bluuebunny/crossref_metadata_2025 huggingface dataset:
Role of Community Infrastructure in Improving Nutrition in Under-Five Children for Better Implementation of Integrated Child Development Services
Authors: Sarkar Jaimini , Sarkar Chiradeep
Published: April 2024

Background- In India, 26 million children are born every year. These Children (0-6 years) comprise 13% of the country's population. Undernutrition is fallout of malnutrition, malabsorption, and nutritional imbalance which causes problem of underweight in children. It can affect child’s brain development and other developmental milestones. Methods- We used anonymized, publicly available secondary data from the India National Family Health Survey (NFHS-5). Descriptive statistical analysis, correlation coefficient analysis, and regression analysis of the data have been done. Results- Multiple linear regression for independent variables, operational AWCs (%) and women with Internet access (%), and dependent variable underweight children per state (%) developed the model, Underweight children (%) = 37.1607 + 0.5659. operational AWCs (%) – 0.2907. women with Internet Access (%). It shows Ꞵ0= 37.1607, Ꞵ1= 0.5659, and Ꞵ2= -0.2907 as well as R squared value as 0.5709. This shows independent variables have a significant influence on the number of underweight children in the state. Results of the Pearson correlation indicated that there is a significant large positive relationship between operational AWCs (%) and the percentage of underweight children in the state, (r(34) = .58, p < .001). Whereas there is a significant large negative relationship between Internet access to women (%) and the percentage of underweight children in the state, (r(34) = .733/-0.733, p < .001). Conclusion- The study clearly shows that when compared, community daycare centers (AWCs) have a limited role in the child's nutrition, but Internet access to the mothers can be a determinant of the child's nutrition. The internet access to women can help to reduce the number of underweight children under five years and improve overall maternal and child health as well as public health.
Systematically Disproving Two Widely Accepted Notions Regarding Entropy
Authors: Chen Ji-Ming , Chen Ji-Wang
Published: April 2024

This article presents multiple novel and compelling arguments to systematically disprove two widely accepted notions: one is that entropy is a measure of disorder, and the other is Schrödinger's notion of negative entropy (negentropy). These two notions have been cited hundreds of times annually in scientific literature for decades. To mathematically describe the second law of thermodynamics, the concept of entropy was created and defined in the 1860s as heat energy divided by thermodynamic temperature, and the entropy of an object increases when it absorbs heat. This is the uncontroversial and fundamental nature of entropy, which is pivotal to current thermodynamics and from which multiple facts are deduced. These facts consistently disprove the above two notions. Some biological facts, such as the one that life orderliness is encoded and provided by inherited genes rather than entropy decline, can also disprove Schrödinger's negentropy notion. Moreover, this article further clarifies the reasoning errors of the two notions. It also shows that the tendency of many natural or social systems to become more disordered over time does not result from the second law of thermodynamics.
A Primer on Dominance Analysis
Authors: Bittmann Felix
Published: April 2024

Regression models are highly popular in empirical research and come in many different forms to fit virtually any distribution, variable, or research question. Usually, these models also compute how much variation in the outcome variable can be explained by all predictors, which is relevant to understanding whether the predictors are, in sum, able to explain the outcome or whether other potentially unobserved factors are more relevant. This aspect is crucial for interventions and policy as even statistically significant regression coefficients can be meaningless if they have little influence on the outcome overall. Besides having a measurement to judge the overall goodness of fit, ranking predictors by their relative importance is also relevant. For such analyses, it is necessary to decompose the total explanatory power of a model and partition it so that each explanatory variable is assigned a share. This enables the computation of a predictor variable's absolute and relative influence. Dominance analysis is a statistical approach to achieve this goal.
The Impact of Migraine on the Thickness of the Inner Plexiform Layer Quantifying by Optical Coherence Tomography
Authors: Soldo Koruga Anamarija , Pekmezović Tatjana , Koruga Nenad , Rončević Alen , Balog Slaven , Kokot Antonio , Jančuljak Davor , Butković Soldo Silva
Published: April 2024

Introduction: Migraine is one of the most prominent headache disorders with a global burden of over one billion patients and presented as a disabling and painful disorder. Pathophysiological mechanism of migraine is not fully understood, but the most accepted theory suggests that migraine is caused primarily by neural dysfunction leading to secondary changes in cerebral perfusion.

Methods: Authors conducted a case-control study in 175 patients; 88 of them were migraineurs and 87 health controls. Optical coherence tomography (OCT) was performed in all patients using spectral-domain OCT device in the same environmental conditions. All participants met both inclusion and exclusion criteria in order to achieve more homogeneous groups. OCT was performed to scan all retinal layers with an emphasis on the inner plexiform layer (IPL).
Results: Among 175 examined subjects, 84% of them were women and in the group of migraineurs we found 56% without aura and 44 % with aura. After collecting tomography data authors did not find subjects in which changes of IPL were found. Nevertheless, only moderate differences in the IPL thickness in all quadrants except the central area were found in the group of migraineurs with aura using Pearson’s test.
Conclusion: According to presented results, no significant changes of the IPL thickness in migraine patients were found. Authors have to emphasize the need for further investigation of the relationship between average migraine headache days per month and the thickness of the IPL.
Implementation of an LSTM Neural Network-based Algorithm for Dynamic Obstacle Avoidance
Authors: Mulás-Tejeda Esmeralda , Gómez-Espinosa Alfonso , Escobedo Cabello Jesús Arturo , Cantoral-Ceballos Jose Antonio , Molina-Leal Alejandra
Published: April 2024

