bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced Tribological Performance of Laser-Textured TiN-Coated Ti6Al4V Alloy Surfaces: A Comparative Study with Untextured Surfaces
Authors: Muniyappan Arulkumar , Muthuvel Prem Ananth , Sanmugam Anandhavelu , Wadaan Mohammad Ahmad , Baabbad Almohannad , Muthuchamy Nallal , Park Kang Hyun
Published: January 2025

Titanium alloy is widely used as a biomaterial due to its strength, lightweight nature, and corrosion resistance. Despite its strength and lightweight nature, its low wear resistance limits its uses in prosthetic components. Laser surface texturing (LST) was used to improve the wear resistance of titanium alloys by creating textured surfaces before applying protective coatings. A biocompatible TiN composite protective coating was applied using physical vapour deposition (PVD) with a thickness of 4 µm. Response surface methodology (RSM) was used to predict the tribological properties by varying input parameters such as material type (TI, T2, T3, and T4), load in N, and sliding velocity in m/s. A pin-on-disc tribometer was used to conduct a unidirectional sliding wear test based on the RSM design. Tribological properties were studied to determine the impact of laser texturing on the bonding strength of the coating. As a result, material type T4 exhibits an improved coefficient of friction and specific wear resistance under varying sliding velocity and load conditions compared to other material types. The study was further supported by an ANSYS simulation, which revealed stress reduction affecting the coefficient of friction and, consequently, wear. The textured surface topography, wear mechanisms, and coating compositions were examined using scanning electron microscopy.
Interactive Multimedia Environment Intervention with Learning Anxiety and Metacognition as Achievement Predictors
Authors: Mavrogianni Aristea , Vasilaki Eleni , Linardakis Michalis , Vasiou Aikaterini , Mastrothanasis Konstantinos
Published: January 2025

Background: Interactive learning environments have emerged as transformative tools in education, enhancing engagement, academic performance, and addressing challenges like learning anxiety. This study examines the influence of multiple variables, including anxiety, internet usage for problem-solving, attitude towards a history course, metacognitive awareness, and interactive learning environments, on seventh-grade students’ academic performance. Methods: Using the Exploration of Attitudes Towards History Scale (EDIS) scale to measure attitudes and the Metacognitive Awareness of Reading Strategies Inventory-Revised Two-Factor Version (MARSI-2fR) to assess metacognitive awareness, the study evaluated historical knowledge across three stages, namely pre-intervention, post-intervention, and a one-month-later retest. A comparative analysis was conducted between the control group and the intervention group. The statistical analyses involved the calculation of correlation coefficients, the implementation of general linear models, and the performance of Wilcoxon signed-rank tests. Results: The findings indicated that prior to the intervention, factors such as learning anxiety and the extratextual component of metacognition were statistically significant predictors of achievement. However, the aforementioned factors ceased to be statistically significant when the parameter of study strategies was incorporated into the statistical model. The impact of the interactive learning environment on students’ achievement is highly statistically significant in terms of post-test scores, while the influence of all other predictors becomes insignificant. The retest confirmed the continued maintenance of the achieved results as evaluated following the intervention. Conclusions: The study confirms previous research demonstrating that interactive learning environments are an effective method of enhancing students’ academic performance and reducing the negative impact of learning anxiety.
Multi-Centroid Extraction Method for High-Dynamic Star Sensors Based on Projection Distribution of Star Trail
Authors: Tang Xingyu , Cao Qipeng , Fu Zongqiang , Xu Tingting , Duan Rui , Yang Xiubin
Published: January 2025

To improve the centroid extraction accuracy and efficiency of high-dynamic star sensors, this paper proposes a multi-centroid localization method based on the prior distribution of star trail projections. First, the mapping relationship between attitude information and star trails is constructed based on a geometric imaging model, and an endpoint centroid group extraction strategy is designed from the perspectives of time synchronization and computational complexity. Then, the endpoint position parameters are determined by fitting the star trail grayscale projection using a line spread function, and accurate centroid localization is achieved through principal axis analysis and inter-frame correlation. Finally, the effectiveness of the proposed method under different dynamic scenarios was tested using numerical simulations and semi-physical experiments. The experimental results show that when the three-axis angular velocity reaches 8°/s, the centroid extraction accuracy of the proposed method remains superior to 0.1 pixels, achieving an improvement of over 30% compared to existing methods and simultaneously doubling the attitude measurement frequency. This demonstrates the superiority of this method in high-dynamic attitude measurement tasks.
Intelligent Wireless Sensor Network Sensor Selection and Clustering for Tracking Unmanned Aerial Vehicles
Authors: Cefai Edward-Joseph , Coombes Matthew , O’Boy Daniel
Published: January 2025

