bluuebunny/crossref_metadata_2025 huggingface dataset:
A Pilot Project on a Community-Supported Approach to Blood Pressure Management to Improve Sustainability in a Rural Community in Bangladesh
Authors: Noor Abdullah , Karmokar Sanjit , Yasmin Mst. Ferdousi , Mouree Mumtahenah Razul , Shojon Mohammad , Hussain Syed Raza , Anwar Abida Binte , Bushra Nafisa Rahman , Rathi Tanusree Mondal , Shreya Shreyashi Manishita , Rafi Md Abdur , Jahan Sanjida , Zaman Rebecca , Gastanaduy Mariella , Yasmin Nelofar , Haque Md Jawadul , Kovvuru Karthik
Published: October 2024

Background: This paper presents a pilot project that applied ethnographic research and facilitation of community organization to promote community support for sustainable chronic disease management in Khoriapara, a marginalized community in Bangladesh.
Methods: Our multidisciplinary approach comprised ethnographic research, community organization, screening, and monitoring. Ethnographic research was utilized to describe the community and identify resources. Facilitation of community organization involved forming the health and inclusion committee by going door to door and selecting workers via key informant preference. All individuals over age 30 within the resident-defined boundary were screened. BP was measured twice at three-minute intervals using an automatic bicep cuff. Hypertension was defined as a consistent systolic ≥140 or diastolic ≥90 measured both times. Self-efficacy scales were administered to identify care gaps and facilitate social support for hypertension patients. The screened-positive patient’s blood pressure was monitored and intervened with medications and social support every two weeks via an internet-based system utilizing local resources. We will present results from March 2020 to December 2022.
Findings: Ethnography research showed that while the residents face barriers to accessing health, education, and nutrition, the community has a distinct identity and can offer resources such as technological knowledge, interpersonal networks, and space to conduct health-related activities. The health and inclusion committee selected via door-to-door approach received acceptance and helped navigate initial conflicts that ensued due to the preferential approach to selecting workers. 260 individuals were screened. Eighteen individuals met the hypertension screening criteria. From October 2020 to December 2022, the mean change in systolic blood pressure decreased by 27 mmHg, and diastolic blood pressure decreased by 9.9 mmHg (p<.05). Resources identified in ethnography have been used to sustain the project with the support of community organization. The pilot project was done in a single community, which limits generalizability.
Interpretation: The project highlights the role of ethnography and a door-to-door approach to community organization in developing sustainable chronic disease management in resource-limited settings.
Effect of the Association of Pelvic Floor Muscles and Inspiratory Muscles Training in Women With Stress Urinary Incontinence Resulting From Chronic Obstructive Pulmonary Disease: Protocol Study
Authors: Dourado Tamires Santos Barbosa , Santos João Lucas Peres dos , de Gouveia Guilherme Pertinni Pertinni
Published: October 2024

Stress Urinary Incontinence is a prevalent issue among women with Chronic Obstructive Pulmonary Disease (COPD), primarily due to the increased intra-abdominal pressure from chronic coughing. This study proposes a novel protocol combining Pelvic Floor Muscle Training (PFMT) and Inspiratory Muscle Training (IMT) to address SUI in women with COPD. The research aims to evaluate the effectiveness of this combined intervention in reducing urinary leakage and dyspnea, thus improving the quality of life for these patients. The study is a randomized, double-blind clinical trial with 64 female participants, aged 18 to 65, who have both COPD and SUI. Participants are divided into an intervention group and a control group, with assessments conducted before and after a five-week treatment period. The primary outcome measured is the daily incidence of urine leakage episodes, while secondary outcomes include functional capacity tests, muscle strength measurements, and various clinical and sociodemographic profiles. Interventions include low to moderate intensity resistance exercises for inspiratory muscles and pelvic floor muscles, progressively increased based on patient progress. The intervention group undergoes IMT with the PowerBreathe device at 50% of their maximum inspiratory pressure, while the control group is set at 10% without modifications. The expected outcomes are a significant reduction in urinary leakage and improved respiratory function, highlighting the potential of this non-invasive and comfortable intervention. The study aims to fill a gap in the literature by providing evidence on the efficacy of combined PFMT and IMT in treating SUI in women with COPD, thereby offering new insights and tools for clinical practice and future research.
Modeling Regional Determinants of Early Motherhood in Colombia and its impact during COVID-19
Authors: Davila Fabian Antonio , Cala-Viteri Favio Ernesto
Published: October 2024

