bluuebunny/crossref_metadata_2025 huggingface dataset:
Breathomics: A Non-Invasive Approach to the Diagnosis of Breast Cancer
Authors: Yockell-Lelièvre Hélène , Philip Romy , Kaushik Palash , Masilamani Ashok Prabhu , Meterissian Sarkis H
Published: February 2025

Breast cancer is the most commonly diagnosed cancer worldwide [1], underscoring the critical need for effective early detection methods to reduce mortality. Traditional detection techniques, such as mammography, present significant limitations, particularly in women with dense breast tissue, highlighting the need for alternative screening approaches. Breathomics, based on the analysis of volatile organic compounds (VOCs) present in exhaled breath, offers a non-invasive, potentially transformative diagnostic tool. These VOCs are metabolic byproducts from various organs of the human body whose presence and varying concentrations in breath are reflective of different health conditions. This review explores the potential of breathomics, highlighting its promise as a rapid, cost-effective screening approach for breast cancer, facilitated through the integration of portable solutions like electronic noses (e-noses). Key considerations for clinical translation - including patient selection, environmental confounders, and different breath collection methods will be examined in terms of how each of them affects the breath profile. However, there are also challenges such as patient variability in VOC signatures, and the need for standardization in breath sampling protocols. Future research should prioritize standardizing sampling and analytical procedures, and validating their clinical utility through large-scale clinical trials.
A Comparative Study of Well-Nourished and Malnutrition-Risk Older People Living in Nursing Home: Vitamin D Status and Physical Function Parameters
Authors: Safitri Fenthy Marlina , Chen Yi-Hsiu , Lee Che-Yu , Chen Jiun-Rong , Shirakawa Hitoshi , Shirakawa Hitoshi
Published: February 2025

This study aims to investigate the Vit D status, physical function parameters and analyze their correlation in older nursing home residents with malnutrition risk and malnutrition. Methods: This study was a cross-sectional study and recruited 152 older residents from multiple nursing homes and divided into well-nourished (n=34), malnutrition risk (n=102) and malnutrition (n=16) groups. The nutrition status was evaluated by mini nutritional assessment short form (MNA-SF), then anthropometric data, biochemical blood test and physical function parameters were evaluated and compared among groups. Compared with well-nourished group, BW (body weight), BMI (body mass index), ASMI (appendicular skeletal muscle index) and calf circumference were significantly lower in the malnutrition risk and malnutrition groups. The malnutrition risk and malnutrition groups also represented the significantly higher SOF (study of osteoporotic fractures) score than that of well-nourished group. Three groups showed the Vit D insufficiency that means blood 25(OH)D level is less than 30ng/dL, although there is no difference among three groups. In addition, The MNA-SF was negatively correlated with BMI, ASMI and calf circumference, whereas positively correlated with SOF score. Regarding the odd ratios, when the score of MNA-SF was low, the odds ratios of low ASMI, low calf circumference, and high SOF score were significantly increased. The institutionalized older adults with malnutrition risk or malnutrition had lower ASMI and calf circumference. However, regardless of nutritional status, occurrence of Vit D insufficiency was observed, and Vit D showed no significant correlation with physical function parameters among the older adults in the nursing home.
Statistical Analysis of Açaí Commercialization and Quantification of Waste Generated (Açaí Seeds) in the City of Belém/Pa
Authors: Corrêa Verena Lúcia Sousa , Ribeiro Haroldo Jorge da Silva , Valois Flávio Pinheiro , Nascimento Mel Zafira Cruz do , Silva Renan Marcelo Pereira , Martins Gabriel Arthur da Costa , Ferreira Raíse Brenda Pinheiro , Brandão Isaque Wilkson de Sousa , Mendonça Neyson Martins , Machado Nélio Teixeira
Published: February 2025

Açaí (Euterpe oleracea) is one of the most important palms of the genus Euterpe and is found distributed on a large scale in the Amazon. In the process of extracting its pulp, waste is generated, called the pit - which corresponds to the endocarp and kernel of the fruit. The research was conducted with the help of the R-Studio tool and took into account the quantity of waste produced, specifically, in the years 2023 and 2024, in the city of Belém do Pará, during the harvest and off-season. Through the statistical Cluster methodology, the grouping of average data was carried out for final definition in the generation of dendrograms. In this way, the present work aimed to employ statistical methods for the collection of quantitative data on the production of açaí waste generated during the high and low production periods of açaí, in addition to proposing locations for grouping for disposal points of açaí seeds based on the route, logistics, and accessibility of the Urban Solid Waste Collection company in the city of Belém. The results obtained, demonstrate that the Jurunas neighborhood had the highest açaí production and consequently, a higher production of wastes. While the Val-de-Cans neighborhood showed the lower percentage regarding the same theme.
Risk Assessment Method for Edge Intelligence Control Platforms Based on Hybrid Game Theory
Authors: He Chuan , Zhang Bo , Zhang Tao , Xi Ze-Sheng , Wang Yun-Fan
Published: February 2025

