bluuebunny/crossref_metadata_2025 huggingface dataset:
Advancements in Surface Coatings for Enhancing Longevity in Hip Implants: A Review
Authors: Nikam Nishant , Shenoy B Satish , K N Chethan , Keni Laxmikant G. , Shetty Sawan , Bhat N Shyamasunder
Published: February 2025

Background/Objectives: The increasing demand for total hip arthroplasty (THA), due to aging populations and active lifestyles, necessitates advancements in implant materials and design. This review evaluates the role of surface coatings in enhancing the performance, biocompatibility, and longevity of hip implants. It addresses challenges like wear, corrosion, and infection, focusing on innovative surface engineering solutions. Methods: The review analyzes various surface modification techniques, including physical vapor deposition (PVD), chemical vapor deposition (CVD), electrophoretic deposition (EPD), plasma spraying, and ion implantation. It also examines their effectiveness in improving tribological properties, biocompatibility, and resistance to infection. Computational methods such as finite element analysis (FEA) are discussed for predicting potential coating failures. Results: The findings underscore the challenges posed by wear debris and corrosion in common configurations, like metal-on-metal (MoM) and metal-on-polyethylene (MoP). Innovative coatings, such as diamond-like carbon (DLC) films and hydroxyapatite (HA) layers, demonstrate enhanced performance by reducing friction, wear, and bacterial adhesion, while promoting osteogenic cell attachment. Surface textures and optimized tribological properties further improve implant functionality. Multifunctional coatings exhibit potential in balancing biocompatibility and infection resistance. Conclusions: Surface engineering plays a critical role in advancing next-generation hip implants. The integration of advanced coatings and surface modifications enhances implant durability, reduces complications, and improves patient outcomes. Future research should focus on combining innovative materials and computational modeling to refine coating strategies for long-term success in THA.
PRICOS: A Robust Paddy Rice Index Combining Optical and Synthetic Aperture Radar Features for Improved Mapping Efficiency
Authors: Lou Yifeng , Yang Gang , Sun Weiwei , Huang Ke , Huang Jingfeng , Wang Lihua , Liu Weiwei
Published: February 2025

Paddy rice mapping is critical for food security and environmental management, yet existing methods face challenges such as cloud obstruction in optical data and speckle noise in synthetic aperture radar (SAR). To address these limitations, this study introduces PRICOS, a novel paddy rice index that systematically combines time series Sentinel-2 optical features (NDVI for bare soil/peak growth, MNDWI for the submerged stages) and Sentinel-1 SAR backscatter (VH polarization for structural dynamics). PRICOS automates key phenological stage detection through harmonic fitting and dynamic thresholding, requiring only 10–20 samples per region to define rice growth cycles. Validated across six agroclimatic regions, PRICOS achieved overall accuracy (OA) and F1 scores of 0.90–0.98, outperforming existing indices like SPRI (OA: 0.79–0.95) and TWDTW (OA: 0.85–0.92). By integrating multi-sensor data with minimal sample dependency, PRICOS provides a robust, adaptable solution for large-scale paddy rice mapping, advancing precision agriculture and climate change mitigation efforts.
Machine Learning to Retrieve Gap-Free Land Surface Temperature from Infrared Atmospheric Sounding Interferometer Observations
Authors: Della Rocca Fabio , Pasquariello Pamela , Masiello Guido , Serio Carmine , De Feis Italia
Published: February 2025

Retrieving LST from infrared spectral observations is challenging because it needs separation from emissivity in surface radiation emission, which is feasible only when the state of the surface–atmosphere system is known. Thanks to its high spectral resolution, the Infrared Atmospheric Sounding Interferometer (IASI) instrument onboard Metop polar-orbiting satellites is the only sensor that can simultaneously retrieve LST, the emissivity spectrum, and atmospheric composition. Still, it cannot penetrate thick cloud layers, making observations blind to surface emissions under cloudy conditions, with surface and atmospheric parameters being flagged as voids. The present paper aims to discuss a downscaling–fusion methodology to retrieve LST missing values on a spatial field retrieved from spatially scattered IASI observations to yield level 3, regularly gridded data, using as proxy data LST from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) flying on Meteosat Second Generation (MSG) platform, a geostationary instrument, and from the Advanced Very High-Resolution Radiometer (AVHRR) onboard Metop polar-orbiting satellites. We address this problem by using machine learning techniques, i.e., Gradient Boosting, Random Forest, Gaussian Process Regression, Neural Network, and Stacked Regression. We applied the methodology over the Po Valley region, a very heterogeneous area that allows addressing the trained models’ robustness. Overall, the methods significantly enhanced spatial sampling, keeping errors in terms of Root Mean Square Error (RMSE) and bias (Mean Absolute Error, MAE) very low. Although we demonstrate and assess the results primarily using IASI data, the paper is also intended for applications to the IASI follow-on, that is, IASI Next Generation (IASI-NG), and much more to the Infrared Sounder (IRS), which is planned to fly this year, 2025, on the Meteosat Third Generation platform (MTG).
Smooth Moves: Comparing Log Dimensionless Jerk Metrics from Body Center of Mass Trajectory and Wearable Sensor Acceleration During Walking
Authors: Brasiliano Paolo , Pavei Gaspare , Bergamini Elena
Published: February 2025

