bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of non-performing financing and operational efficiency on the stability of Islamic banks in Persian Gulf countries
Authors: Salsabilla Lathifah Zaina , Jaya Tiara Juliana
Published: February 2025

IntroductionIslamic banking has become an integral part of the global financial system, particularly in the Persian Gulf region. Due to its reliance on profit-sharing and non-interest-based operations, Islamic banking faces unique challenges in maintaining stability, particularly when financing problems arise. ObjectivesThis study analyzes the effect of Non-Performing Financing (NPF), operational efficiency, and input-output optimization on the stability of Islamic banks in the Persian Gulf countries. MethodThis study employs a quantitative approach using panel data regression models, specifically the random effects model (REM), to analyze data from 27 Islamic banks in eight Persian Gulf countries. The study includes classical assumption tests, such as normality, multicollinearity, and heteroscedasticity, followed by hypothesis testing using t-tests and F-tests.ResultsThe results indicate that both NPF and efficiency have significant negative impacts on the stability of Islamic banks. The t-test reveals that NPF has a probability value of 0.0447 and a negative coefficient, suggesting that higher NPF levels reduce bank stability. Similarly, operational efficiency, as measured by the input and output variables, also shows a negative influence on stability, with a probability value of 0.0435. The F-test confirms that NPF, input, and output significantly affect Islamic bank stability, with an F-statistic probability value of 0.038223.ImplicationsThese findings have important implications for the management of Islamic banks in the Persian Gulf countries. Effective management of NPF is critical for maintaining stability, and operational improvements in efficiency can also enhance financial performance. Islamic banks should focus on improving their financing practices, including better monitoring problematic loans and diversifying revenue streams to reduce reliance on financing income.Originality/NoveltyThis study contributes to the understanding of Islamic bank stability by exploring the combined effects of Non-Performing Financing (NPF) and operational efficiency on bank financial health. By focusing on Islamic banks in the Persian Gulf countries, this study highlights region-specific challenges and offers strategies for mitigating financial risks and enhancing bank resilience through better management of NPF and operational efficiency.
Retrospective Evaluation of Subpleural Consolidations Using Lung Ultrasound in 634 Dogs and 347 Cats
Authors: Kraszewska Katarzyna , Gajewski Michał , Boysen Søren , Buda Natalia
Published: February 2025

Background: Human literature describes vascular patterns in various types of lung consolidations; however, these changes have not been analyzed in dogs and cats. This retrospective analysis of medical records aimed to describe vascular patterns observed in the airless subpleural lung tissue of dogs and cats and to compare these patterns to various lung consolidations and clinical diagnoses according to parenchymal and vascular criteria described in the human literature. Animals: 347 cats and 634 dogs. Methods: This was a retrospective study encompassing medical records obtained between 2018 and 2023. Lung ultrasound was performed in dogs and cats and cases with different sonographically identified airless subpleural lung tissue were selected. Lung consolidations were classified as shred, nodule, wedge sign, mass, and tissue sign. Further classification was based on the parenchymal criteria, the presence or absence of bronchograms and the vascular patterns identified within these regions. Bronchograms were classified as air bronchograms (dynamic and/or static), fluid bronchograms, mixed fluid and air bronchograms, and/or absence of bronchograms. Vascular patterns were classified as tree-like, residual, chaotic, “vascular sign,” and whether they were continuous with and extended from the chest wall or not. Conclusions and Clinical Importance: It is possible to identify and characterize airless subpleural lung tissue in cats and dogs based on the parenchymal and vascular characteristics.
One-X Property Conjecture, Stochastic Orders and Implied Volatility Surface Construction
Authors: Cao Zeyu , Zhao Siqiao , Huang Shaosai
Published: February 2025

In this work, we explore Conjecture 1 proposed in the newly released pioneering paper “Volatility transformers: an optimal transport-inspired approach to arbitrage-free shaping of implied volatility surfaces” by Zetocha Valer, which posits that the “One-X” property is both a necessary and sufficient condition for convex order between non-negative continuous strictly increasing distributions with the same mean. We provide a counterexample demonstrating that the conjecture, as originally stated, does not hold. By examining stochastic orders, particularly the increasing convex order, and the “One-X” property, we propose an enhanced version of the conjecture which is shown to be valid. Furthermore, we discuss the implications of these findings in the context of equity implied volatility fitting and the construction of implied volatility surfaces, highlighting the challenges posed by real-market conditions. In the end, we propose several applications in implied volatility surface construction or simulation. We also discussed the connection between TP2, RR2 and the one-X property.
Inverse Uncertainty Quantification in Material Parameter Calibration Using Probabilistic and Interval Approaches
Authors: Most Thomas
Published: February 2025