Risk assessment techniques have been widely used in edge intelligent control platforms from security protection to decision optimization. In recent years, many researchers have applied machine learning or deep learning to risk assessment in edge intelligent control platforms. However, these approaches face significant challenges, including high computational resource requirements, high data dependency, and poor interpretability. In this paper, we propose a risk assessment method for edge intelligent control platforms based on hybrid game theory, which constructs a two-dimensional security risk assessment framework across cyber and physical domains. The attack tree model is first utilized to meticulously outline the potential attack paths and integrate the mixed-strategy game between attackers and defenders at the leaf nodes. Then, through game-theoretic analysis, the payoff functions of both parties are established, Nash equilibrium is determined to predict strategic choices, and the fuzzy analytic hierarchy process (FAHP) is combined with the CRITIC weighting method to quantify the risk associated with each node in the attack tree model. Finally, the risk values of the root nodes are aggregated to assess the overall security level of the platform. This approach effectively simulates real-world adversarial interactions and improves the accuracy and practicality of risk assessment.
Legal Challenges and Opportunities in Mergers and Acquisitions Between the U.S. and Latin America
Authors: Dela Marta Caio
Published: February 2025

Cross-border mergers and acquisitions (M&A) between the United States and Latin America have intensified in recent decades, reflecting increasing economic integration and the search for new markets. This article analyzes the key legal challenges faced in these operations, focusing on regulatory differences, corporate governance, and the impact of mechanisms such as L-1 and E-2 visas. Through a critical literature review and practical case studies, this study discusses the need for regulatory harmonization, the importance of due diligence, and the strategic role of business immigration visas. Additionally, it presents a new perspective on regulatory impacts, examining how legal adaptation can influence the efficiency of these transactions. The conclusion highlights that while cross-border M&A offers significant opportunities, overcoming legal challenges requires a proactive and collaborative approach among stakeholders.
Affect, Digital Heritage and Circular Economics; the Fate of Dennys Lascelles Wool Store in Geelong
Authors: Rashid Md Mizanur , Khoo Chin Koi , Masoomakhameneh Donya
Published: February 2025

This paper explores the intersection of affect, digital heritage, and the circular economy through the case of Dennys Lascelles Wool Store in Geelong. While its iconic bow truss structure was demolished due to the rapid urban transformation of the city of Geelong, the remaining complex presents opportunities for preservation within a circular economy framework. Affect—the emotional and sensory connections to heritage—plays a vital role in sustaining cultural legacy. Digital tools enable the documentation and engagement of both tangible and intangible heritage, addressing gaps in the Authoritative Heritage Discourse (AHD), which often prioritizes physical preservation considering heritage as something material, non-renewable and fragile. By integrating digital heritage with circular economy principles, this study highlights sustainable preservation strategies. While the bow truss can only survive digitally, the rest of the site can be repurposed, aligning with circular economy practices to retain historical significance within the evolving cityscape. This paper underscores the significance of acknowledging the emotional and historical value of industrial and cultural heritage, employing appropriate digital tools for preservation and engagement, and adopting sustainable practices for the potential adaptive reuse of historic sites. It further advocates for reimagining heritage conservation in the digital era to enhance accessibility, engagement, and sustainability.
Spatial Heterogeneity of Built Environment Perception's Impact on Street Vitality: A Multi-Level Interpretative Framework Based on MGWR-SHAP
Authors: Li Xuemei , Li Baisui , Su Ye
Published: February 2025

Street vitality is crucial for sustainable urban development, yet current understanding of how built environment perceptions influence vitality remains limited by global statistical approaches and the lack of interpretable frameworks for analyzing spatial heterogeneity. This study proposes a novel multi-level interpretative framework combining Multiscale Geographically Weighted Regression (MGWR) with SHAP values to examine spatial variations in perception-vitality relationships. Using multi-source data from Hohhot, China, including mobile phone signals, POI data, and street view imagery, we analyzed how four dimensions of environmental perception influence street vitality across different urban contexts. The analysis reveals significant spatial heterogeneity in perception-vitality relationships, with varying effects across urban locations. Pleasure perception shows the strongest positive influence (SHAP values 0.072-0.103), while convenience perception exhibits an unexpected inverse U-shaped relationship with vitality. The machine learning approach (R² = 0.421) outperforms traditional methods in capturing nonlinear effects and complex interactions. The findings demonstrate the importance of considering both spatial heterogeneity and nonlinear relationships in understanding street vitality, suggesting the need for context-sensitive approaches to urban design and planning interventions.
Studying the Possibilities of Creating Artificial Clouds and Rain
Authors: Magometovich Ali Abshaev , Tahirovich Magomet Abshaev
Published: February 2025

