bluuebunny/crossref_metadata_2025 huggingface dataset:
Is a Large Neck Circumference a Risk Factor for Male Infertility in the Turkish Population?
Authors: Dursunoglu Duygu
Published: November 2023

Background
Currently, the potential role of obesity on semen quality has not yet been fully elucidated. In recent years, alternative anthropometric measurements to body mass index (BMI), which more reflect of body fat distribution, have been established to estimate central adiposity. The association between neck circumference (NC), a novel index of central adiposity, and semen quality has not been explored yet.
Objective
The present study aimed to reveal the potential of NC to predict male infertility.
Subjects and Methods:
This is a cross-sectional study including 4739 male participants aged 17–55 years. Semen parameters included sperm concentration, total count, total motility, progressive motility, rapid progressive motility and vitality. As anthropometric measurements of obesity, BMI and central obesity indices including waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHpR), waist-to-height ratio (WHtR) and NC were examined. The predictive potentials of obesity indices for low semen parameters were evaluated by Receiver Operating Characteristics curve analysis. The associations of obesity indices with semen parameters were analyzed by binary logistic regression analyze after adjusting potential confounders.
Results
Patients with lower semen parameters had higher anthropometric obesity indices than those with normal parameters. The obesity indices had predictive potentials for low semen parameters, excluding WHpR for sperm concentration and, BMI and HC for rapid progressive motility. After adjusting for confounders, the strongest associations were found between HC with sperm count parameters, WC and WHtR with sperm vitality and motility parameters and NC with rapid progressive motility (OR: 2.37, 95% CI: 2.02–2.79, p < .001).
Conclusions
Obesity, particularly central obesity plays important a role in male infertility. The distribution of adipose tissue appears to may have specific roles on sperm functions, resulting in different fertility markers may be affected. A larger NC may be a risk factor for male infertility, specifically low sperm rapid progressive motility.
Opinion of Polish doctors on the use of futile therapy
Authors: Damps Maria , Gajda Maksymilian , Wiktor Łukasz , Byrska Elżbieta Maciejasz , Rybojad Beata , Kowalska Małgorzata , Śniatkowska Alicja Bartkowska , Paprocka Anna Lipińska , Kucewicz Ewa Czech
Published: November 2023

Discontinuation of futile therapy is increasingly discussed in Polish clinical practice. Taking into account the broadly understood well-being of the patient, it is necessary to consider whether all clinical options resulting from medical progress should be used for every patient and on what grounds decisions to limit therapy should be based. Our study aimed to know the opinion of Polish medical staff on the topic discussed. The study was an anonymous survey conducted in paper and electronic versions among doctors of all specialties. An analysis of the collected data was carried out using the methods of descriptive and analytical statistics. The respondents were divided into two groups according to their specialization: intensivists and doctors of other specializations. A total of 323 doctors participated in the study; ​93% of participants were aware of the problem of futile therapy in adults (statistically, significantly more often intensivists, p = 0.002); 95% of respondents supported the idea of discontinuing futile therapy, and over 68% of respondents used the therapy discontinuation protocol. Among the most common reasons for undertaking futile therapy, the respondents declared (more than one answer was possible) fear of legal liability for not taking such action (93.5%), as well as fear of being accused of unethical behavior (62.2%), and fear before talking to the patient/patient’s family and their reaction (57.9%). The respondents also indicated what would facilitate making decisions about limiting futile therapy. These were primarily: precise qualification criteria for limiting therapy and education in this area (95.3%), the patient's declaration of will (87.5%), and a clear legal act (81.3%). The vast majority of study participants supported the idea of limiting futile therapy, and this issue is well-known to Polish doctors.
Novel Insights into the Exact Solutions of the Modified (3+1) Dimensional Fractional KS Equation with Variable Coefficients
Authors: CR Jisha , Jang Bongsoo
Published: November 2023

This study comprehensively explores a unified methodology for deriving exact solutions to the fractional modified (3+1) dimensional Kudryashov-Sinelshchikov (KS) equation featuring variable coefficients. The fractional KS equation, which incorporates fractional local M-derivatives, presents a significant challenge because of its inherent nonlinearity and the introduction of spatially varying coefficients. Of paramount importance are these variable coefficients, as they introduce spatial dependence and intricately capture spatial variations within the equation. This complexity in spatial variation poses a formidable challenge in obtaining exact solutions. Our analytical examination offers profound insights into the intricate interplay between diverse variable coefficients and fractional parameters. This comprehensive analysis greatly enhances our capacity to interpret solutions across various scenarios, enriching our understanding of the nuanced behavior exhibited by the fractional Kudryashov-Sinelshchikov equation. Our investigation encompasses a diverse range of solution forms, including fractional, polynomial, exponential, and others. The outcomes of this study hold profound implications for an extensive array of scientific domains, spanning mathematical physics, fluid dynamics, and nonlinear optics. Furthermore, this research employs advanced data visualization techniques, comprising 3D plots, contour plots, and stream plots, to facilitate a deep comprehension of intricate physical phenomena. These visual aids concurrently illustrate how analytical solutions are influenced by varying conditions.
Ams classification 2010: 45K05, 45G10, 83C15, 35Q35, 35Q68 , 35Q80
Analysis and optimization method of influencing factors for three-dimensional target mixed pixels under zero meteorological view distance
Authors: Wang Jun-Feng , LIU XIAO , CHEN Zhen-Ting , LIU GANG
Published: November 2023

