bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparation of Novel ACE Inhibitory Peptides from Skimmed Goat Milk Hydrolyzed by Multi-Enzymes: Process Optimization, Purification, and Identification
Authors: Hu Wenjing , Shu Guowei , Lei Huan , Du Guanli , Liu Zhengxin , Chen Li
Published: February 2025

This study optimizes the process conditions for preparing angiotensin-converting enzyme (ACE) inhibitory peptides from skimmed goat milk (SGM) hydrolyzed by multi-enzymes using response surface methodology. When the enzymatic hydrolysis time was 90 min, the optimal hydrolysis conditions were a pH of 8.49, enzyme-to-substrate ratio (E/S ratio) of 8.04%, and temperature of 61.54 °C. The hydrolysis degree and ACE inhibitory activity were 65.39% ± 0.01% and 84.65% ± 0.03%, respectively. After purification by ultrafiltration, macroporous resin, and gel filtration, the ACE inhibitory activity of F2-2 in the two components of F2 was higher, with the ACE inhibitory rate of 93.97% ± 0.15% and IC50 of 0.121 ± 0.004 mg/mL. The content of hydrophobic amino acids, fatty amino acids, and aromatic amino acids in component F2-2 accounts for 73.17%, 33.86%, and 33.72%, respectively. Eleven peptides were isolated and identified from the F2-2 components of the enzymatic hydrolysate of SGM, including two peptides without an established database. The peptides mainly came from β casein, αS1 casein, and αS2 casein.
Handheld Laser-Induced Breakdown Spectroscopy (hLIBS) Applied to On-Site Mine Waste Analysis/Evaluation in View of Its Recycling/Reuse
Authors: Senesi Giorgio S.
Published: February 2025

Nowadays, the recovery/recycling/reuse of mining and mineral processing wastes is considered the best approach to support the circular economy and sustainability of mining and metal extraction industries. Mine wastes can be used to restore surface and subsurface land damaged by mining operations, generate fuel for power plants, further extract their component minerals, and as building materials additives. The aim of this perspective paper is to briefly highlight and focus on the most recent analytical potential and performance achieved by handheld laser-induced breakdown spectroscopy (hLIBS) instrumentation in the perspective of its future application in the mine waste sector to quickly identify on-site the presence of useful chemical elements for their possible sustainable recovery.
Next-Generation Drought Intensity–Duration–Frequency Curves for Early Warning Systems in Ethiopia’s Pastoral Region
Authors: Tegegne Getachew , Alemayehu Sintayehu , Dejene Sintayehu W. , Gebre Liyuneh , Zeleke Tadesse Terefe , Tesfaye Lidya , Abdulhamid Numery
Published: February 2025

The pastoral areas of Ethiopia are facing a recurrent drought crisis that significantly affects the availability of water resources for communities dependent on livestock. Despite the urgent need for effective drought early warning systems, Ethiopia’s pastoral areas have limited capacities to monitor variations in the intensity–duration–frequency of droughts. This study intends to drive drought intensity–duration–frequency (IDF) curves that account for climate-model uncertainty and spatial variability, with the goal of enhancing water resources management in Borana, Ethiopia. To achieve this, the study employed quantile delta mapping to bias-correct outputs from five climate models. A novel multi-model ensemble approach, known as spatiotemporal reliability ensemble averaging, was utilized to combine climate-model outputs, exploiting the strengths of each model while discounting their weaknesses. The Standardized Precipitation Evaporation Index (SPEI) was used to quantify meteorological (3-month SPEI), agricultural (6-month SPEI), and hydrological (12-month SPEI) droughts. Overall, the analysis of historical (1990–2014) and projected (2025–2049, 2050–2074, and 2075–2099) periods revealed that climate change significantly exacerbates drought conditions across all three systems, with changes in drought being more pronounced than changes in mean precipitation. A prevailing rise in droughts’ IDF features is linked to an anticipated decline in precipitation and an increase in temperature. From the derived drought IDF curves, projections for 2025–2049 and 2050–2074 indicate a significant rise in hydrological drought occurrences, while the historical and 2075–2099 periods demonstrate greater vulnerability in meteorological and agricultural systems. While the frequency of hydrological droughts is projected to decrease between 2075 and 2099 as their duration increases, the periods from 2025 to 2049 and from 2050 to 2074 are expected to experience more intense hydrological droughts. Generally, the findings underscore the critical need for timely interventions to mitigate the vulnerabilities associated with drought, particularly in areas like Borana that depend heavily on water resources availability.
Modulating Micro-Arc Oxidation Coating Properties on 6061 Aluminum Alloy via OH− to F− Ion Ratio Optimization
Authors: Li Bing , Lei Heping , Yang Xing , Liao Xiuxiang , Huang Zhu , Hao Daichao , Jiang Bingchun
Published: February 2025