The results of experimental and theoretical studies into possibility of creating artificial clouds and rain by stimulating convection based on the following physical principles are discussed: 1) heating of local areas of the surface layer of the atmosphere by artificial aerosol layer that absorbs solar radiation; 2) creation of an updraft along a 30-40 tier garland of black screens lifted on a balloon and warmed by the sun; 3) conducting into the atmosphere a vertically directed high-speed jet fueled by the heat of water vapor condensation on three types of aerosols with different hygroscopic points. The performance of these three methods was evaluated on the basis of theoretical modeling and field experiments. It is shown that the application of the first method requires the creation of an optically dense aerosol layer over an area of about 5-10 km2, existing for at least 30 minutes. This requires such large dosages of aerosol compositions that the application of this method is expensive and acceptable due to atmospheric pollution only in desert areas. Theoretical modeling and experimental testing of the second method showed its complete futility because the large sailing of the screens does not allow to lift the garland having more than 4-5 tiers even in low wind, secondly, adiabatic cooling and wind drift excludes the formation of a continuous updraft flow by adding the updraft pulses created by each tier. Field tests in the UAE of the jet method fueled by condensation heat have shown the possibility of creating small clouds and localized short-term rains. But these results are much lower than theoretically expected. The reason for this is that the air humidity on the days with the experiments was below the hygroscopic point of the two types of aerosols introduced into the jet at the start, secondly, the condensation process is not so fast to provide energy feeding of the jet during its ascent, and the power of the applied aircraft engine D-30 is insufficient to overcome the surface layers of inversion and the destructive effect of wind. Based on these results, it is proposed to use much more powerful aerospace engines with some modernization, the jet of which, rising into the atmosphere, can provide the formation of a powerful convective cloud of the Cb type. To accelerate precipitation formation, a hygroscopic nano-aerosol in the required concentration is introduced into this cloud at a height of 400-500 m using a UAV.
Bridging Science and Lifestyle: A Feasibility Study for Developing a Novel Functional Food to Support Well-being
Authors: Christodoulou Efstratios , Laoutari Sotiria , Athanassiou Fani , Poutli Eleni , Andreou Demetriana , Kourkoutas Yiannis , Koutelidakis Antonios E
Published: February 2025

This study explored the relationship between functional food consumption and mental health well-being, with a focus on predominantly natural functional foods that are well-known for their positive association with mental health. A total of 362 participants from Greece and Cyprus completed an online questionnaire assessing their consumption of functional foods, mental well-being, sleep quality, body composition, and Health-Related Quality of Life (HRQoL) using validated scales. The findings revealed a statistically significant association between the vast majority of functional foods and mental health well-being, as well as significant correlations with HRQoL, sleep quality, and Body Mass Index (BMI). Notably, these functional foods were primarily natural and included key components of the Mediterranean dietary pattern, such as fruits, vegetables, nuts, herbal infusions, and beekeeping products—particularly honey—which demonstrated consistent positive effects across multiple health parameters. The study also highlighted consumer preferences for functional foods that balance sensory appeal with well-being benefits, with milk-based and plant-based beverages, as well as protein and granola bars, identified as ideal delivery formats. Additionally, ingredients like St. John’s Wort and Greek Mountain Tea, known for their mental health benefits, were recognized as valuable additions to future formulations. The majority (66.9%) of participants expressed a willingness to engage in clinical trials, reinforcing the need for further research to validate the efficacy of these ingredients. The results underscore the growing consumer interest in functional foods that promote not only physical health but also psychological resilience and overall quality of life. These findings lay the groundwork for well-designed clinical trials to assess the impact of novel functional foods on mental and physical health.
Predicting Neonatal Risk of Patent Ductus Arteriosus: A Machine Learning Analysis of Maternal Pathology, Medication, and Neonatal Health Indicators Using Random Forest and XGBoost Models
Authors: Jura Ana Maria Cristina , Popescu Daniela Eugenia , Cîtu Cosmin , Biriș Marius , Pienar Corina , Paul Corina , Petrescu Oana Maria , Constantin Andreea Teodora , Dinulescu Alexandru , Roșca Ioana
Published: February 2025

Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mortality. While maternal and neonatal conditions are known contributors, few studies use advanced machine learning (ML) as predictive factors. This study assessed how maternal pathologies, medications, and neonatal factors affect the risk of PDA using traditional statistics and ML algorithms: Random Forest (RF) and XGBoost (XGB). A retrospective 3 year cohort study of 201 NICU neonates assessed maternal and neonatal factors. Logistic regression (LR) and chi-square analyses identified significant predictors, while ML models enhanced predictive accuracy and pinpointed key PDA factors. LR identified prolonged rupture of membranes (>18 hours) as the most significant predictor (OR: 13.03, p<0.001). The ML models identified gestational age, maternal anemia, prenatal care level, birth weight, prolonged rupture of membranes, medication usage, diabetes, pregnancy-induced hypertension, SARS-CoV-2 infection, and cervical cerclage as key predictors. The RF model had 76.3% accuracy, moderate sensitivity (47.4%), and high specificity (90%). XGB performed better with 81.4% accuracy, an AUC of 0.872, sensitivity of 92.5%, and specificity of 57.9%. This study shows that maternal and neonatal factors significantly influence the risk of PDA. ML, particularly XGBoost, enhances predictive abilities, guiding targeted interventions and improving neonatal outcomes.
The Impact of Digital Transformation in Latin America and the Caribbean: Opportunities and Risks in a Context of Economic and Financial Resilience
Authors: Romero Zaleta Miguel Angel , Ochoa-Romerroll Luis Caros
Published: February 2025