Introduction
Early motherhood, defined as occurring in women under 19, poses significant social challenges with immediate and long-term consequences. This study focuses on early fertility rates (early motherhood) in Colombia, examining their relationship with social and demographic factors.
Methods
Departmental-level data from Colombia's Social Protection Information System (RUAF) and the National Administrative Department of Statistics (DANE) were cleaned and aggregated from 2018 to 2023. This allowed the estimation of the overall fertility rate, infant fertility rate, and adolescent fertility rate by department and year. A model was conducted to estimate the influence of recognized risk factors such as low educational attainment (% of under-educated population), poverty level (% of population under subsidized health schemes, current GDP), employment rates (% of workforce participation), violence against women (% of female deaths, both general and violent), and infant mortality. The model was refined to improve performance by removing variables with low contributions to early motherhood.
Results
Fertility indicators focusing on early fertility in Colombia were described. Regions that should be prioritized for early fertility prevention strategies were identified because of their increase in the early pregnancy rate during the pandemic. Significant risk factors found included the percentage of the population under subsidized health schemes, GDP per capita, %violent deaths, % of female deaths, and % deaths among < 18 years of age.
Conclusions
we identified regions that should be prioritized for early fertility prevention strategies, highlighting areas particularly vulnerable that increased early fertility rates during the pandemic. These findings reveal the effects of relaxed public health measures alongside social and demographic factors needed for targeted interventions. Further research is necessary to quantify the impact of specific interventions on early fertility rates.
Obstetric outcomes of women undergoing office hysteroscopy in infertility conditions: a retrospective cohort study
Authors: Gawron Iwona , Zmaczynski Andrzej , Szwech Julia , Szmigiel-Soja Agata , Jach Robert
Published: October 2024

Purpose
To present and compare obstetric outcomes in women undergoing office hysteroscopy (OH) during the diagnostic evaluation and ineffective treatment of infertility due to various underlying factors.
Methods
The retrospective study included women experiencing infertility of diverse type and etiology. Obstetric outcomes, including rates of live births, clinical and biochemical pregnancies, and time to conception, were compared within four preoperative diagnosis groups (idiopathic infertility, uterine polyp, uterine factors other than polyps, and other conditions) and four postoperative diagnosis groups (uterine polyp, clinical features of chronic endometritis (CE), uterine factors, and other findings), taking into account the status of chronic endometritis.
Results
Among preoperative diagnoses, women undergoing hysteroscopy for recurrent miscarriages had the highest percentage of pregnancies, while those with polyps had the lowest (p = 0.012). With a positive CE status and empirical antibiotic treatment, the highest pregnancy rate was in women with idiopathic infertility, while the lowest was in those with polyps (p = 0.011). Regarding hysteroscopic findings, the highest percentage of achieved pregnancies occurred in women undergoing resection of a uterine septum or intrauterine adhesions, while the lowest was observed in those following polypectomy (p = 0.036). No differences in obstetric outcomes were noted concerning CE status. None of the hysteroscopic findings were independent prognostic factors for live birth.
Conclusion
In planning hysteroscopy for idiopathic infertility, verifying CE status is recommended to facilitate treatment and improve obstetric outcomes if positive. The removal of a uterine septum or intrauterine adhesions enhances the rate of achieved pregnancies, regardless CE status.
Contrasting Differences in the Utility of Green Space Accessibility of Major Large-Scale Cities
Authors: Xu Caixia , Zhao Jiawen , Zhang Yuxiang , Xiang Yutong , Feng Wei , Zhou Chan , Sun Liqun
Published: October 2024

One of the Sustainable Development Goals is to provide universal access to green space for urban residents. Nevertheless, whether city dwellers can readily access green space remains unanswered physically and mentally. In this study, we introduce a novel concept, the utility of green space accessibility (GSAU), which integrates three existing indices: green space accessibility (GSA), green space accessibility inequality (GSAI), and travel aversion index (TAI). These indices assess the ease with which residents of 30 major Chinese cities can access green space, considering physical and mental terms. The study identifies contrasting differences in the GSAU between Chinese northern and southern zones. When the willingness of residents to travel is not considered, the cities in the eastern zone have higher GSA and greater GSAI compared to those in the western region. However, when considering the travel willingness of residents, these cities show a clear north-south geographical distribution the number of cities in the southern region with a GSAU higher than 0.6 (including ideal, annual, summer, and winter GSAU) is approximately twice that of northern cities. These findings highlight the need to consider residents' subjective travel willingness for green space based on environmental quality justice.
A novel initial weld point guidance and path planning method for robot welding based on structured light vision
Authors: Wang Tianqi , Li Qiaochu , He Junjie , Li Xiao
Published: October 2024

Aiming at the problems of low efficiency and poor adaptability of teaching-and-playback and offline programming. This paper proposed a method for positioning initial weld point (IWP) and planning welding trajectory based on structured light vision. Firstly, a camera is fixed at the end of the robot to capture images of the welding workpiece from two specific positions. An improved Yolov8 algorithm is employed to recognize IWP, achieving approximate positioning of IWP with "monocular vision dual-position shooting." Subsequently, the position of the camera relative to IWP is determined based on the structured light plane. Image processing is then conducted to extract the structured light feature points, and the feature points are fitted to obtain groove planes and weld seam line, thereby planning the overall welding pose. Experimental results demonstrate that this method can effectively complete the recognition of IWP, the extraction of weld seams, and trajectory planning tasks, which is of positive significance in improving the welding efficiency and adaptive ability of robots in various welding environments and workpiece conditions.
CNEKA: An Algorithm for SDN Controller Placement based on Graph Convolutional Networks
Authors: Rao Yirui , Chen Jue , Qiu Xihe , Wang Lizhi , Tao Hongyu
Published: October 2024

