bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization of fly ash and cement for stabilizing clay soil
Authors: H Nur Md. Robiul , Islam Shriful , Ray Sourav , Sarker Shuva , Islam Junaidul 
Published: August 2024

Abstract

Fly ash and cement are commonly used as soil stabilizers, offering environment friendly solutions for soil improvement. This study aims to determine the ideal combination of fly ash and cement to improve the geotechnical behavior of clay soil collected from a future building construction project in Sylhet, Bangladesh. Strength development in soil was assessed across a wide range of fly ash (0–25%) and cement (0–18%) during 3-, 7-, 14-, and 28-day curing periods. Tests included in this research are: Atterberg limits test, standard Proctor tests, unconfined compressive strength (UCS) and scanning electron microscopy tests. Incorporating fly ash, cement, or both decreased maximum dry density (MDD) and increased optimum moisture content (OMC) of the soil, while soil classification remained consistent. The investigation revealed that fly ash initially had a higher reduction rate in MDD of the mixtures up to around 7% binder content, before cement took precedence. Optimal soil-binder strength was achieved at 5% fly ash and 8% cement after curing for 28 days individually. However, the optimal combination of the binders was identified as 6% (3% fly ash and 3% cement), yielding a 99.51% increase in UCS compared to untreated soil after 28 days. Scanning electron microscopy tests show that the compactness of clay soil increases due to the addition of fly ash and cement. This binder combination (3% fly ash and 3% cement) could be suitable for stabilizing clay soil beneath the shallow foundation of a residential building in the study area.
Data-driven non-intrusive reduced order modelling of selective laser melting additive manufacturing process using proper orthogonal decomposition and convolutional autoencoder
Authors: Chaudhry Shubham , Abdedou Azzedine , Soulaimani Azzeddine 
Published: August 2024

Abstract

Two data-driven, non-intrusive, reduced-order models (ROMs): a convolutional autoencoder-multilayer perceptron (CAE-MLP) and a combined proper orthogonal decomposition-artificial neural network (POD-ANN) are proposed and compared for additive manufacturing (AM) processes. The CAE-MLP uses a 1D convolutional autoencoder for spatial dimension reduction of a high-fidelity snapshot matrix constructed from high-fidelity numerical simulations. The reduced latent space after compression is projected to the input variables using a multilayer perceptron (MLP) regression model. The POD-ANN uses proper orthogonal decomposition-based, reduced-order modeling with the artificial neural network to construct a surrogate model between the snapshot matrix and the input parameters. The accuracy and efficiency of both models are compared based on the thermo-mechanical analysis of an AM-built part. A comparison between the statistical moments from the high-fidelity simulations results and the ROMs predictions reveals a good correlation. Additionally, the predictions are compared with the experimental results at different locations. While both models show good comparison with the experimental results, the CAE-MLP predictions have proven to be better performing than those of the POD-ANN.
Analyzing the Experiences of Buruli Ulcer Disease Patients in Nigeria Using the Socioecological Model of Health: A Qualitative Cross-Sectional Study
Authors: Azubuike Precious Chidozie , Onyekachi Ebuka Light , Enyam Michael Obule , Ogbonna Chimankpam Kingsley , Timothy Promise Nmesomachi , Uchegbu Eberechukwu Ruth , Abuo James , Akinreni Temidayo 
Published: August 2024

