectives
To investigate audiological characteristics of children with WS, analyze the influence factors, and to provide scientific basis for further improvement of ear and hearing care in children with WS.
Methods
WS followed up between June 2020 to June 2024 were underwent a series of audiological examinations such as tympanogram, distortion product otoacoustic emission (DPOAE), auditory brainstem response (ABR) and pure-tone audiometry (PTA), to analyze the audiological characteristics of WS at different ages, and their difference with control group.
Results
The passing rate of tympanogram and DPOAE in WS was significantly decreased when compared with control group (p < 0.05), and these differences were found in all age groups. The lower DPOAE passing rate still remain after the tympanogram abnormal data were excluded. The SNR of 2000-5000Hz were statistically lower in children with WS after tympanogram, DPOAE abnormal data were excluded. No significant difference was found in the passing rate of tympanogram and DPOAE of the 25 subjects after 1–2 years. Threshold of ABR in WS was higher than control group. The latency of wave Ⅰ, Ⅲ and the interpeak latency Ⅰ-Ⅲ in WS were significantly longer (p < 0.05), and the interpeak latency Ⅲ-Ⅴ was significantly shorter than that in control group (p < 0.05). 50% of WS was assessed as HL by PTA, with conductive HL in 60%, sensorineural HL in 20% and mixed HL in 20%, most were mildly. The threshold of 250-8000Hz in WS group were significantly higher than that in control group (p < 0.05), either in air or bone conduction.
Conclusions
This study found that children with WS generally had abnormal functions of the middle ear and inner ear, accompanied with HL, or subclinical cochlear active mechanism dysfunction, and it can occur as early as before 3 years. Prolonged ABR latency suggests delayed myelination of auditory nerve. The shortened Ⅲ-V interval may be an electrophysiological marker in this population. It is recommended to carry out long-term and regular hearing follow-up for this population in order to detect HL early and treat diseases that may contribute to HL in time.
GSS-YOLO: Vehicle detection method and embedded deployment in complex traffic road scenarios
Authors: Lu Shengning , Ren Zhihao , Zhi Yan , Wang Xinhua , Yu Xu , Liang Yong 
Published: November 2024

Abstract

In real-world vehicle detection scenarios, numerous complex and highly uncertain factors, including variations in lighting, motion blur, occlusion, and weather conditions, can significantly impact performance. Autonomous driving and intelligent traffic systems must be able to respond quickly to various traffic situations. In order to reduce the impact of these uncertainties in actual scenarios and improve the accuracy of vehicle detection in complex backgrounds, we propose a new YOLO detector GSS-YOLO based on YOLOv5s. First, in order to reduce the amount of calculation while improving the performance of model detection and maintaining detection accuracy, we replaced all Conv convolutions in the neck with GSConv convolutions. Secondly, in order to reduce the sequence length and reduce the computational complexity while increasing to improve the receptive field of the model and improve feature extraction capabilities, we embed the Swin-Transformer attention mechanism into the C3 module. Finally, in order to increase the model's ability to handle small objects that are difficult to detect or objects in complex backgrounds, we use the FocalModulation module to replace the original fast spatial pyramid pooling module. Compared with traditional YOLOv5s, our method reduces model parameters by 21.21% and GFLOPS by 20.88%. GSS-YOLO can increase mAP by 4.2% and accuracy by 5.5% on the challenging vehicle detection data set UA-DETRAC. We deployed the GSS-YOLO algorithm on the Atlas200DK A2 embedded system. After testing, it can achieve an FPS of 37.04 when the accuracy is only reduced by 0.3, meeting the requirements of real-time detection.
DT-GCNN: Dynamic Triplet Network with GRU-CNN for Enhanced Text Classification
Authors: Li Jiahui , Yang Yuan , Sun Jian , Wang Fen , Chen Shuailiang 
Published: November 2024

Abstract

Text classification is a crucial task in natural language processing, and deep learning models have demonstrated exceptional performance in this domain. However, many deep neural network models struggle to handle complex and imbalanced datasets, and their adaptability across multiple scenarios remains limited. To tackle these challenges, this paper proposes DT-GCNN, a model that integrates GRU for capturing sequence information and CNN for extracting local features. Furthermore, the model incorporates an adaptive soft-margin triplet loss function that dynamically adjusts triplet margins, thereby enhancing the learning quality of the embedding space. During the training process, intelligent algorithms are periodically employed to dynamically reconstruct triplets, thereby enhancing the model's generalization capability. This study conducts extensive experiments on eight datasets from various categories. The results demonstrate that DT-GCNN outperforms most existing baseline models, showing notable superiority in handling complex and imbalanced category tasks. The proposed method also significantly enhances generalization ability and stability, exhibiting excellent performance across diverse datasets.
Bridging the Gap with Convolutional networks: A Graph-based Vision Transformer with Sparsity for Training on Small Datasets from Scratch
Authors: Shan Dongjing , Li Jin , Zhong Lisha , Qu Biao , Han Qi 
Published: November 2024