We investigate the influence of the NaOH to KF ratio in a silicate electrolyte on the corrosion resistance and tribological properties of micro-arc oxidation (MAO) coatings on a 6061 aluminum alloy. By optimizing the electrolyte composition, we achieved significant improvements in coating quality. The surface morphology and composition of the coatings were characterized using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and X-ray diffraction (XRD). Our findings reveal that the coatings produced at a 2:1 NaOH/KF ratio exhibited superior corrosion resistance, with a corrosion potential of −1.279 V, corrosion current density of 1.85 × 10−7 A·cm−2, and protective resistance of 1.50 × 105 Ω·cm2. Additionally, the surface roughness and coating thickness were measured at 0.68 μm and 8.04 μm, respectively, providing a robust foundation for enhancing the anticorrosive and wear-resistant properties of 6061 aluminum alloy.
Enhancing Biodegradable Packaging: The Role of Tea Polyphenols in Soybean Oil Body Emulsion Films
Authors: Sun Jie , Wang Luyang , Chen Han , Yin Guoyou
Published: February 2025

To address the increasingly diverse demands for biodegradable packaging materials, such as for their physical properties and antioxidant properties, this study incorporated tea polyphenols (TPs) into soybean oil body emulsions (SOBs) and added a certain proportion of sodium alginate (SA) and octenyl succinic starch sodium (SSOS) to prepare a biodegradable soybean oil body–tea polyphenol (ST) emulsion film. The study systematically evaluated the effects of different concentrations of TP (0–6 wt.%) on the structure, physicochemical properties, antioxidant activity, and antibacterial activity of ST films. The results showed that the physical properties, such as tensile strength and elongation at break, of the films increased significantly with the addition of TP, and the antioxidant and antibacterial activity also increased with the increase in TP concentration. When TP concentration was 2.5 wt.%, the barrier properties of the film (ST-2.5) significantly improved (p < 0.05), while water content and water solubility decreased. The Fourier transform infrared spectroscopy, scanning electron microscopy, and thermogravimetric analysis results showed that the structure of ST films became tighter at this point. The addition of TP also affected the sensory properties of ST films, such as with an increase in the opacity of the film. Compared with the control, the light transmittance of ST-6.0 decreased by 23.68% at a wavelength of 600 nm, indicating a significant reduction in film transparency. Moreover, the biodegradability test showed that ST films have good degradability. Therefore, the ST film, as a functional edible film, has broad application prospects in the food packaging industry.
Invasion of the Atlantic Ocean and Caribbean Sea by a Large Benthic Foraminifer in the Little Ice Age
Authors: Robinson Edward , Edwards Thera
Published: February 2025

The larger benthic foraminifera is a group of marine protists harbouring symbiotic algae, that are geographically confined to shallow tropical and subtropical waters, often associated with coral reefs. The resulting controls on availability of habitat and rates of dispersion make these foraminifers, particularly the genus Amphistegina, useful proxies in the study of invasive marine biota, transported through hull fouling and ballast water contamination in modern commercial shipping. However, there is limited information on the importance of these dispersal mechanisms for foraminifers in the Pre-Industrial Era (pre-1850) for the Atlantic and Caribbean region. This paper examines possible constraints and vectors controlling the invasion of warm-water taxa from the Indo-Pacific region to the Atlantic and Caribbean region. Heterostegina depressa, first described from St. Helena, a remote island in the South Atlantic, provides a test case. The paper postulates that invasions through natural range expansion or ocean currents were unlikely along the possible available routes and hypothesises that anthropogenic vectors, particularly sailing ships, were the most likely means of transport. It concludes that the invasion of the Atlantic by H. depressa was accomplished within the Little Ice Age (1350–1850 C.E.), during the period between the start of Portuguese marine trade with east Africa in 1497 and the first description of H. depressa in 1826. This hypothesis is likely applicable to other foraminifers and other biota currently resident in the Atlantic and Caribbean region. The model presented provides well-defined parameters that can be tested using methods such as isotopic dating of foraminiferal assemblages in cores and genetic indices of similarity of geographic populations.
The Pond Snails of the Genus Radix (Gastropoda, Lymnaeidae) in Issyk-Kul Lake (Central Asia), with a Review of Radix in Ancient Tectonic Lakes of the World
Authors: Vinarski Maxim V. , Aksenova Olga V. , Khrebtova Irina S. , Kondakov Alexander V. , Spitsyn Vitaly M. , Alekseev Victor R. , Pešić Vladimir , Bolotov Ivan N.
Published: February 2025