Abstract

Introduction Buruli Ulcer Disease (BUD) is a debilitating neglected tropical disease caused by “Mycobacterium ulcerans”, predominantly affecting marginalized populations in tropical and subtropical regions, including Nigeria. This study utilizes the socioecological model of health to explore the complex interplay of individual, interpersonal, community, and societal factors shaping the experiences of BUD patients in Nigeria. Previous research has primarily focused on biomedical aspects, often neglecting the sociocultural and environmental dimensions crucial to patient experiences and outcomes.Methods A qualitative cross-sectional descriptive research design was employed, focusing on selected BUD endemic communities in Enugu State, Nigeria. Ethical approval was obtained from the Enugu State University Teaching Hospital’s Research and Ethics Committee. Data collection involved one Focus Group Discussion (FGD) with eight discussants and six Key Informant Interviews (KII), encompassing a diverse group of BUD patients. The WHO Quality of Life-BREF was adapted for data collection, which was conducted by a trained team. Data were analyzed using content analysis to inductively code themes and identify overarching categories.Results At the individual level, participants reported significant physical and psychological impacts, including pain, discomfort, disfigurement, and stigmatization. Interpersonal experiences highlighted social rejection, loss of social roles, and abandonment by family members. Organizational challenges included job loss, reduced productivity, and financial dependence, while community-level experiences ranged from supportive actions to social isolation and discrimination. Participants noted a lack of comprehensive community support, often exacerbated by misconceptions about the disease.Conclusion BUD patients in Nigeria endure considerable negative psychosocial experiences, particularly at the interpersonal and community levels. Enhancing community awareness and support is crucial to mitigating these impacts. Further research should explore family-level psychosocial experiences and other contributing factors to provide a more comprehensive understanding and inform effective intervention strategies.
Seroprevalence of West Nile, Usutu and Tick borne encephalitis viruses in equids from southwestern France in 2023
Authors: Chevalier Noémie , Migné Camille Victoire , Mariteragi-Helle Teheipuaura , Dumarest Marine , De Mas Margaux , Chevrier Manon , Queré Emilie , Marcillaud-Pitel Christel , Lupo Coralie , Bigeard Clément , Touzet Thierry , Leblond Agnès , Durand Benoit , Depecker Marianne , Gonzalez Gaëlle 
Published: August 2024

Abstract

The circulation of West Nile virus (WNV), Usutu virus (USUV) and Tick-borne encephalitis virus (TBEV) was investigated in southwestern France within the first six months of 2023 following the emergence of WNV in equids in Gironde county in 2022. Blood samples were collected from 494 horses located in Gironde County divided into three zones: the Confluence, the Intermediate zone and the Arcachon basin and tested for WNV, USUV and TBEV specific antibodies. An overall seroprevalence of 14% (95% CI [11%-18%]) for orthoflavivirus antibody was detected in Gironde county. The highest seroprevalence rate for WNV and USUV were detected in the Confluence zone (9%, 95% CI, [6%-13%] and 5%, 95% CI, [3%-8%] respectively). The type of housing (animals kept in pasture only) and the distance to the nearest bird special protection area (SPA) were identified as risk factors for WNV seropositivity. This paper presents the first seroprevalence study investigating WNV, USUV and TBEV infections, conducted in equids located on the Atlantic coast of France and demonstrates an intense circulation of WNV in this region of France as well as equine USUV specific infection.
Hierarchical carbon nanofiber/NiCo2O4 composites as electrode for high-performance supercapacitors
Authors: Zhuo Qiqi , Lv Yalou , Wu Hanzhao , Jiang Jintian , Tang Jijun , Yan Chao 
Published: August 2024

Abstract

Carbon Nanofibers (CNFs)/transition metal oxides (TMOs) composites have obtained much attention as supercapacitor electrode with benefits from the superior electrical conductivity of carbon materials and high capacity of TMOs. However, nano-size TMOs is prone to agglomeration and hard to grow efficiently and uniformly on CNFs due to the surface of CNFs lack effective targets, which limits its performance. In this paper, different hierarchical structures of CNFs-NiCo2O4 were prepared and assembled as supercapacitor electrode. The results showed that CNFs-NiCo2O4 prepared by treatment of potassium permanganate exhibited a high capacitance of 1175 F g− 1 at a current density of 1 A g− 1 and long-term cycling stability, with 93% capacitance retention after 3000 cycles. The excellent electrochemical performance could be attributed to that more active sites were introduced on the CNFs after solvent treatment, which were beneficial for NiCo2O4 to grow uniformly on CNFs. This approach provides a new strategy for controllable design and synthesis of homogeneous hierarchical CNFs/TMOs composites.
Bottleneck factors impacting nurses’ workflow and the opportunity to prioritize improvement efforts: Factor analysis
Authors: Al-Moteri Modi , Aljuaid Jamil , Alsufyani Bander , Alghamdi Amnah , Althobiti Ensherah Saeed , Althagafi Abdulslam 
Published: August 2024