Digital transformation in Latin America and the Caribbean is reshaping the economy, strengthening financial resilience, and optimizing resource management. This study examines the intersection of technological innovation, economic sustainability, and the efficient administration of key sectors such as energy, mining, agriculture, and finance. Through case studies in Brazil, Chile, Mexico, and Colombia, it highlights the impact of artificial intelligence (AI), the Internet of Things (IoT), and digital platforms on operational efficiency and inclusion. However, digital gaps and technological dependence on external providers threaten economic stability. Countries with advanced digital strategies, such as Brazil’s Payment System Instantaneous (PIX) and Chile’s interoperability framework, have demonstrated greater resilience. Digitalization in water and energy management is also driving regional sustainability. The study recommends bridging the digital divide, strengthening cybersecurity, and promoting inclusive governance to ensure equitable access to digitalization. In conclusion, an integrated digital strategy can be a key driver of economic resilience and sustainable development, provided that governments and businesses align efforts toward an inclusive digital agenda.
Blood Groups (Abo/Rh) Influence the Response of Biochemical Markers in Plasmodium falciparum Infection
Authors: Sacomboio Euclides Nenga Manuel , Luzembo Tereza , Almeida Fausto
Published: February 2025

According to the Angolan Ministry of Health, in 2023, 10.3 million cases of malaria were reported, an increase of 23% compared to 2022, however, with several deaths 10,089, against 12,480 in 2022, representing a percentage reduction of 19%. Background/Objectives: To investigate whether blood groups (ABO/Rh) can influence the response of biochemical markers in Plasmodium falciparum infection in patients admitted to some hospital units in Luanda/Angola. Methods: A longitudinal, prospective, and analytical study was carried out on 518 patients hospitalized for malaria in two hospital units in Luanda. Results: Of the 518 malaria patients included in the study, the ORh+ group represented (44.6%), followed by ARh+ (22.2%), BRh+ (22.0%), ABRh+ (6.9%), ORh- (2.7%), ARh- (1.0%) and BRh- (0.6%). Regarding sociodemographic data, there was no statistically significant relationship between age groups, area of residence, serum concentration of creatinine, urea, glucose, ALT, gamma GT, degree of parasitemia, antimalarial treatment, clinical condition, and clinical outcomes with blood groups (P < 0.05). However, there was a statistical relationship between gender, employment status, the blood concentration of direct bilirubin, total bilirubin, and AST with blood groups (P < 0.05). Conclusions: It was evident that the biochemical markers in the response to malaria infection can be influenced by the blood type of the individuals, especially direct bilirubin, total bilirubin, and AST, which showed a statistical relationship with the blood type of the patients studied.
The Ability of ChatGPT to Aid in the Rapid Development of Inoculation Message Treatments: A Case Study and Recommendations
Authors: Mason Alicia , Compton Josh , Cooper Griffin
Published: February 2025

One of the most widely known types of AI technologies in recent years is ChatGPT. ChatGPT is a state-of-the-art language model that has revolutionized natural language processing by generating human-like text with context and coherence, enabling new possibilities for human-AI interaction (Brown et al., 2020). This case study reports on a 10-week conversational AI training initiative to assess whether ChatGPT4 can (a) identify the structural elements and features of conventional inoculation messages (i.e., forewarnings and preemptive refutations); (b) augment inoculation message design features (i.e., linguistic signatures, language, and length); (c) adapt messages for specific audiences (i.e., younger populations, experts); and finally, (d) independently replicate the inoculation message development process on a topic of its choosing. Twenty-one different inoculation messages previously used in published inoculation studies provided the instructional foundation for teaching ChatGPT. A combination of prompting techniques were used (i.e., sequential, active, iterative, and chain of thought prompts) to achieve the goals of the study. Using 29 different prompts we found a high degree of originality within the AI generated inoculation messages; however, structural weaknesses were prevalent regardless of originality. AI generated messages were more difficult to read and required an advanced education level to comprehend. The AI messages were not equivalent with the training exemplars, and, in general, contained higher percentages of complex wording. We also found that ChatGPT struggled with developing the explicit forewarning threat component and did not generate inoculation messages with more than two refutations. Several themes of metaphorical and figurative language were used by the conversational-AI. We describe and contextualize these findings and discuss considerations and recommendations for future study.
Is Living on the Edge the Future of the Internet?
Authors: Karthick Gayathri , Mapp Glenford , Crowcroft Jon
Published: February 2025

