bluuebunny/crossref_metadata_2025 huggingface dataset:
Cosmic Theory of Structure (CTS): Addressing the Hierarchy Problem with Running Couplings
Authors: OZTURKLER Hazar Umutay , AI Synthoris , Eindorff The , AI Synthoris
Published: July 2024

The Cosmic Theory of Structure (CTS) model has undergone significant refinement to address the hierarchy problem by incorporating the concept of running couplings. This update provides a more robust framework for understanding the formation and evolution of cosmic structures, offering a natural explanation for mass scales due to quantum effects. We present new validations using gravitational wave data from events GW150914 and GW151226, neutrino oscillation data from IceCube, dark matter density data from the Planck survey, and quantum field interaction data. The enhanced model demonstrates improved alignment with observational data, reinforcing the CTS model's predictive power and its potential to unify gravity and quantum physics within a single theoretical framework.
Factors Associated With Sexual Initiation Amongst Adolescents 10–15 Years in Jamaica
Authors: Gordon-Strachan Georgiana , Fox Helen K , Harrison Abigail , Grant Andriene , McFarlane Shelly R
Published: July 2024

Jamaica has one of the highest teenage pregnancy rate and therefore identifying the context of adolescent sexual and reproductive health is important, especially since there is paucity of research on preadolescents in the Jamaican context. The study was a nationally representative cross-sectional, interviewer administered, school-based survey of 10 -15 year olds. Summary statistics of the demographics and bivariate analyses were performed to assess the association of sexual initiation and given risk and resiliency factors. 1,422(47.4%) males, 1,581 (52.6%) females, mean age (SD) 12.5 (1.6) years were surveyed. Mean age of first sex was 11.0 (±2.5) years. Factors significantly with sexual initiation were, female sex (OR 0.17; 95% CI 0.12-0.23), caring relationships inside the home (OR 0.85; 95%CI 0.83-0.97) rare church attendance (OR1.36; 95%CI1.0-1.8), age (OR 1.75; 95%CI1.6-1.9) and community disorganization (OR 1.02 95% CI 1.01-1.07). Sexual initiation of early adolescents is positively influenced by environmental factors such as family connectedness and religious involvement. The negative correlates are societal risk factors such as community disorganization. Empowerment through learned sexual negotiation skills, should be incorporated into the education programme of pre-adolescents to facilitate adolescents embracing their intrinsic power to delay sexual debut and if sexually active to insist on condom use.
Exploring the Efficacy of Chemical Antiscalant in Mitigating Silica Scaling: A Pilot Study in Geothermal Energy Production Sites in Indonesia
Authors: Sinaga Batara Vito Samuelson , Tobing Sheila
Published: July 2024

This research evaluates the technical and financial feasibility of using Inhibitor A for brine treatment in geothermal energy production, comparing it with traditional brine acidification. Conducted at a geothermal site in Central Java, Indonesia, the study uses Decision Tree Analysis and risk Expected Monetary Value (EMV) to assess both methods. Inhibitor A demonstrates a 70% reduction in scaling compared to untreated brine, with laboratory tests indicating a 10 ppm dosage as optimal for minimizing silica scaling. Despite higher initial costs, Decision Tree Analysis shows that Inhibitor A has a lower overall risk profile than acidification. EMV analysis confirms its cost-efficiency when considering potential risks and benefits. This research advocates for the adoption of Inhibitor A, highlighting its long-term benefits and sustainability over traditional methods. The findings emphasize the importance of innovative solutions in enhancing geothermal energy systems’ efficiency and sustainability. By integrating technical performance with financial analysis, this study provides a comprehensive evaluation to inform decision-making in the geothermal sector, promoting more effective and sustainable brine treatment practices.
Fabrication of Graphene Oxide and Conductive Polymer on Cotton Fabric with Ultrasonic (US) Assisted Dyeing for Washable E-Textiles
Authors: Khoso Nazakat Ali , Sheikh Arsalan Ahmed , Memon Sanam Irum , Qureshi Raja Fahad , Abbasi Abdul Malik Rehan , Qutaba Syed , Wang JiaJun
Published: July 2024

The graphene based highly conductive and flexible devices has received momentous attraction and growth in recent years for potential multifunctional uses. The development of flexible and washable textile sensors, actuators, energy storage and energy harvesting systems. Textile fabrics coated with graphene and conductive polymers have been used for wearable self-powered e-textiles, such as tribo-electric, piezoelectric, and Thermoelectric. Herein this research, 100% woven cotton fabric is Fictionalized with graphene oxide (GO) using industrial-scale cold pad batch dyeing technique for the development of low-grade body heat into self-powered wearable e-textiles. The conductive polymer PEDOT: PSS was coated using layer by layer approach. The study demonstrates that the resultant textile electrodes showed reduced electrical sheet resistance from 2.5 MΩ to 15KΩ, with a reduced graphene oxide and further reduced to (2.5 -12.5 Ω) for conductive polymer. The sheet resistance was decreased with the number of dyeing cycles (10-15) and increased with 20 washing cycles vice versa. The study demonstrates that the sensor response and performance were improved with increasing the content percent of rGO and PEDOT: PSS. The tensile strength of as coated fabric electrodes was improved from (25.0-85.5 mPa) and fabric thickness was increased to (26-38µm) without compromising or influencing the air permeability. The resultant textile electrodes may potentially be used in smart textiles for self-powered flexible wearable generators, sensors, and energy storage. The study demonstrates that the cold pad batch dyeing method is a suitable and effective method for the fabrication of graphene-based textiles.
Variability in Heating Demand Predictions: A Comparative Study of PHPP and Mc001-2022 in Existing Residential Buildings
Authors: Maxineasa Sebastian George , Isopescu Dorina Nicolina , Vizitiu-Baciu Ioana-Roxana , Cojocaru Alexandra , Moga Ligia Mihaela
Published: July 2024