Abstract

Purpose
Minimizing delays in delivering nursing care is paramount for enhancing the overall quality of care. Certain bottleneck variables restrict the workflow of nurses, resulting in extended shift times. This study is designed to pinpoint and analyze the principal factors contributing to bottleneck issues in nursing workflow, to direct improvement endeavors. This study seeks to provide insights into the key variables contributing to nurses' extended shift times, with the ultimate goal of prioritizing efforts for improvement.
Methods
A descriptive multicenter cross-sectional study was conducted. A scale was developed for this study by the authors after conducting a literature review, subsequently validated, and its reliability was assessed.
Results
Among the 31 bottleneck variables, 29 were retained under three bottleneck factors: (1) Nurse staffing— This pertains to the availability of sufficient nursing staff at all times across the continuum of care; (2) Working environment and quality of care—This refers to the availability of necessary skills and resources for nurses to perform their duties effectively and; (3) Medical devices— This factor concerns the availability of fully functional medical devices required for providing care.
Conclusion
Efforts aimed at enhancing the overall healthcare system should concentrate on addressing bottleneck factors. This may involve the implementation of a healthcare workforce management system, the establishment of standards for a conducive and supportive working environment, and the utilization of a standardized system for the management of medical equipment. The outcomes of this study can be utilized by nurses and policymakers to devise comprehensive strategies for improvement.
Let us Unveil Network Intrusion Features: Enhancing Network Intrusion Detection Systems via XAI-based Feature Selection
Authors: Arreche Osvaldo , Guntur Tanish , Abdallah Mustafa 
Published: August 2024

Abstract

Explainability and evaluation of AI models are crucial parts of the security of modern intrusion detection systems (IDS) in the network security field, yet they are lacking. Accordingly, feature selection is essential for such parts in IDS because it identifies the most paramount features, enhancing attack detection and its description. In this work, we tackle feature selection problem for IDS via suggesting new ways of applying eXplainable AI (XAI) methods for this problem. We identify the crucial attributes originated by distinct AI methods in tandem with novel five attribute selection methods. We then compare many state-of-the-art feature selection strategies with our XAI-based feature selection methods, showing that most AI models perform better when using the XAI-based approach proposed in this work. By providing novel feature selection techniques and establishing the foundation for several XAIbased strategies, this research aids security analysts in the AI decision-making reasoning of IDS by providing them with a better grasp of critical intrusion traits. Furthermore, we make the source codes available, thus the community may develop additional models on top of our foundational XAI-based feature selection framework.
Effects of wind speed, spacing distance and length-width ratio of burner on flame merging and heat transfer of two-line fires
Authors: Huang Xinjie , Hu Junjie , Ding Hailong 
Published: August 2024

Abstract

This paper investigates the effects of wind speed(V=0.25, 0.5 and 0.75 m/s), length-width ratio(n=5,8,10,15,20,25,30 and 40) and spacing distance(0, 10, 20 and 30 cm) on the burning and flame merging characteristics of two-line fires fueled by n-heptane. Experimental results indicate that the flame merging probability Pm decreases gradually with the increasing length-width ratio. Meanwhile, Pm shows an increasing trend with the groove length(L).The correlation between P m with n and L is found. On the other hand, it is found that,flame height and length decrease with the increasing length-width ratio.The flame height and length of upstream flame are smaller than those of downstream flame for different length-width ratios, at the same n and V. With the length-width ratio increase, the flame inclination angle will increase, and that of upstream flame is consistently smaller than that of downstream flame. Based on heat transfer analysis, under the influence of wind speed, the m '' is closely related to (L+W)/LW, showing an increasing trend with length-width ratio.With the increase of spacing distance, the ṁ '' of downstream flame will be larger, equal and then smaller than that of upstream flame.
Fusing Deep Separable Networks for Emotion Recognition in Complex Environments
Authors: Wan Zheng-Hao , Wu Chun-Lei , Tong Si-Yuan , Qiu Shi-Yu 
Published: August 2024

