bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating the Impact of Green Supply Chain Practices on Sustainable Development in Bangladesh
Authors: Emon Md Mehedi Hasan
Published: July 2024

This research aims to explore the adoption and impact of green supply chain practices (GSCP) on sustainable development in Bangladesh. The study seeks to understand the current state of GSCP adoption across various industries, identify key drivers and barriers, assess the perceived benefits and challenges, and evaluate the overall impact on environmental sustainability, economic performance, and social well-being. The research employs a qualitative approach, utilizing interviews with key stakeholders, document analysis, and literature review to gather data and insights. Interviews were conducted with representatives from government agencies, businesses, civil society organizations, and academia to obtain diverse perspectives on GSCP adoption and its implications for sustainable development in Bangladesh. The findings reveal a mixed scenario of GSCP adoption across different industries in Bangladesh, with sectors such as textiles leading the way. Key drivers of GSCP adoption include regulatory pressures, market forces, corporate social responsibility initiatives, and financial incentives. However, organizations face significant barriers such as high upfront costs, lack of awareness and expertise, regulatory uncertainty, and supply chain complexity. Despite these challenges, GSCP offer various benefits, including environmental sustainability, economic performance, and social well-being. Successful initiatives demonstrate tangible impacts, highlighting the potential of GSCP to contribute to sustainable development. The research is limited by its qualitative nature and focus on selected industries and stakeholders. Future studies could employ quantitative methods and broader sampling to provide a more comprehensive understanding of GSCP adoption and its implications in Bangladesh. The findings provide actionable insights for policymakers, industry leaders, and other stakeholders to promote GSCP adoption and enhance sustainable development in Bangladesh. Strategies for overcoming barriers and maximizing benefits are outlined, emphasizing the importance of collaboration and capacity-building initiatives. GSCP adoption can have positive social implications by promoting ethical labor practices, improving working conditions, and fostering community engagement. By prioritizing sustainability, businesses can contribute to social well-being and inclusive growth. This research contributes to the literature on GSCP adoption and sustainable development in Bangladesh by providing empirical insights and practical recommendations. The study adds to the understanding of the drivers, barriers, benefits, and challenges associated with GSCP adoption, highlighting the importance of integrating environmental, economic, and social considerations in supply chain management.
Promoting Human-Elephant Coexistence through Integration of AI, Real-Time Alerts, and Rapid Response
Authors: Rastogi Sankarshan , Bhattacharya Sumana , Vimal Kumar , Yadav Piyush , Singh Negi Himmat , Dinerstein Eric , Shah Wajid Ali , Nagano Yushi , Hirari Sasaki , Gulick Steve , Lee Andy T.L.
Published: July 2024

Human-elephant conflict poses serious conservation challenge in Asia and Africa. We deployed an AI-based camera-alert system in a conflict hotspot in West Bengal, India that accurately detected elephants near villages (266 events) and transmitted real-time alerts ( = 42 seconds). Among detections of separate age and sex classes, lone adult bulls were the most prone to conflict. Real-time alerts permitted rapid response by field personnel to prevent conflict at the site ( = 18.2, SD = 12.4 min to arrival). Frequent detections of humans (33,217 events) on elephant trails highlighted the value of real-time alerts. Four human fatalities and five serious injuries occurred in the study area over a two-year period prior, but none during the study (2023-2024) after deploying the AI-alerting system. Loss of lives and livelihoods underscore the urgency of applying this approach to other elephant ranges and adapting AI models to other conflict-pronespecies to promote coexistence.
Recent Progress in Gene-Targeting Therapies for Spinal Muscular Atrophy: Promises and Challenges
Authors: Haque Umme Sabrina , Yokota Toshifumi
Published: July 2024

Keywords: spinal muscular atrophy (SMA); survival of motor neuron 1 (SMN1); SMN2; SMN protein; antisense oligonucleotide (ASO); nusinersen; gene therapy; onasemnogene; risdiplam; small molecule, combination therapy
Deep Learning Model-Driven Financial Risk Prediction and Analysis
Authors: Yang Tianyi , Li Ang , Xu Jiahao , Su Guangze , Wang Jiufan
Published: July 2024