In model calibration, the identification of the unknown parameter values itself but also the uncertainty of these model parameters due to uncertain measurements or model outputs might be required. The analysis of the parameter uncertainty helps to understand the calibration problem better. Investigations on the parameter sensitivity and the uniqueness of the identified parameters could be addressed within the uncertainty quantification. In this paper we investigate different probabilistic approaches for this purpose, which identify the unknown parameters as multivariate distribution function. However, these approaches require the accurate knowledge of the model output covariance which is often not available. Alternatively, we investigate interval optimization methods for the identification of parameter bounds. The correlation or interaction of the input parameters can be modeled by a convex feasible domain which belongs to feasible solution of the model output within given bounds. We will introduce a radial line-search procedure which can identify the boundary of such a parameter domain for arbitrary non-linear dependencies between model input and output.
Bioprocess Optimization for Pectinase Enzymes Synthesized from Fungal Species Under Solid-State Fermentation Conditions
Authors: Owusu Boakye Sylvester , Domakyaara Zakpaa Hilary
Published: February 2025

Pectinases represent a class of enzymes involved in the breakdown of pectin-rich compounds. The importance of pectinases are well documented as they command at least a quarter of all food enzymes and 70% of all the fruit and juice processing enzymes sold around the world, respectively. The worldwide enzymes market is presently valued at $12.3 billion and is predicted to grow to $20.31 billion by 2030. This study successfully optimized the various conditions that could illicit the synthesis of pectinolytic enzymes using Aspergillus niger obtained from the soil of decomposed fruit and vegetable matter under solid-state fermentation conditions. Under the respective optimized fermentation conditions, the peak pectinase enzyme synthesis had been achieved under pH 6.0 (121.1 U/ml), incubation period of 5 days (117.4 U/ml), substrate morphology/particles size (118.0 U/ml), Peptone as nitrogen source (127.6 U/ml), Potassium chloride (KCl) as mineral salt (112.3 U/ml), Tween-20 as surfactant (126.8 U/ml), inoculum volume of 5.0ml (139.4 U/ml) and powdered Citrus peels as the best carbon source (124.8 U/ml). Under current study, moisture content (70%) and room temperature (25-30°C) and fermentation vessel (2.2L perforated tin tomato cans) were constantly maintained throughout the experiments executed under solid-state fermentation conditions. The success achieved from current study, make this enzyme isolated from Aspergillus niger, a potential candidate for many industrial applications including fruit juice clarification, wine production, food processing, coffee and tea fermentation, protoplast fusion, waste treatment, production of pharmaceuticals, detergents, pulp and paper and biofuels.
Introducing the Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Integral Equations of Volterra-Type: Mathematical Methodology and Illustrative Application to Nuclear Engineering
Authors: Cacuci Dan Gabriel
Published: February 2025

This work presents the general mathematical frameworks of the “First and Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Integral Equations of Volterra Type” designated as the 1st-FASAM-NIE-V and the 2nd-FASAM-NIE-V methodologies, respectively. Using a single large-scale (adjoint) computation, the 1st-FASAM-NIE-V enables the most efficient computation of the exact expressions of all first-order sensitivities of the decoder response to the feature functions and also with respect to the optimal values of the NIE-net’s parameters/weights after the respective NIE-Volterra-net was optimized to represent the underlying physical system. The 2nd-FASAM-NIE-V requires as many large-scale computations as there are first-order sensitivities of the decoder response with respect to the feature functions. Subsequently, the second-order sensitivities of the decoder response with respect to the primary model parameters are obtained trivially by applying the “chain-rule of differentiation” to the second-order sensitivities with respect to the feature functions. The application of the 1st-FASAM-NIE-V and the 2nd-FASAM-NIE-V methodologies is illustrated by using a well-known model for neutron slowing down in a homogeneous hydrogenous medium, which yields tractable closed-form exact explicit expressions for all quantities of interest, including the various adjoint sensitivity functions and first- and second-order sensitivities of the decoder response with respect to all feature functions and also primary model parameters.
The Comprehensive Evolution of ERP Systems: Classification, Financial Integration, and Future AI Integration
Authors: Chen Bing
Published: February 2025

The evolution of ERP systems from rigid on-premise solutions to agile, cloud-native platforms has revolutionized organizational management. Today, ERP systems span diverse industries and functionalities, from financial management to supply chain optimization. This paper synthesizes the capabilities of prominent ERP systems—SAP, Oracle, MRI, iScala, PeopleSoft, JDE, Salesforce, and QuickBooks—highlighting their roles in financial operations and their readiness for AI-driven transformation. Additionally, this paper explores the application of ERP systems in emerging industries such as fintech and biopharma, where the integration of AI and ERP is becoming increasingly crucial for competitive advantage. Recent advancements in AI, such as the development of more sophisticated machine learning algorithms and natural language processing capabilities, are further enhancing the potential of ERP systems to drive business innovation and efficiency.
Global Plasma Model in DC Dual Stage Gridded Ion Thrusters
Authors: Lettera Elpidio , Coppola Giovanni , Panelli Mario
Published: February 2025