Software-Defined Networking (SDN) is an emerging network architecture characterized by the decoupling of the data plane from the control plane, as well as managing the whole network in a centralized logic. As the scale of networks continues to expand, the single-controller architecture is no longer able to meet the performance and reliability requirements of the network. Consequently, a logically centralized while physically distributed multi-controller architecture has been proposed, in which the number and locations of controllers must be determined, formulating the Controller Placement Problem (CPP). In order to solve the CPP and optimize the propagation latency, we propose a Convolutional Node Embedding and K-means Algorithm (CNEKA), which integrates Graph Convolutional Networks (GCN) with the K-means algorithm. More specifically, we adopt the principles of GCN to facilitate mutual information propagation among adjacent nodes, and then use the K-means algorithm to achieve graph segmentation through the low-dimensional embedding vectors calculated by GCN. The study demonstrates that the CNEKA algorithm significantly enhances performance in optimizing average and worst-case latency between controllers and switches, as well as overall network latency, particularly under high controller counts. The algorithm achieves a mere 1.10% deviation from the global optimum in average controller-switch latency, underscoring its high efficacy.
Financial Time Series Forecasting Based on Adversarial Training and Dynamic Weight Design
Authors: Liu Xiang , Ye Zheng , Ge Jun , Cheng Yu
Published: October 2024

To address the challenges of financial market instability, high data correlation , anomalies, and noise, traditional adversarial training methods enhance model robustness and nonlinear modeling capabilities by introducing adversarial samples. However, current research primarily relies on single models and singular adversarial methods, which limits the diversity and adaptability of these approaches. Additionally, perturbing only the output layer overlooks the dynamic characteristics present in various layers of the model. To overcome these shortcomings , this paper proposes a strategy that integrates multiple adversarial methods into different deep learning models, combined with a two-stage training and dynamic weight adjustment. In the first stage, the model identifies fundamental patterns by training on the original dataset. In the second stage, adversarial training is introduced to enhance the model’s ability to cope with complex market conditions. Furthermore, the introduction of dynamic weight parameters allows the model to flexibly adjust the weights of the two stages, thereby improving its adaptability to the characteristics of financial data. This paper also introduces two novel adversarial methods: the Hessian perturbation method and the return volatility perturbation method. These methods not only strengthen the model’s nonlinear modeling capabilities but also enhance its adaptability and generalization ability. Experimental results demonstrate that, on the CSI100 dataset, our proposed comprehensive strategy significantly outperforms baseline models in terms of annualized return, information ratio, and maximum drawdown.This achievement not only validates the effectiveness of adversarial methods in predicting financial time series but also illustrates the contribution of the two-stage training framework in enhancing adversarial training, thereby improving the model's adaptability under complex market conditions. Additionally, the introduction of dynamic weight parameters enables the model to flexibly adjust the focus of each stage, allowing for a more effective response to the dynamic characteristics of financial data.
A comparative analysis of DETR and Conditional DETR for identifying smoking scenes
Authors: Utama Ferzha Putra , Vatresia Arie , Mahendra Robby
Published: October 2024

Smoking remains a significant global public health concern, leading to over 8 million deaths annually and significantly increasing the risk of various diseases. Despite the effectiveness of policies like banning smoking scenes in media and implementing public smoking bans in controlling smoking behaviors, the proliferation of digital media presents new challenges in managing exposure to smoking-related content. In response to these challenges, this study introduces an automated solution that leverages advanced computer vision techniques, specifically utilizing DETR and Conditional DETR models with ResNet-50 backbones, to detect and apply Gaussian blur to smoking scenes in videos. The performance of these models was rigorously evaluated using mean Average Precision (mAP) metrics across datasets containing 4,000, 3,000, and 2,000 images. The results demonstrated that the DETR model achieved the highest AP of 58.5 with the 4000-image dataset, surpassing the Conditional DETR model, which achieved an AP of 55.0 with the 3000-image dataset. Furthermore, in video processing tasks, the DETR model exhibited superior efficiency, with an average processing time of 56.8 seconds, compared to Conditional DETR's 59.2 seconds. The implementation of Gaussian blur effectively obscured smoking activities in the video content, preserving the overall context while significantly reducing the visibility of harmful content. These findings underscore the advantages of the DETR model in terms of both detection speed and accuracy, particularly when applied to larger datasets. This study highlights the potential of DETR in enhancing automated content moderation tools, contributing to the ongoing efforts to mitigate the public health risks associated with smoking in the digital age.
Atmospheric dispersion downstream a two-dimensional obstacle: experimental evaluation of turbulence closure models
Authors: Salizzoni Pietro , Fellini Sofia , Gamel Hervé , Marro Massimo , Soulhac Lionel
Published: October 2024

