bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting CTCF’s cell type-specific binding sites in human genome
Authors: Chai Lu , Gao Jie , Li Zihan , Wang Yunjie , Liu Junjie , Wang Yong , Zhang Lirong , Sun Hao 
Published: November 2024

Abstract

The CCCTC-binding factor (CTCF) is pivotal in orchestrating diverse biological functions across the human genome, yet the mechanisms driving its cell type-specific DNA binding affinity remain underexplored. Here, we collected ChIP-seq data from 67 cell lines in ENCODE, constructed a unique dataset of cell type-specific CTCF binding sites (CBS), and trained convolutional neural networks (CNN) to dissect the patterns of CTCF binding specificity. Our analysis reveals that transcription factors RAD21/SMC3 and chromatin accessibility are more predictive compared to sequence motifs and histone modifications. Integrating them together achieved AUC values consistently above 0.868, highlighting their utility in deciphering CTCF transcription factor binding dynamics. This study provides a deeper understanding of the regulatory functions of CTCF via machine learning framework.
Development and Validation of a Prediction Model for Chronic Thromboembolic Pulmonary Disease
Authors: Liu Guixiang , Wen Jing , Lv Chunyi , Liu Mingjie , Li Min , Fang Kexia , Fei Jianwen , Zhang Nannan , Li Xuehua , Wang Huarui , Sun Yuanyuan , Zhu Ling 
Published: November 2024

Abstract

Background: Acute pulmonary embolism (APE) is a critical disease with a high mortality rate, some of the surviving patients may develop chronic thromboembolic pulmonary disease (CTEPD), which affects the patient’s prognosis. However, the research on the early diagnosis of CTEPD is limited. This study aimed to establish a prediction model for earlier identification of CTEPD.
Methods: This prospective study included 464 consecutive patients with acute pulmonary embolism (APE) confirmed between January 2020 and September 2023, at 7 centers from China. After follow-up for at least 3 months, the patients were divided into the CTEPD and non-CTEPD groups based on symptoms and computed tomography pulmonary angiography (CTPA) or pulmonary ventilation perfusion (V/Q) scans showing residual thrombosis. The independent risk factors for CTEPD were identified via univariate and multivariate logistic regression analyses. Next, a nomogram of predictive model was established, and validation was completed via decision curve analysis (DCA) and receiver operating characteristic curve analysis.
Result: In total, 130 (28%) patients presented with CTEPD. Based on the multivariate analysis, a time interval from symptoms onset to diagnosis (time-to-diagnosis) ≥ 15 days (95% confidence interval [CI]: 3.392–14.972, p < 0.001), recurrent pulmonary embolism (RPE) (95%CI: 1.560–17.300, p = 0.007), right ventricular dysfunction (RVD) (95%CI: 1.042–6.437, p = 0.040), central embolus (95%CI: 1.776–7.383, p < 0.001) and residual pulmonary vascular obstruction (RPVO) > 10% (95%CI: 4.884–21.449, p < 0.001) were identified as the independent predictors of CTEPD. Then, A prediction model with a C-index of 0.895 (95% CI 0.863-0.927) was established for high-risk patients. The nomogram had an excellent predictive performance for earlier identification of CTEPD, with an area under the curve of 0.908 (95%CI: 0.875–0.941) in the training cohort and 0.875 (95%CI: 0.803–0.947) in the validation cohort.
Conclusion：The current study established and validated a reliable nomogram for predicting CTEPD, which could assist clinicians identify the high-risk patients for CTEPD earlier and intervene CTEPH in advance.
The relationship between the triglyceride-glucose (TyG) index and all-cause mortality in ICU patients with primary hypertension: a retrospective study
Authors: Ding JiaCheng , Zhang Kai , Cai XinYu , Li JingQian , Yu Shi , Liu KeYan , Huang MaoXun 
Published: November 2024