Mixed pixels widely exist in the obtained hyper-spectral data,which directly affects the accuracy of optical remote sensing imaging simulation. Aiming at the three-dimensional target under zero meteorological view distance, this paper comprehensively considers the effects of directional reflection characteristics, geometric shadows and background radiation on the generation of mixed pixels.It proposes a method of modeling mixed pixels by taking each surface of a three-dimensional target as an end element component and using the weight coefficient of the distance between the end element groups to the view center. Through designing experiments to simulate different influence conditions such as directional reflection, geometric shadow and background radiation, this paper verifies the influence of the radiation value of the mixed pixels of the three-dimensional target produced by different mixing conditions in the single-pixel field of view. The experimental results show that directional reflection characteristics, geometric occlusion shadows and background radiation have significant effects on the generation of mixed pixels for the three-dimensional targets. The improved mixed pixel modeling method proposed in this paper considering the influence of multiple factors has an average error of less than 10% in modeling accuracy of three-dimensional targets, which is significantly better than traditional linear modeling methods. It can be seen that the research results of this paper have good reference significance for the research of the three-dimensional target mixed pixel radiation model.
Industrial-scale nonmetal current collectors designed to regulate heat transfer and enhance battery safety
Authors: Mai Liqiang , Li Lun , Yang Jinlong , Tan Rui , Shu Wei , Low CheeTong John , Zhang Zixin , Zhao Yu , Li Cheng , Zhang Yajun , Li Xingchuan , Zhang Huazhang , Zhao Xin , Kou Zongkui , Xiao Yong , Verpoort Francis , Wang Hewu , He Daping
Published: November 2023

Safety concerns have become a long-lived challenge that impedes the industrial implementation of high-energy lithium-ion batteries (LIBs). The major safety issue, known as thermal runaway, is triggered by the local thermal aggregation caused by slower heat dissipation than that of heat generation inside the battery. However, how to improve the internal heat transfer is challenged by the low thermal conductivity of metal current collectors (CCs) and the scalable manufacturing of nonmetal CC foils. Here we report a fast thermoresponsive non-metallic CC that can substitute the benchmark metal CCs, i.e., Al and Cu foils, to regulate heat transfer and considerably enhance battery safety. The non-metallic CC was fabricated using graphene (Gr) oxide through a continuous thermal pressing process to afford a dense and defect-free Gr foil of at a hundred-meter level. This Gr foil demonstrates ultra-high thermal conductivity of up to 1400.8 W m− 1 K− 1, about one order of magnitude higher than those of Al and Cu foils. Importantly, tangible LiNi0.8Co0.1Mn0.1O2|| graphite pouch cells integrated with these fast thermoresponsive foils show faster heat dissipation, eliminating the local heat concentration and circumventing the fast exothermic aluminothermic and hydrogen-evolution reactions, which are critical factors causing the thermal failure propagation of LIB packs with Al CCs. Fast thermoresponsive and light weight Gr CC enable LIBs to operate with increased output energy and survive under extremely harsh abuses.
Integral representations for products of two solutions of theAiry equation with shifted arguments and their applications in physics
Authors: Bazarov Kirill V. , Tolstikhin Oleg I.
Published: November 2023

Integral representations for acomplete set of linearly independent products of two solutions of the Airy equation whose arguments differ by z_0 are obtained using the Laplace contour integral method. This generalizes similar integral representations for the case z_0=0 obtained by Reid.The relation to other previous results is discussed. The results are used to obtain the outgoing-wave Green's function for an electron in a static electric field in a closed analytic form.
Mathematics Subject Classification (2010). Primary 33C10; Secondary 30E20
Detection of Osteosarcoma using Deep Feature Extraction with Federated Learning and MLP from Histopathological Images
Authors: Chowdhury Anjir Ahmed , Mahmud S M Hasan , Elahe Md. Fazla , Jahan Hosney , Shoombuatong Watshara , Mahmud Mufti
Published: November 2023

Background: The most common type of cancerous bone tumour is Osteosarcoma. Microscopic analysis of coloured slides is mostly used for Osteosarcoma diagnosis. As Osteosarcoma is highly heterogeneous, pathologists struggle to get a consensus diagnosis. Moreover, manual analysis of microscopic images is laborious, time-consuming, and vulnerable to bias.
Method: In this research, a framework that extracts features based on CNN is developed to predict Osteosarcoma to address previous studies' performance gaps and shortcomings. The dataset used for this experiment is obtained from pathology archives at Children's Medical Center in Dallas, which includes 1144 histology glass slides. First, data augmentation is used to extend the dataset size. This study found Blur, Contrast, and Random augmentation perform well for the Osteosarcoma dataset. Next, we primarily considered six pre-trained transfer learning (TL) models and modified the models to extract features. Then, we examined feature selectors like Genetic Algorithm, Principal Component Analysis, Recursive Feature Elimination and Baruto and found PCA selects the optimal feature set. Finally, we fed the selected features into a fine-tuned MLP called Grid search MLP (GsMLP) and utilised federated learning (FL) to ensure the diversity and privacy of the dataset.
Results: Experiments have revealed that the modified Xception model performs better in extracting features for Osteosarcoma prediction. Also, the proposed framework performed better than state-of-the-art techniques such as Convolutional Neural Network, VGG19, Random Forest, and AdaBoost with 98.20% accuracy and 97.5% Receiver Operating Characteristic - Area Under the Curve.
Rituximab improves Clinical Outcomes of CAR-T therapy for r/r B-ALL via sensitizing Leukemia Cells to CAR-T-mediated cytotoxicity and reducing CAR-T exhaustion
Authors: Li yangzi , Cui Qingya , Liu Sining , Liu Lingling , Li Mengyun , Zhu Xiaming , Kang Liqing , Yu lei , Cui Wei , Tang Xiaowen , Wu Deipei
Published: November 2023