Gridded Ion Thruster (GIT) is a versatile space propulsion device that can be used for a wide range of space missions being characterized by a high trust-to-power ratio and a relatively high specific impulse. In recent years, there has been a significant increase in academic and scientific interest in interplanetary and deep space exploration that has shifted research resources toward boosting the performances of GITs. One promising concept is to separate the extraction process of the ions from their acceleration (Dual Stage). Some researches focused the attention on basic experiments to assess the functioning principle, some tried to simply model its Optical System (OS) and only few of them used a numerical approach to verify it. In this work a global plasma model for both the Direct Current (DC) ionization chamber and OS is proposed. The model combines analytical formulas, describing the plasma physics into ionization chamber, a linear optic model for OS, and a curve-fitting approach, to get performances and working parameters. As input it requires the diameter of the engine and the thrust or power. An educated guess is made by considering the validity of the thrust/diameter-total efficiency curve, obtained for conventional GIT, due to the lack of these data for Dual Stage Gridded Ion Thrusters (DSGIT). Despite this hypothesis, the results obtained by the model are in good agreement with the performances and working parameters of preliminary designed high power (25-50 kW) thrusters, available in open literature and selected for the validation, obtaining for the most differences less than 5 %. Finally the model has been applied to exploit the advantage of DS approach by designing a 1kW thruster: the results are very promising because a ten times smaller thruster than a conventional GIT, could have hundred times higher thrust and power density and an increment of the efficiency and the specific impulse by 25 %.
Evaluation of Power System Stability for a Hybrid Power Plant Using Wind Speed and Cloud Distribution Forecasts
Authors: Tchokomani Moukam Théodore Desiré , Sugawara Akira , Li Yuancheng , Bello Yakubu
Published: February 2025

Power system stability (PSS) is the ability of a system to remain in operating equilibrium which is achieved between the electric power generation and consumption. In this paper, we evaluate PSS for a Hybrid power plant (HPP) combining thermal, wind, solar photovoltaic (PV) and, hydro power generations, in Niigata City. A new method to estimate PV power generation, based on NHK cloud distribution forecast (CDF) and land ratio settings, is also introduced. Our objective is to achieve frequency stability (FS) while reducing CO2 emission in the power generation sector. So, PSS is evaluated from the results of the frequency stability (FS) variable. 6-minutes autoregressive wind speed prediction (6ARW) support for wind power (WP). 1-hour GPV wind farm (1HWF) power is computed from the Grid Point Value (GPV) wind speed prediction data. PV power is predicted by autoregressive modelling and CDF. In accordance with the daily power curve and the prediction time, we can support thermal power generation planning. Actual data of wind and solar are measured every 10-minutes and 1-minute, respectively and the hydropower is controlled. The simulation results of the electricity frequency fluctuations are within ±0.2 Hz of the requirements of Tohoku Electric Power Network Co. Inc., for testing and evaluation days. Therefore, the proposed system supplies electricity stably while contributing to CO2 emission reduction.
New Upper Bounds on the Number of Maximum Independent Sets of a Graph
Authors: Levit Vadim E. , Itskovich Elizabeth J.
Published: February 2025

An \textit{independent set} in a graph comprises vertices that are not adjacent to one another, whereas a \textit{clique} consists of vertices where all pairs are adjacent. For a given graph $G$, let the following notations be defined: the number of vertices in $G$ is $n(G)=n$, the cardinality of a maximum independent set in $G$ is $\alpha(G)-\alpha$, the size of the largest clique in $G$ is $\omega(G)=\omega$, the cardinality of the intersection of all maximum independent sets in $G$ is $\xi(G)=\xi$.

As the main finding of the article, we present an upper bound on the number of maximum independent sets as follows:
\[
s_{\alpha} \leq \sum_{k=0}^{\alpha- \xi} \binom{n - \alpha - \omega + 1}{k} + (\omega - 1) \cdot \sum_{k=0}^{\alpha- \xi - 1} \binom{n - \alpha - \omega + 1}{k}
\]
\[
\leq
\omega \cdot 2^{\min(\alpha - \xi, n - \alpha - \omega - \xi + 1)}.
\]

As an application of our findings, we explore a series of inequalities that connect the number of longest increasing subsequences with the number of longest decreasing subsequences in a given sequence of integers.
HAG-SDP: A Hierarchical Attention-Based Graph Neural Network for Software Defect Prediction
Authors: M Umesh , G Manjula
Published: February 2025

Software defect prediction remains a critical challenge in software engineering, as traditional approaches struggle to effectively capture complex code relationships and dependencies, leading to missed defects and inefficient resource allocation in quality assurance. This paper introduces HAG-SDP, a novel hierarchical attention-based graph neural network approach that addresses these challenges by representing source code as a multi-level graph structure. Our method uniquely combines syntactic and semantic relationships while employing attention mechanisms to identify defect-prone patterns, processing code at multiple granularity levels from individual statements to module-level interactions. We evaluate our approach on the JM1 dataset from the NASA Metrics Data Program, demonstrating superior performance with an accuracy of 87.3%, precision of 83.6%, and F1-score of 82.7%, significantly outperforming both traditional machine learning methods and recent deep learning approaches. The model's attention mechanism not only enhances prediction accuracy but also provides interpretable insights by highlighting potentially problematic code regions. Through comprehensive ablation studies, we demonstrate the significant contribution of each architectural component, particularly the hierarchical structure and attention mechanisms. Our results show robust performance across various defect types, offering practical insights for code review prioritization and testing resource allocation, ultimately contributing to more efficient software quality assurance processes.
Fecal Microbiome and Metabolome Testing: An Emerging Tool for Evaluating Culinary Medicine Interventions
Authors: McDonald* Edwin , Wilson TJ , Temelkova Sara , Deleon Orlando , Lo Elaine , Lofton Saria , Wise Jeannine , Chang Eugene
Published: February 2025