Abstract

Background
Hypertension includes both primary hypertension and secondary hypertension. Primary hypertension is the most common type of hypertension, accounting for 90% to 95% of all cases, with a complex and not fully understood pathogenesis. Insulin resistance (IR) is a metabolic abnormality that has been shown to be quite prevalent among patients with hypertension in existing literature. The triglyceride-glucose index (TyG-i) is a reliable indicator for assessing insulin resistance (IR). This study aims to evaluate the relationship between the TyG index at admission and all-cause mortality
(ACM) in patients with severe primary hypertension, and to explore its role in predicting the future all-cause mortality risk in primary hypertension patients.
Methods
This study employs a retrospective design to categorize all patients into four quartiles based on the TyG index. The Kaplan-Meier (K-M) method was utilized to estimate the survival curves for each group and to compare the survival outcomes across different quartiles. To assess the nonlinear relationship between the TyG index and prognosis, Cox proportional hazards regression models and restricted cubic splines (RCS) were applied, adjusting for potential confounders. Additionally, subgroup analyses were performed to conduct stratified analyses and interaction tests.
Results
The study included 3,829 patients with a mean age of 69±11 years. Kaplan-Meier survival curve analysis showed that patients with higher TyG index levels had higher all-cause mortality rates at 30 days, 60 days, and 90 days post-admission. This indicates that a higher TyG index is associated with an increased risk of death in the short term. Additionally, multivariate Cox proportional hazards regression analysis revealed that an increased TyG index was significantly associated with all-cause mortality at 30 days, 60 days, and 90 days(HR: 1.93, 95% CI: 1.44-2.57, P-value: <0.001; HR: 1.80, 95% CI: 1.38-2.34, P-value: <0.001; HR: 1.72, 95% CI: 1.34-2.21, P-value: <0.001).Meanwhile, restricted cubic splines (RCS) analysis revealed a J-shaped relationship between the TyG index and all-cause mortality. This relationship suggests that as the TyG index level increases, the risk of all-cause mortality also progressively rises.
Conclusion
In summary, among patients with primary hypertension in the intensive care unit, elevated triglyceride-glucose index (TyG-i) levels are associated with an increased risk of short-term mortality.
Multidimensional Differential Equations: Integration and Optimization through Matrix Based Algorithms
Authors: NAIK suhail 
Published: November 2024

Abstract

In this paper, we present the development of a novel algorithms employing matrix-based methods for the integration of dependent and independent first order multidimensional functions. Conventional methods often face limitations when dealing with the complexity and computational demands of such high-dimensional problems. Our approach leverages advanced matrix techniques to efficiently manage and solve these intricate equations, significantly reducing computational execution time and providing a robust framework for a wide range of applications in science, technology, and data science. Building on this foundational work, we introduce a pioneering branching matrix method for optimization. This method utilizes the structural advantages of matrix operations to navigate the solution space effectively, enabling the optimization of complicated systems with high-dimensional dependencies. The novel branching matrix method offers significant improvements in both speed and accuracy over conventional techniques, making it particularly suitable for large-scale optimization problems encountered in fields such as science, technology, and data science.
Monitoring individual rice field flooding dynamics over large scales to improve mosquito surveillance and control
Authors: Randriamihaja Mauricianot , Randrianjatovo Tokiniaina M , Evans Michelle V , Ihantamalala Felana A , Herbreteau Vincent , Révillion Christophe , Delaitre Eric , Catry Thibault , Garchitorena Andres 
Published: November 2024

Abstract

Progress in malaria elimination has been hindered by recent changes in mosquito behaviour and increased insecticide resistance in response to traditional vector control measures, such as indoor residual spraying and long-lasting insecticide-treated nets. There is therefore increasing interest in the use of larval source management (LSM) to supplement current insecticide-based interventions. However, LSM implementation requires the characterization of larval habitats at fine spatial and temporal scales to ensure interventions are well-placed and well-timed. Remotely sensed optical imagery captured via drones or satellites offers one way to monitor larval habitats remotely, but its use at large spatio-temporal scales has important limitations. Here, we propose a method using radar imagery to monitor flooding dynamics in individual rice fields, a primary larval habitat, over very large geographic areas relevant to national malaria control programs aiming to implement LSM at scale. We demonstrate this for a 3,971 km² malaria-endemic district in Madagascar with over 17,000 rice fields. We combined rice field mapping on OpenStreetMap with Sentinel-1 satellite imagery (radar, 10m) from 2016–2022 to train a classification model of radar backscatter to identify rice fields with vegetated and open water, resulting in a time-series of weekly flooding dynamics for thousands of rice fields. From these time-series, we obtained over a dozen indicators for each rice field useful for LSM implementation, such as the timing and frequency of flooding seasons. These monitoring tools were integrated into an interactive GIS dashboard for operational use by vector control programs, with results available at multiple scales (district, sub-district, rice field) relevant for different phases of LSM intervention (e.g. prioritization of sites, implementation, follow-up). Scale-up of these methods could enable wider implementation of evidence-based LSM interventions and reduce malaria burdens in contexts where irrigated agriculture is a major transmission driver.
The Coordinated Development of the Digital Economy and Urban‒Rural Integration in the Yangtze River Delta and Its Spatial Correlation Structure
Authors: Zhou Can , Xiao Tieqiao , Xu Qiaoling 
Published: November 2024