Despite chimeric antigen receptor (CAR) T-cell therapy has achieved great advances in recent year, approximately 50% of relapsed/refractory B cell acute lymphoblastic leukemia (r/r B-ALL) patients treated with CAR-T experience relapse 6 months post CAR-T treatment. CD20 express on 30 to 50% of B-ALL, which makes CD20 Monoclonal Antibody as one of the potential therapy strategies to decrease the tumor burden and improve the efficacy of CAR-T therapy. Adding Rituximab to chemotherapy protocol had been demonstrated to improve the outcome for CD20-positive ALL. However, rare study explored the influence of Rituximab combined with CAR-T therapy. We retrospectively analyzed 20 r/r B-ALL patients who received CAR-T therapy, all of whom had failed multiple lines of therapy. Before CAR-T infusion, we administered Rituximab to 10 patient with high CD20 expression at a dose of 375mg/m2 for 1 day. Meanwhile, we selected 10 patients with the comparable features who underwent CAR-T treatment without Rituximab in the same period as the control group. In vitro, the surface molecule expression and killing of CAR-T post Rituximab-treated B-ALL cells co-incubated with CAR-T cells were detected by flow cytometry. Rituximab combined with CAR-T therapy was effective for improving the long-term outcome of B-ALL patients who have failed multiple lines of therapy. In vitro, we observed that rituximab potentially improved CAR-T efficacy by sensitizing Leukemia Cells to CAR T-mediated cytotoxicity and reducing CAR-T exhaustion.
Primary low-grade endometrial stromal sarcoma of the ovary with mesenteric metastasis: An unusual case report
Authors: Yuan Jun , Fu Yajun , Jiang Xiaohong , Li Na
Published: November 2023

Background
Low-grade endometrial stromal sarcoma (LGESS) accounts for only 0.2% of gynecological malignancies. Primary low-grade extrauterine endometrial stromal sarcoma (LGEESS) is rare, its morphology varies according to the location of the tumor, posing a great diagnostic challenge for clinical pathologists.
Case presentation: A 46-year-old female patient with bilateral ovarian cysts and multiple uterine fibroids underwent ovarian cystectomy and uterine myomectomy in 2013. Color Doppler ultrasound showed multiple uterine fibroids and bilateral ovarian cysts (left: 74×74×64 mm, right: 26×22 mm). Laboratory tests showed an elevated squamous cell carcinoma (SCC) associated antigen. The patient subsequently underwent a total hysterectomy and bilateral salpingo-oophorectomy (BSO). The intraoperative pathological results were diagnosed as benign ovarian cysts. Combined with morphological, immunohistochemistry, and molecular results of the paraffin section, LGEESS is the final diagnosis.
Conclusion
We made a comprehensive case report on the clinicopathological features of LGEESS to provide references for clinical pathologists to avoid misdiagnosis or missed diagnosis in the work.
Chinese Ancient Paintings Inpainting Based on Edge Guidance and Multi-Scale Residual Blocks
Authors: Sun Zengguo , Lei Yanyan , Wu Xiaojun
Published: November 2023

Chinese paintings have great cultural and artistic significance, known for their delicate lines and rich textures. Unfortunately, many ancient paintings have been damaged due to historical and natural factors. The deep learning methods that are successful in restoring natural images cannot be applied to ancient paintings inpainting. Thus, we propose a model named Edge-MSGAN for inpainting Chinese ancient paintings based on edge guidance and multi-scale residual blocks. The Edge-MSGAN utilizes edge images to direct the completion network for generating entire ancient paintings. It then applies the multi-branch color correction network to adjust the colors. Furthermore, the model uses multi-scale channel attention residual blocks to learn the semantic features of ancient paintings at various levels. At the same time, by using polarized self-attention, the model can improve its concentration on significant structures, edges, and details, which leads to paintings that possess clear lines and intricate details. Finally, we have created a dataset for ancient paintings inpainting, and have conducted experiments to evaluate the model’s performance. After comparing the proposed model with the state-of-the-art models from qualitative and quantitative aspects, it is found that our model is better at inpainting the texture, edge, and color of ancient paintings.
RETRACTED: Machine Learning-enhanced Empirical Study of Five Stock Indices in the Concept of Indian Financial Market
Authors: Ghosh Prokarsha
Published: November 2023

The authors have requested that this preprint be removed from Research Square.
Ransomware Detection with CNN and Deep Learning Based on Multiple Features of Portable Executable Files
Authors: Yang Chia-Cheng , Hsu Jia-Ming , Leu Jenq-Shiou , Hsieh Wen-Bin
Published: November 2023