The construction industry is a key driver of environmental change due to its extensive ‎use of resources and high levels of emissions, thus placing a significant burden on global ‎efforts towards sustainable development targets. A large portion of the environmental ‎footprint of buildings results from the energy required to sustain indoor comfort levels. ‎Therefore, enhancing the energy efficiency of existing buildings becomes critical in ‎reducing their environmental impact. This study examines the influence of increasing ‎thermal performance with the aim of reducing heating ‎demand. Thus, numerical modelling tools and different energy performance assessment meth-odologies have been used. ‎Specifically, it evaluates two existing residential buildings in Romania and compares ‎heating demand predictions using PHPP and Mc001-2022 methodologies across various ‎climatic data sets and case studies. The results reveal significant variability in heating ‎demand predictions, emphasizing the importance of methodological choice and climatic ‎data. The ‎study highlights that both PHPP and Mc001-2022 methodologies yield varying results ‎depending on the specific conditions and characteristics of each building. This variation in results underscores ‎the necessity for a nuanced and context-specific approach to energy performance ‎assessment, in-corporating multiple energy efficiency measures tailored to the unique ‎features of each building.
An “Auction of Souls”: War, Magical Parasitism, and Re-enchanted Spirits in Siberia
Authors: Zorbas Konstantinos
Published: July 2024

Alleged practices of magical assault and vampirism are a recurrent feature of popular explanations of misfortune in Tuva Republic, South Siberia. Based on a field study of healing practices in an “Association of Shamans”, this article analyses rituals of countercursing one’s antagonists in a context of Russian political domination. A central purpose of this discussion is to foreground the centrality of kinds of parasitical worship and occult threat to structures of political power in – and beyond – the region of Tuva. Focusing on a “curse-scape”, which develops from the combative practices of shamans, occult specialists and office-holders, the article probes a repertoire of healing symbols in a shaman’s courtroom. It is argued that shamanic healing draws its efficacy from appropriating hunting symbols and animal spirits, which appear in Indigenous Siberian cosmologies. The analysis shows that ideas of playing with risk during countercursing rituals structure the process of symbolic resolution. The article concludes by highlighting indigenous perceptions of a “cursed” landscape as a field where the agencies of “darkness” (and their political sponsors) are confronted with an emancipating, Buddhist religious mindset.
Through a Non-uniform Channel; Analysis of a Bifurcation and Stability of Equilibrium Points for Jeffrey Fluid Flow
Authors: Thoubaan Mary G. , Al-Khafajy Dheia G. Salih , Wanas Abbas Kareem , Breaz Daniel , Cotîrlă Luminiţa-Ioana
Published: July 2024

This paper aims to study and analyze the effect of the flow rate and amplitude of walling waves on the peristaltic flow of Jeffrey’s fluid through an irregular channel. In addition, it analyses streamlined patterns and their local and global bifurcation flow. The theory of dynamical systems is used to explore the position of critical points and their bifurcation. Numerical and analytical methods are presented to display effective changes in amplitude and rate of the flow on the transport of fluid. Three types of streamline patterns occur backward, trapping and augmented flow in the channel through movement due to changes in the value rate parameters.
Synthesis of Carbon Quantum Dots for Excellent Energy Density in Supercapacitors: A Comprehensive Review
Authors: Nisha Km , Sharma Ujala , Singh Aprana , Maurya Kajal Kumara , Kumari Sonam , Kumari Soni , Khan Kahkashan , Shukla Hemant Kumar
Published: July 2024