Abstract

The digital economy plays a crucial role in facilitating the flow of resources between urban and rural areas and addressing development imbalances. This study focuses on 41 cities in the Yangtze River Delta region and uses the entropy-weighted TOPSIS method and coupling coordination degree model to analyze the coupling and coordinated development of the digital economy and urban‒rural integration from 2010–2022. The spatial characteristics of the coordination distribution and network correlation structures are examined via standard deviation ellipses, modified gravity models, and social network analysis, alongside the dominant influencing factors derived from geographic detectors. The results show that (1) there is a disconnection and imbalance between the development of the digital economy and urban‒rural integration in the Yangtze River Delta, with the former progressing significantly faster than the latter. (2) The coupling coordination level improved over the study period, with cities exhibiting higher coordination concentrated in the eastern and southeastern parts of the region, showing an “M”-shaped distribution. (3) The coupling coordination degree displays a spatial distribution pattern from "northwest to southeast," with the center shifting southeastward. Overall, the central area outperforms the northern and southern areas, and the eastern area surpasses the western area. (4) The degree of coupling coordination forms a complex network structure, with core cities expanding from Shanghai, Suzhou, and Wuxi including Nanjing and Changzhou. The network structure has transitioned from a hierarchical to a flat structure, and center degree analysis reveals an increase in influence for Nanjing and Changzhou; however, the distribution of mediating roles is uneven, affecting the network's accessibility and stability. (5) The coordinated development of the digital economy and urban‒rural integration is influenced by different factors over various time periods, with the flow of urban‒rural resources, agricultural modernization, and social equalization being the primary contributors. Finally, on the basis of the analysis results, targeted optimization strategies using the geographic detector model provide a reference for regional urban‒rural development.
Stylet-driven leads vs. lumenless leads as modality for left bundle branch area pacing: A systematic literature review and meta-analysis
Authors: Yu Ga-In , Kim Tae-Hoon , Cho Yun-Ho , Bae Jae-Seok , Ahn Jong-Hwa , Jang Jeong Yoon , Kwak Choong Hwan 
Published: November 2024

Abstract

Left bundle branch area pacing (LBBAP) offers cardiac synchrony benefits over conventional ventricular pacing. Although many procedures and studies on LBBAP have used lumenless pacing lead (LLL), stylet-driven pacing lead (SDL) can also be used. This study compared LLLs and SDLs in LBBAP through a systematic review and meta-analysis of the literature. The PubMed, Embase, and Cochrane Library databases were searched for full-text articles on LBBAP from their respective inception dates to 9 April 2024. The studies comparing LLLs and SDLs were extracted, and electrophysiological characteristics and procedural outcomes were analysed. Of 2201 articles on LBBAP, 7 met the inclusion criteria of comparing LLLs and SDLs as implanted pacing leads. The overall pooled analysis showed non-inferiority in implant success rates for SDLs compared with LLLs for LBBAP (89% vs. 94%, odds ratio: 0.80, 95% confidence interval: 0.37–1.72, P = 0.566). The paced QRS duration of LBBAP using SDL was not significantly different from that using LLLs (standardised mean difference: −0.19 ms, 95% confidence interval: −0.50 to 0.12, P = 0.239). There was no difference in stimulus to left ventricular activation time and paced QRS duration between the two groups. Follow-up pacing parameters were stable in both groups.
Field experiments on the growth conditions of halophytes from Daebudo Tidal Flats, West Sea of Korea
Authors: Bai Jong Il , Hwang Sung Il , Kim Dong Uk , Kim Sung Cheol , Back Sang Ho , Kim Yu Jin 
Published: November 2024