Due to the epidemic, many industries need to rely on computers to perform necessary tasks. In case of a ransomware attack, the consequences are unimaginable. In order to avoid ransomware attacks, many researchers have proposed large number of methods to distinguish between benign programs and ransomware, but ransomware keeps changing, making these methods gradually ineffective and leaving the virus attacks unresolved. This study collected 1200 samples of ransomware with 80 families, includes packed, encrypted, and variants, so that the models could protect against variants of ransomware. Based on the DLL, Subsystem, Subsystem Version, N-gram as features, we made three deep learning models that could support variable shape size. After experiments, the best model Accuracy was 99.77%, Recall was 99.72%, and Precision was 99.81% We also designed a program that could load the completed models, and provide users with the ability to scan their own computers so that they could be protected from ransomware.
2010 MSC: 00-01, 99-00
Forest Fire Monitoring System Supported by Unmanned Aerial Vehicles and Edge Computing: A Performance Evaluation Using Petri Nets
Authors: Sabino Arthur , Lima Luiz Nelson , Brito Carlos , Feitosa Leonel , Caetano Marcos F. , Barreto Priscila Solis , Silva Francisco Airton
Published: November 2023

Forest fires cause damage to life, biodiversity, and properties, affecting natural ecosystems, healthy and only. During the practical application of fire prevention, numerous detection techniques have been thoroughly researched to prevent devastating fires. The techniques improve early fire detection and accelerate emergency response, reducing damage and optimizing system containment operations. Wildfire detection requires a robust infrastructure for equipment, maintenance, and ongoing monitoring. Effective cooperation between components and integration of technologies is key to a consistent and comprehensive response to fires. This article proposes a fire monitoring system using drones, cameras, and edge computing technologies. We use Stochastic Petri Nets (SPN) to model the structure and evaluate the system's performance. The model is parameterizable, allowing adjustments to the components' resource capabilities and service time. Twenty-four parameters can be defined, making it possible to evaluate a wide variety of different scenarios. The results obtained in different scenarios in this work have the potential for auxiliary administrators of monitoring systems to estimate more than six analyses and plan more optimized architectures as needed.
DV-Hop localization algorithm based on SSA and PSO cooptimization
Authors: 余 修武 , 曹 群丹 , 刘 永
Published: November 2023

The ability to obtain the exact location of nodes in a wireless sensor network is crucial for practical applications. The data is not meaningful if the detected data does not accompany its location. Distance-free localization techniques are beneficial to overcome the hardware limitations of sensor nodes and to avoid expensive distance-based techniques. DV-Hop is a distance-free localization algorithm that is well known for its simplicity. However, due to its poor accuracy and its low safety profile. In this paper, the particle swarm algorithm (PSO) and the squirrel search algorithm (SSA) are used to predict the unknown node bits. The particle swarm algorithm has the advantage of individual memory, and through the particle bit update and individual flying mouse position adjustment, the mouse search algorithm is more memorable when optimized. The performance of our proposed algorithm is compared with the performance of existing localization algorithms (including DV-Hop, PSODV-Hop, GADV-Hop, and SSADV-Hop). Extensive simulations show that our proposed new wireless sensor network; Particle population algorithm;Squirrel search algorithm; DV-Hopalgorithm far outperforms other existing algorithms because it achieves higher localization accuracy and effectively reduces the localization error.
Channel Spatio-temporal Convolutional Network for Pedestrian Trajectory Prediction
Authors: Lu Zhonghao , Luo Yonglong , Xu Lina , Hu Ying , Zheng Xiaoyao , Sun Liping
Published: November 2023

Accurate and timely prediction of the future path of agents in the vicinity of an agent is the core of avoiding conflict in automated applications. The traditional method based on the RNN model requires high computational cost in the prediction process, especially for long-series prediction. In order to obtain a more efficient and accurate prediction trajectory, a channel spatio-temporal convolutional network framework, CSTCN, is proposed in this paper. The framework models the spatial environment as a block of data input to the CSTCN and captures spatio-temporal interactions using an improved temporal convolutional network. Compared with the traditional model, the spatial and temporal modeling of the proposed model is calculated in each local time window so that it can be executed in parallel to obtain higher computational efficiency. Experimental results on five trajectory prediction benchmark datasets demonstrate that the proposed model is superior to the other seven state-of-the-art models in efficiency and accuracy.
YOLO-CSM based components defect and foreign object detection on overhead transmission lines
Authors: Liu Chunyang , Ma Lin , Sui Xin , Guo Nan , Yang Fang , Yang Xiaokang , Huang Yan , Wang Xiao
Published: November 2023

Detecting component defects and attaching tiny-scaled foreign objects to the overhead transmission lines are critical to the national grid’s safe operation and power distribution. The urgent task, however, faces challenges such as the complex working environment and the massive amount of workforce investment, for which we propose a deep-learning-aided object detection approach, YOLO-CSM, to address the issue. Combined with two attention mechanisms (Swin Transformer and CBAM) and an extra detection layer, the proposed model can effectively capture global information and key visual features and promote its ability to identify tiny-scaled defects and distant objects in the visual fields. In order to validate this model, this work consolidates a dataset composed of public images and our field-taken picture samples. The experiment verifies the YOLO-CSM as a suitable solution for small and distant object detection that over-performs several well-used algorithms, featuring a 16.3% faster detection speed than YOLOv5 and a 3.3% better detection accuracy than YOLOv7. Finally, this work conducts an interpretability experiment to reveal the similarity between YOLO-CSM’s attention patterns and that of our humans, aiming to explain YOLO-CSM’s advantages in detecting small objects and minor defects in the working environments of power transmission lines.
Topological properties of the space of integrable Henstock-Kurzweil vector distributions.
Authors: Escamilla-Rocha Homero , Alanís-López Lilia , Escamilla-Reyna Juan Alberto
Published: November 2023