Movement smoothness is a critical metric for evaluating motor control and sensorimotor impairments, with increasing relevance in neurorehabilitation and everyday functional assessments. This study investigates the correlation between two smoothness metrics (Log Dimensionless Jerk): LDLJV, derived from body center of mass (BCoM) trajectories using a gold-standard stereophotogrammetric system, and LDLJA, calculated from acceleration data recorded via an inertial measurement unit (IMU) placed at the L1–L2 level. Ten healthy adults (six men and four women; height: 1.71 ± 0.08 m; body mass: 68.2 ± 10.2 kg; age: 34.5 ± 8.5 years) walked on a treadmill at seven different speeds, with stride-specific data analyzed to compute smoothness indices for three anatomical components (antero-posterior, medio-lateral, cranio-caudal). Concordance between the metrics was evaluated using Bland–Altman analysis, Spearman’s correlation, and the mean absolute percentage error. The results revealed weak correlations and substantial biases across all components and speeds, reflecting inherent differences between IMU- and BCoM-derived data. Correcting biases improved alignment but did not eliminate discrepancies. The findings highlight that LDLJA captures only localized trunk accelerations, whereas BCoM-derived LDLJV approximates whole-body dynamics, making direct substitution infeasible. This study emphasizes the need for careful interpretation of IMU-based metrics and contributes to refining their application in real-world gait analyses.
The CHEWMA Chart: A New Statistical Control Approach for Microclimate Monitoring in Preventive Conservation of Cultural Heritage
Authors: Díaz-Arellano Ignacio , Zarzo Manuel
Published: February 2025

A new statistical control chart denoted as CHEWMA (Cultural Heritage EWMA) is proposed for microclimate monitoring in preventive conservation. This tool is a real-time detection method inspired by the EN 15757:2010 standard, serving as an alternative to its common adaptations. The proposed control chart is intended to detect short-term fluctuations (STFs) in temperature (T) and relative humidity (RH), which would enable timely interventions to mitigate the risk of mechanical damage to collections. The CHEWMA chart integrates the Exponentially Weighted Moving Average (EWMA) control chart with a weighting mechanism that prioritizes fluctuations occurring near extreme values. The methodology was validated using RH time series recorded by seven dataloggers installed at the Alava Fine Arts Museum, and, from these, seventy simulated time series were generated to enhance the robustness of the analyses. Sensitivity analyses demonstrated that, for the studied dataset, the CHEWMA chart exhibits stronger similarity to the application of EN 15757:2010 than other commonly used real-time STF detection methods in the literature. Furthermore, it provides a flexible option for real-time applications, enabling adaptation to specific conservation needs while remaining aligned with the general framework established by the standard. To the best of our knowledge, this is the first statistical process control chart designed for the field of preventive conservation of cultural heritage. Beyond assessing CHEWMA’s performance, this study reveals that, when adapting the procedures of the European norm by developing a new real-time approach based on a simple moving average (herein termed SMA-FT), a window of approximately 14 days is more appropriate for STF detection than the commonly assumed 30-day period in the literature.
Path Loss Modeling for RIS-Assisted Wireless Communication in Tunnel Scenarios
Authors: Yang Qi , Wu Yating , Zhao Hengkai , Feng Yichen , Sun Yanqiong , Fang Zhou , Zheng Guoxin
Published: February 2025

Aiming to address the problem of limited transmission distance in applying reconfigurable intelligent surface (RIS) technology, this study leverages a tunnel simulation platform to investigate RIS-assisted wireless communication systems. Through theoretical derivation, we propose a path loss model formula specifically applicable to tunnel scenarios. Simulation results demonstrate that the proposed model accurately reflects the communication performance characteristics of RIS in tunnel scenarios, verifying the capability of RIS technology to enhance signal transmission distance within tunnels in rail transit engineering applications. This finding highlights the significant engineering potential and value of RIS technology.
Optimization of Mucoadhesive Film Reinforced with Functionalized Nanostructured Lipid Carriers (NLCs) for Enhanced Triamcinolone Acetonide Delivery via Buccal Administration: A Box–Behnken Design Approach
Authors: Sodata Patteera , Duangjit Sureewan , Sarisuta Narong , Kraisit Pakorn
Published: February 2025

This research aimed to develop mucoadhesive buccal films incorporating nanostructured lipid carriers (NLCs) loaded with triamcinolone acetonide (TN-films). A Box–Behnken design was employed as a systematic approach to optimize the formulation. Key components of the NLCs—spermaceti, soybean oil, and polysorbate 80—were considered independent variables. The NLCs were prepared and size-reduced using a combination of hot homogenization and ultrasonic probe techniques. Films were cast using hydroxypropyl methylcellulose (HPMC) as the film-forming agent. The TN-films were characterized based on weight, thickness, tensile strength, elongation at break, contact angle, and surface free energy. Linear regression showed that spermaceti increased film weight and thickness, while polysorbate 80 decreased them. The mechanical strength of the films was primarily influenced by spermaceti; higher concentrations of spermaceti resulted in decreased film strength. Additionally, all independent variables contributed positively to the lipophilicity of the films. The TN-films were found to sustain drug release via a Fickian diffusion mechanism, exhibiting rapid swelling and favorable mucoadhesive properties. Moreover, the TN-films demonstrated superior drug release and permeation to pastes and films loaded with emulsions. These findings suggest that the TN-films represent a promising and effective approach for the buccal delivery of triamcinolone acetonide.
Oral History Theater for Young People: Old Wives’ Tales?
Authors: Shu Jack
Published: February 2025