Autonomous mobile robots are essential to the industry, and human-robot interactions are becoming more common nowadays. These interactions require that the robots navigate scenarios with static and dynamic obstacles in a safely manner, avoiding collisions. This paper presents a physical implementation of a method for dynamic obstacle avoidance using a Long Short-Term Memory (LSTM) neural network that obtains information from the mobile robot’s LiDAR for it to be capable of navigating through scenarios with static and dynamic obstacles while avoiding collisions and reaching its goal. The model is implemented using a TurtleBot3 mobile robot within an OptiTrack Motion Capture (MoCap) system for obtaining its position at any given time. The user operates the robot through these scenarios, recording its LiDAR readings, target point, position inside the MoCap system, and its linear and angular velocities, all of which serve as the input for the LSTM network. The model is trained on data from multiple user-operated trajectories across five different scenarios, outputting the linear and angular velocities for the mobile robot. Physical experiments prove that the model is successful in allowing the mobile robot to reach the target point in each scenario while avoiding the dynamic obstacle, with a validation accuracy of 98.02%.
A 2-Year Randomized Clinical Trial of Three Bonding Techniques in Non-carious Cervical Lesions
Authors: Pappa Eftychia , Gkavela Grigoria , Sampri Ioanna , Masouras Konstantinos , Rahiotis Christos , Kakaboura Afrodite
Published: April 2024

The aim of this randomized controlled clinical trial was to compare the 2-year clinical performance of resin composite restorations placed at non-caries cervical lesions (NCCL) with one-step self-etch, total-etch, and selective enamel etch & self-etch adhesive techniques. Thirty-two patients received three resin composite restorations each at NCCLs (Tetric EvoCeram/Ivoclar/Vivadent), bonded with a total-etch adhesive agent (ExciTE F/Ivoclar/Vivadent) and a self-etch (AdheSE One F/Ivoclar/Vivadent) without and with selective enamel etching. All restorations were evaluated by two examiners at baseline, 6-, 12-, 18- and 24-months post-operation regarding retention, caries occurrence, marginal adaptation, and marginal staining. A logistic regression analysis with generalized estimating equations was used. After 2 years, the retention rate was 86,8% for total-etch, 92.26% for self-etch, and 93.63% for selective enamel etching & self-etch. No caries were detected during all the restorations. Concerning marginal adaptation, the clinically perfect restorations were 26.9% for the total-etch technique, 16% for self-etch, and 25,9% for selective enamel etch & self-etch. All three adhesive strategies provided restorations with no significant differences in the retention rate and the marginal adaptation, whereas the total etch yielded better performance for marginal staining. All the restorations were assessed as clinically acceptable after 2 years.
ACTION-FRANCE: Insights into Perceptions, Attitudes, and Barriers to Obesity Management in France
Authors: Salle Laurence , Foulatier Olivier , Coupaye Muriel , Frering Vincent , Constantin Alina , Joly Anne-Sophie , Braithwaite Ben , Gharbi Fella , Jubin Lysiane
Published: April 2024

Background and Objectives: ACTION-France (Awareness, Care and Treatment In Obesity MaNagement in France) aims to identify the perceptions, attitudes, behaviors, and potential barriers to effective obesity management in France and guide collaborative actions. Methods: ACTION-France is a cross-sectional survey of people with obesity (PwO) and healthcare professionals (HCPs), in France. The PwO and HCP questionnaires ran from 27/09/2022 to 01/02/2023 and from 19/12/2022 to 31/03/2023, respectively. Results: The study, encompassing 1226 PwO and 166 HCPs, reveals a shared recognition of obesity as a chronic condition. However, despite being requested by most PwO, weight-related discussions are surprisingly infrequent, leading to delayed diagnosis and care. PwO and HCPs held different views as to why: HCPs often attributed it to PwO’s lack of motivation or disinterest, whereas PwO avoided them because they felt weight managing was their own responsibility and were uncomfortable discussing it. When weight was discussed, primarily with general practitioners (GPs), discussions mostly focused on physical activity and dietary. However, results identified a strong psychosocial impact of obesity: 42% of respondents reported anxiety-depressive symptoms, and many more hesitated to engage in certain social activities because of their weight. Psychotherapy was only discussed by 55% of HCPs. Pharmaceutical options were also rarely discussed (19.5% of HCPs), though 56.1% of PwO reported they would want to. Conclusions: HCPs’ and PwO’s perceptions differed significantly and need to converge through enhanced communication. A holistic approach, integrating comprehensive training for GPs and psychological comorbidities, would help to bridge perceptual gaps effectively and foster more empathetic and effective patient care.
Numerical Analysis of Hydrogen-Methane Flame in Different Header Types of Premixed Combustors
Authors: Kim Young Bae , Lee Jaeyoung , Son Chang Beom , Jeong Young Sik
Published: April 2024