Abstract

With the aim to restore the colonies of four halophyte species (Salicornia europaea, Suaeda glauca, Suaeda japonica, and Suaeda maritima) that live in upper tidal flats, we performed sowing in the tidal flats of Daebudo Island in the West Sea by varying the altitude, sowing time, and sowing depth and measured the germination density, growth rate, and soil environment of the target sea area. We also investigated the growing conditions of large natural colonies of S. japonica formed around the area. The results indicated that altitude and mean grain size strongly influenced halophyte germination and growth. S. europaea, S..glauca, and S. maritima were influenced by altitude, and S. japonica by average grain size. For the same sowing time, germination density was higher for S. japonica and S. maritima without vernalization and S. europaea with vernalization. The more the sawing depth, the higher the germination density and growth of all species. Furthermore, the germination density of S. glauca was significantly lower than that of the other species, making it difficult to evaluate the influencing environmental factors. This is the first study to report germination experiments on tidal flats in Korea, and continuous research will be required to ensure that the halophytes are conserved as second nature by monitoring for environmental pressures and cultivation.
Evaluation of noise in intensive care unit (comparison of two intensive care units)
Authors: Pazani-Kohaki Morteza , Yazdanfar Seyed-Abbas , Panahi Davoud , Arafati Erfan 
Published: November 2024

Abstract

Objective
The present study aims to explore the noise level in two intensive care units of different architectures; then, a comparison of the two wards will be made concerning space size, design, and material effect on noise level reduction.
Materials and Methods
The ICUs were grid passes and by using a B&K sound level meter in several points of various frequencies, the sound pressure level was measured; then, the average was calculated. Then, for simulation and validation, both ICUs were simulated using Odeon Cmbined software.
Results
The average sound pressure level was 61.4 to 62.3 dB, higher than the recommended level in the two ICUs by WHO. The reverberation time in the two ICUs was lower than the standard set by the Iranian National Building Research Center. The lowest reverberation time was at 4 kHz and the highest was at 125 and 250 Hz.
Conclusion
More partitions can be used in the ICU to reduce the sound energy of waves. Partitions should have a high absorption coefficient in mid and high frequencies for better results. Also, small units cannot keep sound-absorbing material which can promote poor acoustic conditions. Generally, the design of single-bed units is more appropriate for an ICU than an open plan.
Hybrid IoT Autonomous Robotics: A Comparative Analysis of Lidar-Based Precision Mapping and Camera-Based Vision Using ROS2 and MediaPipe
Authors: Nanade Sunny , Anne Koteswararao 
Published: November 2024

Abstract

This paper presents a comparative analysis of two IoT-enabled autonomous robotic systems: one employing Lidar-based precision mapping and the other utilizing camera-based vision integrated with ROS2 and MediaPipe for gesture recognition. The Lidar-based robot leverages SLAM (Simultaneous Localization and Mapping) for detailed environmental mapping and obstacle avoidance, making it well-suited for tasks requiring high navigation accuracy. In contrast, the camera-based robot uses real-time vision processing for gesture recognition and object detection, providing an interactive and adaptable interface for human-robot communication. Both systems are evaluated across multiple performance metrics, including mapping accuracy, processing time, and energy consumption. Our results demonstrate that while the Lidar system excels in precise navigation, the camera-based system offers greater flexibility for dynamic interaction scenarios. This analysis offers insights into the strengths and limitations of each approach, paving the way for hybrid systems that combine both precision and adaptability in IoT-based autonomous robotics.
Predicting A-TIG Weld Bead Geometry Using Artificial Neural Networks
Authors: Acharya Samarendra , Patra Soumyadip , Das Santanu 
Published: November 2024