This paper presents findings from an oral history theater project, developed by older individuals, aimed at primary and secondary school students. A professional theater company in Hong Kong has completed a three-year initiative that recruited retired older adults as creative participants. The research employed a mixed-methods approach; usage audience questionnaires completed by students and qualitative analysis to examine how the performances facilitated and empowered both students and older participants through interviews and field observations. Utilizing data and document triangulation as the primary analysis method in this mixed-methods research, the project revealed that younger students responded very positively to the performances by older adults. In addition to empowering both students and elders, the author discusses how the performances contributed to the education of young people in two key areas: moral development and history education. Both aspects suggest an enhancement of intergenerational relationships and the mental well-being of both younger and older individuals.
Smart Sensors and Artificial Intelligence Driven Alert System for Optimizing Red Peppers Drying in Southern Italy
Authors: Fiorentino Costanza , D’Antonio Paola , Toscano Francesco , Capece Nicola , Conceição Luis Alcino , Scalcione Emanuele , Modugno Felice , Sannino Maura , Colonna Roberto , Lacetra Emilia , Di Mambro Giovanni
Published: February 2025

The Senise red pepper, known as peperone crusco, is a protected geographical indication (PGI) product from Basilicata, Italy, traditionally consumed dried. Producers use semi-open greenhouses to meet PGI standards, but significant losses are caused by rot from microorganisms thriving in high moisture, temperature, and humidity, which also encourage pest infestations. To minimize losses, a low-cost alert system was developed. The study, conducted in summer 2022 and 2023, used external parameters from the ALSIA Senise weather station and internal sensors monitoring the air temperature and humidity inside the greenhouse. Since rot is complex and difficult to model, an artificial intelligence (AI)-based approach was adopted. A feed forward neural network (FFNN) estimated greenhouse climate conditions as if it were empty, comparing them with actual values when peppers were present. This revealed the most critical period was the first 3–4 days after introduction and identified a critical air relative humidity threshold. The system could also predict microclimatic parameters inside the greenhouse with red peppers, issuing warnings one hour before risk conditions arose. In 2023, it was tested by comparing predicted values with previously identified thresholds. When critical levels were exceeded, greenhouse operators were alerted to adjust conditions. In 2023, pepper rot decreased.
Performance Analysis in Tourism: Romania’s Competitiveness Among Central and Eastern European Countries
Authors: Ciocoiu Carmen Nadia , Cioc Mihai , Marinescu Corina , Baciu Silviu Gabriel , Sadkowska Joanna
Published: February 2025

Tourism is a critical economic sector for many countries, making substantial contributions to GDP and job creation. Analyzing performance in this domain has become indispensable for understanding and enhancing its economic, social, and environmental impact while promoting the sustainability and competitiveness of tourist destinations. In the context of the prolonged coronavirus pandemic, the tourism field suffered the effects of a weakened economy and a heavily affected society. For this reason, countries and their tourism industries have been looking for ways to improve performance in this sector by trying to address salient determinants related to investments in this industry. This study employs the input-oriented DEA-CRS (Data Envelopment Analysis–Constant Returns to Scale) model to assess Romania’s tourism performance in comparison to 11 other Central and Eastern European (CEE) countries. This analysis utilizes a dataset comprising three input variables and two output variables, with data corresponding to the year 2023. Half of the countries studied are deemed efficient, while only one is found to have a low level of efficiency in the tourism field. Following the analysis of the obtained results, four reference countries were identified, namely, Estonia, Croatia, Poland, and Slovenia. Practically, within the analyzed model, these four countries represent examples of good practices in the efficiency of the tourism industry for the other eight CEE countries.
A Moderated Mediation Analysis of Lebanon’s Food Consumers’ Green Purchasing Intentions: A Path Towards Sustainability
Authors: Naaman Dina , Yeşilada Figen , Aghaei Iman
Published: February 2025

As the concern for climate change and ecological disasters grows globally, different elements that can encourage and increase green behaviors have become a point of attention for scholars and practitioners. The current research primarily focuses on the factors that can impact green purchasing intentions and steps toward achieving sustainable development goals in the Lebanese context and specifically Tripoli. This study examines the role of consumer spirituality in determining green purchasing intentions along with the moderating effect of subjective norms and environmental concerns and the mediating effect of perceived consumer effectiveness. By deploying a cross-sectional survey, 350 responses from food industry consumers were collected using a judgmental sampling technique. The data were analyzed using partial least square–structural equation modeling (PLS-SEM) under the premises of the theory of planned behavior and norm activation theory. The findings suggest that a direct linkage exists between consumer spirituality and green purchasing intentions among Lebanese food consumers. Moreover, the mediating role of perceived consumer effectiveness was partially supported along with the moderating impact of subjective norms. This is while the moderating effect of environmental concerns was not found statistically significant, which implies a distance between being environmentally aware and actions that support this concern. This finding highlights the importance of considering consumers’ spiritual orientation when analyzing the impact of spirituality in the realm of green marketing. The implications of the findings can be beneficial for strategic improvements among firms as well as directions for scholars to expand upon the current understanding.
Robust Discriminative Non-Negative and Symmetric Low-Rank Projection Learning for Feature Extraction
Authors: Zhang Wentao , Chen Xiuhong
Published: February 2025