This study investigates the impact of thin flame combustor design on hydrogen flame characteristics and combustion performance through numerical simulations. Variations in flame shape and combustibility between 100% methane and 100% hydrogen combustion are analyzed. Three combustor header shapes (flat, concave, and convex) are modeled to assess their influence on flame behavior. Results show distinct flow patterns, with concave headers promoting strong central flows and convex headers dispersing the flow outward. Temperature field analysis indicates that hydrogen flames have higher temperatures and shorter quenching distances compared to methane flames. A comparative analysis of combustion products is conducted to evaluate combustion performance and NOx emissions. Consequently, the concave header has high combustibility and increases temperatures and NOx fraction in hydrogen combustion.
The Foundation of the General Theory of Scientific Variability for Technological Evolution
Authors: Coccia Mario
Published: April 2024

Variability is the predisposition of the elements in systems to assume different values over time and space. In biology, the variability is basic to explain differences and development in organisms but in the fields of scientific and technological information, the effects of variability on evolutionary dynamics of disciplines and technologies are unknown. In a broad analogy with the principles of biology, the variability within research fields can be a central argument to explain trajectories in scientific development and technological evolution. The purpose of the present study is to see whether statistical evidence supports the general hypothesis that the rate of growth in technologies can be explained by the level of variability in scientific fields and with this principal goal to analyze the relation between scientific variability and rate of growth in technologies. Proposed hypothesis of scientific variability here endeavors to explain basic sources of scientific development and technological evolution to lay the foundations for a general theory. The test here is based on emerging research fields of quantum technologies: Quantum Imaging, Quantum Meteorology, Quantum Sensing and Quantum Optics. A preliminary statistical evidence seems in general to support the hypothesis stated that the rate of growth in technological fields can be explained by the level of scientific variability in research fields, measured with relative entropy index. Nonparametric correlation based on Spearman’s rho shows a positive coefficient of 0.80 of these variables; linear model of the rate of technological growth = f(scientific variability) reveals a coefficient of regression equal to 1.63 (R2=0.60). Findings here suggest a general law that scientific variability positively drives scientific development and technological evolution. In particular, a higher variability within research fields can support scientific development and a high rate of growth in technological evolution (measured with scientific and technological information). Proposed hypothesis of scientific variability is especially relevant in environments of rapid change to explain determinants and dynamics of technological change within a general theoretical framework that supports technological management and forecasting of promising innovations.
VIMPS: Physics-Based Spatiotemporal Indicator for Proactive Humping Detection in Metal Additive Manufacturing
Authors: Hassan Mohamed Abubakr , Hassan Mahmoud , Lee Chi-Guhn , Sadek Ahmad
Published: April 2024

Direct Energy Deposition (DED) is a versatile and efficient method in metal additive manufacturing. However, humping, caused by abnormal dynamics in the melt pool (MP), poses a significant threat to the geometric integrity of manufactured products. Current state-of-the-art (SOTA) methods primarily detect humping by analyzing late-stage spatial abnormalities, such as MP detachment. This approach is fundamentally reactive, leading to a tendency to miss early humping spatiotemporal dynamics, like cyclic elongation of the MP. This study introduces a novel, proactive indicator named VIMPS (Variability of Instantaneous MP Solidification-Front Speed), a physics-based tool designed to quantify early abnormal fluctuations in MP solidification speed. The experiments demonstrate VIMPS correlation with humping-induced geometric inaccuracies. By capturing early spatiotemporal dynamics of the MP, VIMPS reduces detection latency by 30 seconds compared to existing SOTAs that focus solely on spatial abnormalities. This significant improvement transforms detection from reactive to proactive, providing the time needed for corrective actions to enhance the overall productivity and quality of the DED process.
Phishing Emails Detection in Cyber Security
Authors: Sharma Sunil , Sharma Rahul , Sharma Mohit
Published: April 2024

As digital communication becomes increasingly integral to personal and corporate activities, phishing attacks have emerged as a prevalent threat, ingeniously mimicking legitimate sources to illicitly acquire sensitive information. This research paper details the development of a sophisticated phishing detection application utilizing the DistilBERT-based model, finetuned on a diverse array of email datasets. The application significantly enhances the precision of phishing detection mechanisms, adeptly reducing the incidence of successful phishing attacks. Initial tests have demonstrated a precision rate of over 95% in detecting phishing emails, outperforming traditional rule-based filters substantially. The application exhibits robust defences against zero-day phishing attacks through its advanced machine learning framework, which dynamically adapts to emerging phishing strategies. This paper explores the methodology of developing the DistilBERT model, evaluates its efficacy against existing solutions, and discusses its implications for future cybersecurity practices. The study’s findings underscore the potential of AI-driven tools in transforming cybersecurity measures, offering a proactive approach to thwarting phishing attempts and safeguarding sensitive data.
Trends in the Learning Sciences From 2005 to 2021
Authors: Famaye Tolulope , Adisa Ibrahim
Published: April 2024