Lake Issyk-Kul, situated in the Republic of Kyrgyzstan, is one of the largest lakes in Central Asia. Though this brackish-water basin holds only a species-poor fauna of molluscs, the number of species inhabiting Issyk-Kul and their true taxonomic position remain unsatisfactorily studied. Most nominal species of Mollusca reported from Issyk-Kul are known from empty shells only and have never been studied molecularly. This study reports the results of a revision of the genus Radix (Gastropoda:Hygrophila:Lymnaeidae) based on the integrated approach. We revealed that only two species of this genus inhabit Issyk-Kul Lake: Radix auricularia (Linnaeus, 1758) and R. obliquata (von Martens, 1864). The former species is widespread in the Palearctic and has an enormous range, whereas the latter is considered here to be endemic to Issyk-Kul Lake. All records of R. obliquata from waterbodies other than Issyk-Kul Lake are, most probably, based on misidentification. To date, no molecular evidence of the presence of R. obliquata outside Issyk-Kyl is available. The third species of Radix discussed in this paper, R. subdisjuncta (Nevill, 1878) sensu Kruglov and Starobogatov, 1993, is identical to R. obliquata and represents, most probably, an ecological morph (“race”) of the latter. The paper provides a review of Radix species recorded in other ancient tectonic lakes of the world (Baikal, Victoria, Ohrid, etc.). Though the lymnaeid snails are generally scarce in such lakes, the genus Radix represents an exception, with several species being endemics of various tectonic lakes (Issyk-Kul, Lugu, Skadar, Trichonis, and Biwa).
Incidence, Potential Mechanisms, and Clinical Significance of Cavernous Sinus Air Sign
Authors: Kim Bo Kyu , You Sung-Hye , Kim Byungjun
Published: February 2025

Background/Objectives: The cavernous sinus air sign, historically linked to trauma or venous sinus thrombosis, has recently been reported in association with retrograde venous air embolism, often without clinical significance. Despite this, its exact prevalence, etiology, and clinical relevance remain unclear. This study aims to systematically evaluate the incidence of the cavernous sinus air sign in patients undergoing CT angiography (CTA) and to assess its potential clinical implications. Methods: We retrospectively analyzed data from patients who underwent CTA between January 2021 and December 2021. The cavernous sinus air sign was defined radiologically as air-density foci within the cavernous sinus, with Hounsfield units lower than those of orbital fat. Key variables included clinical indications for CTA, evidence of venous reflux of contrast media, the laterality of contrast injection, and the presence of brachiocephalic vein stenosis. Comparative analyses were performed to identify factors associated with the occurrence of the cavernous sinus air sign. Results: Among the 2,821 patients evaluated, the cavernous sinus air sign was identified in 35 cases (1.2%). Notably, none of these patients had a history of trauma or venous sinus thrombosis. Follow-up CT imaging was available for 27 of the 35 cases (77.1%), and in all instances, the cavernous sinus air sign resolved spontaneously. A statistically significant association was found between the cavernous sinus air sign and left-sided peripheral intravenous contrast injection, observed in 8.6% of affected patients compared to 1.5% in those without the sign (p = 0.001). Venous reflux into the internal jugular vein was also more frequent in patients with the air sign (34.3% vs. 14.1%, p = 0.001). These findings suggest a mechanical component, likely related to retrograde air embolism, influenced by anatomical and procedural factors. Conclusions: The isolated presence of the cavernous sinus air sign, in the absence of relevant clinical conditions, is most likely a benign, incidental finding associated with retrograde air embolism.
Operational Feasibility of Point-of-Care Testing for Sickle Cell Disease in Resource-Limited Settings of Tribal Sub-Plan Region of India
Authors: Thakor Mahendra , Gautam Janesh Kumar , Panigrahi Ansuman , Garasiya Dharmendra , Brhamnia Shankar Lal , Mohanty Suman Sundar
Published: February 2025

Background: Sickle cell disease (SCD) individuals in India are mostly identified when they become symptomatic. To provide a timely diagnosis of SCD to participants, healthcare workers should be competent in using the point-of-care test (POCT). In this study, we aimed to evaluate the competence of healthcare workers to screen infants and adult populations through POCT. Methodology: This study was conducted in pilot mode over 8 months from April to November 2023. A random sampling method was used to select ten auxiliary nursing midwives (ANMs), ten lab technicians (LTs), and five medical officers (MOs). Each selected ANM and LT was supposed to conduct ten tests and MOs to conduct five tests. The POCT used to diagnose sickle cell disease was HemoTypeSC. Results: Among the healthcare workers who participated in the study, 67% belonged to the scheduled tribes. When the ANM and LT competencies were compared for the pre-analytical phase (phase I), ANMs were more competent than the LTs. ANMs were more adept at handling people, whereas the LTs were more competent in conducting the test procedures. When the comparison was made for the analytical phase (phase II), both the ANMs and LTs were found to be equally competent. ANMs followed the standard operating procedure (SOP) more precisely than MOs and LTs. In the post-analytical phase, LTs were found to be more competent than ANMs. The approach used in this study with sub-centers and primary health centers (PHCs) appears to have encouraged the feasibility of the screening program. Conclusions: The results of this study conclude that the healthcare workers in the region are competent to perform the POCT for the diagnosis of sickle cell disease. The POCT may be introduced in the program for the diagnosis of SCD.
Effects of Dance-Based Aerobic Training on Frailty and Cognitive Function in Older Adults with Mild Cognitive Impairment: A Randomized Controlled Trial
Authors: Sánchez-Alcalá Marcelina , Aibar-Almazán Agustín , Carcelén-Fraile María del Carmen , Castellote-Caballero Yolanda , Cano-Sánchez Javier , Achalandabaso-Ochoa Alexander , Muñoz-Perete Juan Miguel , Hita-Contreras Fidel
Published: February 2025