Feature extraction plays a vital role in pattern recognition and computer vision. In recent years, low-rank representation (LRR) has been widely used in feature extraction, due to its robustness against noise. However, existing methods often overlook the impact of a well-constructed low-rank coefficient matrix on projection learning. This paper introduces a novel feature extraction method, i.e., robust discriminative non-negative and symmetric low-rank projection learning (RDNSLRP), where a coefficient matrix with better properties, such as low-rank, non-negativity, symmetry and block-diagonal structure, is utilized as a graph matrix for learning the projection matrix. Additionally, a discriminant term is introduced to increase inter-class divergence while decreasing intra-class divergence, thereby extracting more discriminative features. An iterative algorithm for solving the proposed model was designed by using the augmented Lagrange multiplier method, and its convergence and computational complexity were analyzed. Our experimental results on multiple data sets demonstrate the effectiveness and superior image-recognition performance of the proposed method, particularly on data sets with complex intrinsic structures. Furthermore, by investigating the effects of noise corruption and feature dimension, the robustness against noise and the discrimination of the proposed model were further verified.
Pythagorean Fuzzy TOPSIS Method of Excessive Hesitation
Authors: Du Xiuli , Zhou Rui , Lu Kun , Cheng Weilong
Published: February 2025

In cases where the comprehensive hesitation degree among experts in decision-making is excessively high, the calculation of the comprehensive evaluation index using the TOPSIS method may lead to asymmetric bias. To address this issue, a formula for the comprehensive evaluation index considering excessive hesitation is proposed, followed by the introduction of a Pythagorean fuzzy TOPSIS method that accounts for high hesitation. Initially, the Pythagorean fuzzy number is utilized to calculate the comprehensive hesitancy of the evaluation matrix by experts. Subsequently, when excessive hesitancy is detected, a ranking correction coefficient is proposed to adjust the comprehensive evaluation index, which helps to prevent misjudgment of the optimal solution and ensures the symmetry of optimal decision-making, thereby yielding a more accurate and reasonable ranking of alternatives. Finally, experimental examples demonstrate the feasibility and effectiveness of the proposed method.
Evaluating Spatial Allocation of Resilient Medical Facilities in Megacities: A Case Study of Shanghai, China
Authors: Gao Peng , He Yuchen , Zhang Xinyue
Published: February 2025

In response to public health emergencies, the importance of resilient medical facilities—such as large exhibition centers and sports venues that can be rapidly converted into temporary emergency hospitals—has become increasingly evident. This study focuses on these potential medical resources within megacities, using Shanghai as a case study. Employing advanced analytical tools including the kernel density two-step floating catchment area method, Lorenz curves, and Gini coefficient, we systematically evaluated the spatial allocation of 36 resilient medical facilities in Shanghai. The findings indicate that Shanghai’s resilient medical facilities ensure 4.5 emergency beds per thousand residents, with large exhibition centers and sports venues demonstrating exceptional conversion capabilities far surpassing those of ordinary public venues. However, the study also uncovers significant disparities in spatial allocation: these facilities are predominantly concentrated in the city center, leading to notable deficiencies in accessibility and equity for suburban areas. The opportunity for residents to access emergency medical services decreases progressively from the city center outward, a trend consistent across various travel time scenarios. The calculated Gini coefficient underscores an extremely uneven spatial configuration of resilient medical facilities, well beyond the warning threshold, suggesting substantial service disparities between different regions during emergencies, which poses potential risks to public health. Our research provides valuable insights for megacities aiming to more effectively address future public health challenges and enhance societal resilience.
Impact of Emission Standards on Fine Particulate Matter Toxicity: A Long-Term Analysis in Los Angeles
Authors: Badami Mohammad Mahdi , Aghaei Yashar , Sioutas Constantinos
Published: February 2025