Sensor selection is a vital part of Wireless Sensor Network (WSN) management. This becomes of increased importance when considering the use of low-cost, bearing-only sensor nodes for the tracking of Unmanned Aerial Vehicles (UAVs). However, traditional techniques commonly form excessively large sensor clusters, which result in the collection of redundant information, which can deteriorate performance while also increasing the associated network costs. Therefore, this work combines a predictive posterior distribution methodology with a novel simplified objective function for optimally identifying and forming smaller sensor clusters before activation and measurement collection. The goal of the proposed objective function is to reduce network communication and computation costs while still maintaining the tracking performance of using far more sensors. The developed optimisation algorithm results in reducing the size of selected sensor clusters by an average of 50% while still maintaining the tracking performance of general traditional techniques.
Image-Driven Hybrid Structural Analysis Based on Continuum Point Cloud Method with Boundary Capturing Technique
Authors: Seo Kyung-Wan , Park Junwon , Park Sang I. , Song Jeong-Hoon , Yoon Young-Cheol
Published: January 2025

Conventional approaches for the structural health monitoring of infrastructures often rely on physical sensors or targets attached to structural members, which require considerable preparation, maintenance, and operational effort, including continuous on-site adjustments. This paper presents an image-driven hybrid structural analysis technique that combines digital image processing (DIP) and regression analysis with a continuum point cloud method (CPCM) built on a particle-based strong formulation. Polynomial regressions capture the boundary shape change due to the structural loading and precisely identify the edge and corner coordinates of the deformed structure. The captured edge profiles are transformed into essential boundary conditions. This allows the construction of a strongly formulated boundary value problem (BVP), classified as the Dirichlet problem. Capturing boundary conditions from the digital image is novel, although a similar approach was applied to the point cloud data. It was shown that the CPCM is more efficient in this hybrid simulation framework than the weak-form-based numerical schemes. Unlike the finite element method (FEM), it can avoid aligning boundary nodes with regression points. A three-point bending test of a rubber beam was simulated to validate the developed technique. The simulation results were benchmarked against numerical results by ANSYS and various relevant numerical schemes. The technique can effectively solve the Dirichlet-type BVP, yielding accurate deformation, stress, and strain values across the entire problem domain when employing a linear strain model and increasing the number of CPCM nodes. In addition, comparative analysis with conventional displacement tracking techniques verifies the developed technique’s robustness. The proposed technique effectively circumvents the inherent limitations of traditional monitoring methods resulting from the reliance on physical gauges or target markers so that a robust and non-contact solution for remote structural health monitoring in real-scale infrastructures can be provided, even in unfavorable experimental environments.
An Airborne Gravity Gradient Compensation Method Based on Convolutional and Long Short-Term Memory Neural Networks
Authors: Zhou Shuai , Yang Changcheng , Cheng Yi , Jiao Jian
Published: January 2025

As gravity exploration technology advances, gravity gradient measurement is becoming an increasingly important method for gravity detection. Airborne gravity gradient measurement is widely used in fields such as resource exploration, mineral detection, and oil and gas exploration. However, the motion and attitude changes of the aircraft can significantly affect the measurement results. To reduce the impact of the dynamic environment on the accuracy of gravity gradient measurements, compensation algorithms and techniques have become a research focus. This paper proposes a post-error compensation algorithm using convolutional and long short-term memory neural networks (CNN-LSTMs). By leveraging convolution feature extraction capabilities and considering the temporal dependencies of dynamic measurement parameters with LSTM, the model demonstrates a stronger ability to learn from severely coupled time series data, resulting in a significant improvement in the compensation performance. This method outperforms traditional neural networks’ multi-layer perceptrons (MLPs) in terms of compensation accuracy on both simulated and measured airborne gravity gradient data from Heilongjiang Province.
Combining a Standardized Growth Class Assessment, UAV Sensor Data, GIS Processing, and Machine Learning Classification to Derive a Correlation with the Vigour and Canopy Volume of Grapevines
Authors: Dillner Ronald P. , Wimmer Maria A. , Porten Matthias , Udelhoven Thomas , Retzlaff Rebecca
Published: January 2025

Assessing vines’ vigour is essential for vineyard management and automatization of viticulture machines, including shaking adjustments of berry harvesters during grape harvest or leaf pruning applications. To address these problems, based on a standardized growth class assessment, labeled ground truth data of precisely located grapevines were predicted with specifically selected Machine Learning (ML) classifiers (Random Forest Classifier (RFC), Support Vector Machines (SVM)), utilizing multispectral UAV (Unmanned Aerial Vehicle) sensor data. The input features for ML model training comprise spectral, structural, and texture feature types generated from multispectral orthomosaics (spectral features), Digital Terrain and Surface Models (DTM/DSM- structural features), and Gray-Level Co-occurrence Matrix (GLCM) calculations (texture features). The specific features were selected based on extensive literature research, including especially the fields of precision agri- and viticulture. To integrate only vine canopy-exclusive features into ML classifications, different feature types were extracted and spatially aggregated (zonal statistics), based on a combined pixel- and object-based image-segmentation-technique-created vine row mask around each single grapevine position. The extracted canopy features were progressively grouped into seven input feature groups for model training. Model overall performance metrics were optimized with grid search-based hyperparameter tuning and repeated-k-fold-cross-validation. Finally, ML-based growth class prediction results were extensively discussed and evaluated for overall (accuracy, f1-weighted) and growth class specific- classification metrics (accuracy, user- and producer accuracy).
Sensor for a Solid–Liquid Tribological System
Authors: Zhang Ruize , Yu Zeyang , Fan Zhikai , Wang Shanshan , Xiang Yihui , Liu Yanfei , Wang Zhongnan
Published: January 2025