Background/Objectives: The purpose of this study has been to evaluate the effects of a dance-based aerobic training program on frailty, cognitive impairment, executive functions, and verbal fluency in older adults with mild cognitive impairment. Methods: Randomized clinical trial, whose sample was made up of 92 older adults, of which 47 performed rhythmic physical activity for 12 weeks. Data on frailty were collected through FRAIL, cognitive function through the Mini-Mental State Examination (MMSE), cognitive impairment through The Montreal Cognitive Assessment (MoCA), verbal fluency using the Isaac test, and executive functions with the Trail Making Test (TMT). All variables were measured before and after the intervention by an independent researcher blinded to the treatment. Results: Participants in the experimental group showed statistically significant improvements in frailty (Cohen’s d = 0.60), cognitive function (Cohen’s d = 0.98), cognitive impairment (Cohen’s d = 1.22), verbal fluency (Cohen’s d = 0.61) and executive functions (Cohen’s d = 0.64). Conclusions: This study demonstrated that a 12-week dance-based aerobic training program can significantly reduce frailty and improve cognitive abilities in older adults with mild cognitive impairment. These improvements suggest that the intervention is not only effective in terms of physical health, but also in promoting mental health and general well-being.
Transfer of POCUS Skills of Anesthesia Trainees from the Simulation Laboratory to Clinical Practice: A Follow-Up Pilot Evaluation After ABC US Protocol Training
Authors: Simon Robert , Petrișor Cristina , Bodolea Constantin , Antal Oana , Băncișor Marta , Moldovan Orlanda , Puia Ion Cosmin
Published: February 2025

Background/objectives: Point-of-care ultrasound (POCUS) in the intensive care unit (ICU) has gained much attention in the last few years as an alternative to the classic ways of assessing and diagnosing life-threatening conditions in critical patients. During the COVID-19 pandemic, we proposed a POCUS protocol based on the airway, breathing, and circulation (ABC) approach to quickly evaluate and diagnose life-threatening diseases in critical patients with acute respiratory failure and shock, and later, we used it as a curriculum to teach POCUS to anesthesia and intensive care trainees. Methods: We developed an evaluation protocol where evaluators with experience in POCUS in critically ill patients had to assess the trainee’s ultrasound scan; this was based on the ABC protocol taught in the simulation laboratory and applied in a clinical setting at the bedside. Results: Statistically significant differences were observed in some categories evaluated regarding independence and diagnosis. Conclusion: Initial POCUS simulation-based training using an ABC POCUS protocol (that demonstrated good results in the simulation laboratory) is useful when transferring US skills to the bedside and is applicable in daily clinical practice with good results in terms of operator independence.
Real-World Efficacy and Safety of Dupilumab Use in Japanese Adult Patients with Atopic Dermatitis: A Single-Center, Retrospective, 104-Week, Observational Study
Authors: Ikegami Tetsuharu , Igawa Ken
Published: February 2025

Background/Objectives: Dupilumab is an interlekin-4 receptor antibody that exerts its efficacy by inhibiting the signaling pathway of interleukin-4/interleukin-13, and it is currently used clinically as a highly potent therapeutic for atopic dermatitis. However, there have been few reports on the therapeutic effect of dupilumab using long-term real-world data. To accumulate further real-world data through long-term use of dupilumab, we performed a retrospective study on the courses of patients with atopic dermatitis who were treated with dupilumab for at least 104 weeks in our university hospital. Methods: We examined the treatment courses of 30 adult patients. Results: Subjective (e.g., itch visual analog scale and Dermatology Life Quality Index) and objective (e.g., Eczema Area and Severity Index) indices and some biomarkers showed improvements over time with dupilumab treatment, even in cases with poor early response to dupilumab treatment. As for the therapeutic effect on anatomical regions, although the therapeutic effect on the head and neck region was weak in the early stages, it improved over time, and at 104 weeks, it showed a therapeutic effect that was comparable to other regions. Conclusions: Therefore, our study demonstrated the advantages of prolonged administration of dupilumab in atopic dermatitis.
Assessing the Management and Evaluation of Impacted Wisdom Teeth in a Dental Teaching Hospital
Authors: Al Subaie Ahmed , Alruwili Raghad , Alkhuadher Bayan , Alzawwad Sarah , Alzamil Wareef , Al-Khalifa Khalifa S.
Published: February 2025