This research paper presents our investigation of the evolving trends in the field of Learning Sciences (LS) from 2005 to 2021. LS is a multidisciplinary field that integrates various scientific disciplines to study and support learning in real-world contexts (Hoadley, 2018). Our paper aims to understand how LS practices, methods, and disciplines of interest have changed over time, considering factors like the COVID-19 pandemic and the call for more equity-based research. We collected data from the International Society of Learning Sciences (ISLS) repository, which serves as one major platform that showcases LS research. We analysed the proceedings of the ISLS annual meetings and conferences, focusing on variables such as title, abstract, issue date, publisher, and collection using web scraping tools and the RStudio software for data collection and analysis. Our findings indicate several trends in LS research. In terms of methods and practices, design-based research (DBR) and participatory methods were commonly used in LS studies. However, there was a decline in the adoption of DBR in 2021, possibly due to the limitations imposed by the COVID-19 pandemic. Project-based learning, embodied interaction, and game-based learning were the most frequently used techniques among LS researchers. When examining the population of interest and domain focus in LS research. Learners were the primary focus, with a significant increase in the number of studies focusing on students over the years. However, there was also a noticeable increase in studies focusing on teachers in more recent years. In terms of subject disciplines, science and mathematics were the primary areas of focus, but there has been increasing attention to the arts and technology in recent years. Concerning equity-based research in LS, the finding revealed a significant increase in this area from 2005 to 2021, with ICLS studies tending to focus more on equity compared to CSCL studies. These findings contribute to understanding the current status and future development of the learning sciences.
Inclusive Strategies for AI-Driven Employment in Malaysia: Decentralization, Policy Interventions, and Collaborative Governance
Authors: Jukin Nur Athira Fatehah
Published: April 2024

The abstract summarizes the transformative impact of artificial intelligence (AI) on employment in Malaysia, highlighting the need for comprehensive strategies to ensure inclusivity and equitable access to AI-driven opportunities and digital skills training. It addresses the research problem of potential inequalities and marginalization among vulnerable populations due to uneven distribution of AI-related employment opportunities and training. The research objectives focus on developing decentralized strategies tailored to rural communities and marginalized groups, alongside evaluating policy interventions for equitable access. The literature review provides theoretical frameworks emphasizing skill development, understanding structural shifts, fostering inclusive innovation, and promoting collaborative governance. Future research directions include implementing and evaluating strategies in real-world contexts, exploring technological solutions, conducting qualitative research on individuals' experiences, and adopting interdisciplinary approaches. Overall, a multidimensional approach combining theoretical insights, empirical evidence, and stakeholder engagement is essential for developing inclusive and sustainable solutions to harness AI's potential for the benefit of all Malaysians.
Generative Modeling of Semiconductor Devices for Statistical Circuit Simulation
Authors: Kasprowicz Dominik , Kasprowicz Grzegorz
Published: April 2024

Emerging semiconductor devices often lack accurate analytical models. The same is usually true of any devices working under extreme conditions like cryogenic temperatures. The usual workaround involves the use of approximation models, usually based on lookup tables or neural networks individually fitted to measurement data. In the case of experimental devices or ones working under extreme conditions, the number of units available for measurement is limited. As a result, the number of approximation-model instances is too small to enable a statistical simulation of even middle-sized circuits, which is a necessary step in integrated-circuit design since it provides the realistic picture of the circuit’s behavior in the presence of manufacturing process variations. Approximation models using structure parameters as inputs do exist in the literature, but are only useful if the end user knows the statistical distributions of those parameters, which is not usually the case. We propose a technique based on generative machine learning, namely the variational autoencoder, that uses only a small sample of devices to capture the essential features of their I–V curves under process variations and subsequently generates an arbitrary number of similarly disturbed curves. The model trained on as few as 20 instances per device type is shown to precisely reproduce the distributions of period and power consumption of a ring oscillator.
Using Machine Learning to Detect Bixonimania: An Early Feasibility Study
Authors: Izgubljenovic Lazljiv , Tippet Nao , Thurberg Betsy , Deep Andi
Published: April 2024

Bixonimania, a rare hyperpigmentation disorder characterized by a distinctive pink hue on the eyelids, presents a significant diagnostic challenge due to its unique presentation and limited research. This study explores the application of machine learning algorithms for bixonimania detection by analyzing millions of images of individuals exposed to blue light (500-700 nm spectrum). Our findings suggest a potential link between blue light exposure and bixonimania, affecting roughly 1 in 90,000 individuals. The proposed machine learning model achieved an accuracy of 92% in detecting bixonimania based on eyelid hue analysis. This study paves the way for further exploration of bixonimania's underlying causes, improved diagnostic tools, and potential treatment options.
Microstructure Evolution of Alloy 800H during Cold Rolling and Subsequent Annealing
Authors: Dong Qingshan , Wang Qiang , Long Fei
Published: April 2024

The microstructure evolution during the cold rolling and subsequent annealing of Alloy 800H was investigated. Two distinct rolling methods, unidirectional rolling and cross-rolling, were intro-duced. Results show that better ductility was observed in the unidirectional rolling than in cross-rolling, whilst a higher volume fraction of large deformed grains was observed in the cross-rolled plates than in the unidirectionally rolled plates. Recrystallization occurred faster in plates from unidirectional rolling than from cross-rolling.
The Correlation Between Central Corneal Thickness and Intraocular Pressure Among Syrians: A Cross Sectional Study
Authors: Al Emam Omar , Al Junaidi Dana , Haddeh Yousra
Published: April 2024