Chronic diseases, including cardiovascular disease, stroke, diabetes, and cancer, are among the leading causes of death in the US. An unhealthy diet is one of the most significant risk factors underlying these chronic, noncommunicable diseases. Eating out has become increasingly common, while home-cooking has declined. Culinary Medicine is an evidenced-based strategy that incorporates culinary arts in nutrition education. Multiple studies indicate that Culinary Medicine can improve eating behaviors, expand culinary knowledge, and improve confidence in one's cooking ability. However, Culinary Medicine studies often rely on subjective data such as Food Frequency Questionnaires and 24-hour dietary recall. These instruments are subject to bias. Dietary biomarkers enhance Culinary Medicine evaluations. Since diet is a well-known modulator of the gut microbiome and its metabolites, we argue that fecal microbiome and metabolome assessments are valuable in investigating the outcomes of Culinary Medicine studies.
A Quinoxaline 1,4-Dioxide Activates DNA Repair Systems in Mycobacterium smegmatis: A Transcriptomic Study
Authors: Bekker Olga B. , Galanova Olesya O. , Vatlin Aleksey A. , Frolova Svetlana G. , Shitikov Egor A. , Bespiatykh Dmitry A. A. , Klimina Ksenia M. , Veselovsky Vladimir A. , Ilyasov Rustem A. , Smirnova Svetlana V. , Reznikova Diana A. , Kochetkov Nikita I. , Maslov Dmitry A. , Danilenko Valery N.
Published: February 2025

In 2022, the World Health Organization reported that tuberculosis (TB) was the second leading cause of death globally from a single infectious agent, following COVID-19. The development of new antitubercular agents with novel mechanisms of action for use in complex TB therapy is considered a key approach to combating TB. In this study, we examined the gene expression profile of M. smegmatis when exposed to a promising antituberculosis agent, quinoxaline 1,4-dioxide (QdNO) 7-chloro-2-(ethoxycarbonyl)-3-methyl-6-(piperazin-1-yl)quinoxaline-1,4-dioxide-1 (LCTA-3368). We investigated how the bacterial response changed with different doses (1/4 × MIC, 1/2 × MIC, and 1 × MIC) and durations (30 minutes and 90 minutes) of treatment with the drug. Our analysis revealed significant upregulation of genes involved in DNA repair and replication processes, as well as changes in the expression of 95 genes encoding proteins with oxidoreductase activity. These findings support the proposed mechanism of antibacterial action of QdNOs, which is associated with the formation of free radicals leading to DNA damage.
Total Sealing Technique: A Novel Surgical Approach that Sig-nificantly Reduces the Incidence of Upper Extremity Lymphedema Following Axillary Dissection in Patients with Breast Cancer
Authors: Ikeda Naoya , Nagata Takuya , Umemura Teiji , Watanabe Manabu
Published: February 2025

Background/Objectives: In a previous study, we reported a novel surgical procedure called the Total Sealing Technique (TST), which uses a bipolar vessel-sealing system to reduce lymphatic leakage during axillary dissection for breast cancer. Follow-up ob-servations showed a lower incidence of breast cancer-related lymphedema (BCRL) in patients in the TST group. Therefore, in this current study, we aim to investigate and compare the incidence of BCRL between two groups (TST and conventional electrocautery (CONV)) and discuss why the incidence of BCRL was significantly lower in the TST group than in the CONV group. Methods: We conducted a comparative analysis of 36 patients who underwent total mastectomy with axillary lymph node dissection (ALND) using the CONV procedure during the first three years, and 35 patients who underwent the same procedure using TST during the subsequent three years. We evaluated the incidence of BCRL and its association with the risk factors in both groups. Results: The incidence of BCRL was 2.9% in the TST group and 22.2% in the CONV groups, respectively (p = 0.028). In the TST group, no significant association was found between the incidence of BCRL and known risk factors. However, in the CONV group, the incidence of BCRL was signifi-cantly higher in younger patients and in those who received neoadjuvant or postoperative chemotherapy, a taxane-containing regimen, or > 600 mL of drainage. Conclusions: TST with LigaSure™ Exact Dissector significantly reduces BCRL incidence, suggesting that it may become an important surgical procedure for axillary dissection in breast cancer in the future.
Critical Minerals Mining: A Path Toward Sustainable Resource Extraction and Aquatic Conservation
Authors: Mohamed Abdel-Mohsen O. , Paleologos Evan K. , Mohamed Dina , Fayad Adham , Al Nahyan Moza T.
Published: February 2025