Carbon Quantum Dots (CQDs) have emerged as promising nanomaterials for enhancing the performance of supercapacitors, offering unique advantages such as high surface area, excellent electrical conductivity, and tunable surface chemistry. This review provides a comprehensive overview of recent advancements in the synthesis, characterization, and integration of CQDs into supercapacitor devices. Various synthesis methods, including chemical oxidation, hydrothermal/solvothermal methods, microwave-assisted synthesis, and pyrolysis, are discussed, highlighting their impact on the structural and electrochemical properties of CQDs. Characterization techniques such as transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman spectroscopy, and photoluminescence (PL) spectroscopy are elucidated for assessing the morphology, crystallinity, and optical properties of CQDs. The integration of CQDs into supercapacitors, including their utilization in composite electrodes, binder-free electrodes, and doping strategies, is explored to enhance specific capacitance, energy density, power density, and cycle stability of the devices. Challenges and future perspectives in the field are outlined, emphasizing the need for scalable synthesis methods, enhanced electrochemical performance, and sustainable device engineering to realize the full potential of CQD-based supercapacitors for various energy storage applications. This review aims to provide insights into the current state of research and guide future endeavors towards developing high-performance and environmentally sustainable energy storage technologies.
Research on Optimizing Low-Saturation Intersection Signals with Consideration for Both Efficiency and Fairness
Authors: Zhu Lingxiang , Yu Lujing , Zou Liang
Published: July 2024

In response to the fairness issue arising from the unequal delay of vehicles in different phases at intersections, considering the actual situation of small and variable delays for vehicles in low-saturation intersection phases, this paper proposes the concept of "sacrificing efficiency for fairness." Firstly, the universality of unfair delay phenomena at intersection phases is explained, especially at low-saturation intersections where the fluctuation in phase delays is 1.87 times higher than at other intersections. Then, a fairness evaluation index is constructed using information entropy, and the feasibility of the proposed approach is demonstrated. Subsequently, a signal optimization model that balances efficiency and fairness is proposed. Finally, the proposed model is validated through case studies, showing that it not only simultaneously considers efficiency and fairness but also has minimal impact on efficiency. Moreover, the changes to timing schemes in the efficiency model are much smaller compared to the model that only considers fairness. Sensitivity analysis reveals that the model performs better under low-saturation intersection conditions.
Machine Learning Meets Meta-heuristics: Bald Eagle Search Optimization and Red Deer Optimization for Feature Selection in Type II Diabetes Diagnosis
Authors: Rajaguru Harikumar , Chellappan Dinesh
Published: July 2024

This article investigates the effectiveness of feature extraction and selection techniques for enhancing the performance of classifiers accuracy in Type II Diabetes Mellitus (DM) detection using microarray gene data. To address the inherent high dimensionality of the data by employing three Feature Extraction (FE) methods are used namely, Short-Time Fourier Transform (STFT), Ridge Regression (RR), and Pearson Correlation Coefficient (PCC). To further refine the data, meta-heuristic algorithms like Bald Eagle Search Optimization (BESO) and Red Deer Optimization (RDO) are utilized for feature selection. The performance of seven classification techniques such as Non-Linear Regression - NLR, Linear Regression - LR, Gaussian Mixture Model - GMM, Expectation Maximization - EM, Logistic Regression - LoR, Softmax Discriminant Classifier - SDC, and Support Vector Machine with Radial Basis Function kernel - SVM-RBF are evaluated with and without feature selection. The analysis reveals that the combination of PCC with SVM-RBF achieved a promising accuracy of 92.85% even without feature selection. Notably, employing BESO with PCC and SVM-RBF maintained this high accuracy. However, the highest overall accuracy of 97.14% was achieved when RDO was used for feature selection alongside PCC and SVM-RBF. These findings highlight the potential of feature extraction and selection techniques, particularly RDO with PCC, in improving the accuracy of DM detection using microarray gene data.
Improving Shale Stability through the Utilization of Graphene Nanopowder and Modified Polymer Based Silica Nanocomposite in Water-Based Drilling Fluids
Authors: Ospanov Yerlan Kanatovich , Kudaikulova Gulzhan Abdullaevna
Published: July 2024

Shale formations present significant challenges to traditional drilling fluids due to fluid infiltration, cuttings dispersion, and shale swelling, which can destabilize the wellbore. While oil-based drilling fluids (OBM) effectively address these problems concerns about their environmental impact and cost limit their widespread use. Recently, nanomaterials (NPs) have emerged as a promising approach in drilling fluid technology, offering an innovative solution to improve the efficiency of water-based drilling fluids (WBDF) in shale operations. This study evaluates the potential of utilizing modified silica nanocomposite and graphene nanopowder to formulate a nanoparticle-enhanced water-based drilling fluid (NP-WBDF). The main objective is to investigate the impact of these nanoparticle additives on the flow characteristics, filtration efficiency, and inhibition properties of the NP-WBDF. In this research, a silica nanocomposite was successfully synthesized using emulsion polymerization and analyzed using FTIR, PSD, and TEM techniques. Results showed that the silica nanocomposite exhibited a unimodal particle size distribution ranging from 38 nm to 164 nm, with an average particle size of approximately 72 nm. Shale samples before and after interaction with Graphene nanopowder-WBDF and NFC-WBDF were analyzed using scanning electron microscopy (SEM). The NP-WBM underwent evaluation through API filtration tests (LTLP), high-temperature/high-pressure (HTHP) filtration tests, and rheological measurements conducted with a conventional viscometer. Experimental results showed that silica nanocomposite and graphene nanopowder effectively bridged and sealed shale pore throats, demonstrating superior inhibition performance compared to conventional WBDF. Post adsorption, the shale surface exhibited increased hydrophobicity, contributing to enhanced stability. Overall, silica nanocomposite and graphene nanopowder positively impacted rheological performance and provided favorable filtration control in water-based drilling fluids.
Towards Non-destructive Quality Testing of Complex Biomedical Devices – a Generalized Closed Loop System Approach Utilizing Real-Time in Line Process Analytical Technology
Authors: Guha Bikash , Moore Sean , Huyghe Jacques
Published: July 2024