Abstract

This research is dedicated to addressing the challenges of model training and application implementation in the field of traditional face emotion recognition. The proposed scheme is a lightweight facial emotion recognition system based on deep separable networks. The scheme optimizes the Xception network structure in three stages. Initially, the residual module and the deep separable module are combined in order to enhance the efficiency of feature extraction. Subsequently, global average pooling is employed in lieu of the traditional fully connected layer, thereby reducing the number of parameters. Finally, the channel information is integrated through the 2×2 convolution and the point-by-point convolution, which effectively minimizes the loss of information while retaining more valuable feature information. The solution employs the Fer2013 dataset from the Kaggle platform for training with the objective of enhancing the accuracy of emotion recognition in diverse and complex environments within a simulated real-world setting. Furthermore, the objective is to develop a lightweight model that can be deployed in practical applications. The recognition accuracy has now reached an industry-leading level. Moreover, the project has developed a face emotion recognition system that has been validated through the construction of a real-time vision system. This system is capable of completing the tasks of face detection and emotion classification in complex environments, thus providing a solid foundation for the practical application of emotion recognition technology. The source code for the proposed method will be available at https://github.com/Alex-star-arch/Fusing-Deep-Separable-Networks-for-Emotion-Recognition-in-Complex-Environments.
Prediction of Yearly Mean Sunspot Number using Machine Learning Methods
Authors: Paraskakis Nikolaos , Hristopulos Dionissios T. 
Published: August 2024

Abstract

The number of sunspots is an important indicator of solar activity, which has an impact on space weather and the Earth’s climate. Hence, sunspot number prediction is an integral part of solar cycle monitoring for the National Aeronautics and Space Administration, the European Space Agency and other space and environmental agencies. The advent of novel machine learning tools creates new opportunities for modeling and prediction of time series datasets. This paper compares predictions of the yearly sunspot number with three different machine learning methods in terms of prediction performance, computational speed, and interpretability. The methods explored involve a stochastic approach (Gaussian process regression), a method based on decision trees (Light gradient boosting machine), and a long-short-term memory neural network. The relative strengths and weaknesses of each method are discussed.
Immunomodulatory effects of albendazole, trichlorobendazole and wortmannilactone F on Clonorchis sinensis infection
Authors: Duan Guihua , Zhang Baoyue , Gong Xiarong , Xun Linting , Zhao Xueru , Li Yongli , Song Zhengji 
Published: August 2024

Abstract

Background
Albendazole, trichlorobendazole and wortmannilactone F are widely used anti-trematode drugs to treat fluke worm infections. However, their immunomodulatory effects and hepatic toxicity in Clonorchis sinensis infection treatment are unknown. This study evaluated the regulatory effects of these anti-helminthic drugs on hepatic fibrosis and immune responses in the rat model of Clonorchis sinensis infection.
Methods
Sprague-Dawley rats were infected by Clonorchis sinensis thorough gavage. Hematoxylin and Eosin (H&E) and Masson staining were performed to examine the degree of hepatic injury and fibrosis. Plasma levels of glutamic-pyruvic transaminase and albumin were analyzed by ELISA. Flow cytometry was used to detect the frequency of immune cells in the blood sample upon different drug treatments.
Results
Fecal examination showed that the administration of trichlorobendazole and wortmannilactone F could effectively eliminate the parasites, and albendazole was also able to reduce the parasite load. Albendazole had little damage to the liver tissues, while wortmannilactone and triclorobendazole could induce severe hepatic damages. Masson staining further revealed high level of hepatic fibrosis after wortmannilactone F and triclorobendazole treatment, which was accompanied by the increased CK-19 keratin expression after wortmannilactone F treatment. Albendazole administration was able to reduce the plasma level of IL-2 and decrease the proportion of CD4 + and CD8 + T lymphocytes in the blood, while the other two drugs failed to do so.
Conclusion
Wortmannilactone F and triclorobendazole showed strong anti-parasitic effect against Clonorchis sinensis infection, but induced severe liver damages. Albendazole could reduce parasite load and also showed immunomodulatory effect.
Process evaluation of the FluCare cluster randomised controlled trial: Assessing the implementation of a behaviour change intervention to increase influenza vaccination uptake among care home staff in England
Authors: Katangwe-Chigamba Thando , Alsaif Faisal , Anyiam-Osigwe Adaku , Bion Veronica , Clark Allan , Garrett Hilary , Griffiths Alys Wyn , Guillard Cecile , Hammond Amber , Holland Richard , Jones Liz , Patel Amrish , Pitcher Jennifer , Risebro Helen , Scott Sion , Seeley Carys , Sims Erika J. , Stirling Susan , Wagner Adam P , Wright David J , Birt Linda 
Published: August 2024