The rising demand for critical minerals essential for modern technologies, renewable energy solutions, and advanced electronics has intensified mining activities worldwide. While these minerals are vital for a sustainable future, their extraction and processing often pose significant threats to aquatic ecosystems. Findings indicate that mining operations result in severe water contamination through heavy metals and toxic discharge, habitat destruction due to sedimentation and landform alterations, and disruption of hydrological cycles affecting both surface and groundwater. Additionally, the biodiversity of aquatic life is at significant risk, with examples such as mercury bioaccumulation in the Amazon Basin and coral reef degradation in Indonesia. This paper examines these impacts in detail, supported by global case studies, and explores strategies for mitigating these effects through sustainable mining practices, advanced water treatment technologies, and robust regulatory frameworks.
Improved Ionization Potential Depression Model Incorporating Dynamical Structure Factors and Electron Degeneracy for Non-Ideal Plasma Composition
Authors: Seitkozhanov Yeldos , Shalenov Erik , Dzhumagulova Karlygash
Published: February 2025

In this work, we present an improved model for ionization potential depression (IPD) in dense plasmas that builds upon the approach introduced by Lin et al., which utilizes a dynamical structure factor (SF) to account for ionic microfield fluctuations. The main refinements include: (1) replacing the Wigner–Seitz radius with an ion-sphere radius, thereby treating individual ionization events as dynamically independent; and (2) incorporating electron degeneracy through a tailored interpolation between Debye–Hückel and Thomas–Fermi screening lengths. Additionally, we solve the Saha equation iteratively, ensuring self-consistent determination of the ionization balance and IPD corrections. These modifications yield significantly improved agreement with recent high-density and high-temperature experimental data on warm dense aluminum, especially in regimes where strong coupling and partial degeneracy are crucial. The model remains robust over a broad parameter space, spanning temperatures from 1 eV up to 1 keV and pressures beyond the Mbar range, thus making it suitable for applications in high-energy-density physics, inertial confinement fusion, and astrophysical plasma research. Our findings underscore the importance of accurately capturing ion microfield fluctuations and electron quantum effects to properly describe ionization processes in extreme environments.
The Road Map to Digital Twin of Kyrenia: Challenges, Opportunities, and Future Directions
Authors: Akçit Nuhcan
Published: February 2025

This study explores the creation of a digital twin for Kyrenia, Cyprus, focusing on the challenges and opportunities presented by this innovative urban planning tool. We discuss the integration of real-time data, citizen engagement, scalability, environmental sustainability, and the economic and social impacts of implementing a digital twin. The research identifies key gaps in current literature and proposes future research directions to enhance the utility of digital twins in urban development.
Sleep Benefits Prose Memory Consolidation in University Students
Authors: Malloggi Serena , Conte Francesca , De Rosa Oreste , Ficca Gianluca , Righi Stefania , Viggiano Maria Pia , Giganti Fiorenza
Published: February 2025

Background: Sleep plays a pivotal role in memory consolidation, especially for declarative memory. While extensive research has examined sleep's impact on simple declarative materials, such as word lists, its effect on more complex narrative passages remains less studied. This study aimed to investigate the effect of sleep on prose memory consolidation. Methods: In a within subject design, participants learned prose passages and were tested both immediately and after a retention interval spent either asleep or awake. Results: Analyses revealed a positive effect of sleep, with participants recalling more textual details in the sleep condition. Correlational analyses further support this outcome, showing a positive association between specific sleep features (i.e., sleep cycles) and prose memory performance. Conclusions: Our finding suggests that sleep facilitates consolidation of complex declarative memory traces, counteracting the decay that occurs during wakefulness; correlational analyses further support this outcome. Overall, these findings underscore the importance of sleep for everyday learning and comprehension, particularly when processing complex textual information.
Energy Production from Urban Solid Waste: Short-Term Management and Storage
Authors: Domingues Nuno Soares
Published: February 2025

A new stage is now in full development with objectives and targets set by the European Union with regard to reducing the production of Municipal Solid Waste (MSW). The targets also include the increasing selective collection, reuse, recycling and organic and energy recovery of the waste produced. At the same time, the European Union has also set targets for the overall reduction of greenhouse gas emissions and for increasing the use of alternative renewable energy sources. In this context, one of the sources of renewable energy that is beginning to be used for the production of electricity in our country is biogas, which comes from the anaerobic decomposition of MSW deposited in landfills, while achieving two objectives: reduce the emission of methane into the atmosphere, through the burning of biogas from landfills, as required by Decree-Law No. 152/2002 of May 23rd and contribute to the energy recovery of waste.
Untapped Potential of AI in Insurance: A Novel Framework for Enhancing Customer Experience Through Personalization, Trust, and Ethical AI Practices
Authors: Abdollahi Zamharir Mohammad
Published: February 2025