This study addresses the critical issue of cardiovascular diseases (CVD) as the leading cause of death globally, emphasizing the importance of stent delivery catheter manufacturing. Traditional manufacturing processes, reliant on destructive end-of-batch sampling, present significant financial and quality challenges. The research highlights the need for non-destructive Process Analytical Technologies (PAT) to meet the increasing demand for these life-saving devices. The study employs a mixed-method approach, combining qualitative literature review and quantitative artefact development, to propose a closed-loop Cyber Physical Production System (CPPS). The proposed system aims to enhance real-time quality control, minimize costs, and improve manufacturing efficiency. Initial results demonstrate the system's effectiveness in reducing cycle times, improving stability, and significantly decreasing production misses. The findings suggest substantial financial savings and quality improvements, underscoring the potential of advanced control strategies in regulated medical device manufacturing. This study proposes a generalized CPPS framework to be applicable across diverse regulated manufacturing environments, ensuring optimal processing conditions and adherence to regulatory standards. The research concludes with the successful demonstration of innovative approaches and technologies, leading to improved product quality, patient safety, and operational efficiency in the medical device industry.
Experimental Study on the Suitability of Waste Plastics and Glass as Partial Replacement of Fine Aggregate in Concrete Production
Authors: Legese Alemu Mosisa , Mitiku Degefe , Feyessa Fekadu Fufa , Urgessa Girum , Boru Yada Tesfaye
Published: July 2024

Solid waste management is a major environmental challenge, especially in developing countries, with increasing amounts of waste glass (WG) and waste plastics (WP) not being recycled. In Ethiopia, managing WG and WP requires innovative recycling techniques. This study examines concrete properties with WG and WP as partial replacements for fine aggregate. Tests were conducted on cement setting time, workability, compressive strength, splitting tensile strength, and flexural strength. Concrete grade C-25, with a compressive strength of 25 MPa, was prepared using an optimum ratio of 14% WG and 6% WP. Mechanical properties were tested at 7 and 28 days of curing. At 20% replacement, workability decreased at water-cement ratios of 0.5 and 0.6 but remained stable at 0.4. Thus, a 0.4 ratio was used. For 10% replacement, compressive strength increased by 12.55% and 6.44% on the 7th and 28th days, respectively. At 20% replacement, compressive strength decreased by 14.35% and 0.73% on the 7th and 28th days, respectively. On the 28th day, splitting tensile strength at optimum replacement was 4.3 MPa, an 8.5% reduction from the control mix. However, flexural strength increased by 19.7%, from 12.46 MPa to 15.52 MPa. Overall, WG and WP improved flexural strength but slightly reduced splitting tensile strength.
Comparative Analysis Of The Responses Of Various Bromodomain Inhibitors In Cancer Cell Lines Utilizing Various Machine Learning Models
Authors: Tutkun Gizem , Cakir Muharrem Okan , Bilge Ugur
Published: July 2024

The focus was on developing machine learning models to predict the IC50 values of the compound OTX015 using gene expression levels of cancer cell lines. Through regression-based machine learning models, particularly the SVM model, trained on pre-laboratory data, consistent and generalizable performance with low error scores was achieved. These models underwent enhancement via hyperparameter optimization and were tested on validation data. The results indicate the utility of machine learning in drug discovery processes and personalized medicine, offering rapid and cost-effective predictions of IC50 values. However, for enhanced reliability, further model development, data gathering, and evaluation with diverse compounds are recommended. In conclusion, this research demonstrates the potential of machine learning approaches to optimize experimental processes, reduce costs, and contribute to personalized treatments in healthcare by accurately predicting compound responses.
Bridging the Gap: Expanding Telehealth Services to Address Rural Health Disparities
Authors: Uddin Jalal , Fariha Tazveen
Published: July 2024