This study investigates the turbulent dispersion of pollutants in the wake of a two-dimensional square obstacle, focusing on assessing the reliability of turbulence closure models used in atmospheric pollutant dispersion. Utilizing Laser Doppler Anemometry (LDA) and Particle Image Velocimetry (PIV), we characterized the flow dynamics, identifying a recirculation zone with an average length of 6H downstream of the obstacle. This zone, characterized by high shear and increased turbulent viscosity, plays a crucial role in turbulent momentum exchange. We evaluated the turbulent kinetic energy (t.k.e.) budget, estimating its dissipation rate ($\varepsilon$), and found traditional isotropy and Taylor hypothesis methods inadequate within the wake region.
Furthermore, we explored pollutant dispersion from a linear source located downstream. Analysis of mean concentration and variance revealed that the log-normal distribution is most effective for modeling concentrations within the recirculating region, while the Gamma distribution suits areas outside it. Testing various closure models for turbulent mass fluxes highlighted the limitations of the Simplified Gradient Diffusion Hypothesis model, favoring more complex closure models for longitudinal trends, though these still faced challenges with intensity estimation. The Simplified Gradient Diffusion Hypothesis model proved robust for vertical mass fluxes, with satisfactory results in turbulent diffusivity and turbulent Schmidt number calculations.
Our findings underscore the necessity for improved spatial resolution in measurements near pollutant sources, particularly between 0.5H and 2H downstream. The experimental results allowed us to assess the reliability of a wide variety of parameterizations adopted in Reynolds-Averaged Navier-Stokes (RANS) formulations and within pollutant dispersion models. This database serves as a benchmark to test the accuracy of more sophisticated modeling approaches such as Large Eddy Simulations (LES) and Direct Numerical Simulations (DNS).
Public Sector Job Guarantees and Family Planning Choices in Rural India
Authors: Kishore Siddharth , Manning Dale T.
Published: October 2024

We exploit the staggered timing of an employment guarantee program in rural India to investigate how providing work opportunities affects married women’s use of family planning methods. Using survey data from rural India, we employ a difference-in-differences strategy and inverse-probability-of-treatment weighting to control for confounding factors influencing family planning decisions. Results suggest an increase of 1.8 percentage points (a 3.2% increase from the variable’s sample mean) in the use of modern family planning methods among married women after the introduction of an employment guarantee program. Results are robust to the choice of controls, regression weights, and matching method. We also demonstrate that program impacts increase with the amount of time a workfare program has been in place. These results provide empirical evidence that employment guarantees that include women can affect family planning choices, with important implications for economic development outcomes.
Small Traffic Sign Detection Algorithm Based on Multi-Scale Feature Fusion
Authors: Zhang Jing , Du Xiaoyu , Zhou Ye , Tan Yajun
Published: October 2024

In autonomous driving, traffic sign detection is easily affected by environmental lighting, changes in target size, and complex backgrounds. To address these issues, this paper proposes a multi-scale traffic sign detection algorithm, SS-YOLO (Small Sign). This method enhances multi-scale feature fusion by generating additional high-resolution feature layers and optimizes small object detection by removing the large-object detection head. At the same time, the C3 module is replaced with the more efficient C3-DS module, and the EMA attention mechanism is introduced to improve the ability to capture channel information. Additionally, the DySample upsampling operator is used in the feature fusion layer to increase the receptive field and optimize feature fusion. Experimental results show that SS-YOLO achieves an average precision (mAP) of 86.8% on the CCTSDB 2021 dataset, a 10.5% improvement over YOLOv5s, while reducing the number of parameters by 23.23%, achieving both fewer parameters and higher detection accuracy.
Optimized 3-D Chaotic Map for Compressed Image Encryption for Secure Communication
Authors: Tiwari Akshat , Diwan Prachi , Diwan Tarun Dhar
Published: October 2024

In today’s digital world, there is a significant increase in data transfer online especially in multimedia form. This online transmission faces many cyber threats such as denial-of-service attacks, phishing, man-in-the-middle attacks, etc. These threats result in potential security risks and raise the need for secure communication. In this paper, a chaotic map-based encryption technique is presented. The proposed algorithm presents optimized parameter-based 3D chaotic maps for image encryption. The method integrates three primary components: stacked autoencoder (SAE), optimized parameter-based chaotic mapping, and encryption/decryption module, to ensure robust and secure encryption of images. The result evaluated the proposed secure image encryption algorithm with a randomness test, pixel adjacency correlation test, and differential analysis. The mean entropy was approx. 7.9 and the mean number of pixels changing rate (NPCR) was approx. 99.8, unified average changing intensity (UACI) was approx. 33.46. Moreover, the proposed algorithm also investigated the result under noise attacks and shows better cryptanalysis results as compared to comparative state-of-art models.
Causal roles of gut microbiota in OS etiology suggested by genetic study
Authors: Wei Wei , Zhou Zihuan , Li Xiaolin , Wu Zhipeng , Xiao Jianru , Wei Haifeng
Published: October 2024