This study explores the impact of artificial intelligence (AI) on customer experience in the insurance industry, with a focus on the mediating roles of personalization and trust. Using a sample of 500 customers from various insurance companies, data were collected through a structured questionnaire and analyzed using Structural Equation Modeling (SEM). The results reveal that AI significantly enhances customer experience by improving personalization and building trust. Furthermore, personalization and trust play crucial mediating roles in the relationship between AI and customer experience. The study provides actionable insights for insurance companies, emphasizing the need to leverage AI technologies to deliver personalized services and foster trust, thereby enhancing customer experience and loyalty. These findings contribute to the existing literature by offering a comprehensive understanding of the role of AI in transforming customer experience in the insurance sector. The study highlights the importance of leveraging AI technologies to deliver personalized services and foster trust, thereby enhancing customer experience and loyalty. These findings provide actionable insights for insurance companies aiming to optimize their AI strategies. These findings contribute to the literature by providing a comprehensive understanding of how AI transforms customer experience in the insurance sector through the mediating roles of personalization and trust.
Diffusion Models at Scale: Techniques, Applications, and Challenges
Authors: Abul-Fazl Sa'dia , Dina Rasim , Fairuza Hafez
Published: February 2025

Diffusion models have emerged as a powerful class of generative models, offering state-of-the-art performance across various domains such as image synthesis, audio generation, and molecular design. Their unique approach, which involves modeling data distributions through iterative noise addition and denoising processes, has established them as a robust alternative to traditional generative frameworks like GANs and VAEs. However, the scalability of diffusion models—essential for handling high-dimensional data, large-scale datasets, and complex multimodal tasks—poses significant challenges. This survey provides a comprehensive overview of scalable diffusion models, focusing on the innovations that enable their efficient training and sampling. We explore advancements in noise schedules, neural architectures, and sampling acceleration techniques, alongside strategies for training on large-scale datasets and deploying models in resource-constrained environments. Furthermore, we highlight the transformative applications of scalable diffusion models across fields such as creative content generation, healthcare, scientific research, and more. Despite their successes, diffusion models face critical challenges, including computational inefficiency, resource-intensive training, and ethical concerns related to bias and misuse. We discuss these open challenges and outline promising directions for future research, emphasizing the need for interdisciplinary collaboration and task-specific adaptations. By addressing these challenges, scalable diffusion models have the potential to redefine the boundaries of generative modeling, driving innovation and enabling new applications in science, technology, and creative industries. This survey aims to serve as a valuable resource for researchers and practitioners seeking to understand and advance the field of diffusion models.
Serum Prolidase Activity in Silicosis and Its Relationship with Oxida-Tive Stress and Inflammation Markers
Authors: Ergün Dilek , Ergün Reca , Özkan Esin , Bacanlı Merve , Körez Muslu Kazım
Published: February 2025

Background:This study aimed to evaluate the prognostic significance of serum prolidase ac-tivity in silicosis and to examine its relationship with oxidative stress and inflammatory param-eters. Methods: One hundred thirteen patients with silicosis, 70 workers with a history of exposure who did not develop the disease and 53 healthy volunteers of similar age and gender were included in the study. Serum levels of prolidase, superoxide dismutase, catalase, 8-hydroxy-2-deoxyguanosine, glutathione peroxidase, glutathione reductase, tumor necrosis factor α, fibroblast growth factor, interferon-gamma, and interleukins (IL) 1α and 1β were measured. Genetic damage was assessed by measuring 8-hydroxy-2'-deoxyguanosine in serum. Results: The difference was not statistically significant because serum prolidase activity was higher in the silicosis and silica-exposed group than in healthy controls.Serum superoxide dis-mutase and glutathione peroxidase levels were significantly lower in the exposure and silicosis groups compared to the control group. 8-hydroxy-2'-deoxyguanosine and tumor necrosis factor α, fibroblast growth factor, interferon-gamma, and IL-1α were significantly higher in the exposure and silicosis groups than in the control group. In individuals with high prolidase activity, both oxidative stress and inflammation parameters were high. Conclusion:The fact that serum prolidase activity is closely associated with inflammation, fibrosis, and oxidative stress in sili-cosis suggests that prolidase can be used in the early diagnosis and follow-up of silicosis. Early disease diagnosis is important for stopping exposure and taking preventive measures.
Green Synthesis of Alginate/Hydroxyethyl Cellulose (SA/HEC) Hydrogels Cross-Linked by Ca2+/Mg2+ Ions and Their Anti-Microbial Efficacies
Authors: Shahitha Fathima , Ghosh Soumya , Al Saadi Hani , Abdullah Alsibani Mohammed , Al-Amri Issa Sulaiman , Al-Harrasi Ahmed , Al Abri Aisha , Al Hinai Asma , Al Hosni Saif , Al Hatmi Abdullah
Published: February 2025