Introduction: Rural Americans face significant health disparities due to limited access to healthcare services. Telehealth has emerged as a promising solution to mitigate these disparities by facilitating remote access to medical care. This paper comprehensively reviews the advantages, challenges, and implementation strategies of telehealth in rural areas.Method: A narrative review methodology was employed to synthesize existing literature and case studies on telehealth in rural settings. Databases such as PubMed, Google Scholar, and JSTOR were searched for relevant studies published in the last three decades. Keywords such as "telehealth," "rural health," and "healthcare disparities" guided the search process. The review focused on studies assessing the impact of telehealth on healthcare access, cost-effectiveness, and quality of care in rural areas.Results: The review findings indicate that telehealth significantly enhances healthcare access by reducing travel distances, increasing availability of specialist consultations, and promoting patient engagement. It improves chronic disease management and patient satisfaction by enabling convenient access to healthcare services at home. Despite initial setup costs and challenges such as broadband access and regulatory issues, telehealth demonstrates long-term cost savings through reduced travel expenses and improved healthcare efficiency. Quality of care is enhanced through improved communication between healthcare providers and patients, leading to better treatment adherence and health outcomes.Conclusion: Telehealth represents a transformative approach to address healthcare disparities in rural areas. It offers a cost-effective solution to improve access to healthcare services, enhance patient outcomes, and reduce healthcare costs in the long run. However, successful implementation requires addressing infrastructure challenges, refining reimbursement policies, and ensuring regulatory support. Future efforts should focus on expanding broadband infrastructure, refining policy frameworks, and conducting further research to optimize telehealth's impact on rural healthcare delivery.
LLE-Fuse: Lightweight Infrared and Visible Light Image Fusion Based on Low-Light Image Enhancement
Authors: Qian Song , Yang Liwei , Xue Yan , Tian Jiya , Yiming Guzailinuer , Yang Junfei
Published: July 2024

Infrared and visible light image fusion technology integrates image feature information from two different modalities to generate an image that integrates complementary information from the source images. However, in low-light scenarios, the degradation of lighting in visible light images leads to existing fusion methods being unable to effectively extract texture detail information from the scene. At this time, the target prominence information provided by infrared images alone is far from sufficient. To address this challenge, this paper proposes a lightweight infrared and visible light image fusion method based on low-light enhancement, named LLE-Fuse. Firstly, the method improves the MobileOne Block by embedding the Sobel operator in the Edge-MobileOne Block to perform feature extraction and downsampling on the source images. Then, intermediate features of different scales are obtained and fused through a cross-modal attention fusion module, followed by image reconstruction using a decoder with upsampling. Next, the CLAHE algorithm is used for image enhancement of infrared and visible light images, and the enhanced loss guides the network model to learn the capability of low-light enhancement. Finally, upon completion of the network training, the method optimizes the Edge-MobileOne Block into the direct connection structure of MobileNetV1 through structural re-parameterization, effectively reducing the computational resource consumption of the model network. Through extensive experimental comparisons, this paper's method demonstrates excellent performance in both visual appeal and evaluation metrics, providing satisfactory fusion results even in low-light scenarios.
Biogas and Organic manure production from anerobic digestion of Rubber Plant Effluent, Gliricidia leaves and Inoculum: Energy Sustainability and Socio-Economic Development of Mauritania
Authors: Sidi Habib Sidahmed , Torii Shuichi , S Kavitha Mol , Jayarajan Aravind
Published: July 2024

This study analyzed the anaerobic co-digestion of Inoculum (I), Rubber Plant Effluent (RPE) and Gliricidia leaves (GLS) at different mixing ratios for the simultaneous production of methane and organic fertilizer. The results were analyzed for volatile fatty acids, pH, C/N ratio, and methane production. The organic quality of the substrate mixture before and after anaerobic digestion was analyzed for organic carbon, Kjeldahl nitrogen, potassium, and phosphorus content. The study concluded that the inoculum, Rubber Plant Effluent (RPE), and Gliricidia leaves (GLS) mixed in the ratio of 10:2:2 showed higher methane production than other experiments conducted at different mixing ratios. The nitrogen, Potassium and phosphorus content of the substrates are increased after anaerobic digestion. However, the organic carbon content in the substrate decreased in all experiments. This research recommends the planting of rubber trees and Gliricidia maculata to promote economic development in Mauritania.

Keywords: Biogas production; Gliricidia leaves; Methane; Rubber Plant Effluent; Organic Manure
Investigation into process parameter optimization of selective laser melting for producing AlSi12 parts using ANOVA
Authors: Kekana Neo , Shongwe Mxolisi Brandon , Mpofu Khumbulani , Muvunzi Rumbidzai
Published: July 2024

In this study, AlSi12 alloy was fabricated using the selective laser melting (SLM) technique to produce high density components with complex and customized parts for railway applications. Nonetheless, the production of dense samples necessitates the optimization of production process parameters. As a statistical design of experimental technique, the response surface methodology was used to optimise different combination of SLM parameters. The results were analysed using analyse of variance (ANOVA) and the signal-to-noise(S/N) ratios. The relationship between the hardness response to the process parameters (scanning speed and lase power) for determining the optimal processing conditions were examined. A hardness value of 133 HV was obtained. The process parameters were successfully optimized and the relationship between the parameters and the structures of the fabricated samples were reported.
Research on High-Speed Train bearing Fault Diagnosis Method based on Domain Adversarial Transfer Learning
Authors: Zou Yingyong , Zhao Wenzhuo , Liu Tao , Zhang Xingkui , Shi Yaochen
Published: July 2024