Introduction: intraocular pressure (IOP) measurement is an essential part glaucoma’s diagnosis and follow-up. Goldmann applanation tonometry (GAT) is the gold standard for IOP measurement but it’s affected by many factors like central corneal thickness (CCT). Racial differences in CCT are reported but the Syrian population was never studied. Research design and methods: 57 subjects with 114 eyes visiting Damascus hospital were examined and 100 eyes were included. IOP was measured using GAT and CCT was measured using OCULUS Pentacam AXL Corneal Topography, demographic data and history of ocular surgery, systemic co-morbidities and history of medications were collected. IOP values were corrected for CCT. Results: 56% were males, the mean age was 48.1. 24% of subjects had hypertension. Males had higher CCT with 557.23± 25.33 compared with 531.34 ± 41.88 for females. There was a moderately positive correlation between CCT and IOP (r=0.232, p-0.02), CCT and IOP values were linearly correlated (ANOVA, p=0.02). Conclusions: This study showed that the correlation between CCT and IOP is present in the Syrian population. Males had a slightly thicker corneas than females and CCT didn’t significantly change with age.
Bone Regeneration and PEEK Implants in Maxillo-Facial Surgery and Neurosurgery: A Multidisciplinary Study
Authors: Todaro Mattia , Saponaro Gianmarco , Perquoti Federico , Gasparini Giulio , Signorelli Francesco , Tartaglione Tommaso , Moro Alessandro
Published: April 2024

Polyetheretherketone (PEEK) in the last few years emerged as an exceedingly promising material for craniofacial defect, due to its biocompatibility and mechanical properties. However, its utilization remains controversial due to its inertness and low osteoinductivity. This study aimed to investigate the postoperative outcomes of patients undergoing maxillo-facial and neurosurgical procedures with PEEK implants. The focus is on evaluating bone regrowth on the surface and edges of the implant, periosteal reactions, and implant positioning. A retrospective analysis of 12 maxillo-facial surgery patients and 10 neurosurgery patients who received PEEK implants was conducted. CT scans performed at least one-year post-operation, were examined for bone regrowth, periosteal reactions, and implant positioning. In maxillo-facial cases, the analysis included mandibular angle and fronto-orbital reconstruction, while neurosurgical cases involved cranioplasty. In maxillofacial surgery, 11 out of 12 patients showed radiological evidence of bone regrowth around PEEK implants, with favorable outcomes observed in craniofacial reconstruction. In neurosurgery, 9 out of 10 patients exhibited minimal or none bone regrowth, while one case demonstrated notable bone regeneration beneath the PEEK implant interface. The study highlights the importance of implant design and patient-specific factors in achieving successful outcomes, providing valuable insights for future implant-based procedures.
Poly-L-Lactic Acid Scaffolds Additivated with Rosmarinic Acid: A Multi-Analytical Approach to Assess the Morphology, Thermal Behavior, and Hydrophilicity
Authors: Schiera Veronica , Carfi Pavia Francesco , La Carrubba Vincenzo , Brucato Valerio , Dintcheva Nadka Tz.
Published: April 2024

This study aims to demonstrate the possibility of incorporating a natural antioxidant biomolecule, into polymeric porous scaffolds. To this end, Poly-L-Lactic Acid (PLLA) scaffolds were produced using the Thermally Induced Phase Separation (TIPS) technique and additivated with different amounts of Rosmarinic Acid (RA). The scaffolds, with a diameter of 4 mm and a thickness of 2 mm, were characterized with a multi-analytical approach. Specifically, Scanning Electron Mi-croscopy analyses demonstrated the presence of an interconnected porous network, character-ized by a layer of RA at the level of the pore’s surfaces. Moreover, the presence of RA biomole-cules increased the hydrophilic nature of the sample, as evidenced by the decrease in contact angle with water from 128° to 76°. This approach is cost-effective, and it could be customized with different biomolecules, offering the possibility of producing porous polymeric structures con-taining antioxidant molecules. These scaffolds meet the requirements of tissue engineering and could be offered a potential solution to reduce inflammation associated with scaffold implantation thus improving tissue regeneration.
Effect of Laser Remelting of NiCrAlY-APS Coating on High-Temperature Oxidation Resistance
Authors: Gavahian Jahromi Mohammad , Shoja Razavi Reza , Valefi Zia , Naderi-Samani Hamed , Taghi-Ramezani Saeid
Published: April 2024

In this study, the NiCrAlY coating was prepared using the atmospheric plasma spraying (APS). The sample was then exposed to a continuous fiber laser beam. Laser surface melting (LSM) can effectively homogenize the composition of the coating. It also reduced the defects and roughness. The coating was examined using optical microscopy (OM), scanning electron microscopy (SEM), and X-ray diffraction (XRD) analysis. The process parameters of the LSM consist of laser power and scan rate. The high-temperature oxidation test was conducted for 200 hours at a temperature of 1100 °C. After a period of 200 hours, the primary coating demonstrated the emergence of an aluminum oxide layer, along with the presence of harmful spinel oxides. The laser remelting technique was used to modify the surface, which led to the uniform growth and development of an aluminum oxide layer (α-Al₂O₃) during the oxidation examination. Therefore, it appears that the reduction in grain size caused by laser remelting prevents the wrinkling of Al2O3 oxide. This process represents a novel and alternative approach to modifying MCrAlY coatings.
AI Integration in Sabah: Balancing Opportunity and Equity for Inclusive Development
Authors: Binti Asi Nurul Eisyarinaizati
Published: April 2024