Eco-friendly antimicrobial hydrogels derived from carbohydrate polymers are receiving significant attention for their sustainable and cost-effective properties. This study focuses on developing antimicrobial hydrogels based on alginate and hydroxyethyl cellulose (SA/HEC) using a green chemistry approach. The impact of bivalent metal ions on cross-linking efficiency and the hydrogels' physicochemical properties were analyzed, with hydrogels produced in various forms, such as beads, sponges, and films, characterized by SEM, XRD, TGA, FTIR, and UV-vis spectroscopy. Calcium (Ca²⁺), magnesium (Mg²⁺), and Ca²⁺/Mg²⁺ combinations were explored, revealing that Ca²⁺ and Ca²⁺/Mg²⁺ combinations demonstrated excellent cross-linking efficiency, while Mg²⁺ alone was insufficient for cross-linking. However, adding small amounts of Ca²⁺ improved Mg²⁺ cross-linking capacity, yielding stable SA/HEC hydrogels. Beads exhibited porous structures (2–20 µm), and films with a thickness of ~150 µm were produced, showcasing strong mechanical and thermal stability. Additionally, in-situ synthesized silver nanoparticles (AgNPs) within SA/HEC hydrogels exhibited antimicrobial activity against Escherichia coli ATCC 25922, Staphylococcus aureus ATCC 29213, and fungal strains Candida albicans ATCC 14053 and Candida krusei ATCC 6258. This study successfully demonstrates a green chemistry method to synthesize water-insoluble hydrogels cross-linked with Ca²⁺/Mg²⁺ ions with inherent antimicrobial properties.
Methods for Assessing Neurodevelopmental Disorders in Rodents: A Critical Review of Behavioral Tests and Methodological Considerations Searching to Improve Reliability
Authors: Echefu Boniface Ezenwata , Becker Maria , Stein Dan , Ornoy Asher
Published: February 2025

Many neurobehavioral tests are used for the assessment of human-like behaviors in animals. Most of them were developed in rodents and are used for the assessment of animal models that mimic human neurodevelopmental and neuropsychiatric disorders (NDD). We have described tests for assessing social behavior, social interaction and social communication; tests for restricted and repetitive behaviors; tests for cognitive impairment, for sensory stimuli, for anxiety like behavior and for motor coordination deviations. These tests are used to demonstrate autistic-like behavior as well as other NDD. We described possible general pitfalls in the performance of such studies, as well as probable individual errors for each group of tests assessing specific behavior. The mentioned pitfalls may induce crucial errors in the interpretation of the results, minimizing the reliability of specific models of defined human NDD. It is imperative to minimize these pitfalls and also use sufficient and reliable tests that are able to demonstrate as many of the traits of the human disorder, grade the severity of the specific deviations and the severity of the tested NDD by using a scoring system. Due to possible gender differences in the clinical presentations of NDD, it is important to carry out studies on males and females.
Synergistic Analysis of Habitat Quality and Urbanization Based on InVEST Modeling
Authors: Wu Meiqing , Zhu Lanwei , Luo Lei , Dou Liduo , He Yuxin , Guo Yifei
Published: February 2025

Since its completion in 214 BCE, the primary function of the Lingqu Canal has evolved from military transportation and irrigation to tourism. Today, with the advancement of urbanization, the canal’s functions have further diversified, giving rise to economic models such as "Agriculture + Tourism," "Water Conservancy + Tourism," and "Culture + Tourism." These developments have stimulated regional economic growth and enhanced the value of the Lingqu Canal as a cultural heritage site. However, due to high population density along both banks, complex production activities, lagging infrastructure development, and weak regulatory capacity, certain sections of the canal are experiencing significant sediment accumulation, water quality degradation, and ecosystem deterioration. The habitat quality along the canal is declining, placing the integrity of the Lingqu Canal itself at risk. Therefore, exploring the synergistic effects between urbanization and habitat quality—while also examining both the economic benefits and trends in habitat quality changes resulting from transformations in the canal’s functions—is crucial not only for its sustainable development but also for ensuring its long-term preservation and utilization as a World Cultural Heritage site. Based on land use data from 2000 to 2023 and utilizing the InVEST model, this study investigates the spatiotemporal evolution of habitat quality along the Lingqu Canal. Additionally, it analyzes the driving factors using the Geodetector model. A spatial autocorrelation analysis is conducted to explore how the functional diversification of the canal impacts economic development, ecological protection, and sustainable development. The findings are as follows: (1) The average habitat quality index along the Lingqu Canal increased from 0.63 in 2000 to 0.76 in 2023, reflecting a consistent annual increase with an average growth rate of 0.83%. This indicates significant ecological restoration efforts during this period. (2) The spatial variation in habitat quality along the canal between 2000 and 2023 results from multiple influencing factors, with changes in land use, precipitation levels, and population density identified as key determinants. (3) A strong correlation exists between habitat quality along the Lingqu Canal during this period and local Moran’s I index values, revealing high-high clusters predominantly located in urban centers in the eastern regions. This demonstrates notable spatial synergies, suggesting that the diversification of the canal’s functions has significantly facilitated the harmonious coexistence of ecological protection and local economic development, providing valuable insights for the sustainable development of global historical and cultural heritage
African Swine Fever Epidemic in Vietnam: A Scoping Review
Authors: Chuong Vo Dinh , Schambow Rachel A. , Diep Nguyen Thi , Minh Phan Quang , Long Nguyen Van , To Nga Bui Thi , Perez Andres M.
Published: February 2025