Edge and fog computing have enhanced traditional client-server computing. However, the emergence of Smart Cities is rapidly changing this outlook because they must provide essential services, including ubiquitous communications, intelligent transport systems, advanced medical platforms, and urban infrastructure management. This demands a secure and resilient low-latency, high-bandwidth environment to provide a sustainable Quality of Service to applications and services. To meet this challenge, a new computing and networking ecosystem must be developed in which servers are managed and run from the edge of the Internet rather than from the centre as they currently are. This ecosystem is called the Intelligent Edge Environment (IEE) and is seen as the next major evolutionary step for the Internet. This journal article explores the development of this new paradigm. Firstly, the Reference Model for the IEE is detailed. Then, new mechanisms needed to build an Implementation Model of the IEE are discussed. The paper then examines the design of a new Internet to meet the challenges of developing Smart Cities.
Sensor Monitoring of the Conveyor Working Operation with Oscillating Trough Movement
Authors: Hrabovský Leopold , Pravda Štěpán , Fries Martin
Published: February 2025

The paper presents measured vibration magnitudes on the trough surface and on the frame of a laboratory model of a vibrating conveyor, detected by acceleration sensors. The vibration source is a DC asynchronous vibration motor with two discs with unbalanced masses mechanically attached to the end parts of the rotor. The trough of the vibrating conveyor is supported by four rubber springs of two types, which are characterized by considerable spring stiffness. Digital signals measured by the sensors, which carry information about the magnitude of acting vibrations, can be remotely transmitted from their place of action via a WI-FI router to the operating station, where they are subjected to the deailed computer based analysis. The highest mean magnitude of the effective vibration velocity (4.8 mm·s-1) in the vertical direction was measured on a model vibrating conveyor, with rubber springs of stiffness of 54 N·mm-1, with the unloaded trough without the conveyed material. The lowest mean magnitude of the effective vibration velocity (1.2 mm·s-1) in the vertical direction with a weight of 5.099 kg of conveyed material on the trough. Rubber springs, of optimum stiffness, dampen the vibrations transmitted to the machine frame. From their sizes, it is possible to remotely monitor the working operation of the vibrating conveyor or to obtain information about the failure of one or several used rubber springs. The paper provides guidance on how to design an optimum spring stiffness, which has a major impact on the magnitude of vibrations transmitted to the frame or foundations of a particular vibratory machine design. Measured signals from acceleration sensors detecting the magnitude of the vibration allow remote monitoring of the optimum operating condition of the vibration equipment depending on predetermined parameters, namely the trough inclination angle, the throw angle, the rotor speed of the vibration motor, the spring stiffness and the amount of material on the trough surface.
Diversity and Distribution of Zoonotic Fungal Diseases in Africa: Multisectoral One Health Strategy is Crucial for Cost-Effective Preparedness and Prevention
Authors: Ahmed Ayman , Mohamed Nouh Saad , Siddig Emmanuel Edwar
Published: February 2025

Emerging zoonotic fungal diseases represent a significant public health challenge in Africa, highlighting the complex interplay between human, animal, and environmental health. This review examines the distribution of various medically important fungi with zoonotic potential, including Emergomyces, Blastomyces, Coccidioides, Cryptococcus, dermatophytes, Histoplasma, Sporothrix, Talaromyces, Paracoccidioides, Aspergillus, and Malassezia in Africa. The evidence suggests that many of these infections are underdiagnosed due to the lack of surveillance and diagnostic capabilities, particularly in immunocompromised populations. The rise in these fungal infections, often linked to increasing HIV prevalence and environmental factors, emphasizes the need for comprehensive public health strategies. Effective interventions should focus on enhancing surveillance, raising awareness, improving diagnostic capacity, and fostering collaboration across health sectors through a One Health approach to mitigate the risks associated with these emerging pathogens.
Fine-Tuning Small Language Models for Domain-Specific AI: An Edge AI Perspective
Authors: Aralimatti Rakshit , Shakhadri Syed Abdul Gaffar , KR Kruthika , Angadi Kartik
Published: February 2025