Abstract

The main issue that TIG welding experiences is limited weld penetration which eventually restricts its productivity. In order to overcome this difficulty and incomparable advantages of TIG welding, a method known as activating flux tungsten inert gas (A-TIG) welding was introduced, and is currently the focus of extensive research. When compared to traditional TIG welding, A-TIG welding is well capable of improving the aspect ratio by around 200% and weld penetration depth by about three times or even more. The present research tries to examine the impact of various fluxes on 8 mm thick grade 304 austenitic stainless steel regarding weld bead geometry. In this investigation, 3-factor 3-level RSM with Box-Behnken design method with 15 experimental runs were considered. In this experiment, a novel ternary flux mixture comprising of SiO2, TiO2 and Fe2O3 of different proportions such as 72:18:10, 65:25:10 and 45:45:10 were used. The sample with the optimal response, i.e. depth of penetration of 6.507 mm, bead width of 8.58 mm and reinforcement value as 0, had the welding parameters set as 160A current, 1.778 kJ/mm heat input, flux ratio of SiO2, TiO2 and Fe2O3 of 65:25:10 and root gap as 1.4 mm. A scanning electron microscope (SEM) and an optical microscope are used to examine the microstructure of the weld zone. Additionally, hardness of the welding zone is assessed and the maximum value is measured as 66 HRC. Satisfactory results are obtained with ANOVA for validation and ANN as an estimation tool.
FragNet: A Graph Neural Network for Molecular Property Prediction with Four Layers of Interpretability
Authors: Panapitiya Gihan , Gao Peiyuan , Maupin C Mark , Saldanha Emily G 
Published: November 2024

Abstract

Molecular property prediction is a crucial step in many modern-day scientific applications including drug discovery and energy storage material design. Despite the availability of numerous machine learning models for this task, we are lacking in models that provide both high accuracies and interpretability of the predictions. We introduce the FragNet architecture, a graph neural network not only capable of achieving prediction accuracies comparable to the current state-of-the-art models, but also able to provide insight on four levels of molecular substructures. This model enables understanding of which atoms, bonds, molecular fragments, and molecular fragment connections are critical in the prediction of a given molecular property. The ability to interpret the importance of connections between fragments is of particular interest for molecules which have substructures that are not connected with regular covalent bonds. The interpretable capabilities of FragNet are key to gaining scientific insights from the model’s learned patterns between molecular structure and molecular properties.
Efficacy and Safety of Rivaroxaban in the Treatment of Carotid Artery Disease: A Systematic Review
Authors: HMMP Bandara , GD Hannibal , PLGC Liyanage 
Published: November 2024

Abstract

Background
Globally, cardiovascular diseases continue to be the major cause of death, with carotid artery disease (CD) playing a significant role in stroke incidence. Rivaroxaban, a direct oral anticoagulant (DOAC), has shown potential in reducing the risk of systemic embolism and stroke in carotid artery disease patients.
Objective:
To evaluate the safety and effectiveness of rivaroxaban in patients with carotid artery disease compared with standard treatments.
Method:
A review was conducted following the PRISMA guidelines, with searches performed in the MEDLINE and Cochrane databases using predefined keywords. From 80 initially identified studies, four met the inclusion criteria. Eligible studies were randomized controlled trials (RCTs) involving adults aged above 18 with cardiovascular disease published in English from 2017 onward and compared rivaroxaban with standard therapies. Studies were excluded if they did not focus primarily on rivaroxaban, included patients under 18, or were not RCTs. The quality of the selected studies was assessed via the Cochrane risk of bias revised tool, and all the studies were deemed to be of low risk.
Results
The studies included in the review compared rivaroxaban versus warfarin, rivaroxaban alone versus aspirin, and rivaroxaban in combination with aspirin versus aspirin alone. Whether used alone or in combination with aspirin, rivaroxaban has shown varying efficacy in reducing cardiovascular and other thrombotic events. Rivaroxaban and aspirin together significantly decreased overall mortality (p = 0.01) and the risk of myocardial infarction, stroke, cardiovascular death, and acute limb ischemia (p < 0.001). However, there was a higher chance of major and minor bleeding, especially gastrointestinal bleeding, when using rivaroxaban (p < 0.001). Rivaroxaban did not differ statistically significantly from warfarin or aspirin.
Conclusion
Rivaroxaban, especially with aspirin, reduces major cardiovascular events and thrombotic events but increases the risk of bleeding. These findings highlight the need for careful risk-benefit assessment when considering rivaroxaban for carotid artery disease.