This study examines long-term trends in fine particulate matter (PM2.5) composition and oxidative potential in Los Angeles based on data from the University of Southern California’s Particle Instrumentation Unit, with chemical composition retrieved from the EPA’s Air Quality System (AQS). While regulatory interventions have reduced PM2.5 mass concentration and primary combustion-related components, our findings reveal a more complex toxicity pattern. From 2001 to 2008, the PM2.5 oxidative potential, measured via the dithiothreitol (DTT) assay, declined from ~0.84 to ~0.16 nmol/min/m3 under stringent tailpipe controls. However, after this initial decline, PM2.5 DTT stabilized and gradually increased from ~0.35 in 2012 to ~0.97 nmol/min/m3 by 2024, reflecting the growing influence of non-tailpipe emissions such as brake/tire wear. Metals, such as iron (Fe, ~150 ng/m3) and zinc (Zn, ~10 ng/m3), remained relatively stable as organic and elemental carbon (OC and EC) declined, resulting in non-tailpipe contributions dominating PM2.5 toxicity. Although PM2.5 mass concentrations were effectively reduced, the growing contribution of non-tailpipe emissions (e.g., brake/tire wear and secondary organic aerosols) underscores the limitations of mass-based standards and tailpipe-focused strategies. Our findings emphasize the need to broaden regulatory strategies, targeting emerging sources that shape PM2.5 composition and toxicity and ensuring more improvements in public health outcomes.
Exploring the Variability of Three Be Stars with TESS Observations
Authors: Andrade Laerte , Pereira Alan W. , Emilio Marcelo , Janot-Pacheco Eduardo
Published: February 2025

Be stars are rapidly rotating B-type stars surrounded by circumstellar disks formed from self-ejected material. Understanding the mechanisms driving mass ejection and disk formation, known as the Be phenomenon, requires a detailed investigation of their variability and underlying physical processes. In this study, we analyze the photometric, spectroscopic, and seismic characteristics of three Be stars—HD 212044, 28 Cyg, and HD 174237—using high-cadence data from the TESS mission and spectral data from the BeSS database. Photometric variability was analyzed through iterative prewhitening and wavelet techniques, revealing distinct frequency groups associated with non-radial pulsations (NRPs). Spectral data provided equivalent width measurements of the Hα line, which correlated with photometric changes, reflecting dynamic interactions between the stars and their disks. Seismic analysis identified core rotation rates and buoyancy travel times for HD 212044 and 28 Cyg, offering insights into internal stellar processes and angular momentum distribution. HD 212044 exhibits a strong negative correlation between photometric brightness and Hα equivalent width, whereas this correlation is weaker in the case of 28 Cyg. The findings for these two stars highlight the interplay between NRPs, rapid rotation, and circumstellar disk dynamics. In contrast, the case of HD 174237 presents an example of how a binary system with mass transfer and a B-type component is revealed when observed simultaneously with space-based photometry and ground-based spectroscopy, demonstrating the importance of distinguishing classical Be stars from interacting binaries.
Utilizing NF-κB Signaling in Porcine Epithelial Cells to Identify a Plant-Based Additive for the Development of a Porcine Epidemic Diarrhea Virus Vaccine
Authors: Hoa Nguyen-Thanh , Afzal Haroon , Doan Thu-Dung , Murtaza Asad , Yen Chia-Hung , Chung Yao-Chi
Published: February 2025

The nuclear factor-kappa B (NF-κB) signaling pathway plays a crucial role in regulating immune responses in epithelial cells. In this study, we established a porcine epithelial NF-κB reporter cell line (PK15-KBR) as an in vitro platform to screen plant-based extracts for their potential use as vaccine adjuvants against porcine epidemic diarrhea virus (PEDV). The NF-κB inducers were further tested for toxicity assessments, either using CCK-8 assays or intramuscular injection in mice, finally followed by vaccination studies to evaluate their adjuvancy. Initial experiments confirmed that TNF-α effectively activated NF-κB signaling in PK15-KBR cells in a dose-dependent manner, validating the platform’s reliability at Z’ value of 0.68. Of the 224 testers, 3 candidates, including chamomile, mulberry and Boerhaavia diffusa, showed induction activity; however, only chamomile induced a dose-dependent response in PK15-KBR cells. As a proof of concept, chamomile, used as an adjuvant in oral vaccination, demonstrated significantly higher IgG levels at an early stage (day 14, p < 0.05) and enhanced IgA titers. These findings highlight the use of the PK15-KBR cell line in identifying mucosal adjuvants and position chamomile extract as a promising candidate for enhancing vaccine-induced immunity.
Water Quality Engineering and Wastewater Treatment III
Authors: Hung Yung-Tse , Abdel Rahman Rehab O. , Aziz Hamidi Abdul , Al-Khatib Issam A. , Imai Tsuyoshi
Published: February 2025

The provision of clean water is a vital element to ensure life sustainability; this can be achieved by designing and implementing effective prevention and control measures to protect water resources [...]
Removal Efficiency and Mechanism of Typical PPCPs onto Novel Cyclodextrin–Graphene Oxide Composite Adsorbent in Aqueous Solutions
Authors: Zhang Ziyang , Wang Wenhui , Liu Fangyuan , Chen Hongrui , Zhang Xiaoran , Tan Chaohong , Gong Yongwei
Published: February 2025