The Shakti series of 100M, 250M, and 500M models offers compact, resource-efficient language models designed for edge AI deployment. Unlike large models like GPT-3 and LLaMA that demand cloud-based infrastructure, Shakti models operate seamlessly on low-resource devices, including smartphones, smart TVs, IoT systems, drones, and low-end GPUs. They ensure minimal energy consumption, privacy-preserving computation, and real-time performance without internet dependency. Optimized for efficiency, Shakti models come in quantized versions (int8, int5, int4) for even faster, lighter execution on edge devices. The 2.5B Shakti model has demonstrated strong performance while maintaining low latency, paving the way for the smaller, highly efficient 100M, 250M, and 500M models. Built on Responsible AI principles, Shakti prioritizes fairness, transparency, and trust while mitigating risks such as bias, privacy concerns, and high carbon footprints. These models are ideal for sensitive domains like finance, healthcare, and legal services, providing cost-effective, sustainable, and scalable AI solutions with on-device data security. Each model is tailored for specific applications. Shakti-100M excels in text generation, summarization, and chatbots for IoT and mobile apps. Shakti-250M specializes in domain-specific tasks such as contract analysis and personalized financial or healthcare advice. Shakti-500M, a versatile model, enhances customer support, content creation, and virtual assistants with multilingual capabilities and long-context understanding. By decentralizing AI, the Shakti series democratizes access to intelligent, ethical, and impactful AI solutions across industries.
Recent Advances in the Engineering of Cytochrome P450 Enzymes
Authors: Liu Chang , Chen Xi
Published: February 2025

Cytochrome P450 enzymes (CYPs) are versatile heme-containing monooxygenases involved in the metabolism of endogenous and exogenous compounds, as well as natural product biosynthesis. Their ability to catalyze regio- and stereoselective oxidation reactions makes them valuable in pharmaceuticals, fine chemicals, and biocatalysis. However, wild-type CYPs suffer from low catalytic efficiency, limited substrate specificity, and instability under industrial conditions. Recent advances in protein engineering—rational design, semi-rational design, and directed evolution—have enhanced their activity, stability, and substrate scope. These strategies have enabled CYPs to be engineered for applications like C–H functionalization, carbene transfer, and complex molecule biosynthesis. Despite progress, challenges remain in optimizing efficiency, expanding substrate ranges, and scaling production for industrial use. Future directions include integrating CYPs with other biocatalysts, improving high-throughput screening, and applying machine learning to enzyme design. This review highlights recent developments and the promising future of engineered CYPs in sustainable chemistry, drug development, and high-value chemical production.
WLAM- Attention: Plug-and-Play Wavelet Transform Linear Attention
Authors: Feng Bo , Xu Chao , Li Zhengping , Liu Shaohua
Published: February 2025

Linear attention has gained popularity in recent years due to its lower computational complexity compared to SoftMax attention. However, its relatively lower performance has limited its widespread application. To address this issue, we propose a plug-and-play module called Wavelet-Enhanced Linear Attention Mechanism (WLAM), which integrates Discrete Wavelet Transform (DWT) with linear attention. This approach enhances the model's ability to express global contextual information while improving the capture of local features.Firstly, we introduce DWT into the attention mechanism to decompose the input features. The original input features are utilized to generate the query vector Q, while the low-frequency coefficients are used to generate the key K. The high-frequency coefficients undergo convolution to produce the value V. This method effectively embeds global and local information into different components of the attention mechanism, thereby enhancing the model's perception of details and overall structure.Secondly, we perform multi-scale convolution on the high-frequency wavelet coefficients and incorporate a Squeeze-and-Excitation (SE) module to enhance feature selectivity. Subsequently, we utilize the Inverse Discrete Wavelet Transform (IDWT) to reintegrate the multi-scale processed information back into the spatial domain, addressing the limitations of linear attention in handling multi-scale and local information.Finally, inspired by certain structures of the Mamba network, we introduce a forget gate and an improved block design into the linear attention framework, inheriting the core advantages of the Mamba architecture. Following a similar rationale, we leverage the lossless downsampling property of wavelet transforms to combine the downsampling module with the attention module, resulting in the Wavelet Downsampling Attention (WDSA) module. This integration reduces the network size and computational load while mitigating information loss associated with downsampling.We apply Wavelet-Enhanced Linear Attention Mechanism (WLAM) to classical networks such as PVT, Swin, and CSwin, achieving significant improvements in performance on image classification tasks. Furthermore, we combine Wavelet Linear Attention with the Wavelet Downsampling Attention (WDSA) module to construct WDLMFormer, which achieves an accuracy of 84.2% on the ImageNet-1K dataset.
Monk Fruit Extract and Sustainable Health: A PRISMA-Guided Systematic Review of Randomized Controlled Trials
Authors: Kaim Urszula , Labus Karolina
Published: February 2025