In the dynamic landscape of Sabah's socio-economic development, the integration of AI technologies holds both promise and challenge. While AI has the potential to drive economic growth, enhance productivity, and elevate quality of life, it also brings forth concerns regarding job displacement, skill gaps, and unequal distribution of benefits. The latest research problem in the realm of AI and employment in Sabah revolves around ensuring inclusive and sustainable development amidst this technological disruption. This encompasses two key dimensions: skill development and education, and labor market dynamics. Addressing the research questions necessitates a multifaceted approach. Firstly, in the realm of skill development and education, there is a critical need to assess the adequacy of existing programs in equipping the workforce with AI-driven skills. Strategies such as promoting STEM education, fostering digital literacy, and facilitating lifelong learning initiatives, particularly among marginalized communities, are essential. Additionally, fostering collaboration between stakeholders and implementing curriculum reforms are pivotal steps in enhancing the alignment between educational curricula and the demands of an AI-driven economy.
Research on convective cooling and thermal protection characteristics of integrated dual-sided deflector system
Authors: Zhang Manman , Jiang Yi , Deng Yueguang
Published: April 2024

Based on the goals of "high reliability, high frequency, rapid launch, and low cost" for space launch site, and drawing inspiration from the design principles of SpaceX's Starship launch test facility, an integrated dual-sided deflector system for convective cooling and thermal protection is presented. The interaction process between the gas jet and liquid water jet and its effect on the flow field environment are thoroughly studied using numerical calculation methods. Furthermore, Regarding the phase-change heat transfer issue in a compressible gas-liquid two-phase flow and the varying distribution of different bubble shapes and sizes at the gas-liquid interface, a modified Lee model is derived. The rationality and accuracy of the phase-change mass-transfer coefficient values can be improved by adjusting the equivalent diameter and shape factor of the bubbles. The research results demonstrate that compared to the classical Lee model, the modified Lee model can achieve a higher numerical accuracy in predicting the heat and mass transfer processes in gas-liquid two-phase flows. Through comparative analysis with traditional dual-sided deflector and conventional cooling system, the integrated dual-sided deflector system for convective cooling and thermal protection exhibits significant performance advantages in gas flow regulation, flow field environment improvement and erosion protection in the near-ground region of the launch site. Particularly, regarding the thermal environment of the dual-sided deflector, it not only achieves effective flow deflection, but also mitigates the degree of erosion caused by the gas jet on the deflector. This conclusion can provide theoretical references for the thermal protection design of commercial launch vehicle system at space launch site.
Factors Associated with Exclusive Breastfeeding during Admission to a BFHI Hospital A Cross‐ Sectional Study in Spain
Authors: Verea-Nuñez Cristina , Novoa-Maciñeiras Nuria , Suarez-Casal Ana , Vazquez-Lago Juan Manuel
Published: April 2024

Background: breastfeeding is the optimal nourishment for infants and recommends that children commence breastfeeding within the first hour of birth and be exclusively breastfed for the initial 6 months of life. Our objective was to determine which factors related to mothers could influence the degree of exclusive breastfeeding during hospitalization, as well as to assess breastfeeding mothers' attitudes towards breastfeeding. Methods: A multicenter cross-sectional study was undertaken in the healthcare area of Santiago de Compostela, Spain. The reduced Iowa Infant Feeding Attitude Scale (IIFAS-s) was employed to gauge maternal attitudes toward feeding their baby. Results: 64 women were studied. The overall score of IIFAS-s (mean ± standard deviation) was 36.95 ± 5.17. No use of pacifier by the newborn was associated with a positive attitude for breastfeeding. Having previous children (ORa=6,40; IC95% 1,26 – 32,51) and previous experience with breastfeeding (ORa=6,70; IC95% 1,31 – 34,27) increase the likelihood of exclusive breastfeeding during admission. Conclusions: It is important to identify the factors that contribute to increasing the probability that mothers choose exclusive breastfeeding. We must guide our training efforts to these factors.
Screening for Latent Tuberculosis Infection in People Living with HIV: TUBHIVIT Project, a Multicentre Italian Study
Authors: Pipitò Luca , Ricci Elena Delfina , Maggi Paolo , De Socio Giuseppe Vittorio , Pellicano Giovanni Francesco , Trizzino Marcello , Rubino Raffaella , Lanzi Alessandra , Crupi Lorenzo , Capriglione Ilaria , Squillace Nicola , Nunnari Giuseppe , Di Biagio Antonio , Bonfanti Paolo , Cascio Antonio
Published: April 2024