Solid–liquid lubrication systems have been widely used to enhance tribological behaviors. Alongside offering exceptional lubrication and wear-resistance performance, the active control of the tribological behavior of lubrication systems in accordance with service conditions is equally critical. To achieve this goal, accurately monitoring the condition of the lubrication system is fundamental. This review article aims to provide a fundamental understanding of different sensors for monitoring the condition of lubricants, as well as the friction and wear properties. Specifically, the sensors suitable for engineering applications are detailed introduced. Through this review, we wish to provide researchers in mechanical engineering with a clear technical overview, which can guide the design of intelligent lubrication systems with suitable sensors.
Phase Equilibrium of CO2 Hydrate with Rubidium Chloride Aqueous Solution
Authors: Kasai Ryonosuke , Kamiya Leo , Ohmura Ryo
Published: January 2025

Salt lakes are a rich source of metals used in various fields. Rubidium is found in small amounts in salt lakes, but extraction technology on an industrial scale has not been developed completely. Clathrate hydrates are crystalline compounds formed by the encapsulation of guest molecules in cage-like structures made of water molecules. One of the most important properties for engineering practices of hydrate-based technologies is the comprehension of the phase equilibrium conditions. Phase equilibrium conditions of CO2 hydrate in rubidium chloride aqueous solution with mass fractions of 0.05, 0.10, 0.15 and 0.20 were experimentally investigated in the pressure range from 1.27 MPa to 3.53 MPa, and the temperature was from 268.7 K to 280.6 K. The measured equilibrium temperature in this study decreased roughly in proportion to the concentration of the RbCl solution from the pure water system. This depression is due to the lowering of the chemical potential of water in the liquid phase by the dissolution of RbCl. Experimental results compared with other salt solution + CO2 hydrate systems showed that the equilibrium temperatures decreased to a similar degree for similar mole fractions.
Familiar Yet New: How Design-Driven Innovation and Brand Image Affect Green Agricultural Product Purchase Intentions in the Live Streaming Environment
Authors: Zhu Xuguang , Zhang Yihan , Wu Zeyu
Published: January 2025

With the rapid development of live streaming e-commerce, green agricultural products have become an important consumer category. However, sales still face challenges such as weak brand effects, content homogeneity, and the lack of professional hosts. Research shows that various factors influence consumers’ purchase intentions, with design-driven attributes and brand image playing crucial roles. However, their impact in the context of green agricultural product live streaming remains underexplored. This study, based on the S-O-R theory, investigates the factors that stimulate consumer purchase intentions for green agricultural products and reveals the influence of design-driven attributes on purchase intentions. A total of 472 valid responses were collected through a questionnaire. The results indicate that social presence and brand image have a positive impact on purchase intention, with green perceived value and emotional attitude acting as full mediators. However, design-driven attributes do not have a significant direct impact on purchase intention. Nevertheless, emotional attitude plays a significant mediating role between design-driven attributes and purchase intention. This study contributes to the research on consumer behavior and perceived value in live streaming environments, particularly emphasizing the importance of design-driven attributes, and provides insights for optimizing live streaming strategies and improving agricultural product design.
Exploring Job Satisfaction in the Platform Economy: A Multidimensional Study of Mobile Digital Platform Workers in Chile
Authors: Lay-Raby Nelson , Cea-Gonzalez Pablo , de la Fuente-Mella Hanns , Ríos-Vásquez Gonzalo
Published: January 2025

This study examines job satisfaction among mobile digital platform workers in Chile, addressing the gap in understanding the interplay between autonomy, social support, and technology in the platform economy. It explores how these factors shape job satisfaction through the following research question: How do autonomy, social support, and technological factors influence job satisfaction in the platform economy? Using a quantitative methodology, 398 platform workers from three Chilean regions participated in a survey, with data analyzed via logistic regression models to evaluate the impact of sociodemographic and psychological variables. The findings highlight that autonomy and social support significantly enhance job satisfaction, while technological usability and transformation are pivotal for positive work experiences. The study concludes that fostering worker autonomy, robust support systems, and user-friendly technologies is critical for improving job satisfaction in the gig economy. These insights contribute to the academic literature and inform strategies for policymakers and platform operators, emphasizing the need for tailored approaches to enhance worker well-being and organizational outcomes.
Comparative Techno-Economic Analysis of Gray Hydrogen Production Costs: A Case Study
Authors: Beigi Kheradmand Azam , Heidari Soureshjani Mahdi , Jahangiri Mehdi , Hamawandi Bejan
Published: January 2025