Objectives
Osteosarcoma (OS) represents a prevalent primary malignant bone tumor with limited treatment options at present. The relationship between gut microbiota and OS remains ambiguous, with uncertainty surrounding whether this association is causal or influenced by bias. To investigate the potential link between gut microbiota and the development of OS, we conducted a two-sample Mendelian randomization (MR) analysis.
Methods
We employed a two-sample MR study design to elucidate the causal association between gut microbiota and OS. Our analysis encompassed a total of 196 bacterial features across five taxonomic levels: Phylum, Class, Order, Family, and Genus. The MR analysis incorporated the inverse-variance-weighted (IVW), weighted median, MR-Egger, weighted mode, and simple median methods. The primary analysis was conducted using the IVW method, and the MR results were validated through heterogeneity tests, sensitivity analysis, and pleiotropy analysis.
Results
Our findings revealed significant associations between nine distinct bacterial traits and OS using the IVW method. Specifically, we identified that genus. Odoribacter.id.952 (OR: 15.19; 95% CI: 2.08, 111.18; p = 0.007) and genus.Clostridiumsensustricto1.id.1873 (OR: 10.78; 95% CI: 1.78, 65.32; p = 0.009) were associated with a significantly increased risk of OS. Conversely, genus.LachnospiraceaeUCG001.id.11321 (OR: 0.21; 95% CI: 0.06, 0.70; p = 0.011) was found to significantly decrease the risk of OS.
Conclusions
Research suggests specific gut microbiota affect OS risk, highlighting their role in disease development and paving the way for new OS treatment strategies.
Comparison of Prognosis Between Epidermal Growth Factor Mutation Positive and Negative Groups in Lung Adenocarcinoma Patients with Brain Metastases
Authors: UNAT Damla SERÇE , ARIKAN Şener , BALCI Günseli , ERMİN Sinem , MERTOĞLU Aydan , KIRBIYIK Ozgur
Published: October 2024

Introduction:
Brain Metastasis (BM) in Non-Small Cell Lung Cancer (NSCLC) is still important reason of morbidity and mortality despite the advances in the cancer treatment. Using Tyrosine Kinase Inhibitors against Epidermal Growth Factor Receptors (EGFR) mutations revolutionized in NSCLC treatment. We investigated whether the presence of EGFR mutation influences survival in patients with Lung Adenocarcinoma with BM.
Material and Methods
The data of the patients with pathological diagnosis of NSCLC and BM at tertiary hospital were analyzed retrospectively in terms of survival. A total of 2554 patients diagnosed with NSCLC pathologically between 01.01.2010 and 01.01.2021 were identified. After exclusion of patients with lack of data, unknown EGFR mutation status, no brain metastasis and additional malignancy 336 patients were included to the study.
Results
It is found that EGFR (+) patients were more female dominant (48.6% vs 13.3% p < 0.0001) and were have less history of smoking (%47.2 vs %87.1, p < 0.0001) and were better survival (%79.2 vs %92.8). We found negativity of EGFR increased death risk by 1.700 times (95% CI: 1.323–2.183, p < 0.0001) in univariate analysis and by 1.724 times (95% CI 1.251–2.377, p = 0.0001) in multivariate analysis. When overall survivals have been compared estimated overall survival time of EGFR (-) patients were 10.088 (95% CI 8.571–11.606) months and of EGFR (+) patients were 11.829 months (95% CI 10.336–13.323) (p < 0.001).
Conclusion
EGFR positivity was associated with survival. Also, survival was significantly longer in EGFR-positive patients with brain metastases diagnosed with NSCLC.
Differential Excitatory-Inhibitory Balance within Dorsolateral Prefrontal Cortex Shapes Inter-network Interactions in Working Memory
Authors: Yi Chunzhi , Zhu Haiqi , Zhang Shaoshi , Li Yangping , Lv Zehua , Zhou Shijie , Wei Baichun
Published: October 2024

Working memory involves complex activation of and interactions among multiple brain areas. However, little is known about how these large-scale activity and interaction patterns relate to resting state activity and originate from excitatory and inhibitory interactions. Here, we combine the analysis of fMRI activation, functional and structural connectivity with large-scale neural network modelling and molecular-enriched PET analysis to show how the excitatory and inhibitory neuronal activities within dorsolateral prefrontal cortex (DLPFC) relate to the inter-network interactions and activation patterns aroused by working memory tasks. Our results indicate that the activation and interaction of the frontoparietal and default-mode networks, which differ between resting state and working memory, depend on the level of DLPFC activity and on its functional and structural interactions with these networks. By perturbing a large-scale neural network model developed using resting-state fMRI and performing molecular-enriched analysis on both fMRI and PET images, we find evidence that a differential activation of excitatory and inhibitory vs neuron populations within DLPFC may ignite the transition from the resting state to working memory. Our study provides a mechanistic understanding of how regional DLPFC excitatory and inhibitory neural activity combines with functional and structural inter-area connections to support the large-scale network dynamics supporting working memory.
Clinical effect analysis of three-port laparoscopic and choledochoscopic common bile duct exploration without T-tube in the treatment of emergency cholecystolithiasis combined with common bile duct stones
Authors: Wang Xirang , Li Yuxiang , Kang Jian , Wu Yunpeng , Zhang Jun , Tao Hehui , Wang Li , Rong Ruizhou , Wang Miao , Liu Kang , Ban Zhen
Published: October 2024