Sustainable health approaches promote functional food alternatives that support metabolic well-being while reducing reliance on added sugars and artificial sweeten-ers. Monk fruit extract (MFE), a natural, non-caloric sweetener, is gaining interest for its potential metabolic benefits, but its effects and regulatory status require further evaluation. Objective: This PRISMA-guided systematic review synthesizes findings from randomized controlled trials (RCTs) assessing the impact of MFE on metabolic health, lipid profiles, inflammation, and regulatory considerations. Methods: The lit-erature search was conducted across PubMed, Scopus, Web of Science, and Cochrane Library. Inclusion criteria were human RCTs evaluating MFE’s metabolic effects, while animal studies, reviews, and mixed-intervention trials were excluded. Study quality was assessed using the Cochrane risk of bias tool and the Jadad scale. Results: Ten randomized controlled trials met the inclusion criteria, demonstrating that monk fruit extract (MFE) reduces postprandial glucose levels by 10–18% and insulin responses by 12–22%. Some studies also reported reductions in inflammatory markers (↓IL-6, ↓TNF-α). No severe adverse effects were observed. Regulatory analysis indicated that MFE is approved for use in the United States and China, while its status remains under review in the European Union. Conclusions: MFE shows potential as a functional food ingredient for metabolic health. However, long-term clinical trials and a harmonized regulatory framework are essential to confirm its safety and efficacy within sustaina-ble health strategies.
Sustainable Digital Transformation: Exploring Energy-Efficient Computing and Circular Design Innovations
Authors: William Barnty , Mabel Emmanuel
Published: February 2025

The rapid pace of technological advancement in digital transformation has created new opportunities for enhancing sustainability across various sectors. This article explores the intersection of energy-efficient computing and circular design innovations, focusing on how digital technologies can contribute to reducing environmental impacts while promoting sustainable practices. By examining the role of energy-efficient computing, such as low-power processors, edge computing, and cloud optimization, alongside circular design principles like material reuse, waste reduction, and product lifecycle management, the article investigates how these innovations support a more sustainable digital economy. Drawing on case studies and recent advancements, the study highlights key benefits, including energy savings, reduced e-waste, and the potential for creating more sustainable products and services. However, the research also identifies challenges, including high implementation costs, integration complexities, and the need for industry-wide standards. The findings underscore the importance of cross-sector collaboration, policy frameworks, and investment in R&D to overcome barriers and accelerate the adoption of energy-efficient computing and circular design. The article concludes with recommendations for future research and the role of digital technologies in fostering a circular economy, ultimately contributing to a more sustainable and resource-efficient digital future.
Design and Analysis of Accelerometer MEMS for Range of Motion Applications
Authors: Jadoon Nabeel Ahmad Khan , Sharma Ashutosh , Puventhiram Vaigunthan
Published: February 2025

This report introduces a differential capacitance accelerometer principle and the implementation of a reference design, modification of design to meet the design specifications defined for the Range of Motion (ROM) analysis application. The modified design is analysed for its structural and operational stability and evaluated against the design specification and standard design criteria. With the proposed model the sensitivity of 4.62 fF/g was achieved and around 15 mV/g of sense voltage.
Toward Robust Security Orchestration and Automated Response in Security Operations Centers with a Hyper-Automation Approach Using Agentic AI
Authors: Ismail Ismail , Kurnia Rahmat , Brata Zilmas Arjuna , Nelistiani Ghitha Afina , Heo Shinwook , Kim Hyeongon , Kim Howon
Published: February 2025

The evolving landscape of cybersecurity threats demands the modernization of Security Operations Centers (SOCs) to enhance threat detection, response, and mitigation. Security Orchestration, Automation, and Response (SOAR) platforms play a crucial role in addressing operational inefficiencies; however, traditional no-code SOAR solutions face significant limitations, including restricted flexibility, scalability challenges, inadequate support for advanced logic, and difficulties in managing large playbooks. These constraints hinder effective automation, reduce adaptability, and underutilize analysts’ technical expertise, underscoring the need for more sophisticated solutions. To address these challenges, we propose a hyper-automation SOAR platform powered by Agentic-LLM, leveraging large language models (LLMs) to optimize automation workflows. This approach shifts from rigid no-code playbooks to AI-generated code, providing a more flexible and scalable alternative while reducing operational complexity. Additionally, we introduce the IVAM framework, comprising three critical stages: (1) Investigation, structuring incident response into actionable steps based on tailored recommendations, (2) Validation, ensuring the accuracy and effectiveness of executed actions, and (3) Active Monitoring, providing continuous oversight. By integrating AI-driven automation with the IVAM framework, our solution enhances investigation quality, improves response accuracy, and increases SOC efficiency in addressing modern cybersecurity threats.
Effects of Wheelchair Seat Sagging on Seat Interface Pressure and Shear, and Its Relationship with Changes in Sitting Posture
Authors: Sasaki Kiyo , Yoshikawa Yoshiyuki , Nagayoshi Kyoko , Yamazaki Kodai , Nagai Kenta , Ikeda Koji , Jono Yasutomo , Maeshige Noriaki
Published: February 2025