The integration of deep learning models into financial risk prediction and analysis has significantly transformed traditional approaches. While conventional quantitative methods often rely on simplistic metrics like maximum drawdown, the advent of deep learning necessitates a more nuanced evaluation, emphasizing the model's generalization ability, especially during market crises such as stock market crashes. This paper explores the critical aspects of evaluating deep learning models' risk control capabilities in finance, underscoring the importance of understanding both statistical metrics and generalization abilities, particularly in adverse market conditions. By examining deep learning models' performance in scenarios like stock market crashes and highlighting the significance of cross-validation techniques, this study aims to offer practitioners insights into constructing robust risk management systems. It advocates for a comprehensive approach integrating quantitative analysis with macroeconomic factors to enhance financial risk prediction and analysis in volatile markets. The experimentation reveals that different deep generative models excel in various aspects of financial time series analysis, with generative adversarial networks (GANs) demonstrating superior performance in predicting Value at Risk (VaR) and variational autoencoders (VAEs) excelling in return rate prediction. Moreover, integrating multiple models further enhances predictive performance, leveraging the strengths of each model to compensate for individual weaknesses. Overall, this paper underscores the potential and significance of deep generative models in financial time series analysis, offering a roadmap for improved risk management and decision-making in financial markets.
A Review on the Versatile Applications of Plant-Based Essential Oils in Food Flavoring, Culinary Uses and Health Benefits
Authors: Hassid Alissar , Salla Mohamed , Krayem Maha , Khaled Sanaa , Hassan Hussein , El Khatib Sami
Published: July 2024

Plant-based essential oils are important natural products rich in volatile compounds, and they have various applications in medicine, food, perfumery and cosmetics. These substances can be produced using various methods, such as steam distillation and solvent extraction. Their chemical composition is influenced by geographical and climatic conditions, production methods, and intrinsic factors. Published articles and literature were scanned to gather the required information. Previous studies have shown that essential oils possess chief health benefits, including antimicrobial, anti-inflammatory, antioxidant, and psychological effects. Consequently, they have wide applications in the food industry as preservatives in food systems and in active packaging, edible coating, probiotic foods, and flavoring. Essential oils can be successfully utilized in flavoring foods and beverages such as cheese, ice cream, and soft drinks. Despite their great antimicrobial and flavoring roles, it is important to further investigate their possible interactions with food components and the physiochemical characteristics of foods flavored with essential oils.
Thermo-Mechanical and Thermo-Electric Properties of a Carbon-Based Epoxy Resin: An Experimental, Statistical and Numerical Investigation
Authors: Spinelli Giovanni , Guarini Rosella , Guadagno Liberata , Vertuccio Luigi , Romano Vittorio
Published: July 2024

Due to their remarkable intrinsic physical properties, carbon nanotubes (CNTs) can enhance mechanical properties and confer electrical and thermal conductivity to polymers currently investigated for use in advanced applications based on thermal management. An epoxy resin filled with varying concentrations of CNTs (up to 3 wt.%) was produced and experimentally characterized. The electrical percolation curve identified two critical filler concentrations: 0.5 wt%, near the electrical percolation threshold, suitable for exploring mechanical and piezoresistive properties, and 3 wt% for investigating thermo-electric properties due to the Joule effect with applied voltages ranging from 70V to 200V. Numerical models were developed using multiphysics simulation software. Once validated with experimental data, these models were used to investigate additional physical properties of the composites. Furthermore, a statistical approach based on the design of experiments (DoE) was employed to examine the influence of certain thermal parameters on the final performance of the materials. The purpose of this research is to promote the use of contemporary statistical and computational techniques alongside experimental methods to enhance understanding of materials science. New materials can be identified through these integrated approaches, or existing ones can be more thoroughly examined.
Computational Test for Conditional Independence (with Categorical Variables)
Authors: Thorjussen Christian B. H. , Liland Kristian Hovde , Solberg Lars Erik , Måge Ingrid
Published: July 2024