African swine fever (ASF) has had a devastating impact on Vietnam’s swine industry since its emergence in 2019, leading to the culling of six million pigs. This paper aimed to review the epidemiological dynamics of ASF in Vietnam and measures applied to control the disease. ASF progressed through an initial epidemic phase (2019-2020) and has transitioned into a more endemic phase (2021-2024). The disease spread rapidly during the epidemic phase, driven by human-mediated transmission routes and inadequate biosecurity practices, particularly on smallholder farms. To control ASF, the Vietnamese government endorsed a national control plan including biosecurity enhancements, disease surveillance, establishing ASF-free compartments, developing ASF vaccines, and strengthening the capacity of veterinary services. While these measures have helped reduce the number of outbreaks, challenges persist, including the emergence of recombinant ASF strains, limited vaccine adoption, and gaps in veterinary infrastructure. ASF has substantially changed Vietnam’s swine industry, shifting toward reducing small-scale household farming and increasing professional households and large-scale farms. As ASF has transitioned into an endemic phase, sustainable strategies focusing on continuous monitoring, improved vaccination coverage, and education programs are essential to mitigate its impacts and ensure the resilience of Vietnam’s swine industry.
Study on Relationship between Mechanical Properties and Water Absorption Characteristics of Mortars by Using Digital Image Correlation Method (DICM)
Authors: Usman Muhammad , Nakamura Hikaru , Karam Muhammad Shoaib , Miura Taito , Igarashi Go
Published: February 2025

Evaluation of water absorption in concrete is regarded as an important indicator for assessing the causes of its deterioration and durability. Traditionally adopted methods for durability assessment in concrete materials, however, lack in providing real-time monitoring of the absorption process and that about the material deformability at surfaces (volumetric changes) caused by swelling in cement hydrates (i.e. C-S-H). In this study, a one-dimensional water absorption test was performed on small-size mortar specimens of three different strengths, and their top (flattened) surface was continuously monitored for volume changes by utilizing surface strain gauges along with DICM. After the water absorption test, the same specimens were tested for mechanical properties such as compressive strength and Young’s modulus. Moreover, the water absorption characteristics, like depth/rate, were evaluated in DICM by tracing changes of waterfront positions with the progression of strains during the water absorption process in mortars. Additionally, the surface strain gauges confirmed the accuracy of strains evaluated by DICM. The absorption characteristics obtained from observations in DICM were correlated with the mechanical properties and expansion strain of the test specimens. The results indicated that the durability properties were not only related to the water absorption rate but also to the mechanical properties and volume changes due to saturation.
Engineered Nanoparticles (ENPs) in Aquatic Environments and Soil-Plant Ecosystems: Transformation, Toxicity, and Environ-Mental Challenge
Authors: Islam A.K.M. Nazrul , Ridwan Asib , Neon Asif Karim , Rab Md. Fozle , Uddin Md. Nizam
Published: February 2025

The ever-increasing use of engineered nanoparticles (ENPs) in industries, medicine, and consumer products has resulted in their uncontrolled release into aquatic environments and soil-plant systems. ENPs may transform and release toxic by-products upon release, raising concerns about their environmental behavior and potential risks. However, accurately measuring ENP concentrations in these ecosystems remains a significant challenge. Recent studies have highlighted the toxic effects of ENPs on various organisms, but assessing the risk in aquatic and soil-plant systems remains a critical issue in nanoecotoxicology. ENPs interact with environmental materials, including organic matter, soil, sludge, and other pollutants, forming complex assemblies that may alter their toxicity and environmental fate. This study examines the interactions of ENPs in aquatic and soil-plant environments, focusing on their transformation, toxicity, and ecological impact. The goal is to identify knowledge gaps and outline directions for future consideration for a better understanding of the environmental risks of ENPs. Additionally, the research addresses the challenges of evaluating nanotoxicity and highlights the need for improved environmental regulations and assessment techniques for engineered nanomaterials.
Revisiting the Fraud Triangle in Corporate Frauds: Towards a Polygon of Elements
Authors: Roffia Paolo , Poffo Michele
Published: February 2025

The fraud triangle (Cressey, 1953) has long served as a fundamental model for under-standing corporate fraud, emphasizing opportunity, pressure, and rationalization. Over time, this framework evolved with the fraud diamond (Wolfe & Hermanson, 2004), which introduced capability, the fraud pentagon (Marks, 2012), which added arrogance, and the fraud hexagon (Vousinas, 2019), which incorporated collusion and reshaped arrogance.
Building on these developments, this study proposes a seventh dimension: the pleasure of risk-taking and challenge. This psychological factor highlights the gratification some individuals derive from engaging in fraud as a high-stakes game. Through a qualita-tive analysis of five major corporate fraud cases—Société Générale, Enron, Wirecard, Parmalat, and Theranos—this study highlights the presence of this additional motiva-tional factor.
By introducing the fraud polygon, this research provides a more comprehensive framework for understanding corporate fraud’s multifaceted nature. This model has significant implications for both academic research and practical fraud prevention, offering insights into the interplay between systemic vulnerabilities and intrinsic motivations.