In this work, we prove that the space of integrable Henstock-Kurzweil vector distributions denoted as DHK([a,b],X) has a complemented copy of c0. We show conditions for DHK([a,b],X) to have a complemented copy of l1 and a copy of l∞. We also give conditions for DHK([a,b],X) to have property (V) and the Dieudonné property. Furthermore, we prove that DHK([a,b],X) does not have property (u).
Mathematics Subject Classification (2010). Primary 26A39, 58A30; Secondary 46B03, 46B04.
Geographical Complexity, Fiscal Decentralization, and Equalization of Regional Basic Public Services
Authors: Liu Jianghao , Song Meizhe
Published: November 2023

Scholars often overlook the complexity of the terrain, an important factor influencing the equalization of regions’ basic public services. This study utilizes data from 278 prefecture-level cities in China from 2011 to 2021. It employs the ASTER GDEM 30M resolution digital elevation data to identify and extract terrain complexity characterized by slope, elevation, and topographic variation. It empirically examines the terrain complexity’s impact on the equalization of regions’ basic public services and its underlying mechanisms. The results reveal that as terrain complexity increases, the equalization level of regions’ basic public services decreases. The mechanism analysis infers that terrain complexity aggravates the degree of fiscal decentralization, resulting in a wider disparity of basic public services among regions. Additionally, the exploratory analysis divulges that the expansion of communication networks augments the complex terrain’s impact on widening regional disparities in basic public services.
Analysis and Improvement of Machine Learning Models for Detecting Street Lighting Lamps
Authors: Silva Igor Caetano , Salgado Ricardo Menezes , Varejão Igor Mattos , Varejão Flavio Miguel
Published: November 2023

The Brazilian public lighting network is maintained by city halls. To bill the energy provided to city halls, energy distribution companies should maintain an updated database of network poles, their lamp types, and wattages. However, it is common to encounter issues with misinformation, where the company is not notified about changes in the public lighting network by city halls and cannot update its database appropriately. To mitigate commercial losses, companies have resorted to sending teams for manual infrastructure checks, which is an expensive, time-consuming, and unreliable process. In this regard, this work aims to optimize the models proposed in the literature capable of accurately classifying the type and wattage of lamps on public lighting poles based on data collected from radiometric sensors and a professional camera. Data is processed using traditional machine learning and deep learning algorithms, along with more sophisticated validation techniques such as data transformation and hyperparameter optimization to achieve improved results. Based on this methodology, the results demonstrate that models employing more robust algorithms (Support Vector Machine, XGBoost, Random Forest, and Multilayer Perceptron) can attain a final average accuracy of 80-86%. This confirms the usefulness of this methodology as an alternative solution to address the issue of public lighting billing.
DYE-SENSITIZED SOLAR CELLS (DSSC): AN APPROACH TO PRACTICE IN UNDERGRADUATE TEACHING
Authors: Moreira Jeniffer , dos Santos Karine , Garcia Matheus , Rodrigues Raphael , Sequinel Thiago , Roman Daiane , de Carvalho Cláudio
Published: November 2023

The aim of this work was to construct and characterize dye-sensitized solar cells (DSSC) using alternative materials and low-cost equipment. Instead of using the TiO2 semiconductor, a water-based white paint pigment was employed as a substitute. This pigment, when combined with natural dyes, absorbs visible light and acts as the photoelectrode. Pencil graphite was utilized to create the conductive layer, serving as the positive electrode. Lugol’s solution was employed as the electrolyte to establish electrical contact between the two electrodes. These materials were assembled between two glasses with a conductive surface made of tin oxide doped with fluorine (FTO glass). Subsequently, the assembled devices were exposed to three types of lamps: daylight (45 W), LED (15 W), and halogen (105 W), all positioned at the same height as the solar cell. Voltage and current measurements were taken using a simple multimeter. These results enabled the correlation of theoretical concepts related to absorption (dye) and light emission (lamp) ranges, different types of anchoring groups, and the dye-semiconductor anchoring mode. The voltage and current production were found to depend on the type of lighting source. However, it became evident that several factors beyond those mentioned strongly influenced the energy production mode of the solar cell.
Production analysis of manufacturing industry in a single vacation policy under disaster
Authors: S Jeyakumar , B Logapriya
Published: November 2023

The disaster in queueing system with second optional service is considered. Arriving customer of this system will receive the essential service and optional second service if needed. When the system is interrupted by the disaster, the server initiates the repair period making all the customer leave the system immediately. The server, when idle, takes single vacation. The disaster cannot happen when server is under vacation or in repair period. The above queueing system is analysed using supplementary variable technique to obtain the probability generating function for various parameters and effects of parameters are explained graphically with numerical illustrations.
A GPU-based hydrodynamic numerical model for urban rainstorm inundation simulations
Authors: Han Hao , Hou Jingming , Jin Zhao , Luo Pingping , Li Guodong , Zhang Ye , Gong Jiahui , Luo Da , Yang Siqi
Published: November 2023