Despite Iran’s considerable renewable energy (RE) potential and excellent wind capacity and high solar radiation levels, these sources contribute only a small fraction of the country’s total energy production. This paper addresses the techno-economic viability of gray hydrogen production by these renewables, with a particular focus on solar energy. Given the considerable potential of solar energy and the strategic location of Shahrekord, it would be an optimal site for a hydrogen generation plant integrated with a solar field. HOMER Pro 3.18.3 software was utilized to model and optimize the levelized cost of hydrogen (LCOH) of steam reforming using different hydrocarbons in various scenarios. The results of this study indicate that natural gas (NG) reforming represents the most cost-effective method of gray hydrogen production in this city, with an LCOH of −0.423 USD/kg. Other hydrocarbons such as diesel, gasoline, propane, methanol, and ethanol have a price per kilogram of produced hydrogen as follows: USD −0.4, USD −0.293, USD 1.17, USD 1.48, and USD 2.15. In addition, integrating RE sources into hydrogen production was found to be viable. Moreover, by implementing RE technologies, CO2 emissions can be significantly reduced, and energy security can be achieved.
Geoethics and Sustainability: Addressing Challenges in Environmental Education for Achieving the SDGs
Authors: Mendonça Samuel , Piovesana Gabriel Franco , Pissolito Vanessa
Published: January 2025

Geoethics, which explores the ethical implications of Earth sciences, requires a philosophical effort to deepen our understanding of the field. Sustainability, particularly in the context of the energy transition, necessitates a critical examination of the limits to societal development. While advancing new forms of energy production is crucial, it is equally important to investigate the ethical boundaries of such studies. This article addresses the question: how can environmental education, in the context of sustainability and geoethics, respond to the challenges posed by SDG Goals 3 and 4? These goals—Ensure healthy lives and promote well-being for all at all ages, and Quality Education—are fundamental for preserving global living conditions. This study explores how environmental education can tackle sustainability issues from an ethical standpoint, focusing on geoethics as a key dimension. Using bibliographic research, exploratory and critical analysis as method, the paper examines the intersection of geoethics and sustainability, with particular emphasis on the ethical dimensions of energy transition. The findings underscore the urgent need to improve education—especially in schools—to prepare children and young people to navigate the ethical limits of sustainability. A secondary outcome of this paper is to highlight the critical role of ethics in shaping environmental education for a sustainable future.
The Efficiency of the New Extended EWMA Control Chart for Detecting Changes Under an Autoregressive Model and Its Application
Authors: Karoon Kotchaporn , Areepong Yupaporn
Published: January 2025

Control charts are frequently used instruments for process quality monitoring. Another name for the NEEWMA control chart is the new extended exponentially weighted moving average (new extended EWMA) control chart. The lower control limit (LCL) and upper control limit (UCL) are equally spaced from the center line, giving it a symmetrical design. Because of its symmetry, the NEEWMA chart is very good at identifying even the tiniest changes in operation by detecting deviations from the target in both upward and downward directions. This study derives an explicit formula for the average run length (ARL) of the NEEWMA control chart based on the autoregressive (AR) model with exponential white noise. The focus is on the zero-state performance of the NEEWMA control chart, which is derived using explicit formulas. Banach’s fixed-point theorem was used to prove existence and uniqueness of this formula. The accuracy of this formula is validated by comparing it to the numerical integral equation (NIE) method using percentage accuracy (%Acc). The results show that the NEEWMA control chart is more efficient than the ARL evaluated by the NIE method, particularly regarding computation time. The performance of the NEEWMA control chart is compared with the EWMA and extended EWMA control charts by evaluating both the ARL and standard deviation run length (SDRL). The NEEWMA control chart outperforms the others in detection performance, followed by the extended EWMA and EWMA control charts. Further verification of its superior performance is provided through comparisons using the average extra quadratic loss (AEQL) and the performance comparison index (PCI), which confirm that it outperforms both the EWMA and extended EWMA control charts across various parameters and shift sizes. Finally, an illustrative example using real-life economic data demonstrates its efficiency.
An Adaptive Voltage Reference-Based Multi-Objective Optimal Control Method for the Power Flow Symmetry of Multi-Terminal DC Systems with the Large-Scale Integration of Offshore Wind Farms
Authors: Zhang Yuanshi , Feng Yiwen , Xu Tongxin , Li Yilei , Du Xinye , Yuan Chaoyang , Chen Hongrui
Published: January 2025

The optimization of the symmetry of MTDC systems after a contingency is crucial for the stable and economic operation of the MTDC systems. In this paper, a multi-objective optimal control method for the power flow symmetry of MTDC systems for the large-scale integration of offshore wind farms is proposed. A mirror relationship between the available headroom of DC lines and VSCs and their actual power flow distribution performance is established. A corresponding symmetry index is established for the MTDC network, and the multi-objective optimization problem is converted into a series of single-objective problems by the normal boundary intersection method, and solved by the original dyadic interior point method, so as to obtain the Pareto optimal solution with uniform distribution. The compromise optimal solution is decided according to the entropy weight double-basis point method, which provides decision-making guidance for the operators. The simulation results show that the normal boundary intersection method can solve the multi-objective dynamic optimal control problem of the VSC-HVDC system quickly and efficiently, and improve the symmetry of the power flow in an MTDC network.
Graceful Local Antimagic Labeling of Graphs: A Pattern Analysis Using Python
Authors: Alam Luqman , Semaničová-Feňovčíková Andrea , Popa Ioan-Lucian
Published: January 2025