Objective
To investigate the clinical application value of three-port laparoscopy combined with choledochoscopic common bile duct exploration without T tube in the treatment of emergency patients with choledocholithiasis.
Methods
From December 2023 to July 2024, the clinical data of 103 patients with emergency cholecystolithiasis complicated with common bile duct stones in the Department of General Surgery, Beijing Fengtai Youanmen Hospital were collected. Among them, 44 patients underwent three-port laparoscopy combined with choledochoscopy for common bile duct exploration without T-tube operation, and 59 patients underwent four-port laparoscopy combined with choledochoscopy for common bile duct exploration with T-tube drainage. The preoperative, intraoperative and postoperative indexes of the two groups were compared.
Results
There was no significant difference in preoperative general data between the two groups (all P > 0.05). Three-port laparoscopic T-tube-free method was better than four-port laparoscopic T-tube method in postoperative pain, removal of abdominal drainage tube and length of hospital stay (all P<0.05). There was 1 case of pancreatitis in each group. There was no conversion to open surgery, no residual stones, no hemobilia and no biliary stricture in both groups. There was 1 case of bile leakage after four-hole T-tube placement and 1 case of bile leakage after T-tube removal.
Conclusion Three-hole laparoscopy combined with choledochoscopy for common bile duct exploration without T-tube in emergency patients is safe and feasible. Compared with T-tube group, T-tube-free method is more consistent with the concept of rapid recovery.
Engagement in outreach services among persons experiencing unsheltered homelessness in a Southwestern Urban County: A spatial study
Authors: Mercado Micaela , Drobnyh Klim , Gentry Katie , Law Lara , Shuman Sara , Dibarrart Francisca , Runger George , Ferguson Kristin
Published: October 2024

This study explored how engagement in street outreach services is impacted by the locations where structurally vulnerable individuals experiencing unsheltered homelessness enroll. Logistic regression models were applied to 2022 outreach service contact data to analyze spatial concentrations of engagement across 11 location types. The highest spatial concentration of outreach service contacts occurred in the downtown area of an urban city. Results showed that gender, race, and ethnicity moderated the relationship between engagement and locations where contacts occurred. Among racial and ethnic groups, American Indian/Alaska Native/Indigenous and Hispanic/Latino clients had significantly lower odds of outreach service contacts near the downtown area compared to White clients. In comparison, Black/African American/African and Asian/Asian American clients had higher odds. Additionally, Black/African American/African women had lower odds of outreach service contacts near the downtown area compared to White women. Women had higher odds of contacts near motels than men. High utilizers of outreach services had higher odds of contacts near the downtown area, with gender and race moderating this relationship. Spatial analysis is a novel approach to understanding geographic context where structurally affected individuals engage in services. These findings highlight the need to tailor outreach strategies better to serve diverse populations in different geographic contexts.
A contribution to 3D tracking of deformable bubbles in swarms using temporal information
Authors: Wang Lantian , Ma Tian , Lucas Dirk , Eckert Kerstin , Hessenkemper Hendrik
Published: October 2024

Reliable Lagrangian 3D tracking of individual bubble swarm members allows a deeper understanding of hydrodynamic bubble-bubble interactions and their collective rise. For multi-view measurements, we have recently developed such a tracking method \citep{hessenkemper20243d}, which is able to track deformable bubbles with low to moderate view obstruction through the bubbles to each other. In the present work, we aim to further enhance the 3D tracking performance by incorporating 2D temporal information in the form of previously established 2D tracks in each view. The new 3D tracking method is able to disambiguate cross-view object associations at each time step by using the 2D track information accumulated over time. In addition, the 2D track information is used in two post-processing steps to improve the completeness of established 3D trajectories. Compared to the previous 3D tracking method, the extended 3D tracking framework shows noticeable improvements in tracking ability, accuracy and completeness of trajectories.
Central Nervous System depressant outcome of Artemisia monosperma Delile ethanolic extract in male rats via modulating GABAergic pathway: Phytochemical analysis
Authors: Elewa Naglaa Z. , Khairy Mohamed H. , Ahmed Amal M. , Abdelaty Asmaa I. , Amro Ahmed , Zeid Ehsan Abu
Published: October 2024

This current study aimed to examine the depressive outcome of Artemisia monosperma Delile ethanolic extract (ARM-EE) on the central nervous system (CNS) of male rats. Screening phytochemicals was done using GC˗MS and HPLC analysis. The study included four equal groups (n = 10): 1st Control, 2nd Diazepam (DIZ 1 mg/kg B.wt.), 3rd ARM high group (ARM-H 800 mg/kg B.wt.), and 4th ARM low group (ARM-L 400 mg/kg B.wt). Dosing was orally and daily for 21 days. The acute oral LD50 was valued to be more than 2 g/kg. HPLC analysis revealed the presence of vanillin, syringic acid, naringenin, coffeic acid, rutin, gallic acid, and querectin. Administration of ARM-EE extract significantly (p < 0.001) decreased the hole crosses and fall-off time in the rotarod test. In the open field test, ARM-EE significantly (p < 0.001) decreased locomotor and exploratory behaviors. ARM-EE administration significantly (p < 0.05) increased the brain γ-aminobutyric acid (GABA), dopamine (DA), and serotonin (5˗HT) levels. ARM-EE administration significantly (p < 0.05) up-regulated the brain mRNA expression levels of GABA type a receptor-associated protein (Gabarap) and brain-derived neurotrophic factor (BDNF), meanwhile, expression levels of monoamine oxidase A (Maoa) was significantly (p < 0.05) downregulated. The results of the ongoing research suggest for the first time that the A. monosperma ethanolic extract owns CNS depressant and antioxidative outcomes in a murine model. The CNS-depressive properties of the ARM-EE could be attributable to its phytochemical components. Further toxicological studies are required for the semi-purified phytochemical components of the ARM plant.
Grants and innovations: Funding world innovations, interregional knowledge transfer, or neighbourhood copycats
Authors: Röder Martin , Procher Vivien D. , Urbig Diemo
Published: October 2024