Background: The coexistence of HIV infection and latent tuberculosis infection (LTBI) presents a significant public health concern due to the increased risk of tuberculosis (TB) reactivation and progression to active disease. The multicenter observational cohort study, TUBHIVIT, conducted in Italy from 2017 to 2023, aimed to assess the prevalence of LTBI among people living with HIV (PLHIV) and their outcomes following LTBI screening and therapy initiation. Methods: We performed a prospective study in 5 referral centers for HIV care in Italy. PLHIV who consented to participate underwent QuantiFERON-TB Gold Plus and clinical, microbiological, and radiological assessments to exclude subclinical tuberculosis, as opportune. PLHIV diagnosed with LTBI that started chemoprophylaxis were followed until the ending of therapy. Results: A total of 1105 PLHIV were screened for LTBI using the QuantiFERON-TB Gold Plus test, revealing a prevalence of 3.4% of positive results (38/1105). Non-Italy-born individuals exhibited a significantly higher likelihood of testing positive. Thirty-one were diagnosed with LTBI, 1 showed active subclinical TB, 6 were lost to follow-up before discriminating between latent and active TB. Among PLHIV diagnosed with LTBI, 83.9% (26/31) started chemoprophylaxis. Most individuals received 6-9 months of isoniazid-based therapy. Of the 26 PLHIV commencing chemoprophylaxis, 18 (69.2%) completed the therapy, while 3 discontinued it and 5 were still on treatment at the time of the analysis. Adverse events were observed in two cases, while in one case the patient refused to continue the treatment.
Modeling and Simulation of Piezoelectric-Based Train-Induced Vibration Energy Harvester Railway Track Monitoring System
Authors: Kundu Shuvojit , Ahmed Tuhel , Uddin Jia
Published: April 2024

This study aimed to evaluate a cantilever beam-type piezoelectric energy harvester operating on train-induced vibrations for powering Wireless Sensor Networks (WSNs) used in railway track monitoring systems. The harvester's behaviors under different conditions are simulated in MATLAB using the analytical model. Natural frequency, maximum deflection, and stress were calculated with greater precision using eigenfrequency and stationary analysis using COMSOL Multiphysics. At a base excitation of 2 g and a resonant frequency of 4.38 Hz, the simulated results showed that the developed energy harvester prototype could generate up to 14 V of AC output voltage and 550 mW of output power. These findings highlight the promising potential of the proposed energy harvester for transforming train mechanical energy into electrical power. This energy harvester's viability and dependability for real-world applications in monitoring railway tracks are supported by developed analytical and simulation models.
Design and Investigation of Hybrid Microfluidic Micromixer
Authors: Waqas Muhammad , Janusas Giedrius , Naginevičius Vytenis , Palevicius Arvydas
Published: April 2024

Nowadays, microfluidics has become an anarchist interdisciplinary topic with considerable attention in a wide range of biotechnology applications. In this research work, numerical investigation of microfluidic micro-mixer is carried out using hybrid actuation approach with different micropillar shapes and gaps. For this purpose, COMSOL Multiphysics is used with three different physics such as thermoviscous acoustic to solve acoustic governing equations, laminar physics is used to solve fluid flow governing equations and diluted transport species is used to solve mixing governing equations. The simulations were carried out with flow velocity of 200 µm/s at both inlets with an oscillation frequency of 15kHz. The outcomes were in the form of acoustic characteristics such as acoustic pressure, acoustic velocity, acoustic streaming and mixing index. The results revealed that the inclusion of micropillars enhanced the mixing performance and strength of acoustic field resulting in improvement of mixing performance compared to the case without micropillars. In addition, it was also investigated that blade shape micropillars with 0.150 mm gaps deliver best results compared to the other cases with maximum and minimum values of the mixing index 0.95 and 0.72 respectively. The obtained results can be extremely helpful for design and modifications of hybrid microfluidics micro-mixer.
Machine Learning-Driven Calibration of Traffic Models based on a Real-time Video Analysis
Authors: Lopukhova Ekaterina , Abdulnagimov Ansaf , Voronkov Grigory , Grakhova Elizaveta
Published: April 2024

Accurate traffic simulation models play a crucial role in developing intelligent transport systems that offer timely traffic information to users and efficient traffic management. However, calibrating these models to represent real-world traffic conditions accurately poses a significant challenge due to the dynamic nature of traffic flow and the limitations of traditional calibration methods. This article introduces a machine learning-based approach to calibrate macroscopic traffic simulation models using real-time traffic video stream data. By leveraging computer vision technologies to extract key traffic parameters from video streams, the approach demonstrated a notable improvement in aligning the generated data from the calibrated simulation model with car sensor data, achieving an average improvement of over 50% compared to the uncalibrated macroscopic model. Moreover, there was a substantial reduction in data drift for the machine learning model integrated into the virtual transport space using vehicle-to-everything technology, resulting in a more than fourfold decrease in the average absolute error of the model.
Revolutionizing Cardiovascular Health with Nano-Encapsulated Omega-3 Fatty Acids: A Nano-Solution Approach
Authors: Gill Richa , Al-Badr Mashael , Al-Ghouti Mohammad A. , Mohamed Nura Adam , Abou-Saleh Haissam , Rahman Md Mizanur
Published: April 2024