Graph labeling is the process of assigning labels to vertices and edges under certain conditions. This paper investigates the graceful local antimagic labeling of various graph families, excluding symmetric labelings, using computational experiments and Python-based algorithms. Through these experiments, we identify new results and patterns within specific graph classes. The study expands on the existing literature by offering computational evidence, proposing algorithms for the verification of labelings, and exploring the relationship between the local antimagic labeling and the chromatic number. Our results increase the understanding of graph labeling and offer insights into its computational aspects.
Study on the Dynamic Response of the Carbody–Anti-Bending Bars System
Authors: Apostol Ioana-Izabela , Mazilu Traian , Dumitriu Mădălina
Published: January 2025

Ride comfort is an important requirement that passenger rail vehicles must meet. Carbody–anti-bending system is a relatively new passive method to enhance the ride comfort in passenger rail vehicles with long and light carbody. The resonance frequency of the first bending mode (FBM) of such vehicle is within the most sensitive frequency range that affects ride comfort. Anti-bending bars consist of two bars that are mounted under the longitudinal beams of the carbody chassis using vertical supports. When the carbody bends, the anti-bending bars develop moments in the neutral axis of the carbody opposing the bending of the carbody. In this way, the carbody structure becomes stiffer and the resonance frequency of the FBM can be increased beyond the upper limit of the discomfort range of frequency, improving the ride comfort. The theoretical principle of this method has been demonstrated employing a passenger rail vehicle model that includes the carbody as a free–free Euler–Bernoulli beam and the anti-bending bars as longitudinal springs jointed to the vertical supports. Also, the method feasibility has been verified in the past using an experimental scale demonstrator system. In this paper, a new model of the carbody–anti-bending bar system is proposed by including three-directional elastic elements (vertical and longitudinal direction and rotation in the vertical–longitudinal plane) to model the fastening of the anti-bending bars to the supports and the vertical motion of the anti-bending bars modelled as free–free Euler–Bernoulli beams connected to the elastic elements of the fastening. In the longitudinal direction, the anti-bending bars work as springs connected to the longitudinal elastic elements of the fastening. The modal analysis method is applied to point out the basic properties of the frequency response functions (FRFs) of the carbody–anti-bending bars system, considering the bounce and FBMs of both the carbody and the anti-bending bars. A parametric study of the FRF of the carbody shows that the vertical stiffness of the fastening should be sufficiently high enough to eliminate the influence of the modes of the anti-bending bars upon the carbody response and to reduce the anti-bending bars vibration in the frequency range of interest. Longitudinal stiffness of the elastic elements of the fastening is critical to increase the bending resonance frequency of the carbody out of the sensitive range. Longer anti-bending bars can improve the capability of the anti-bending bars to increase the bending resonance without the risk of interference effects caused by the bounce and bending modes of the anti-bending bars.
CXCL-10 in Cerebrospinal Fluid Detects Neuroinflammation in HTLV-1-Associated Myelopathy with High Accuracy
Authors: Da Silva Samya Jezine , Cabral-Castro Mauro Jorge , Faria Luiz Claudio , Rosadas Carolina , de Araújo Maria Fernanda Lopes , Dutra Ana Caroline Soares , Yamano Yoshihisa , Taylor Graham , Puccioni-Sohler Marzia
Published: January 2025

Background and Objectives: HTLV-1-associated myelopathy (HAM) is a chronic progressive inflammatory disease of the spinal cord. This study assesses the diagnostic accuracy of the neuroinflammatory biomarkers neopterin and cysteine-X-cysteine motif chemokine ligand 10 (CXCL-10) in cerebrospinal fluid (CSF) for HAM. Methods: CSF samples from 75 patients with neurological disorders—33 with HAM (Group A), 19 HTLV-1-seronegative with other neuroinflammatory diseases (Group B), and 23 HTLV-1-seronegative with non-neuroinflammatory diseases (Group C)—were retrospectively evaluated. CSF examination included routine analysis, neopterin, and CXCL-10. The diagnostic potential of the biomarkers was evaluated using receiver operating characteristic curves. Results: Higher white cell counts and concentrations of protein, neopterin, and CXCL-10 in CSF were detected in group A (patients with HAM) and group B (p < 0.05). Neopterin showed good accuracy for HAM (A) (cut-off 15 nmol/L, 80% sensitivity, 74% specificity) and other neuroinflammation (group B) (cut-off 20 nmol/L, 79% sensitivity, 83% specificity). CXCL-10 demonstrated the highest accuracy in both groups, with Group A (cut-off 110 pg/mL, 97% sensitivity, 96% specificity) and Group B (cut-off 220 pg/mL, 100% sensitivity, 100% specificity). Conclusions: Neopterin and CXCL-10 in CSF are accurate biomarkers for detecting neuroinflammation, including HAM. CXCL-10, in particular, is the superior biomarker for both chronic and acute neuroinflammatory diseases.
The Role of Partnerships in Supporting COVID-19 Vaccine Uptake Among Migrants: A Qualitative Case Study from Tamil Nadu and Punjab, India
Authors: Meghani Ankita , Palanisamy Bharathi , Singh Sunita , Singh Tanya , Kanagat Natasha , Gupta Anil , Singh Kapil , Soni Gopal Krishna
Published: January 2025