Background: Untreated impacted wisdom teeth can lead to complications, including delayed healing and inferior alveolar nerve damage. Delayed management is further complicated by age-related comorbidities. Aim: This study aimed to evaluate the management of impacted wisdom teeth in a teaching dental hospital and identify challenges faced by dental care providers. Materials and Methods: A retrospective radiographic study was conducted using data from electronic medical records and panoramic radiographs of patients. Independent variables included demographics and clinical details of wisdom teeth, such as type and presence of impaction, associated pathology, nerve proximity, second molar resorption, and extraction difficulty. The study assessed the evaluation of dental care provider practices in managing impacted wisdom teeth. Chi-square tests analyzed relationships between management type, provider level, and extraction difficulty. Results: Data from 270 panoramic radiographs and dental records were analyzed. Most cases were not managed (n = 216, 80%), irrespective of extraction difficulty or care provider level (undergraduate vs. graduate). There was no significant association between care provider levels and the type of management or between impaction difficulty and management type (p > 0.05). Conclusions: The findings highlight a lack of proper evaluation and management of impacted wisdom teeth, regardless of the provider’s experience. In hospital settings, all care providers should ensure the timely evaluation and management of impacted wisdom teeth to prevent complications.
Unique Method for Prognosis of Risk of Depressive Episodes Using Novel Measures to Model Uncertainty Under Data Privacy
Authors: Pękala Barbara , Kosior Dawid , Rząsa Wojciech , Garwol Katarzyna , Czuma Janusz
Published: February 2025

The research described in this paper focuses on key aspects of learning from data concerning the symptoms of depression and how to prevent it. The computer support system designed for that purpose combines data privacy protection from various sources and uncertainty modeling, especially for incomplete data. The mentioned aspects are key to real-life medical diagnostic problems. From among the different paradigms of machine learning, a federated learning-based approach was chosen as the most suitable to take up the challenge. Importantly, computer support in medical diagnostics often requires algorithms that are appropriate for processing data expressing uncertainty and that can ensure high-quality diagnostics. To achieve this goal, a novel decision-making algorithm is used that employs interval entropy measures based on the theory of interval-valued fuzzy sets. Such an approach enables one to take into account diagnostic uncertainty, express it exactly, and interpret it easily. Furthermore, the applied classification technique offers the possibility of a straightforward explanation of the diagnosis, which is a situation required by many physicians. The presented solution combines innovative technological approaches with practical user needs, fostering the development of more effective tools in mental health prevention.
One Who Hesitates Is Lost: Monetary Policy Under Model Uncertainty and Model Misspecification
Authors: Ajevskis Viktors
Published: February 2025

This paper investigates how different parametrisations of the monetary policy reaction function and different mechanisms of expectation formation shape the macroeconomic outcomes in the estimated Smets–Wouters type of DSGE model. The initial macroeconomic conditions of the simulations correspond to the high inflation environment of early 2022. The simulation results show that, under the hybrid expectations, the terminal monetary policy rate is significantly higher than under the rational expectations for all Taylor rule parametrisations. Under hybrid expectations, the inflation rate is much more persistent than under the rational expectations; three years is not enough to reach the inflation target of two percent, even for the quite hawkish calibration of the Taylor rule. In the modelled economy, relatively fast inflation stabilisation for the hawkish Taylor rule has its own price in form of the cumulative output loss when compared with the dovish Taylor rule. Simulations are also performed for the case where the central bank misspecifies the expectation formation mechanism in the DSGE model and follows an interest rate path implied by a false model. The results show that the hawkish reaction is preferable for both correctly and incorrectly specified models.
Redesigning Assessments for AI-Enhanced Learning: A Framework for Educators in the Generative AI Era
Authors: Khlaif Zuheir N. , Alkouk Wejdan Awadallah , Salama Nisreen , Abu Eideh Belal
Published: February 2025

The emergence of generative artificial intelligence (Gen AI) in education offers both opportunities and challenges, particularly in the context of student assessment. This study examines faculty members’ motivations to redesign assessments for their courses in the Gen AI era and introduces a framework for this purpose. A qualitative methodology was employed, gathering data through semi-structured interviews and focus groups, along with examples of redesigned assessments. Sixty-one faculty members participated in the study, and the data were analyzed using both deductive and inductive thematic approaches. Key motivations for redesigning assessments included maintaining academic integrity, preparing learners for future careers, adapting to technological advancements, and aligning with institutional policies. However, the study also highlighted significant challenges, such as the need for professional development and addressing equity and accessibility concerns. The findings identified various innovative assessment approaches tailored to the requirements of the Gen AI era. Based on these insights, the study developed a conceptual framework titled “Against, Avoid, Adopt, and Explore”. Future research is needed to validate this framework and further refine its application in educational contexts.
Faculty Development Interventions in Medical Education During the COVID-19 Pandemic: A Systematic Review
Authors: Karimi Hengameh , Khawaja Sarwar
Published: February 2025