Objectives: Wheelchair seat sagging is hypothesized to increase pressure and shear forces, potentially leading to pressure injuries. The objective of this study was to assess the impact of correcting wheelchair seat sagging on ischial pressure, shear force, and posture in a population of healthy adults. Methods: Twenty-four healthy adults, meeting specific anthropometric requirements for proper wheelchair fit, were recruited. Participants were evaluated under two conditions: with seat base correction (With Correction) and without it (No Correction). Correction was achieved using insert panels. Ischial pressure was measured using a pressure-mapping system, shear force was assessed with a specialized sensor, and posture was recorded via accelerometers. The primary analysis compared peak pressure index (PPI), shear force, slide, and postural changes between conditions. Subgroup analyses were conducted for participants who exhibited higher shear force values. Results: There was no statistically significant difference in ischial pressure between the No Correction and With Correction conditions. However, shear force and slide were significantly reduced when seat sagging was corrected. Accelerometer data showed no significant difference in postural changes between conditions, although the With Correction condition displayed a slight trend toward greater positional variability over time. Conclusions: These findings indicate that correcting seat sagging can reduce shear force and slide, potentially lowering the risk of pressure injuries. Future studies should include older adults, who may experience additional musculoskeletal and skin changes, to confirm these results. Addressing seat sagging could be an important component of comprehensive pressure injury prevention strategies.
MECHANISMS FOR MANAGING THE ECONOMIC SECURITY OF AGRICULTURAL ENTERPRISES: THEORETICAL ASPECTS
Authors: Bohdaniuk I. , Mandych S.
Published: February 2025

Abstract. The agricultural sector plays a key role in providing the population with food, supporting employment in rural areas, and funding the budget. However, this sector faces numerous threats that can affect its stability and development.
The main risks faced by agriculture include unpredictable weather conditions that can cause significant damage to the crop, fluctuations in prices for agricultural products, changes in exchange rates, and the impact of global economic crises. Therefore, there is an urgent need for effective economic security management mechanisms that will allow agricultural enterprises to maintain stability, develop, and protect their interests.
The article is devoted to studying theoretical aspects of the mechanisms for managing the economic security of agricultural enterprises.
It has been established that research and improvement of mechanisms for managing the economic security of agricultural enterprises are of great importance. This allows the agricultural sector to function effectively, reduce risks, and ensure food security, which is strategically important for the stable development of both rural areas and the economy as a whole.
It has been proven that the economic security of agricultural enterprises ensures the business's stability and adaptability to risks and changes in the market environment.
It has been determined that an agricultural enterprise's security management system should be comprehensive and adapted to the industry's specific conditions, covering financial, land, technological, legal, and organizational components. This allows for minimizing risk impact and ensuring the enterprise's sustainable development.
It is substantiated that the mechanisms for managing the economic security of agricultural enterprises should cover financial, technological, organizational, and legal aspects. This would allow for the creation of a sustainable system of protection against risks and ensure stable development in a dynamic market environment.
FORMATION OF COST COSTS AND ASSESSMENT OF EFFECTIVENESS OF EVENT EVENTS OF AN INDUSTRIAL ENTERPRISE
Authors: Masalab O. , Tkachova N. , Tataryntseva Y.
Published: February 2025

Abstract. The article examines a comprehensive approach to determining the cost of event costs, which is the basis for effective management of financial resources. The authors consider the main factors affecting cost, including optimization of production processes, efficient use of raw materials and materials, and improvement of cost management. Thus, reducing cost becomes a strategic direction that allows enterprises not only to increase profitability, but also to strengthen their positions in the market. The authors prove that the effectiveness of event events should be assessed both by quantitative (ROI, break-even point) and qualitative indicators (increasing brand awareness, increasing customer loyalty). The ROI indicator is key to assessing the feasibility of costs, and calculating the payback allows you to determine the efficiency of using financial resources. Intangible effects play an important role in the long term, although they are more difficult to measure.
The Tradition of the Pilgrimage to the Tomb of Mbah Priok in North Jakarta, Indonesia: A Socio-Economic Study from a Religious Perspective
Authors: Nurainun  , Muhamad Ridwan Effendi
Published: February 2025

Abstract
The tradition of grave pilgrimage is an integral part of religious life in Indonesia, reflecting spiritual values while influencing social and economic dynamics. The Mbah Priok grave in North Jakarta serves as a symbol of cultural and spiritual heritage, attracting pilgrims from diverse backgrounds. However, modernization and socio-economic changes pose challenges to maintaining the relevance of this tradition. This study aims to uncover the role of the Mbah Priok grave in preserving religious traditions and highlighting its impact on the social and economic aspects of the local community. The primary objective is to identify the grave's role as a center for religious practices or traditions and its influence on the surrounding community. This research employs a qualitative. Data were collected through participatory observation, in-depth interviews, and documentation, utilizing instruments such as interview guides, field notes, and recording devices. Sampling techniques involved purposive sampling, which was further developed using snowball sampling. The findings reveal that the tradition of pilgrimage to Mbah Priok strengthens social values such as cooperation and solidarity, enhances adherence to religious norms, and creates new economic opportunities through local trade activities. The conclusion highlights the importance of balanced strategies for preserving traditions alongside modern developments, ensuring this tradition remains a significant part of the cultural and spiritual identity of the community.