When funding innovations, policy makers often prioritize explorative innovations because of their novelty, overlooking the varied newness within exploitative innovations. By focusing on the imitative nature of exploitative innovations, we distinguish between local imitation — simple replication — and interregional imitation, which involves cross-regional knowledge transfer that is critical for industry renewal and national competitiveness. Examining 4,093 startups, we advocate for a nuanced approach to grantmaking that is tailored to a firm’s industry and strategic position as defined by its entrepreneurial orientation (EO). Our results show that grants foster explorative innovation in high EO startups, while low EO startups contribute through interregional knowledge transfer. This highlights the importance of recognizing high and low EO as different strategic approaches in innovation policy and emphasizing interregional knowledge transfer as an important source of market novelty.
Contemporary strategies for marketing electronic library resources to students: a study of technical universities in Ghana
Authors: Baayel Patrick
Published: October 2024

This paper is derived from a recently concluded doctoral study which delved into innovative strategies for marketing electronic resources (e-resources) in technical universities in Ghana. The ultimate focus was on enhancing student engagement and utilisation of e-resources. The research adopted mixed method design where both quantitative and qualitative processes were employed to gather insights. A sample of 932 (5%) registered student users out of 18,640 from 10 technical universities (TUs) were selected using a stratified random sampling process. Additionally, 34 library professionals were included using a census approach. The respondent rates were 76% (706) for student respondents and 62% (21) for library and information professionals. The study findings indicate that the predominant methods for creating awareness among students include being directed by lecturers, informed by colleagues, library notices, posters, signage, and orientation events. Additionally, Web 2.0 technologies, predominantly social media marketing, instant SMS messages, URL links, institutional website projection, video and audio tutorials, and digital display screens, are all well accepted by students for promoting e-resources. The study emphasises the importance of leveraging technology-based marketing strategies for effective e-resource marketing and recommends integrating these strategies and tools into Ghanaian TU libraries’ marketing efforts. The aim is to maximise the visibility, accessibility, and utilisation of e-resources. This research provides valuable insights for libraries in technical universities to improve their marketing approaches and enhance student engagement with e-resources.
Expanding Elastic Moduli Bounds in Solid-Void Metamaterials: Poisson's Ratio Dependence and Optimal Design
Authors: Tekoğlu Cihan , Ickin Oguz
Published: October 2024

Two-phase solid-void mechanical metamaterials achieve exceptional properties through microstructural adjustments, including any isotropic Poisson’s ratio (−1 to 1 in two dimensions, −1 to 0.5 in three dimensions). Establishing theoretical bounds on these properties is essential for optimising material performance. However, as demonstrated herein, current research often overlooks isotropy constraints, limiting the upper bounds of elastic moduli to a narrow range of Poisson's ratios. In this study, we extend these bounds, revealing significant variability contingent on Poisson's ratio. Through the analysis of five truss lattice materials, each approaching these new bounds in specific Poisson's ratio ranges, we elucidate the interrelationships among deformation mechanisms, elastic moduli, and Poisson's ratio. Notably, we present the first stretching-dominated, isotropic, two-dimensional lattice materials that approach the upper elastic moduli limits as Poisson's ratio approaches -1. These findings provide valuable guidance for designing lightweight, stiff metamaterials across the entire Poisson's ratio spectrum.
The Potential of Neural Networks in Teacher Preparation for Foreign Language Classes and Educational Content Creation
Authors:   Transbaikal State University, Eremina Victoria M.
Published: October 2024