Background: During the COVID-19 pandemic, migrant populations remained under-immunized due to limited access to health care, language barriers, and vaccine hesitancy. The USAID-funded MOMENTUM Routine Immunization Transformation and Equity project supported the government in collaborating with various local health and non-health partners to identify and vaccinate migrants. This case study examines the roles of project partners and the strategies each entity implemented to increase COVID-19 vaccine uptake among migrants, as well as the perceptions regarding the effectiveness of these strategies. Methods: We designed a qualitative explanatory case study guided by the Behavioral and Social Drivers framework and RE-AIM implementation science frameworks. We conducted 31 focus group discussions and 50 in-depth interviews with migrants, project partners, community leaders, and government stakeholders in Tamil Nadu and Punjab. Results: In both states, partnerships with health departments, private employers, and community-based organizations were essential for identifying and vaccinating un- and under-vaccinated migrant groups. In Tamil Nadu, collaboration with the Department of Labor and mobile medical units facilitated vaccination camps at construction sites. In Punjab, religious institutions organized sessions at places of worship, and the Border Security Force enabled health workers to reach migrants living near the border. In both states, key strategies—involving influencers to discuss the importance of vaccine safety and value, bringing vaccination services to migrants’ workplaces and homes at flexible times and mandating workplace vaccination to encourage vaccination—shifted perceptions towards vaccination and increased vaccine uptake among migrants. Conclusions: The strategies and partnerships identified in this study highlight the broader implications for future public health interventions, demonstrating that collaboration with the private sector and faith-based organizations can enhance routine immunization efforts, particularly when localized to organizations that understand community needs and can address specific barriers and motivators.
In Vitro Evaluation of Ruminal Digestibility, Fermentation Characteristics, and Bacterial Diversity of Kenaf Crop at Various Cutting Heights
Authors: Li Mengwei , Hassan Faiz-ul , Lin Qian , Arshad Muhammad Adeel , Akhtar Muhammad Uzair , Peng Lijuan , Yang Chengjian , Liang Xin , Huang Jiaxiang
Published: January 2025

The current study investigated the in vitro degradability, in vitro gas production, methane (CH4) production, and ruminal bacterial community of kenaf plants cut at different heights (130, 160, 190, 220, and 250 cm). These samples were subjected to an in vitro batch culture system using buffalo rumen fluid to measure gas and CH4 production at 3, 6, 9, 12, 24, 36, 48, and 72 h of incubation. Results reveal that crude protein (CP) concentration was the highest at the 220 cm height compared with the other heights. With the increase in height, gas and CH4 production decreased. However, the CH4 production at 190 cm was higher compared with the other plant heights. Dry matter degradation was higher at 190 cm and 220 cm, while ammonia-N and microbial CP were higher at the 220 cm height compared with the other heights. However, neutral detergent fiber degradation was the highest at the 130 cm height. Total volatile fatty acids, acetic acid, acetic acid/propane ratio, and pH value did not differ among the treatments, except for propionic acid, which was higher at the 130 cm and 160 cm heights. Overall, harvesting kenaf at plant heights of up to 220 cm was better in terms of its promising nutritional quality, improved dry matter degradation, and microbial CP contents.
Degradation of X-Ray Contrast Media in Anaerobic Membrane Bioreactors
Authors: Konopka Jakub , Kalka Joanna , Żabczyński Sebastian
Published: January 2025

The presence of pharmaceutical compounds, including iodinated contrast media (ICM), in aquatic systems poses significant ecological and health risks due to their biological activity at low concentrations. This study investigated the removal efficiency of three selected ICM—diatrizoate, iohexol, and iodipamide—from synthetic hospital wastewater using anaerobic membrane bioreactors (MBRs) operated at varying sludge ages of 40, 70, and 100 days. The results indicated that the performance of the MBRs in removing organic compounds improved with increased sludge age. Diatrizoate exhibited the highest removal efficiency, achieving 72% at a sludge age of 40 days and nearly 90% at 70 and 100 days, with no substantial differences between the two higher sludge ages. In contrast, iohexol and iodipamide demonstrated relatively low and inconsistent removal efficiencies, reaching a maximum of 40%, with no observable dependency on sludge age. The findings underscore the importance of optimizing sludge age in biological treatment processes for effective ICM removal.
The Synthesis of Functionalized W5O14 Nanorods for the Adsorption of Bismarck Brown R from Wastewater
Authors: Fatima Bushra , Ahmad Rabia , Alsebaii Naha Meslet , Al-Ghamdi Azza A. , Aldahiri Reema H. , Alzahrani Elham A. , Kumar Khanna Manoj , Oh Seungdae , Siddiqui Sharf Ilahi
Published: January 2025