Abstract

Vision Transformers (ViTs) have achieved impressive results in large-scale image classification. However, when training from scratch on small datasets, there is still a significant performance gap between ViTs and Convolutional Neural Networks (CNNs), which is attributed to the lack of inductive bias. To address this issue, we propose a Graph-based Vision Transformer (GvT) that utilizes graph convolutional projection and graphpooling. In each block, queries and keys are calculated through graph convolutional projection based on the spatial adjacency matrix, while dot-product attention is used in another graph convolution to generate values. When using more attention heads, the queries and keys become lower-dimensional, making their dot product an uninformative matching function. To overcome this low-rank bottleneck in attention heads, we employ talkingheads technology based on bilinear pooled features and sparse selection of attention tensors. This allows interaction among filtered attention scores and enables each attention mechanism to depend on all queries and keys. Additionally, we apply graphpooling between two intermediate blocks to reduce the number of tokens and aggregate semantic information more effectively. Our experimental results show that GvT produces comparable or superior outcomes to deep convolutional networks and surpasses vision transformers without pre-training on large datasets. The code for our proposed model is publicly available on the website: GitHub/GvT.
Effect of using safely managed drinking water services on child diarrhoea
Authors: Greenwood Esther E. , Freymond Mathilda , Scheidegger Andreas , Lauber Thomas , Tussupova Kamshat , Pickering Amy J. , Julian Timothy R. 
Published: November 2024

Abstract

Diarrhoeal disease remains a leading cause of mortality in children under five in low- and
middle-income countries (LMICs) (1). Universal access to safe drinking water, as called for
under Sustainable Development Goal 6, is often motivated by perceived health benefits with a
historical focus on achieving diarrhoeal disease reductions (2). Here, we show through
structural causal modelling that household use of safely managed drinking water services
(SMDWS) significantly reduces risks of diarrhoea in children under five compared to the use
of drinking water services not fulfilling all of the SMDWS criteria (Relative risk (RR)= 0.90,
95% CI= 0.83-0.98) and services classified as less than basic (RR=0.87, 95% CI=0.78-0.97)
across 24 LMICs. Secondary analyses point towards contributions of drinking water
availability and fecal contamination at the point of use to risks of child diarrhoea. Specifically, risk reductions of between 4-6% were observed with every 1-log10 decrease in E. coli
contamination in stored drinking water. Our findings reaffirm the importance of SMDWS in
protecting against diarrhoeal disease, while suggesting that achieving universal access will
provide only modest additional reductions in child diarrhoea in LMICs. Further reductions will require
Distribution of glutathione peroxidase-1 immunoreactive cells in pancreatic islets from type 1 diabetic donors and non-diabetic donors with and without islet cell autoantibodies is variable and independent of disease
Authors: Pala Kaaj , Sun Kevin Xueying , Krogvold Lars , Dahl-Jørgensen Knut , Reddy Shiva 
Published: November 2024

Abstract

During type 1 diabetes (T1D), oxidative stress in beta cells may cause early dysfunction and initiate autoimmunity. Mouse islets express lower levels of reactive oxygen species (ROS) clearing enzymes, glutathione peroxidase (GPX), superoxide dismutase (SOD) and catalase in comparison with several other tissues. It remains unclear if human beta cells show a similar deficiency, particularly during T1D or show a higher degree oxidative resistance. We compared islet cell distributions and determined graded intensities of glutathione peroxidase1 (GPX1), a key enzyme which detoxifies hydrogen peroxide, by applying combined immunohistochemistry for GPX1, insulin and glucagon, in pancreatic sections from new-onset T1D (group 1), non-diabetic autoantibody-negative (group 2), non-diabetic autoantibody-positive (group 3) and long-term diabetic (group 4) donors. Islets from all study groups demonstrated either uniform but graded staining intensities for GPX1 in almost all islet cells or strong staining in selective islet cells with weaker intensities in the remaining cells. GPX1 was present in selective glucagon and in insulin cells also and in cells negative for both hormones, with stronger intensities in a higher percentage of glucagon than insulin cells. The enzyme was absent in a higher percentage of beta cells than glucagon cells independent of disease or autoantibody positivity. We conclude that a proportion of human beta cells and glucagon cells express GPX1 but show heterogeneity in its distribution and intensities, independent of disease or autoantibody status. Pharmacologic attempts to boost GPX1 level in human beta cells during early T1D or in isolated islets for transplantation may offer clinical benefits.
Multi-foucs imaging under complex surface and structure
Authors: Zhang Liyan , Li Ang 
Published: November 2024

Abstract

Improving the imaging accuracy of geological formations under dual complex conditions (including complex surface and structure) is essential for precisely illustrating structural morphology and understanding reservoir characteristics. The multi-focus imaging is a real surface imaging method that takes into account signal-to-noise ratio and resolution. Drawing upon the principles of paraxial ray theory and Hubra's two wavefronts theory, this approach employs a global optimization inversion algorithm to determine the radii and exit angles of the two wavefronts. Furthermore, it incorporates a non-hyperbolic travel time formula for accurate correction. By combining receiving channels from different CMP channels within the same Fresnel band radius, this method effectively enhances both signal-to-noise ratio and resolution of seismic data. The multi-focus imaging technique is a surface imaging method that considers both signal-to-noise ratio and resolution. Drawing upon the principles of paraxial ray theory and Hubra's two wavefronts theory, this approach employs a global optimization inversion algorithm to determine the radii and exit angles of the two wavefronts. Furthermore, it incorporates a non-hyperbolic travel time formula for accurate correction. By combining receiving channels from different CMP channels within the same Fresnel band radius, this method effectively enhances both signal-to-noise ratio and resolution of seismic data.