A novel β-cyclodextrin–graphene oxide (β-CD/GO) composite adsorbent was synthesized via a hydrothermal method. Removal efficiency and mechanisms of typical pharmaceutical and personal care products (PPCPs) by the β-CD/GO composite were investigated in aqueous solutions. The results demonstrated that the β-CD/GO composite was successfully formed through cross-linking between β-CD and GO nanosheets, exhibiting enriched hydroxyl groups, a porous layered structure, and good thermal stability. The adsorption of cimetidine (CTD), sulfamethazine (SMZ), and diclofenac (DCF) onto the β-CD/GO composite was well described by pseudo-first-order and pseudo-second-order kinetic models, and Langmuir isotherm. The maximum adsorption capacities of CTD, SMZ, and DCF onto the β-CD/GO composite were 58.86, 35.62, and 29.11 mg g−1 at 298 K, respectively. The adsorption process was rapid and reached equilibrium after 6 h. The adsorption followed a monolayer mechanism and was an exothermic process. The adsorption capacity decreased with increasing pH values and ion concentrations. The β-CD/GO composite exhibited maximum adsorption capacities of 17.69, 16.96, and 16.23 mg g−1 for CTD, SMZ, and DCF, respectively, under a pH of 4 with a dosage of 1.0 g/L at 298 K for 6 h. Due to the combined impacts of electrostatic interaction, hydrogen bonding, and host–guest interaction, the adsorption of PPCPs onto β-CD/GO composite was fast and efficient. β-CD/GO composite exhibited superior adsorption efficacy and structural stability, which highlighted its promising application in the elimination of micropollutants from aqueous solutions.
Modeling and Technical-Economic Analysis of a Hydrogen Transport Network for France
Authors: De Wolf Daniel , Magidson Christophe , Sigot Jules
Published: February 2025

This work aims to study the technical and economical feasibility of a new hydrogen transport network by 2035 in France. The goal is to furnish charging stations for fuel cell electrical vehicles with hydrogen produced by electrolysis of water using low-carbon energy. Contrary to previous research works on hydrogen transport for road transport, we assume a more realistic assumption of the demand side: we assume that only drivers driving more than 20,000 km per year will switch to fuel cell electrical vehicles. This corresponds to a total demand of 100 TWh of electricity for the production of hydrogen by electrolysis. To meet this demand, we primarily use surplus electricity production from wind power. This surplus will satisfy approximately 10% of the demand. We assume that the rest of the demand will be produced using surplus from nuclear power plants disseminated in regions. We also assume a decentralized production, namely, that 100 MW electrolyzers will be placed near electricity production plants. Using an optimization model, we define the hydrogen transport network by considering decentralized production. Then we compare it with more centralized production. Our main conclusion is that decentralized production makes it possible to significantly reduce distribution costs, particularly due to significantly shorter transport distances.
The Emotional Edge of Skincare Brands in Online Reviews: Impact on Purchase Decisions
Authors: Mulyana Makruf Kausar , Layman Chrisanty V.
Published: February 2025

Objective: This study aims to investigate the impact of online reviews on the intention to purchase skincare products in Indonesia, emphasizing emotional value as a novel moderating factor in this relationship. Research Design & Methods: The study employs a quantitative research design using a survey methodology. Data were collected from 257 respondents, and PLS-SEM (Partial Least Squares SEM) was used to analyze the results. Findings: The study found that source credibility, review valence, and review quantity significantly influence purchase intention. Additionally, emotional value amplifies the positive effects of these factors, offering deeper insights into its role in shaping consumer decisions. Implications and Recommendations: The findings suggest that marketers should prioritize not only enhancing the credibility of online reviews but also leveraging the positive impact of review valence and review quantity to boost purchase intention. Marketers can enhance review credibility by collaborating with trusted influencers or ensuring reviews come from verified users. Positive review valence can be achieved by encouraging satisfied customers to share their experiences, while increasing review quantity can be accomplished by incentivizing customers to leave feedback. These combined strategies, focusing on credibility, sentiment, and quantity, can significantly influence consumer decisions, creating stronger emotional connections and driving purchase intentions. Contribution & Value Added: This study is one of the few that explores the moderating effect of emotional value on the relationship between online reviews and purchase intention, filling an existing gap in understanding emotional factors in consumer behavior. It provides valuable contributions to academic literature and offers practical strategies for marketers in Indonesia’s rapidly growing skincare industry.
Renal infarction Incidence, Risk Factors and Risk of Mortality and Kidney Replacement Therapy
Authors: Cheikh Hassan Hicham I. , Murali Karumathil M. , Lambert Kelly , Bahous Sola A. , Kalab Siba , Kilani Hala , Mullan Judy
Published: February 2025

Background:

Renal infarction is a rare medical condition, with most studies focusing on prevalence and risk factors. Very few studies examined long term outcomes, and to our knowledge there are no studies comparing patients with renal infarction to a control group for long term outcomes such as mortality or kidney replacement therapy (KRT). We used a hospital population database to examine incidence, prevalence and risk factors for renal infarction and long-term outcomes such as mortality and KRT, comparing patients with renal infarction to the general population and to a matched cohort.

Methods:

Retrospective cohort study of adult patients from an Australian Local Health (2008- 2017). We examined the incidence and prevalence of renal infarction along with risk factors associated with a renal infarction. We compared patients with a renal infarction to the general population and a 1:5 matched cohort to examine risk of mortality and KRT. Logistic regression was used to examine risk factors for renal infraction with odds ratio (OR) and 95% confidence intervals (95%CI), and Cox proportional hazard regression was used to determine hazard ratio (HR).