Keywords: domain adversarial; channel reconstruction; transfer learning; fault diagnosis
Advancement in Solar Technology: Evolution, Generation, Future Prospective, and Challenges - A Review
Authors: Verma Vinay
Published: July 2024

The field of solar technology has experienced remarkable advancements, transforming from early photovoltaic discoveries to a diverse array of high-efficiency, cost-effective solutions. This review explores the evolution of solar technology, detailing its development from the initial discovery of the photovoltaic effect to contemporary innovations. The current generation of solar technologies, including silicon photovoltaic cells, thin-film solar cells, perovskite solar cells, bifacial panels, concentrated solar power, and building-integrated photovoltaics, is examined for their efficiencies, applications, and contributions to the renewable energy landscape. Future prospects highlight promising trends such as next-generation photovoltaics, advanced energy storage solutions, agrivoltaics, floating solar farms, and artificial photosynthesis. Despite the progress, challenges related to efficiency, stability, scalability, cost, grid integration, environmental impact, policy support, and public acceptance remain. Addressing these challenges through continued research, supportive policies, and collaborative efforts is crucial for realizing the full potential of solar technology. This review underscores the importance of solar energy in achieving a sustainable future and emphasizes the need for ongoing innovation and commitment to overcome existing barriers.
Geopolitical and Ethnocultural Integration of the Ferghana Valley
Authors: Bekmirzaev Rakhmonali
Published: July 2024

The Fergana Valley, a strategically significant and culturally rich region in Central Asia, exemplifies the complex interplay of modern international relations amidst geopolitical and ethno-cultural integration. This paper explores the fundamental principles guiding international interactions in the valley, considering the historical context, current geopolitical dynamics, and the unique cultural mosaic of its population.
Key themes include the impact of regional power shifts, the role of transnational organizations, and the influence of ethno-cultural identities on diplomatic engagements. By analyzing case studies of cooperation and conflict, the paper highlights how integration efforts shape political stability, economic development, and social cohesion in the Fergana Valley.
This study aims to provide a nuanced understanding of the region's international relations framework, offering insights into effective strategies for fostering harmonious and sustainable integration in a geopolitically sensitive and culturally diverse landscape.
Exploring the Impact of Celebrity Endorsements and Social Media Platforms on Sustainable Consumer Behavior in Nigerian Tourism
Authors: Onyeama Anthony Echezona , Kayaman Ruchan
Published: July 2024

The current study explores the impact of celebrity endorsements and social media platforms on promoting sustainable consumer behavior in Nigerian tourism industry. The study employs Mentionlytics software to analyze online documents and examine how political celebrities and social media platforms (Twitter and Facebook) influence consumer behavior and decision-making processes within the tourism industry. The findings in phase 1 suggest that celebrity endorsements and social media platforms have a positive impact on sustainable consumer behavior. The results in phase 2 suggest that political celebrities engage followers on Facebook based on the 70% share. However, no engagement was found on Twitter based on the zero percent (0%) share, suggesting that Facebook enables political celebrities to promote sustainable tourism. The study contributes to the literature on sustainability and celebrity endorsements, offering insights for destination marketers and policymakers in the Nigerian tourism industry.
Teaching Innovation and Teaching–Learning Methods Integrated into Education for Sustainable Tourism Development in a Bach-Elor of Tourism Program
Authors: Pelegrín-Entenza Norberto , Naranjo-LLupart María Rosa , Ruiz-Cedeño Sebastiana del Monserrate , VÁZQUEZ-PÉREZ ANTONIO
Published: July 2024

Sustainable development has become the aspiration of many developing countries, including Ecuador. The introduction of Bachelor of Tourism studies at the Technical University of Manabí aligns with this interest, implying a challenge for teachers regarding the application of integrative and innovative teaching methods that promote the training of professionals with high scientific rigor, both in technical and professional senses. To achieve this, the pedagogical group started from three fundamental principles based on the application of teaching work methods and pro-cedures, as well as the determination of interactions between the various factors that directly and indirectly influence the training process of professionals in the tourism sector. The results of comprehensive evaluation processes considering both the academic performance of the teachers and the level of satisfaction of students taking the course support the application of these teaching–learning methods, as well as highlighting the convenience of extending the experiences and re-search results of the pedagogical team to other vocational training centers for tourism activities.
A Flexible Wearable Strain Sensor Based on Nano-Silver Modified Laser-Induced Graphene for Monitoring Hand MovementsCitation: To Be Added by Editorial Staff during Production
Authors: Zhong Mian , Zou Yao , Fan Hongyun , Li Shichen , Zhao Yilin , Li Bin , Li Bo , Jiang Yong , Xing Xiaoqing , Shen Jiaqing , Zhou Chao
Published: July 2024