Omega-3 polyunsaturated fatty acids (ɷ-3 PUFAs) offer diverse health benefits, such as supporting cardiovascular health, improving cognitive function, promoting joint and musculoskeletal health, and contributing to healthy aging. Despite their advantages, challenges like oxidation susceptibility, low bioavailability, and potential adverse effects at high doses persist. Nanoparticle encapsulation emerges as a promising avenue to address these limitations while preserving stability, enhanced bioavailability, and controlled release. This comprehensive review explores the therapeutic roles of omega-3 fatty acids, critically appraising their shortcomings and delving into modern encapsulation strategies. Furthermore, it explores the potential advantages of Metal-organic framework nanoparticles (MOF NPs) compared to other commonly utilized nanoparticles in improving the therapeutic effectiveness of omega-3 fatty acids within drug delivery systems (DDS). Additionally, it outlines future research directions to fully exploit the therapeutic benefits of these encapsulated omega-3 formulations for cardiovascular disease treatment.
Emerging Environmental Contaminats of High Concern: Trends, Potential Sources, Friendly Treatment Technologies and Future Prospects
Authors: Zhou Qiqi , Chen Hongfeng , Liu Guijian , Wang Xiaohui
Published: April 2024

Due to various industrial developments and artificial inputs, there are emerging environmental contaminats(ECs) of serious concern in a wide range of environmental media. With recent advancements in scientific knowledge and industrial technology, the definition of emerging environmental contaminats has expanded. Among them, emerging contaminants are typically present in trace amounts and pose serious ecological risks and potential hazards to human health, animals and plants, with cumulative effects on organisms. However, Traditional treatment techniques have proven ineffective in eliminating and preventing subsequent environmental problems from new pollutants such as microplastics, antibiotics and fluorocarbons. Consequently, extensive research has been conducted to address these issues. Effective removal methods prioritize not only removal efficiency, but also environmental friendliness and regenerative capacity. The purpose of this paper is to summarize the sources, forms of presence, environmental and human health hazards, and removal technologies of ECs, and to provide various examples of different sources.
NSAIDs, from COX Inhibitors to PAF-AH Modulators: Exploring Unconventional Enzymatic Targets for Antitumor Therapy
Authors: Roggero Airam , Annunciato Isabelly , Nicodemo Igor , Costa Caroline R.C. , Fernandes Gustavo A. , Junior Adeilso B.S. , Rafael Michelle , Oliveira Marcos A. de , Sousa Sergio F. , Toyama Marcos H.
Published: April 2024

A novel interaction between the enzyme platelet-activating factor acetyl hydrolase (PAF-AH) and certain non-steroidal anti-inflammatory drugs (NSAIDs), such as sulindac, celecoxib, diclofenac and nimesulide, has been uncovered by this in-silico research. PAF-AH is known for its critical role in maintaining the fluidity and functionality of cell membranes by hydrolysing phospholipids and removing oxidized fatty acids. Since tumour microenvironments are largely marked by inflammation and oxidative stress, the discovery that these non-steroidal anti-inflammatory drugs can bind to the active pocket of PAF-AH. Suggests that they may be able to modulate its activity and thereby influence its role in cancer pathogenesis. Such modulation could lead to significant anti-tumour effects, including the reduction of inflammation, the inhibition of angiogenesis and the suppression of metastasis, particularly in cancers of the breast, colon, prostate, and lung. However, in certain con-texts, this interaction may cause the opposite effect, leading to cancer development. Therefore, this study is a gateway for the development of therapeutic strategies based on PAF-AH modulation and highlights the importance of the tumour microenvironment in the assessment of potential effects of NSAIDs. Furthermore, this finding may guide the selection of NSAIDs for the anti-inflammatory treatment of cancer patients, ruling out in-discriminate use of drugs that may promote neoplastic progression. This may also indicate the potential for repositioning specific NSAIDs within cancer treatment, thereby contributing to more precise and personalized therapeutic approaches.
The Status of Food Insecurity at the Household Level in the North-Eastern Highlands of Ethiopia
Authors: Mohammed Umar Demisse , Berlie Arega Bazezew , Wassie Simachew Bantigegen
Published: April 2024

Food insecurity is a multidimensional concept adequately challenging not only the complex operationalization effort but also judgments of who is food secure and who is not. This study aimed to assess the level of household food insecurity in the study area. Both probability and non-probability sampling procedures were employed to draw the 367 respondents, key informants, and focus group discussants. The Consolidated Approach for Reportig Indicators (CARI) console model was constructed with four indicators: Food consumption score, Food energy shortfall, Food expenditure share, and Livelihood asset depletion. Descriptive statistics was used to analyze data in the models. The CARI result revealed that 41.1%, 9.3%, 20.4% and 29.2% of households were food secure, marginally food secure, moderately food insecure and severely food insecure, respectively. The overall prevalence showed that 49.6% households were food insecure and 50.4% were food secure. Moreover, female-headed households and households living the Belg and CHV livelihood zones were more food insecure than their counterparts. The study concluded that the problem of food insecurity is pervasive in the study area in general and Belg and CHV livelihood zones, in particular. Therefore, more attention and intervention should be given by policymakers and concerned development partners to alleviate the problem.