Results:

Of the 140,099 patients included a renal infarction occurred in 119 (0.1%) with a crude incidence of 1.9 per 10,000 patient years (95%CI 1.6- 2.2). Factors associated with the risk of a renal infarction were age (OR 1.17 by decade, 95%CI 1.06- 1.30), atrial fibrillation (OR 2.55, 95%CI 1.54- 4.28), valvular heart disease (OR 2.88, 95%CI 1.26- 6.57) and peripheral vascular disease (OR 7.69, 95%CI 4.54- 13.4). During follow-up there was no increased risk of mortality after adjusting for age and comorbidities (HR 1.19, 95%CI 0.89- 1.61). However, the risk of KRT was significantly elevated even after adjusted for confounder (HR 8.4, 95%CI 3.6- 19.7). These results remained valid in the matched analysis.

Conclusions:

Renal infarction is an uncommon event. The risk of mortality is not significantly increased when compared to the general population after adjusting for confounders. However, the risk of KRT remains significantly increased.
Beyond Boundaries: Transnational Identity in Contemporary Indian Literature
Authors: Udhayakumar S.
Published: February 2025

The predominant notion of Contemporary Indian literature is to explore the profound analysis of identity in the perceptions of displacement narratives, cultural negotiation, and personal transformation. In Salman Rushdie’s Midnight Children and Jhumpa Lahiri’s The Namesake are considered pioneering novels that elucidate the complexity of transnational experiences, whose individual identities are continuously transferred across geographical and emotional boundaries. The predominant notion of Contemporary Indian literature is to explore the profound analysis of identity in the perceptions of displacement narratives, cultural negotiation, and personal transformation. In Salman Rushdie’s Midnight Children and Jhumpa Lahiri’s The Namesake are considered pioneering novels that elucidate the complexity of transnational experiences, whose individual identities are continuously transferred across geographical and emotional boundaries. Characters reflect the essential postcolonial figure – constantly caught between different cultural environments, questioning traditional ideas of indigenous. The struggle and exploration of the characters Saleem Sinai and Gogel Ganguli are greater than the protagonists; their diasporic consciousness and their lives represent the intertwined between their self-efficiency and collective consciousness, metaphorically personified with the thematic frameworks. The vital inquisition of identity as a variable and vibrant concepts are evident in Rushdie’s magical realism and Lahiri’s nuanced psychological observation. These novels appropriately exhibited the transnational experiences which are not merely connected with geographical alteration but also connected with psychological quest of self-realization. The complicated practice of cultural hybridization is depicted in the struggle of the characters where these personal narratives interconnect with inclusive notions of historical and migratory experiences.Thus, personal narratives effectively project the way of how contemporary Indian literature goes beyond the representation of ordinary things, becoming a crucial part where different cultures interact and come to terms with each other. By exposing on these central characters, the novels demonstrate how the limits of national boundaries are not solid and unchanging.Rushdie and Lahiri frames a concreating narratives that encounter monolithic understandings of cultural identity by intersecting personal experience with the wide spread socio-political backdrops. Their novels highlight the cross national borders can intensely change people. And they expressed that being displaced opens a new path of thinking about self and communal.
Artificial Intelligence on Learning Experience: An Outlook
Authors: Mirunalini M. , Komail V.
Published: February 2025

New technology and tools multiply daily in that digital age. The rise of Artificial Intelligence has sparked with new wave of advancements with its features becoming more and more integrated into our everyday lives. Artificial Intelligence in education enhances individualized learning, permits to progress at their own pace, facilitates collaboration easy access to wide range of resources, empowers students to explore deep understanding beyond the traditional classroom. Challenges faced by the students such as it leads to passive learning, requires digital skills to use the features. The broad objective of the study is to examine the benefits and challenges of Artificial Intelligence in learning experiences. Higher Education Students from under graduate, Post graduate and Ph.D scholars from Government, Government aided, Self-Finance colleges were chosen for the study by Stratified random sampling technique. A set of survey questionnaire with 40 items comprised of benefits and challenges faced through in learning experiences with a 5 point Likert scale with each statement rated strongly agree (5), agree (4), neutral (3), disagree (2), strongly disagree (1). The study revealed that students agreed that the benefits are great to the extent and challenges are at modest. Practical contributions to organize adequate training programmes regarding potential benefits and ethical considerations of using Artificial Intelligence. Continuous learning support is desirable and changes in guidelines, curriculum design and assessment ensures exploiting the benefits of Artificial Intelligence in learning experiences.
Evaluation of Malayalam Language Instruction and Learners’ Attitudes, Achievements, and Current Conflcts in Language Instruction: A Study of Second Language Teaching in Kerala Higher Education
Authors: Pratheesh P. , Reema Mary
Published: February 2025