The response capacities of urban flood forecasting and risk control can be improved by strengthening the computational abilities of urban flood numerical models. In this work, a GPU-based hydrodynamic model is developed to simulate urban rainstorm inundations. By simulating rainstorm floods in a certain area of Xixian New City, the established model can implement high-resolution urban rainstorm inundation simulations with significantly accelerated computing performances. The accelerated computation efficiencies of the different rainstorm event simulations under resolutions of 5 and 2 m are quantitatively analysed, showing that the absolute and relative speedup ratios for all scenarios of applying two GPUs range from 10.8 to 12.6 and 1.32 to 1.68 times as much as those of a CPU and a single GPU, respectively. The application of a large-scale rainstorm inundation simulation shows the excellent acceleration performance of the model compared to previous research. In addition, the greater the number of computational grids included in the simulation, the more significant the effect on the acceleration computing performance. The proposed model efficiently predicts the spatial variation in the inundation water depth. The simulation results provide guidance for urban rainstorm inundation management, and they improve the time and efficiency of urban flood emergency decision-making.
A new evaluation framework for the assessment of wastewater heat recovery potential coupled with wastewater reuse
Authors: Ramadhan Eza , Oh Jeill
Published: November 2023

The integration of wastewater heat recovery (WWHR) and wastewater reuse offers a numerous advantage, making its application possible in various sectors. Nevertheless, this concept faced challenges to the identification of appropriate location. Existing research lacks comprehensive evaluation methods that encompass a various factor for effective decision-making. This study introduces a new evaluation framework that involves different aspects, including thermal energy potential and spatial distribution analysis. The novelty of this research lies in its unique focus on the combination of WWHR and wastewater reuse. Moreover, it introduces a structured evaluation framework that considers multiple criteria and expert opinions, enhancing decision-making precision. Multi-criteria decision analysis (MCDA) was applied to select assessment criteria, which were categorized into three aspects: water–energy supplier, water–energy consumers, and water–energy station. The relative importance of criteria was determined using the analytical hierarchical process (AHP). The results of the AHP highlight significance of factors: treated wastewater flow rate; treated wastewater temperature; water–energy supply distance, and type of water–energy consumer. These factors were assigned weight values of 0.297, 0.186, 0.123, and 0.096, respectively. It is emphasizing their influence in the decision-making process that potential locations depend on the water–energy supplier and water–energy consumer as supply and demand sources.
¿Se puede educar el criterio sobre el juicio moral? Una perspectiva crítica al intuicionismo social y al racionalismo kolhberiano
Authors: Morandín Ahuerma Fabio , Salazar Morales Jaime
Published: November 2023

El dualismo razón-emoción infiere que existen dos esferas para la valoración ética: una racional, de pensamiento lógico con el que se toman decisiones morales ponderadas, y otra, en la misma persona, no racional, emotiva, que responde de manera automática a los estímulos y a las impresiones. Una de las propuestas para salvar esta zanja bivalente es el enfoque de intuicionismo social, que amalgama tanto la posición emotiva-intuitiva para la construcción del juicio moral como elementos antropológicos, sociales y culturales que forman el criterio definitivo de la persona para enfrentar dilemas morales. Otras posturas, entretanto, plantean que el juicio moral se construye de manera gradual y progresiva desde la educación, de forma racional. En este trabajo se critican las dos teorías pues se considera que generan una dicotomía reduccionista ―y por momentos excluyente― entre los procesos racionales formativos de la moral y las impresiones generadas por las emociones. Se concluye que sí es posible educar el criterio para el juicio moral porque, en el fondo, no hay una dicotomía excluyente entre intuición y razonamiento, sino que, en cambio, se complementan.
Aprendizajes derivados de la implementación de un dispositivo pedagógico en condiciones de enseñanza remota por Covid-19
Authors: Giraldo Cadavid Diana Alexandra , Fernández García Diego Armando
Published: November 2023

Se presenta la experiencia de implementación de un dispositivo pedagógico en una institución educativa rural. El objetivo es contribuir al estudio de la incorporación de medios digitales en la escuela mediante la descripción y el análisis de ciertas adaptaciones pedagógicas que tuvieron lugar en condiciones de enseñanza remota por covid-19. Bajo el enfoque de la investigación-acción en educación, se orientaron y acompañaron a estudiantes de secundaria en la creación de videos cortos en torno a la promoción ambiental y el desarrollo sostenible. A partir de un análisis cualitativo, se identificaron como adaptaciones importantes: 1) la flexibilización de tiempos, ritmos y etapas de la enseñanza y el aprendizaje; 2) el agenciamiento y la movilización de competencias digitales por parte del docente para reforzar la relación pedagógica; y 3) el énfasis puesto en los aspectos comunicativos de los medios digitales para favorecer la creación y la expresión de los estudiantes. En general, se aborda una reflexión sobre los recursos, los medios y las estrategias que se precisan para responder a la heterogeneidad de los escenarios educativos o a condiciones inéditas como las generadas por la pandemia.
papel do crítico “amador” de obras literárias em mídias sociais digitais
Authors: Marinho Ferreira Julio
Published: November 2023

Este trabalho é um recorte de uma tese de doutorado em andamento sobre os usos do on-line como uma nova forma de atividade laboral, tendo nos livros e seus derivativos como filmes e séries, os produtos a serem comercializados em uma sociedade deslocada para o digital em função de uma pandemia global causada pelo Covid-19. Dessa forma, através de uma abordagem sociológica sobre os usos de mídias sociais digitais, no caso YouTube, busco nos chamados/as booktubers – desenvolvedores de conteúdos on-line a partir de livros – tecer uma análise sobre as potencialidades interativas como a utilização de uma imagem de si, de uma reputação on-line e das capacidades de produção de seguidores no contexto digital. Com isso, a atividade de formação de opiniões e de resenhas críticas sobre literatura, em seus variados escopos, aparece como um substrato a ser observado.
A emergência de uma teoria feminista decolonial
Authors: Adono da Silva Juliana
Published: November 2023