The onset of the COVID-19 pandemic in March 2020 began a series of disruptions that rapidly impacted medical education across the globe. This review collates current literature that relates to medical education faculties’ development interventions as a result of the pandemic, with an emphasis on the effectiveness and type of strategies for intervention, such as the usefulness of hybrid and digitalised education. The study used PRISMA guidelines when conducting the literature survey with specified inclusion and exclusion criteria across numerous academic databases. From this survey, 1158 articles were found. The EndNote programme was used to identify and remove duplicate pieces. From this, 479 abstracts were reviewed. A total of 36 articles were selected for their relevance; from this, 11 were deemed to have met the inclusion criteria to warrant full-text analysis. To identify bias risk in these 11 studies, the Newcastle–Ottawa Scale (NOS) was utilised. The study findings have two major themes: (1) information about faculty development interventions; and (2) the nature of articles written in the pandemic. From this, it was indicated that faculty development initiatives are useful for improving teachers’ competency and for enhancing teachers’ adoption of digitalised learning to ultimately bolster the resilience of their teaching. The findings also show that there is a strong need to have robust frameworks in place for faculty development, and that such frameworks must be followed in and beyond the pandemic period to improve the long-term incorporation of online learning into medical education.
A Blockchain Address Generation Method Based on the Improved SM9 Algorithm
Authors: Wang Ruimin , Fan Haolong , Liu Kezhen
Published: February 2025

In recent years, governments have regarded blockchain technology as a key breakthrough in independent innovation of core technologies and have attached great importance to its development. In current blockchain solutions, the elliptic curve digital signature algorithm (ECDSA) is usually combined with the Keccak Hash Algorithm 256-bit Variant (keccak256) to generate blockchain addresses. Although the ECDSA algorithm is based on the Public Key Infrastructure (PKI) system, which has prominent issues such as complex deployment processes, high operation and maintenance costs, low efficiency, and difficulties in adapting to a large number of users, it still holds an important position and has a broad application foundation in the field of cryptography. This paper aims to circumvent the existing flaws of the PKI system rather than discarding the strong and well-proven PKI system. Instead, it endeavors to explore the application of the Identity-Based Cryptography (IBC) system in blockchain and reduce dependence on foreign cryptographic algorithms. This study adopts the SM9 algorithm based on the IBC and combines it with the SM3 algorithm to generate blockchain addresses. Considering users’ use, this paper improves the original SM9 algorithm based on the original SM9 algorithm, enabling users to perform functions such as signing and encryption with just a single pair of public and private keys. Experimental results indicate that the time consumed by this proposed scheme in blockchain address generation is 1.29 times that of the existing schemes, and the length of the blockchain addresses generated is the same as that of the existing ones.
Enhancing Security in Software Design Patterns and Antipatterns: A Framework for LLM-Based Detection
Authors: Andrade Roberto , Torres Jenny , Ortiz-Garcés Iván
Published: February 2025

The detection of security vulnerabilities in software design patterns and antipatterns is crucial for maintaining robust and maintainable systems, particularly in dynamic Continuous Integration/Continuous Deployment (CI/CD) environments. Traditional static analysis tools, while effective for identifying isolated issues, often lack contextual awareness, leading to missed vulnerabilities and high rates of false positives. This paper introduces a novel framework leveraging Large Language Models (LLMs) to detect and mitigate security risks in design patterns and antipatterns. By analyzing relationships and behavioral dynamics in code, LLMs provide a nuanced, context-aware approach to identifying issues such as unauthorized state changes, insecure communication, and improper data handling. The proposed framework integrates key security heuristics—such as the principles of least privilege and input validation—to enhance LLM performance. An evaluation of the framework demonstrates its potential to outperform traditional tools in terms of accuracy and efficiency, enabling the proactive detection and remediation of vulnerabilities in real time. This study contributes to the field of software engineering by offering an innovative methodology for securing software systems using LLMs, promoting both academic research and practical application in industry settings.
Three-Dimensional Mesh Character Pose Transfer with Neural Sparse-Softmax Skinning Blending
Authors: Liu Siqi , Yin Mengxiao , Li Ming , Zhan Feng , Hua Bei
Published: February 2025

Three-dimensional mesh pose transfer transforms the pose of a source model into the pose of a reference model while preserving the source model’s identity (body detail). It has tremendous potential in computer graphics tasks. Current neural network-based methods primarily focus on extracting pose and body features, not entirely using the articulated body structure of humans and animals. We propose an end-to-end pose transfer network based on skinning deformation to address these issues. This network first extracts skinning weights and model joint features. Then, they are decoded to transfer the source model to a pose similar to the reference model while preserving the features of the source model. During feature extraction, we utilize the features of the k-nearest neighborhoods and one-ring neighborhoods to enable the network to learn the body details of the model better. Additionally, we apply skinning weights and joint features to capture the variation in the source model pose compared to the reference model pose and then use a decoding network to obtain the target model, replacing linear blend skinning. We conducted experiments on datasets such as SMPL, SMAL, FAUST, DYNA, and the MG dataset to provide empirical evidence and demonstrate that our method is the best in quantitative experiments. Our method efficiently transfers poses while better preserving the identity of the source model.
Generalized Multivariate Symplectic Sparsest United Decomposition for Rolling Bearing Fault Diagnosis
Authors: Sun Weikang , Liu Yanfei , Peng Yanfeng
Published: February 2025