Conditional Independence (CI) testing is fundamental in statistical analysis. For example, CI testing helps validate causal graphs or longitudinal data analysis with repeated measures in causal inference. CI testing is difficult, especially when testing involves categorical variables conditioned on a mixture of continuous and categorical variables. Current parametric and non-parametric testing methods designed for continuous variables and can quickly fall short in the categorical case. This paper presents a computational approach for CI testing for categorical data types, which we call computational conditional independence (CCI) testing. The test procedure is based on permutation and combines machine learning prediction algorithms and Monte Carlo Cross-Validation. We evaluated the approach through simulation studies and assessed the performance against alternative methods; the generalized covariance measure (GCM) test, the kernel conditional independence (KCI) test, and testing with multinomial regression. We find that the computational approach to testing has utility over the alternative methods, and we can achieve better control over type-I-error rates. We hope this work can expand the toolkit for CI testing for practitioners and researchers.
An In-silico Designing of Vaccine against All Serotypes of Dengue Virus Based on Virtual Screening of B-Cell and T-Cell Epitopes
Authors: Ullah Hikmat , Ullah Shaukat , Jinze Li , Yang Fan , Tan Lei
Published: July 2024

Dengue virus is a global health problem most prevalent in tropical and subtropical regions. However, after the approval of two vaccines, Dengvaxia, TV003/TV005 of Takeda, for its prevention, problems were reported, like enhanced risks of infection or less efficiency of protection. Since then, more struggles have been in demand for the development of better vaccines. Here, we conducted a new design through an in-silico strategy. Initially, epitopes were chosen based on their antigenicity, immunogenicity, and binding affinity with MHC molecule, while excluded with allergenicity, toxicity and potential risk of antibody dependent enhancement. Subsequently, a core antigen was constructed with selected epitopes and linked with distinct adjuvant proteins to achieve three candidate vaccines, PSDV-1~3. PSDV-2 was chosen for further validation based on their advantage in physicochemical and structural properties. With a panel of simulations, this artificial protein showed tight binding with pattern recognition receptors, good stability, robust immune induction, and ultimately was confirmed as a high quality vaccine candidate. The plasmid for its recombinant expression was then designed accordingly. With our new design, one more choice was obtained for the effective protection from Dengue virus. Further experimental validations are still require to confirm it protection capacity and safety.
Is the Sublingual Artery a Reliable Alternative for Intraoral Anastomoses in Head and Neck Free Flap Reconstruction? Anatomical Basis and Preliminary Results
Authors: Starke Vasco , Wallner Jürgen , Stigler Robert , Mannschatz Sidney , Müller Jakob , Brenner Erich
Published: July 2024

Background/Objectives: Head and neck free flap reconstructions are often required to treat tumors or extensive post-traumatic jaw defects. The facial artery is the standard receiving vessel for intraoral microvascular anastomoses. However, its use is associated with several disadvantages, such as lesions of buccal nerve branches or the parotid duct and variability in course and diameter. This study aims to investigate whether sublingual artery branches can be considered an alternative intraoral supply vessel to the facial artery to avoid these drawbacks. Methods: 12 formalin-fixed cadaveric heads with 24 sides were dissected. The sublingual artery's origin, course, branching pattern, and distribution were examined. In addition, the diameters of the branches of the sublingual artery were assessed to identify potential supply vessels for anastomoses. Results: In ten of the 24 cases (41.7 %), the sublingual artery originated from the lingual artery and nine cases (37.5 %) from the facial artery. The main trunk of the sublingual artery was present in the floor of the mouth in all cases (100 %) with a diameter of ≥ 0.9 mm in vitro (1 mm in vivo). In 15 of the 24 half heads (62.5 %), branches of the sublingual artery with ≥ 0.9 mm were identified in this space. Conclusions: The large diameter of the sublingual artery on the floor of the mandible suggests that this vessel or its branches could be considered alternative pedicles for intraoral anastomoses in mandibular microvascular free flap grafts.
Application of Multiple geophysical Exploration Methods in the Exploration of Marine Sand Resources in the Northern Offshore Waters of the South China Sea
Authors: Yu Gang , Hu Xichong , Fang Jie , Yang Ying , Zhang Yongcong , Lin Jinhui , Liu Jingyi , Qian Libing
Published: July 2024