A teoria feminista tem sido repensada a partir de múltiplas epistemologias, vertentes e perspectivas, de forma contextualizada à realidade local das pensadoras e às demandas presentes nas lutas históricas das diferentes correntes do movimento feminista. Com isso, as diversas vertentes teóricas feministas, como epistemologias plurais, buscam abordar a violência de gênero desde múltiplas perspectivas. Dentre tais correntes está o feminismo decolonial, cuja centralidade de pauta abrange a crítica à colonialidade de gênero. Diante disso, o presente trabalho busca demonstrar a contribuição da produção científica da teoria feminista decolonial às epistemologias feministas, como ferramenta analítica da violência de gênero como um problema social. Para tanto, realizou-se pesquisa bibliográfica, com base em fontes secundárias de análise. Conclui-se que, com base na perspectiva contra-hegemônica presente na teoria feminista decolonial, esta produção científica se propõe como uma verdadeira revolução científica no campo dos estudos de gênero.
Comparison of Metabolic Effects of Three Different Treatment Combinations with Retrospective Real-life Data in People Living with HIV
Authors: Simsek Adem , Karabay Oguz , Guclu Ertugrul , Toptan Hande
Published: November 2023

Introduction:

Comorbidities are increasing in people living with HIV (PLHIV), and
different treatment options have advantages and disadvantages. It is important to compare information
from real-life treated cases. The aim of this study was to retrospectively evaluate the data on
efficacy and clinical and laboratory findings during different antiretroviral therapies.

Methods:

Retrospective file data of 47 PLHIV using Dolutegravir and Lamivudine (3TC/DTG),
Tenofovir Alafenamide Emtricitabine and Elvitegravir Cobicistat (EVG/c/TAF/FTC) and Tenofovir
Disoproxil Fumarate and Emtricitabine and Efavirenz (EFV/FTC/TDF) were analyzed. Data
of the patients at baseline and 12 months after antiretroviral therapy (ART) were compared.

Results:

About 47 PLHIV were included in the study. Of the patients, 22 (46.8%) were in the
3TC/DTG group, 19 (40.4%) in the EVG/c/TAF/FTC, and 6 (12.8%) in the EFV/FTC/TDF
group. After 12 months of treatment, BMI, HIV-RNA, CD4, WBC, hemoglobin, MCV, PDW,
RDW, platelet count, creatinine, eGFR, HDL, AST, glucose values of the 3TC/DTG group were
significantly different (p<0.05). After 12 months of treatment, BMI, HIV-RNA, CD4 count,
MCV, creatinine, eGFR, HDL, LDL, TG, TC, AST, and HOMA-IR values of the
EVG/c/TAF/FTC treatment group were significantly different (p<0.05). After 12 months of treatment,
HIV RNA, total bilirubin, and LDL values in the EFV/FTC/TDF treatment group were statistically
different (p<0.05).

Conclusion:

All treatment groups showed a decrease in HIV-RNA and an increase in CD4 at the
end of one year. While CD4 elevation is lower in EFV recipients than in integrase inhibitor (INSTI)
recipients, weight gain is higher in INSTI recipients. While the lipid profile was more positively
affected in the 3TC/DTG group, lipid profiles were more negatively affected in the
EVG/c/TAF/FTC group, although liver and kidney functions were preserved.
Bioactivity-guided Separation of Antinociceptive and Antioxidant Subfractions from Alkaline Chloroform Fraction of Fenugreek Seeds (Trigonella foenum-graecum L.) in an Animal Model
Authors: Asadi Amir , Mandegary Ali , Pournamdari Mostafa , Abbasi Mahboobe , Mohamadi Neda , Sharififar Fariba
Published: November 2023

Background:

Antinociceptive effect of fenugreek seeds (Trigonella foenum-graecum L.)
has been reported in different animal models in response to various chemical or thermal stimuli. In a
recent study, alkaline chloroform fraction (AKC) of this plant has exhibited the greatest analgesic
effect.

Objective:

In the present study, to isolate the active component(s) from the plant, the subfractions
resulting from AKC column chromatography were evaluated in an animal model for anti-nociception
effect.

Methods:

From the 17 separated fractions, 5 major fractions (F4, F6, F14, F15 and F16) were used for
the formalin test at three different doses (2.5, 5 10 mg/kg). Antioxidant activity of the most active
subfractions was studied too.

Results:

Subsections F16 and F14 (5, 10 mg/kg) showed the greatest analgesic effect and reduced,
which was similar to morphine and even stronger than morphine in some doses. The greatest antioxidant
activity was observed by F14 (radical inhibition percentage of 17.34± 0.14 in DPPH assay, reduction
power percentage of 74.05±4.23 in RPA versus green tea (91.68± 3.04 and 97.59± 6.24 in
DPPH assay and RPA test respectively). The absorbance of F14 was 0.25±0.11 in the FTC method in
comparison to ascorbic acid 10 μg/ml and 100 μg/ml (0.72±0.33 and 0.05±0.41 respectively).