The non-stationary characteristics of the vibration signals of rolling bearings will be aggravated under variable speed conditions. Meanwhile, multichannel signals can provide a more comprehensive characterization of state information, providing multiple sources of information that facilitate information fusion and enhancement. However, traditional adaptive signal decomposition methods generally assume that the frequency information is constant and stationary, and it is difficult to achieve a unified decomposition when dealing with multichannel time-varying signals. Therefore, the intention of this paper is to propose a multichannel signal adaptive decomposition method applicable to variable speed conditions. Specifically, this paper takes advantage of the strong adaptability and robustness of symplectic geometric mode decomposition (SGMD). To improve its applicability to multichannel time-varying signals at variable rotational speeds, a generalized multivariate symplectic sparsest united decomposition (GMSSUD) method is proposed. In GMSSUD, firstly, the completely adaptive projection (CAP) method is employed to achieve a unified representation of the multichannel signals. Then, the generalized demodulation method is introduced to stabilize the signal and subsequently reduce the noise through component screening and reconstruction. Finally, with the new proposed operator as the optimization objective, the constructed sparse filter parameters are optimized to achieve the frequency band segmentation. The analysis results demonstrate that the GMSSUD method possesses higher decomposition precision for multichannel signals with variable speeds and also has a stronger diagnosis ability for variable-speed bearing faults.
DualAD: Exploring Coupled Dual-Branch Networks for Multi-Class Unsupervised Anomaly Detection
Authors: He Shiwen , Chen Yuehan , Wang Liangpeng , Huang Wei , Xu Rong , Qian Yurong
Published: February 2025

Anomaly detection (AD) is crucial in various domains such as industrial inspection, medical diagnosis, and video surveillance. Previous advancements in unsupervised AD often necessitated training separate models for different objects, which can be inefficient when dealing with diverse categories in real-world scenarios. This paper addresses the recently proposed task of multi-class unsupervised anomaly detection (MUAD), which is more practical and challenging. We begin by reviewing the first MUAD framework, UniAD, and analyzing the characteristics of end-to-end feature reconstruction networks that can adapt to various backbone architectures. Building on these insights, we introduce a novel MUAD framework called DualAD. Our approach is based on the innovative design of a Coupled Dual-Branch Network (CDBN), which integrates a Wide–Shallow Network (WSN) with a Narrow–Deep Network (NDN), leveraging the strengths of both to achieve superior performance. We explore a fully transformer-based homogeneous design for the CDBN and introduce a more lightweight heterogeneous CDBN design that integrates a transformer with a Memory-Augmented Multi-Layer Perceptron (MMLP). Experimental results on the MVTec AD and VisA datasets demonstrate that DualAD outperforms the recent state-of-the-art methods and exhibits robust performance across various pre-trained backbone architectures.
Real-Time Adaptive and Lightweight Anomaly Detection Based on a Chaotic System in Cyber–Physical Systems
Authors: Park Jung Kyu , Baek Youngmi
Published: February 2025

When cyber–physical systems (CPSs) are connected to the Internet or other CPSs with connectivity, external adversaries can potentially gain access to the CPS and attempt to control the electronic control units (ECUs). In particular, the lack of confidentiality and integrity in the controller area networks (CANs) of CPSs makes it difficult to distinguish malicious data from legitimate data. The security vulnerabilities of CPSs, which are frequently exposed to adversaries, pose the risk of destabilizing the lives of humans. Therefore, we propose a real-time adaptive and lightweight anomaly detection (RALAD) mechanism that efficiently and securely detects anomalies within a given virtual group though verification of the data integrity and key management of stateless synchronization based on a chaotic system while driving. These characteristics prevent an adversary from authenticating maliciously modified messages even though it captures legitimate messages on the CAN bus. RALAD shows a clear difference from others in terms of (1) its unique secret key-sharing method and approach to secret key generation for each message, (2) safe controlling support after detecting anomalies, and (3) its software-based solution that eliminates the need for hardware secure modules. It leads to freedom from the issues of additional cost, weight, and wiring in CPSs. The proposed method achieves real-time anomaly detection, and the experiment results show a 100% detection rate for all attacks. This demonstrates that RALAD maintains high reliability and efficiency, even under various bus load conditions and attack rates.
Forecasting Heat Power Demand in Retrofitted Residential Buildings
Authors: Guz Łukasz , Gaweł Dariusz , Cholewa Tomasz , Siuta-Olcha Alicja , Bocian Martyna , Liubarska Mariia
Published: February 2025