Abstract

Background
Care home staff (CHS) influenza (flu) vaccination rates in England are consistently lower (≈ 15% in 2023) than World Health Organisation recommendations (≥ 75%). The FluCare trial examined the effectiveness of a multi-component intervention (including on-site flu vaccination clinics, information materials including video, £850 incentive and monthly monitoring with feedback) designed to address known barriers to flu vaccine uptake amongst CHS. This paper reports an embedded process evaluation designed to understand implementation of the FluCare intervention and provide explanations for observed effects in the trial.
Methods
The FluCare trial was conducted between November 2022 and March 2023. A mixed methods process evaluation was conducted employing questionnaires, semi-structured interviews, video analytics (no. clicks and duration of view) and clinic logs (no. clinics delivered, days/time clinics were delivered, and no. staff vaccinated). CHS (including managers) and vaccination providers (pharmacists, nurses and general practitioners) were purposively and conveniently selected, respectively, for the interviews. Descriptive statistics were obtained for quantitative data, and qualitative data were analysed thematically.
Results
FluCare intervention implementation varied across CHs, with clinics and videos not being implemented in 35% and 43% of the intervention CHs respectively. In addition, clinic days and times varied depending on provider (pharmacy or general practice) and CH. Partial intervention implementation was partly influenced by managers’ engagement and sub-organisational cultures marked by negative narratives around vaccines. Contextual barriers included delivery of clinics late in the flu season. A greater indication of implementation fidelity was positively associated with change in staff attitudes and behaviours, with some getting vaccinated for the first time.
Conclusions
Variation in implementation of the FluCare intervention provides an explanation for detecting a difference where the intervention was fully implemented in the main trial. Manager and leader engagement is vital for both successful implementation and staff engagement. Avoidable contextual barriers, such as late timing of clinics, must be addressed to enhance flu vaccination uptake by CHS. More work is needed to understand the role of CH leaders in influencing intervention implementation, sub-organisational cultures and vaccination attitudes.
Trial registration
ISRCTN ISRCTN22729870. Registered on 24 August 2022
Performance Analysis of Pipe-Jacking Waste Soils Solidified with Cement under Balanced Earth Pressure Conditions
Authors: Youjun Xu , Zhenyu Li , Zhigang Chen , Huichao Han , Minghao Yan 
Published: August 2024

Abstract

The utilization of pipe-jacking soil poses challenges due to its complex composition, which comprises polyacrylamide (PAM) and sodium bentonite (Na-Ben) surfactants, hindering drainage and solidification. Improper handling may induce environmental pollution. To address this problem, cement solidification was explored after modification with PAM and Na-Ben. By performing indoor resistance tests, freeze–thaw cycles, wet–dry cycles, SEM, XRD, and IR experiments, it was found that within certain ratios, cement solidification effectively stabilizes pipe-jacking waste soil. Specifically, PAM minimally impacts pipe-jacking waste-soil strength, whereas Na-Ben slightly reduces it. Microscopic analysis revealed that although water absorption hinders hydration reactions, PAM (at lower concentrations) promotes mineral particle cohesion during cement solidification. Na-Ben tends to aggregate, leading to uneven internal structure and inhibiting cementitious product formation