Conclusion:

Separated subfractions exhibited more antinociceptive effect than AKC fraction, so
further separation can lead to the acquisition of antinociceptive compound (s), while AKC fraction
was found to be more potent antioxidant than separated sub-fractions in all three experiments. So,
most likely, the anti-nociception effect of subfractions might be achieved via other mechanisms than
antioxidant activity. Based on phytochemical screening, AKC and all sub-fractions especially F14,
F15 and F16 were positive for the presence of alkaloids and only F14 was positive for flavonoids.
NAT2 Gene Variants as a Provocative Factor for the Severe Course of
COVID-19 Pneumonia in Ukrainian Patients
Authors: Fishchuk Liliia , Rossokha Zoia , Pokhylko Valeriy , Cherniavska Yuliia , Tsvirenko Svitlana , Vershyhora Viktoriia , Popova Olena , Fastovets Maryna , Kaliuzhka Olena , Gorovenko Nataliia
Published: November 2023

Background:

Previous studies indicate a close relationship between the severity of
COVID-19 and oxidative stress. N-acetyltransferase 2 (NAT2) is an enzyme that metabolizes a
wide range of xenobiotics and plays an important role in the regulation of reactive oxygen species,
consequently contributing to the development of oxidative stress.

Aim:

To determine the impact of NAT2 gene variants on the risk of developing and the progression
of severe COVID-19-associated pneumonia in patients from the Poltava region of Ukraine.

Methods:

The study included 117 patients who were diagnosed with severe COVID-19 pneumonia
and received treatment in the intensive care unit. The NAT2 gene variants were identified
through the PCR-RFLP method.

Results:

The presence of the AA genotype of the A803G variant in patients with severe
COVID-19 pneumonia is associated with an almost 3-fold reduction in the risk of lethal outcomes.
The presence of the TT genotype of the C481T variant was associated with the need for artificial
lung ventilation. Patients in the study group with a heterozygous GA genotype of the
G590A variant demonstrated a notable rise in the risk of developing systemic inflammatory response
syndrome and acute respiratory distress syndrome, with a nearly 2.5-fold and 3-fold increase,
respectively. The G857A variant was not associated with the risk of developing the above--
mentioned complications in the examined patients.

Conclusion:

The obtained results suggested that the NAT2 gene variants might influence the incidence,
course, and adverse consequences of COVID-19.
Reduction of Nitrate and Acrylamide in Heat-processed Meats using treatment with Lactobacillus Casei and Plant Extracts
Authors: Abbasi Mahsa , Behbahani Mandana , Roumi Mehrnaz
Published: November 2023

Background:

Food security has always been a concern in the multi-factorial systems
analysis of health and wellbeing. The presence of nitrate and acrylamides in cooked meat leads to
negative health outcomes.

Objective:

This study aimed to reduce nitrate and acrylamide content in different kinds of meats
(chicken, turkey, lamb, beef, quail, and fish) using some plant extracts and lactobacillus treatment.

Methods:

The extracts were prepared from Coriandrum sativum, Nigella sativa, and Thymus
leaves and stem. The used bacteria was Lactobacillus casei subsp. rhamnosus LCR6013. Acrylamide and nitrate were measured by liquid chromatography and colorimetric spectrophotometry
methods

Results:

The results showed that both bacterial treatment and plant extracts could reduce the
amount of acrylamide and nitrate. The most reduction in the amount of acrylamide and nitrate was
obtained by adding Thymus and Nigella sativa extracts, followed by coriander extract and bacterial inoculum. Also, bacterial treatment was more effective for nitrate reduction than acrylamide.

Conclusion:

It was concluded that the plant extracts and bacterial treatment are appropriate solutions to reduce the amount of acrylamide and nitrate during the baking process of meat.
Marital Satisfaction in Postpartum Women: The Role of Personality, Body Image Satisfaction, Anxiety, and Sexual Function
Authors: Youseflu Samaneh , Maleki Azam , Niroomand Soudabeh
Published: November 2023

Background:

The postpartum period is considered a vulnerable and stressful period for
many women due to various hormonal, physical, and psychosocial changes, such as adapting to
parental rules, changes in body and self-image, loss of autonomy, breastfeeding, and taking care
of the baby

Objective:

This study aimed to test a conceptual model considering the interrelated role of anxiety,
body image satisfaction, sexual function, type of personality, income, and education on women’s
marital satisfaction. Also it also aimed to test the mediating role of sexual function and anxiety.

Methods:

In this cross-sectional study, 447 lactating women were recruited from January to April
2019. Women answered some questionnaires including a socio-demographic checklist, female sexual
function index (FSFI), Body Self-Relation Questionnaire (BSRQ), the Enrich Marital Satisfaction,
and the NEO Personality Inventory (NEO PI-R). Data were analyzed using the descriptive
test, and Path analysis was done with LISREL software.

Results:

Results show that sexual function (β= 0.44), anxiety (β= -0.26), and educational level (β=
0.47) are the main predictors of marital satisfaction (dependent variable). Sexual function and anxiety
were two main mediators; variables, such as anxiety (β= -0.35), body image satisfaction (β=
0.19), and extraversion personality (β= 0.19) (independent variables), with an effect through sexual
function, can impress marital satisfaction indirectly.

Conclusion:

Identifying relationships between anxiety, educational level, sexual function, anxiety,
body image, and personality with the quality of life of postpartum women highlights the importance
of designing interventions to improve marital satisfaction. Given these relationships, it is recommended
that health professionals educate women about body changes during postpartum and
find ways to improve mothers' marital satisfaction.