In this research, a tungsten oxide was prepared via a green (biogenic) synthesis route where sodium tungstate dihydrate and Punica granatum peel extract were used as a precursor and a reducing/capping agent, respectively. The characterization of the prepared tungsten oxide was performed through various spectroscopic and microscopic techniques. The characterization results revealed the preparation of highly crystalline and nanorod-shaped (length = 123 nm and width = 31.3 nm) tungsten oxide with a probable chemical formula of W5O14. Various functional groups on the W5O14 surface were also reported. The prepared nanorods were further used for the removal of Bismarck Brown R (BBR) dye from water in a batch manner. By varying the dose of nanorods (0.5–3.0 g L−1), BBR solution pH (2−10), contact time (15–120 min), BBR concentration in solution (10–60 mg L−1), and temperature of BBR solution (30, 40, and 50 °C), the optimized condition for maximum adsorption efficiency was measured. The results revealed that 2.0 g L−1 amount of nanorods of tungsten oxide were used to remove ~98% of BBR dye from its 10 mg L−1 at 30 °C and 7.0 pH. The temperature-dependent adsorption data were fitted to different types of non-linear isotherm models (e.g., Langmuir and Freundlich) to assess the adsorption potential and adsorption mechanisms in relation to temperature impacts. The synthesized nano-adsorbent fits the Langmuir as well as the Freundlich isotherm model with a maximum adsorption capacity of 17.84 mg g−1. Pseudo-first-order, pseudo-second-order, and Elovich kinetic models were used for the study of adsorption kinetics. BBR adsorption onto the W5O14 nanorods follows the pseudo-second-order rates. The present adsorption is governed by physico-chemical adsorption with predominant chemical interactions.
Russian identity and migration processes
Authors:   Department of Humanities and Socio-Economic Disciplines of the Faculty of Law of the VUI FSIN of Russia, Timoshchuk A. S.
Published: January 2025

Multiculturalism, transnationalism, acculturation, adaptation, assimilation — all these are
various models of integration of newcomers. However, the gap between theory and practice
is still huge. Russians are concerned about the growth of ethnic crime, enclavization,
ghettoization of certain areas, and the criminalization of the foreign labor market. Is it possible
to preserve the existing socio-cultural context and solve the labor force problem?
Sustainable practices in lead acid battery recycling
Authors: Radja Khatir , Selami Nada , Khadra Kessairi , Abdelkader Fidjah , Laid Guerrida
Published: January 2025

Recycling automotive batteries is a vital practice in the context of sustainability. Purchasing power in developing and emerging economies has increased dramatically over the past decades, especially when considering the proliferation of consumer cars worldwide. Consequently, the growing manufacturing volume of automotive batteries inevitably leads to increased battery waste, thus placing significant pressure on the sustainable development of human society. Recycling lead-acid batteries as a sustainable product is not only environmentally beneficial but also economically beneficial. A typical new lead-acid battery contains up to 80% recycled lead, and the plastic and battery components are also recyclable. When combined, almost all environmentally hazardous materials in the battery can be recycled. In this paper, we will study the recycling of lead-acid batteries used in fuel-powered cars. The results show that 54.4% of the metals in the battery, 28% of the plastics, and 17% of the liquids can be recycled, which provides materials for the manufacture of new batteries or for other uses.
A importância da análise de inteligencia policial militar por intermédio da unidade operacional de área da polícia militar do paraná, na prevenção de crimes e da violência em ambientes escolares
Authors: Kamakawa Edson , Silva Cláudio Roberto Longo
Published: January 2025

O presente artigo tem por objetivo enfatizar a importância da realização da análise pelos agentes de inteligência das Unidades Operacionais da Polícia Militar do Paraná na prevenção de crimes e da violência em ambientes escolares. Durante o bojo da pesquisa será evidenciada a necessidade de maior aproximação do setor de inteligência das Unidades de área da PMPR com os profissionais da educação procurando identificar possíveis delitos que estejam ocorrendo nos estabelecimentos de ensino e arredores que apresentam conexão com o corpo discente, visando a realização de constantes análises das Agências Locais de Inteligência para subsidiar o Comando da Unidade na tomada de decisões e consequentemente no planejamento das ações a serem realizadas, frisando que a integração com o Batalhão de Patrulha Escolar Comunitária e outras Forças Policiais como Polícia Civil, Polícia Penal, Polícia Cientifica e Guarda Municipal, bem como, Poder Judiciário e Ministério Público Estadual, apresenta um fluxo de informações importantes tanto na questão policial quanto judicial, de maneira constante e não somente quando do alarde de possíveis ataques ou relatos de outros crimes. Como metodologia, a investigação tem como enfoque a pesquisa qualitativa-interpretativista e tipo de estudo exploratório, descritivo e explicativo, e apresenta como classificação a pesquisa bibliográfica e documental. Na conclusão tem-se a análise da importância desse implemento nas ações preventivas no ambiente escolar.
Fourier Transform Near-Infrared Spectroscopy (FT-NIR(S)) and artificial neural network for the quantitative detection of grape juice adulteration by the addition of apple juice
Authors: Silveira Paula Giarolla , Silva Carlos Ramon de Paula , Contado José Luis , Anjos Virgílio de Carvalho dos , Bell Maria José Valenzuela , Santos Amanda Aparecida Lima dos , Rocha Roney Alves da
Published: January 2025