Artificial intelligence (AI) technologies are now being extensively used in various fields of human activity, including science and education. Neural networks, which are AI algorithms, are widely used in language learning. The relevance of this study is due to the need to study the potential of neural networks in the process of preparing a teacher of higher school for foreign language classes. Using neural networks, the university teacher demonstrates the ability not only to choose teaching materials but also to adapt them to the real learning environment, as well as to create new materials, taking into account various available resources and educational needs. The use of neural networks helps to optimize the process of teacher’s preparation for classes. This study aims to analyze the didactic potential of Twee and Perplexity AI neural networks, as well as to examine their use in the preparation for foreign language classes and the creation of educational content for students in various fields of professional training. The research methods we applied involved analysis, comparison, generalization of scientific literature, observation, study of experience and products of activity, analysis of educational literature, modeling of educational process. The scientific novelty of the study is the development of methods of using Twee and Perplexity AI neural networks in the preparation of a set of exercises on the formation of main types of speech activity among non-linguistic students. The conclusion can be drawn that it is necessary to further develop the methodology of teaching foreign languages with the help of artificial intelligence technologies which would help in generating the unique educational content and a set of communication exercises. Twee and Perplexity AI neural networks are effective pedagogical and didactic tools in teacher preparation for foreign language classes. Keywords: artificial intelligence, Twee and Perplexity AI neural networks, creation of educational content, methods of foreign language teaching, AI technologies application
The Analogy Method as an Element of Research Work of Junior Students
Authors:   Ural Federal University named after the first President of Russia B. N. Yeltsin, Geyn Aleksandr G. , Knysh Alla A. ,   Ural Federal University named after the first President of Russia B. N. Yeltsin
Published: October 2024

The article explores the possibility of increasing the efficiency of research work within the framework of lectures and practical classes for junior students. We have identified a contradiction between the potential of research work in the development of students’ research competencies in the process of teaching junior students and the insufficient development of productive methods for introducing research tools in addition to skills in working with sources of information and methods of conducting experimental work. We are talking about tools that allow you to identify objects of research, put forward and formulate hypotheses, test hypotheses, etc. The solution to the problem is realized through the developed methodology of lectures and practical classes, containing elements of intellectual tools of scientific activity in a systematic connection with the subject methodology. The method of analogy has been chosen as a specific tool for scientific activity. A system for assessing the levels of mastering the skills of intellectual tools of students’ scientific activities has been developed and an experimental test of the effectiveness of the developed methodology has been carried out. These methods, implemented for a higher mathematics course for non-core specialties, as well as algebra and mathematical analysis courses for mathematical and IT specialties, can be transferred to other disciplines of the theoretical cycle. This is the practical significance of the study. Keywords: research activity, levels of research activity, analogy method, research methodology
Evaluating Airline Passengers’ Satisfaction during the COVID-19 Pandemic: A Case Study of AirAsia Services through Sentiment Analysis and Topic Modelling
Authors: Yu Lee Jie , Md Saad Nor Hasliza , Kun Zhu , ElSayad Ghada
Published: October 2024

AirAsia has emerged as a dominant force among prominent low-cost airlines in recent years. However, the COVID-19 pandemic outbreak has severely impacted airline services, including AirAsia. There is a strong need for airline services to monitor customer experience and satisfaction from online customer reviews on the website to keep pace with changing customer perceptions toward their service quality. A growing number of travelers choose to express their experiences and emotions on online customer review platforms, resulting in substantial online airline service evaluations. The research analyzes 796 online customer reviews from Skytrax, a well-known online airline review website. The information hidden in customer-generated reviews is analyzed with the text mining technique, including topic modeling and sentiment analysis. The research uses the Latent Dirichlet Allocation (LDA) model for topic analysis and the Valence Aware Dictionary for Sentiment Reasoning (VADER) model for sentiment analysis. The sentiment ratio for AirAsia’s online reviews is approximately 59% positive and 41% negative. Only four reviews are neutral. The findings indicate that the online review of AirAsia has a greater proportion of positive sentiments than negative sentiments. In addition, the topic modeling shows hidden topics with the top high-probability keywords concerned with interior and seat, baggage, online service, staff service, flight schedule, and refund. The research demonstrates using sentiment analysis and topic modeling on customer review data as a more thorough alternative to survey-based models for researching airline service. The research contributes to the methodological advancements in text mining analysis and expands the current knowledge of customer review data.
Smart Aquaculture Design for Vannamei Shrimp Farming Based on Quality Function Development
Authors: Setiawan Budi , Surantha Nico
Published: October 2024

In the fishery industry, Indonesia’s large water area has the potential for developing and cultivating fisheries such as vannamei shrimp. For this reason, aquaculture, particularly vannamei shrimp farming, can play a crucial role in Indonesia’s economy and food supply. However, challenges such as fluctuating water quality, disease outbreaks, turbidity levels, and irregular shrimp feeding schedules in ponds can affect the productivity and sustainability of shrimp farming. The smart aquaculture system integrates technologies, such as IoT-based sensors, automated feeding mechanisms, and real-time water quality monitoring to optimize the farming process. The research proposes a smart aquaculture design for vannamei shrimp farming based on the Quality Function Development (QFD) method. It starts by creating questionnaires to identify stakeholders’ level of interest. The questionnaire results are used as a reference for system redesign using the QFD method to improve the quality and quantity of shrimp harvest, cultivating effectively and efficiently and helping and facilitating the supervision of pond managers on pond water quality, feeding, and feed availability. The result highlights the application of QFD in creating a tailored, technology-driven solution that supports better decision-making, resource optimization, and improved shrimp health. The system reduces human error, enhances farm management, and promotes higher yields by providing real-time data and automation. The evaluation results show that the proposed design can achieve high stakeholder satisfaction. It also achieves better scores compared to the other two competitor’s designs.