Marine sand, in addition to oil and gas resources, is the second largest marine mineral resource. The rational development and utilization of marine sand resources are conducive to the growth of the marine economy. Marine sand can be categorized into surface marine sand and buried marine sand. Buried marine sand deposits are buried beneath the sea floor, making it challenging to locate them due to their thin distribution. Consequently, there exist numerous technical difficulties associated with marine sand exploration. In this study, various geophysical methods such as sub-bottom profile survey and single-channel seismic survey were employed in the northern offshore waters of the South China Sea along with offshore engineering geological drilling. As a result, two distinct marine sand bodies were delineated within the study area. Additionally, five reflective interfaces (R0, R1, R2, R3 and R4) were identified from top to bottom. These interfaces can be divided into five seismic sequences: A2, B2, C2, D2 and E2 respectively. Three sets of strata were recognized: the Quaternary Holocene Marine sedimentary layer (Q4m), the Upper Pleistocene alluvial layer, and the diluvial sedimentary layer (Q3al+pl) as well as the Upper Pleistocene Marine sedimentary layer (Q3m). Sequence A2 and B2 corresponded to Quaternary Holocene Formation (Q4m) within the study area while sequence C2 corresponded to B2 as well as upper Pleistocene alluvial and alluvial deposits (Q3al+pl), which represent one of the main occurring layers of sand in this region. Lastly, E2 represents a layer composed mainly of silty clay and round gravel known as upper Pleistocene marine sediment layer (Q3m). In total, two ore bodies containing marine sand have been discovered during this study. The estimated total resource amounts approximately 46 million m³ with an average thickness around 11 meters.
Strip Adjustment of Multi-Temporal LiDAR Data - A Case Study at the Pielach River
Authors: Wimmer Michael H. , Mandlburger Gottfried , Ressl Camillo , Pfeifer Norbert
Published: July 2024

With LiDAR (Light Detection and Ranging) time series being used for various applications, optimal realisation of a common geodetic datum over many epochs is a highly important prerequisite with direct impact on accuracy and reliability of derived measures. In our work, we develop and define several approaches to the adjustment of multi-temporal LiDAR data in a given software framework. These approaches ranging from pragmatic to more rigorous solutions are applied to an 8 year time series with 21 individual epochs. The analysis of the respective results suggests that a sequence of bi-temporal adjustments brings the best results while being more flexible and computationally viable than the most extensive approach of using all epochs in one single multi-temporal adjustment. With a combination of sparse control patches measured in the field and one selected reference block, we obtain relative datum discrepancies in the range of 1-2 cm for the complete time series. Based on our findings, we formulate design criteria for setting up and adjusting future time series with the proposed method.
Biomarker Profiling by Targeted Metabolomic Analysis of Plasma and Urine Samples in Type 2 Diabetes Mellitus Patients and Early Diabetic Kidney Disease
Authors: Mogos Maria , Socaciu Carmen , Socaciu Andreea Iulia , Vlad Adrian , Gadalean Florica , Bob Flaviu , Milas Oana , Cretu Octavian Marius , Suteanu-Simulescu Anca , Glavan Mihaela , Balint Lavinia , Ienciu Silvia , Iancu Lavinia , Jianu Catalin , Ursoniu Sorin , Petrica Ligia
Published: July 2024