Grape juice is popular for its taste and nutritional value, but due to its high commercial value, it is sometimes adulterated with apple juice, which contains naturally occurring sorbitol. This study used Fourier Transform Near-Infrared Spectroscopy (FT-NIR) alongside Artificial Neural Networks (ANN) to detect sorbitol in grape juice, aiming to identify adulteration. Two key NIR spectral bands, 12400–7400 cm−1 and 6400–5500 cm−1, were strongly correlated with sorbitol concentration in adulterated samples. The combination of FT-NIR and ANN provided accurate quantification of sorbitol levels, demonstrating that this method is a promising tool for the rapid detection of adulteration in grape juice with apple juice.
Producing 100+ MPa Field Concrete in Developing Countries: Requirements and Challenges
Authors: ElHawary Youssef , Hamdy Mohamed , Haroun John , Youssef Omar , Breakah Tamer , Nagib Mohamed
Published: January 2025

Over the past three decades, there has been a paradigm shift in the concrete industry in which high strength and high performance concrete became more widely in use. However, producing ultra-high strength concrete surpassing 100 MPa compressive strength in the field remains a challenging task. This is primarily due to the various factors involved in such concrete and its sensitivity to many of these factors. This study aims at producing field concrete surpassing 100 MPa compressive strength using readily available materials worldwide. The study also addresses the requirements and challenges of 100+ MPa concrete in the field in order to possess similar properties to conjugate mixtures produced in the laboratory having same mix proportions. Concrete mixtures were prepared with different water-to-cement ratios and incorporated variety of chemical and mineral admixtures. Tests included fresh concrete, self-consolidation as well as hardened concrete properties in order to determine the properties of the concrete produced. The impact of other vital factors such as mixing process, ambient temperature, curing process and pumping are addressed taking field conditions into consideration. Several field visits were conducted to monitor field concrete that was produced using the designated mixtures. The study herein revealed that reaching 100 plus MPa concrete is doable using variety of readily-available constituents and mix proportion. However, the study pinpoints the importance of other crucial factors and field practices. Recommendations are provided to concrete users and practitioners to exercise better quality control and ensure high rate of success in producing ultra-high strength concrete in the field.
Enhancing Compressed Earth Block Performance: Effects of Gelatinized Starch and Fiber Reinforcement on Mechanical Properties
Authors: Bailly Gabo Cyprien , El Mendili Yassine , Konin Athanas , Khoury Eliane
Published: January 2025

This study investigates the impact of starch stabilization and fiber reinforcement on the mechanical properties of Compressed Earth Blocks (CEBs). Various stabilization methods were tested to enhance the mechanical performance of CEBs, with a focus on starch as a natural binder and the incorporation of hemp as natural fibers. The research findings indicate that while starch slightly reduced internal cohesion by 13%, the addition of fibers alone significantly improved compression resistance by increasing strength by a factor of 3.57. When combined with starch, the effectiveness of fibers on compression resistance slightly decreased to a factor of 3.21. Cement stabilization, though providing the highest strength with a factor of 7, poses greater environmental challenges due to its high energy consumption and carbon emissions. In contrast, starch and natural fibers offer promising, eco-friendly alternatives that enhance CEB performance while reducing environmental impact. This study highlights the potential for integrating sustainable materials into construction practices to meet both structural and environmental objectives.
Avaliação do conhecimento das gestantes frente a toxoplasmose congênita
Authors: Felix Jhennifer Estevão , Scussel Ana Carolina de Morais Oliveira , Rosa Maria Julia Granero , Silva Anna Clara Balbina , Pimenta Paloma Cristina , Silva Maria Juliana Ribas do Nascimento da , Franco Priscila Silva , Gomes Angelica de Oliveira
Published: January 2025

Introdução: A toxoplasmose é uma doença causada pelo parasita Toxoplasma gondii, cuja transmissão vertical é considerada a forma mais grave da doença pois, pode levar infecção e sequelas ao feto. A toxoplasmose congênita ou suas sequelas podem ser evitadas por estratégias de promoção à saúde e prevenção primária que irão ajudar a reduzir os danos causados pela infecção congênita. Métodos: Estudo exploratório descritivo com abordagem quantitativa, realizado no Ambulatório Maria da Glória do HC-UFTM. A população de estudo compreendeu gestantes que realizaram pré-natal no Setor de Ginecologia e Obstetrícia. Foi utilizado no estudo um questionário estruturado para realização da coleta de dados com as gestantes. Após coleta de dados elaborou-se um banco de dados no aplicativo Microsoft Office Excel e os dados foram analisados de modo descritivo no programa Statistical Package for the Social Sciences. Resultados: Foram entrevistadas 174 gestantes, com idade variando de 13 a 43 anos, a maioria residentes de Uberaba. Das gestantes entrevistadas, 34,5% relataram não conhecer a doença. Dentre as gestantes que relataram conhecer ou ter ouvido falar sobre a doença algumas se equivocaram quanto aos modos de transmissão e prevenção da doença e boa parte não soube identificar as formas de prevenir a infecção do gato. Conclusão: o conhecimento das gestantes sobre modos de infecção e medidas preventivas da toxoplasmose são precários. Algumas condutas ou hábitos das gestantes as colocam sob risco de infecção reforçando a necessidade de implementação de ações educativas sobre toxoplasmose para gestantes e profissionais da saúde.