The conservancy and advancement of the state language, the Malayalam (one of the classical Indian languages), hold significant cultural, social and educational significance in Kerala. Being the official language of the state and the medium of education up to secondary school, it shapes students’ linguistic skills and cultural competencies. However, the value and effectiveness of Malayalam language teaching and learning in higher education remains a question since the use of Malayalam as the medium of instruction is not permitted in higher education in Kerala. This study attempts to evaluate the current state of Malayalam language instruction in higher education sector of Kerala, focusing on learners’ attitudes, achievements, and present conflicts surrounding language instruction. Using a mixed-methods approach, the study combines quantitative surveys and qualitative interviews to wrinkle comprehensive data from students and teachers from various colleges of Kerala. The findings indicate that there is a general positive attitude towards Malayalam, highlighting a strong cultural connection and a desire for proficiency among all stakeholders. However, there are substantial disparities in outcome of learning which indicate that instructional modalities may not sufficiently meet varied learning needs (teacher deficit), as well as perceived gap in pre-requisite basic abilities, vocabulary, word context, spelling, and grammatical norms (learner deficit). The present conflicts in language instruction rooted in curriculum constraints, resource limitations, and a perceived undervaluation of regional languages in favour of global languages. The findings are significant with respect to policy recommendations and pedagogical strategies to promote effective language teaching, enhance student engagement, and reconcile existing conflicts, and ultimately fostering a more robust environment for Malayalam language learning.
A rare presentation of systemic lupus erythematosus in a paediatric patient: a case report
Authors: Leng Kah Suen , Khaw Adeline Mae Li
Published: February 2025

Background: Systemic lupus erythematosus (SLE) is the prototype of a multisystem autoimmune disease. We report a rare case of severe vaso-occlusive retinopathy as the first presenting feature of SLE in a child.
Case presentation: An 11-year-old girl presented with sudden blurred vision in the right eye for 1 day. Visual acuity in the right eye was counting fingers. The patient was diagnosed with combined central retinal artery and vein occlusion in the right eye. Fundus examination of the left eye was normal. On day 2, vision in the right eye deteriorated to no light perception and the left eye’s fundus developed Roth spots. Laboratory findings suggested SLE. The patient was comanaged by a multidisciplinary team consisting of paediatrics, rheumatology, and ophthalmology.
Conclusion: We highlight the significance of early detection and multidisciplinary approach in the management of this patient to protect the fellow eye and for systemic control of inflammation.
HYBRID EDGE-CLOUD AI FOR RURAL STEM EDUCATION: AN OFFLINE-CAPABLE MOBILE SYSTEM INTEGRATING CLAUDE, GEMINI, AND OLLAMA LLMS TO OPTIMIZE ASSESSMENTS IN LOW-CONNECTIVITY CONTEXTS
Authors: Beltran Diego E.
Published: February 2025

Rural STEM education in developing regions faces critical challenges including intermittent connectivity, scarce technological resources, and inadequate access to quality instructional support. This paper presents a novel hybrid edge-cloud AI system designed to optimize assessments and personalized learning in low-connectivity contexts through the integration of multiple large language models(LLMs). The proposed mobile-first architecture combines offline-capable Progressive Web Applications(PWAs) with a distributed AI framework: Ollama’s lightweight LLMs (1.5–3.8B parameters) for edgeprocessing, Anthropic Claude 3.5 Sonnet for deep pedagogical analysis, and Gemini 1.5 Flash for rapidand cost-efficient cloud-based responses. A six-layer technical architecture enables QTI-standard assessments with LaTeX rendering, adaptive testing, and multi-level feedback generation, while maintaining functionality during internet outages through service workers and local storage. Preliminary evaluation at a Colombian rural school demonstrated a 9.6% increase in mathematics scores (Cohen’s d = 0.484), complete elimination of low-performing students (0–35 point range), and 85% student satisfaction with exam preparation support. The hybrid AI system achieved 60–95% feedback accuracy across models while reducing latency from 8–10 days (manual grading) to 15–20 minutes. A comprehensive cost-benefit analysis revealed 99.9% savings over cloud-dependent platforms (e.g., ALEKS McGraw Hill: $1.56 vs. $1,253 per student over five years), primarily through elimination of recurring internet costs. These results validate the technical feasibility and pedagogical efficacy of edge-cloud AI synergies in resource-constrained environments, offering a scalable model for national education frameworks prioritizing digital inclusion and equitable STEM access.
Structural, Electronic and Topological Properties of Carboplatin Conjugate with Fullerenol
Authors: Pushkarchuk A. L. , Bezyazychnaya T. V. , Potkin V. I. , Dikusar E. A. , Soldatov A. G. , Kilin S. Ya. , Nizovtsev A. P. , Kutsen S. A. , Yermak D. V. , Pivovarchik T. S. , Migas D. B. , Kulchitsky V. A.
Published: February 2025

The article presents the calculation of the structural and electronic characteristics of a conjugate consisting of the drug carboplatin (C6H12N2O4Pt) and a fullerenol (C60(OH)24) nanocarrier by the HF-3c method. Optimization of the geometric structure of the conjugate in an aqueous medium was carried out using the same level of theory and the polarizable continuum model. To clarify the nature of the intermolecular bond and assess the strength of the interaction between the carboplatin molecule and fullerenol, a topological analysis of the mechanisms of non-covalent interaction was performed based on the quantum theory of atoms in molecules. Individual paired atomic non-covalent interactions in the conjugate were analyzed and their energies were estimated using the correlation between the interaction energy and the characteristics of the electron density at the critical points of the bonds. It is shown that the conjugate is formed due to weak interaction forces between carboplatin and fullerenol, ensuring the release of the drug when delivering it to the corresponding DNA region without significant energy costs. The studied conjugates can be used for targeted drug delivery.