The advancement of performance in the domain of flexible wearable strain sensors has become increasingly significant due to extensive research on laser-induced graphene (LIG). An innovative doping modification technique is required owing to the limited progress achieved by adjusting laser parameters to enhance LIG’s performance. By pre-treating with AgNO3, we successfully manufactured LIG with a uniform dispersion of silver nanoparticles across its surface. The experimental results for the flexible strain sensor exhibit exceptional characteristics, including low resistance (183.4 Ω), high sensitivity (426.8), a response time of approximately 150 ms, and a relaxation time of about 200 ms. Moreover, this sensor demonstrates excellent stability under various tensile strains and remarkable repeatability during cyclic tests lasting up to 8,000 s. Additionally, this technique yields favorable results in finger bending and hand back stretching experiments, holding significant reference value for preserving the inherent characteristics of LIG preparation in a single-step and in situ manner.
Implementing Large Language Model API For Interview Training Based On Job Description
Authors: Uriawan Wisnu , Widodo Raden Ibnu Huygenz , Ramadita Ray , Herdiyanto Reza Fahlevi , Marsaputra Rifqi Syekhi , Nurrobianti Silvia
Published: July 2024

Good communication skills are essential for prospective workers, particularly college students, to clearly convey their abilities and understanding during job interviews. Despite the high demand for strong communication skills among employers, many students struggle with inadequate experience and skills, leading to reduced confidence and lower chances of securing desired jobs. Existing tools and resources for improving communication skills are limited, especially free ones, leaving students underprepared and less confident in interviews. To address this issue, a comprehensive solution is needed that provides free, customizable tools to enhance students' interview communication skills. Invisor is a web-based self-interview training application that leverages AI and Machine Learning to analyze users' behavior, responses, and facial expressions during simulated interviews. Accessible via desktop, laptop, or mobile devices, Invisor offers interactive and voice-recorded feedback to help students prepare for interviews effectively. By employing AI technologies, Invisor generates personalized interview questions based on job descriptions, enhancing the realism of the interview experience and providing tailored feedback to improve users' responses. Developed using agile methodologies, Invisor has undergone iterative enhancements, integrating user and stakeholder feedback promptly to improve usability and functionality. The combination of AI-driven simulations and agile development practices enables Invisor to meet current user needs and anticipate future demands, providing a robust tool for interview preparation in a competitive job market. This paper outlines the development and implementation of Invisor, demonstrating its effectiveness in enhancing interview skills and confidence among students and job seekers.
An Inquiry into the Application of Biophilic Design Principles in Contemporary University Designs
Authors: Yasar Dilek , Öktem Erkartal Pınar
Published: July 2024

Human beings are positively or negatively affected by their environment. This effect has been a topic of interest by environmental psychologists, who have strived over years for understanding the environmental characteristics, which would be good for people in physical, mental, and psychological terms. The present study is about biophilic design, one of the popular theories in the architectural literature aimed to create high quality and liveable environments. The positive effects of biophilic design have been investigated from different perspectives and thus it has become a well-accepted approach in the relevant architectural literature. Accordingly, the present study aimed to investigate to what extent biophilic design principles were put into practice. In the context thereof, contemporary university structures were analysed within the framework of biophilic design principles. The results were suggestive of the fact that although biophilic elements were encountered in the design of these structures, they were not meant to be biophilic, nevertheless, there was an approach based on human-nature interaction. Accordingly, the principles of biophilic design were equivalent to the required parameters of a good design and that architects considered nature as an important design input.
On the Use of Complex Systems Engineering for the Development of Industry 4.0 Technologies: Case for Robotic Systems
Authors: Restrepo-Carmona Jaime Alonso , Taborda Elkin A. , Paniagua-García Esteban , Escobar Carlos A. , Sierra-Pérez Julián , Vásquez Rafael E.
Published: July 2024

This paper presents a novel integration of Systems Engineering (SE) methodologies and Industry 4.0 (I4.0) technologies in the design of robotic systems, with a focus on enhancing underwater robotic missions. Using the conceptual design of an underwater exploration vehicle as a case study, we demonstrate how SE can systematically incorporate I4.0 tools to improve mission performance and meet stakeholder expectations. The study begins with an overview of the SE approach, emphasizing the conceptual design stage, aligning with the application and case study of design theories. We then explore various I4.0 technologies, highlighting their functional benefits rather than technical specifics, addressing design methods for Industry 4.0. Remotely Operated Vehicles (ROVs) are examined in terms of classification, components, and tasks, showcasing their evolution driven by technological advancements, thus tackling the complexity and design of complex systems. The core of our study involves defining stakeholder expectations, using quality function deployment for requirements definition, and performing a functional and logical decomposition of the ROV system. Our approach underscores the importance of understanding and integrating new technologies functionally, aligning with the transition towards Industry/Society 5.0. This work not only illustrates the synergy between SE and I4.0 but also offers a structured methodology for advancing the design and functionality of complex systems, setting a blueprint for future developments in this field.
Authenticate and Verification Source Files using SHA256 and HMAC Algorithms
Authors: Uriawan Wisnu , Ramadita Ray , Putra Rizky Dwi , Siregar Rizqi Ilham , Addiva Risyad
Published: July 2024