The incidence of diabetes mellitus (DM) continues to rise worldwide and one of the most serious microvascular complications is diabetic kidney disease (DKD), which is the leading cause of end-stage renal disease. Current bi-omarkers such as urinary albumin excretion rate have limitation for early detection of DKD. In our study we used ultra-high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry (UHPLC-QTOF-ESI+-MS) techniques to quantify previously analyzed metabolites, such as tryptophan, kynurenic acid, taurine, l-acetylcarnitine, glycine, and tiglylglycine. We performed the targeted analy-sis of metabolites from urine and serum samples, collected from 110 subjects. Of these, 90 patients with type 2 DM (T2DM) were divided according to the urinary albumin/creatinine ratio (UACR) into normoalbuminuria 300 mg/g groups, respectively, while 20 subjects were rep-resented by healthy controls. Through various validation methods, we identified several metabolites as potential biomarkers, such as kynurenic acid, glycine, and l-tryptophan in serum and l-acetylcarnitine, tiglylglycine, and tau-rine in urine.
Cellular and Molecular Biology of Mitochondria in Chronic Obstructive Pulmonary Disease
Authors: Li Chin-Ling , Liu Shih-Feng
Published: July 2024

Abstract:
Chronic Obstructive Pulmonary Disease (COPD) is a continually advancing respiratory disorder, characterized by enduring airflow limitation along with long-lasting inflammation in the airways. An expanding pool of evidence is emphasizing how mitochondrial dysfunction directly impacts the development and progression of COPD. This comprehensive review delves deeper into the intricate cellular and molecular biology of mitochondria within the framework of COPD, spotlighting significant alterations in structure and function that accompany mitochondrial dysfunction.
In this narrative, we delve into the observed changes in mitochondrial shape, behavior, and respiratory chain complex alterations seen in individuals afflicted with COPD. The discussion includes implications on cellular signaling pathways and how this affects the natural process of programmed cellular death (apoptosis) and cellular aging, particularly in reference to COPD. Additionally, we consolidate ongoing therapeutic strategies, honing in on the management of COPD through a focus on mitochondrial dysfunction. Prominent among these strategies is the potential role of antioxidants and mitochondrial biogenesis inducers, which are emerging as promising fields of intervention.
Furthermore, we embark on an overview of the possible use of mitochondrial biomarkers as innovative tools in diagnosing COPD, evaluating disease progression, and monitoring the efficacy of COPD treatments. As we unravel the rather complex interplay between mitochondrial biology and COPD, this review highlights the critical importance of formulating treatments that target mitochondrial dysfunction. The ultimate goal of these strategic interventions is to slow down the rate of COPD progression and significantly improve patient outcomes.
Lastly, though our understanding of the nexus between COPD and mitochondrial dysfunction has significantly enhanced, ample scope remains for further investigation. Improved insights into the mechanisms of mitochondrial dysfunction, discovered biomarkers, and targeted therapies could encompass a revolutionary step towards comprehensive disease management. The future of COPD treatment seems to lean towards a combination of strategies, prioritizing not only the management of symptoms but also focused on preserving and restoring lung function, improving physical capacity, and enhancing quality of life for COPD patients.
Electrochemical Aptasensor for Label-Free Detection of Oxytetracycline
Authors: Kourti Dimitra , Geka Georgia , Nemtsov Lidia , Ahmadi Soha , Economou Anastasios , Thompson Michael
Published: July 2024

Oxytetracycline (OTC) serves as a widely employed antibiotic in veterinary treatment and prevention of infections, potentially leaving residues in animal-derived food products, such as milk, that are consumed by humans. Given the detrimental effects of prolonged human exposure, it becomes imperative to develop precise and sensitive methods for monitoring the presence of OTC in food. This work reports on the fabrication of a label-free electrochemical aptasensor for the determination of OTC as a proof-of-concept.
Brittle Fracture of Iron and Steel and the Sharp Upper Yield Point are Caused by Cementite Grain Boundary Walls
Authors: Altshuler Thomas Lafe
Published: July 2024