The accurate prediction of heat demand in retrofitted residential buildings is crucial for optimizing energy consumption, minimizing unnecessary losses, and ensuring the efficient operation of heating systems, thereby contributing to significant energy savings and sustainability. Within the framework of this article, the dependence of the energy consumption of a thermo-modernized building on a chosen set of climatic factors has been meticulously analyzed. Polynomial fitting functions were derived to describe these dependencies. Subsequent analyses focused on predicting heating demand using artificial neural networks (ANN) were adopted by incorporating a comprehensive set of climatic data such as outdoor temperature; humidity and enthalpy of outdoor air; wind speed, gusts, and direction; direct, diffuse, and total radiation; the amount of precipitation, the height of the boundary layer, and weather forecasts up to 6 h ahead. Two types of networks were analyzed: with and without temperature forecast. The study highlights the strong influence of outdoor air temperature and enthalpy on heating energy demand, effectively modeled by third-degree polynomial functions with R2 values of 0.7443 and 0.6711. Insolation (0–800 W/m2) and wind speeds (0–40 km/h) significantly impact energy demand, while wind direction is statistically insignificant. ANN demonstrates high accuracy in predicting heat demand for retrofitted buildings, with R2 values of 0.8967 (without temperature forecasts) and 0.8968 (with forecasts), indicating minimal performance gain from the forecasted data. Sensitivity analysis reveals outdoor temperature, solar radiation, and enthalpy of outdoor air as critical inputs.
Virtual Synchronous Generator Based on Hybrid Multi-Vector Model Predictive Control
Authors: Yan Yinyu , Fan Zhiyuan , Sun Yichao , Wang Wei , Yang Dongmei , Wei Zheng
Published: February 2025

This paper proposes a hybrid multi-vector model predictive control (MPC) to reduce the harmonic content in the output current of a two-level virtual synchronous generator (VSG). Compared to traditional two-vector MPC, the proposed hybrid multi-vector MPC has twelve sets of voltage vectors, meaning that the number of iterative calculations required in each cycle is identical for both control methods. Compared to the three-vector MPC, the proposed method requires more iterative calculations per control period but achieves optimal harmonic content in the output current. In addition, different from the traditional MPC methods, this paper incorporates frequency variation weights into the cost function, which further reduces the harmonic content in the output current. Finally, the effectiveness of the proposed control strategy is validated through a simulation model built in MATLAB/Simulink.
Economic Viability and Environmental Benefits of Integrating Solar Photovoltaics in Public Community Buildings
Authors: Alhazmi Mohannad , Alfadda Abdullah , Alfakhri Abdullah
Published: February 2025

Saudi Arabia relies heavily on fossil fuels for electricity generation, leading to significant environmental challenges, including high levels of greenhouse gas emissions. This study evaluates the environmental and financial impacts of integrating solar PV systems in public buildings, specifically mosques and schools, in the central region of Saudi Arabia. Using machine learning-based forecasting, we analyzed power consumption and solar generation patterns. The results show that the integration of solar photovoltaic (PV) systems could lead to a reduction of 1.02 million tons of CO2 emissions annually and a 48% decrease in net present cost. These findings highlight the potential of solar PV to mitigate environmental harm while offering financial benefits in alignment with Saudi Arabia’s renewable energy objectives
Assessment of the Modulus of Rupture and Modulus of Elasticity in Static Bending of Yellow Pine Earlywood and Latewood
Authors: Mańkowski Piotr , Karwat Zbigniew , Laskowska Agnieszka
Published: February 2025

The purpose of this research was to investigate the modulus of rupture (MOR) and modulus of elasticity (MOE) in the static bending of yellow pine (Pinus ponderosa Douglas ex C. Lawson) earlywood and latewood. The relationship between the properties of these wood zones and the MOR and MOE of yellow pine wood tested was determined with the methodology specified in the standards. An important element of the research was to verify the suitability of the developed method for testing the MOR and MOE of small wood samples obtained from the earlywood and latewood zone. The MOR of the earlywood was about 6% higher than the MOR of the pine wood determined using standard samples, and these differences were not statistically significant. However, the MOR of the latewood was approximately three times higher than the MOR of the pine wood determined using standard samples, and these differences were statistically significant. The MOR of the latewood was found to be 2.5 times higher than the MOR of the earlywood. The MOE of the latewood was found to be two times higher than the MOE of the earlywood. This was due to the density of particular wood zones and the dimensions of structural elements—tracheids. The maximum load (Fmax) transferred by latewood zones was four times higher than the Fmax transferred by earlywood zones. The deflection at the Fmax of the earlywood zone was 20% smaller than the deflection at the Fmax of the latewood zone.
A Methodological Framework for AI-Driven Textual Data Analysis in Digital Media
Authors: Cordeiro Douglas , Lopezosa Carlos , Guallar Javier
Published: February 2025

The growing volume of textual data generated on digital media platforms presents significant challenges for the analysis and interpretation of information. This article proposes a methodological approach that combines artificial intelligence (AI) techniques and statistical methods to explore and analyze textual data from digital media. The framework, titled DAFIM (Data Analysis Framework for Information and Media), includes strategies for data collection through APIs and web scraping, textual data processing, and data enrichment using AI solutions, including named entity recognition (people, locations, objects, and brands) and the detection of clickbait in news. Sentiment analysis and text clustering techniques are integrated to support content analysis. The potential applications of this methodology include social networks, news aggregators, news portals, and newsletters, offering a robust framework for studying digital data and supporting informed decision-making. The proposed framework is validated through a case study involving data extracted from the Google News aggregation platform, focusing on the Israel–Lebanon conflict. This demonstrates the framework’s capability to uncover narrative patterns, content trends, and clickbait detection while also highlighting its advantages and limitations.