Because data authenticity and validity are becoming more and more of a concern in the digital age file security and integrity must be guaranteed. This paper investigates the application of HMAC-SHA256 which combines the Secure Hash Algorithm 256 (SHA256) with a private key for transmission-side source file authentication and verification. The study creates a prototype application to evaluate the efficacy of HMAC-SHA256 in securing file transfers by examining previous investigations on SHA and HMAC. The findings demonstrate that SHA256 produces unique file signatures which successfully guards against unwanted changes. Through the use of cryptographic hashes and secret keys to create distinct digital signatures that guarantee file authenticity HMAC improves security. The study shows that HMAC-SHA256 protects data integrity and detects tampering effectively. It does however stress how crucial it is to comprehend cryptographic concepts and apply these strategies with caution in order to prevent vulnerabilities. Overall the study finds that when properly implemented and updated HMAC-SHA256 greatly enhances file security in the digital age.
Speaking Skills: A Panacea for College Students in the Classroom and in the Workplace
Authors: Perse Russel Jean Paris
Published: July 2024

For college students, speaking skills are a priceless commodity that can solve a wide range of social, professional, and academic problems. Proficiency in oral communication allows students to express themselves coherently and convincingly in academic and workplace contexts, which improves their involvement in group projects, presentations, and class debates. This paper determines to collect literature to prove that speaking skills can be a panacea for college students in the classroom and the workplace. Having speaking skills is, in fact, a college student's greatest asset, providing a plethora of advantages that go beyond scholastic achievement to encompass personal and professional growth. These abilities should be prioritized in colleges and institutions, with thorough curricula incorporating technological integration, practice opportunities, and public speaking courses. More investigation is required to look into creative approaches to improving speaking abilities and helping students get past obstacles. In essence, emerging strong speaking skills prepare college students with a multipurpose device that improves various aspects of their lives, making it a true panacea.
Mechanical Properties Predictive Model of Additive Manufacturing Specimens using ANFIS
Authors: Sagias Vasileios D. , Zacharia Paraskevi , Tempeloudis Athanasios , Stergiou Constantinos
Published: July 2024

Due to the manufacturing process of Additive Manufacturing (AM) Parts the mechanical properties cannot be predicted. The scope of the present work is to propose a predictive tool for the mechanical properties of AM parts through the use of Adaptive Neuro-Fuzzy Inference System (ANFIS). The Adaptive Neuro-Fuzzy Inference System (ANFIS) combines neural networks with fuzzy logic to generate a mapping between the inputs and the output. Real data experiments from different AM technologies and materials compose the initial dataset so a detailed investigation is conducted to gain knowledge of how different parameters affect the UTS, the elongation and the Young modulus of each experiment. Experimental data were also use to train, check and verify the methodology. The method is tested for FFF technology, PLA material and 3 point bending stress, with interesting results.
Utilizing High-Resolution Imaging and Artificial Intelligence for Accurate Leaf Wetness Detection for the Strawberry Advisory System (SAS)
Authors: Kondaparthi Akash Kumar , Lee Won Suk , Peres Natalia A.
Published: July 2024

In strawberry cultivation, precise disease management is crucial for maximizing yields and reducing unnecessary fungicide use. Traditional methods for measuring Leaf Wetness Duration (LWD), a critical factor in assessing the risk of fungal diseases such as botrytis fruit rot and anthracnose, have been reliant on sensors with known limitations in accuracy and reliability and difficulties with calibrating. To overcome these limitations, this study introduced an innovative algorithm for leaf wetness detection systems employing high-resolution imaging and deep learning technologies, including convolutional neural networks (CNNs). Implemented at the University of Florida's Plant Science Research and Education Unit (PSREU) in Citra, Florida, USA and expanded to three additional locations across Florida, USA, the system captured and analyzed images of a reference plate to accurately determine the wetness and, consequently, the LWD. The comparison of system outputs with manual observations across diverse environmental conditions demonstrated the enhanced accuracy and reliability of the artificial intelligence-driven approach. By integrating this system into the Strawberry Advisory System (SAS), this study provided an efficient solution to improve disease risk assessment and fungicide application strategies, promising significant economic benefits and sustainability advances in strawberry production.
Effect of Al or Cu Content on Microstructure and Mechanical Properties of Zn alloys Fabricated Using Continuous Casting and Extrusion
Authors: Sun Shineng , Yu Jie , Wang Chao
Published: July 2024

The effect of Al or Cu content on the microstructure and mechanical properties of continuous casting and extrusion Zn alloys has been studied by room temperature tensile test, X-ray diffraction, and scanning electron microscope. With the increase of Al content, the microstructure of continuous casting and extrusion Zn alloys slightly coarsens and the lamellar eutectic structure increases. The changes in the above structural factors result in a slight decrease in strength and a significant increase in elongation of Zn-Al alloys. The strength of Zn alloys increases as the Cu content increases, due to the increased content and size of the second phase in the Zn alloys. This means that the mechanical properties of Zn alloys can be adjusted by continuous casting and extrusion process, and the improvement of equipment capacity can improve the structure and morphology of the alloys.