Brittle fracture of iron and steel above twinning temperatures are caused by cementite grain boundary wall cracks. These were revealed by an Atomic Force Microscope. At temperatures below the Ductile-Brittle Transition, cracks must propagate longitudinally within the cementite walls until the stress is sufficient high for the cracks to propagate across ferrite grains. Calculations using these concepts correctly predict the stress and temperature at the Ductile-Brittle Transition required for fracture to occur. At temperatures above the Ductile-Brittle Transition for hypoeutectoid ferritic steels, dislocations must fracture these walls transversely for plastic deformation to continue. This is responsible for the upper yield point at the elastic limit in these steels followed by a large drop in stress to the lower yield point. Here the walls surround completely all of the grains. Where the walls are segmented such as in iron, dislocations can pass around the walls resulting in a gradual change from elastic to plastic deformation. The Cottrell atmosphere theory of yielding is not supported experimentally. It was the best available until later experiments including those using the Atomic Force Microscope were obtained. Methods are presented here giving yield strength versus temperature and also the parameters for the Hall-Petch and Griffith equations.
Current Status and Development Trend of Research on Polymer-based Kinetic Inhibitors for Natural Gas Hydrates
Authors: Liu Shujie , Wang Sunan , Luo Jiansheng , Xu Yilong , Ren Liangliang , Xiang Xiong , Geng Tie , Xu Botao , Guo Lei
Published: July 2024

As the understanding of natural gas hydrates as a vast potential resource deepens, their importance as a future clean energy source becomes increasingly evident. However, natural gas hydrates tend to secondary generation during extraction and transportation, leading to safety issues such as pipeline blockages. Consequently, developing new and efficient natural gas hydrate inhibitors has become a focal point in hydrate research. Kinetic Hydrate Inhibitors (KHIs) offer an effective solution by disrupting the nucleation and growth processes of hydrates without altering their thermodynamic equilibrium conditions. This paper systematically reviews the latest research progress and development trends of KHIs for natural gas hydrates, covering their development history, classification, and inhibition mechanisms. It particularly focuses on the chemical properties, inhibition effects, and mechanisms of polymer inhibitors such as polyvinylpyrrolidone (PVP) and polyvinylcaprolactam (PVCap). Studies indicate that these polymer inhibitors provide an economical and efficient solution due to their low dosage and environmental friendliness. Additionally, this paper explores the environmental impact and biodegradability of these inhibitors, offering guidance for future research, including the development, optimization, and environmental assessment of new inhibitors. Through a comprehensive analysis of existing research, this work aims to provide a theoretical foundation and technical reference for the commercial development of natural gas hydrates, promoting their safe and efficient use as a clean energy resource.
Remimazolam and its place in the current landscape of procedural sedation and general anesthesia
Authors: Goudra Basavana , Brohan Matthew , Brohan Janette
Published: July 2024

Remimazolam was derived from its parent compound by adding an ester linkage into its structure, so that the drug becomes a substrate for ester metabolism. As a result, it undergoes organ independent ester hydrolysis, although the clinical benefits in terms of shorter recovery are not uniformly observed in clinical practice. Remimazolam is mainly tested in procedural sedation. In comparison to propofol, the current gold standard for procedural sedation, its proposed attractiveness is shorter wake-up times and a clear-headed recovery Its clear advantage over propofol is better hemodynamic stability, lack of pain on injection and availability of a reversal agent in the form of flumazenil. Data on patient and proceduralist’s satisfaction are lacking. Remimazolam is also used for induction and maintenance of general anesthesia in Japan (where it is approved for this purpose). In this scenario, it is not clear if it can achieve the same degree of lack of recall as propofol. The use of remimazolam in obstetrics, pediatrics and in high-risk population is an emerging area.
Leveraging Generative Artificial Intelligence for Financial Market Trading Data Management and Prediction
Authors: Bai Xinzhu , Zhuang Shikai , Xie Hangyu , Guo Lingfeng
Published: July 2024

The paper explores using generative artificial intelligence (AI) in financial market data management and forecasting. By integrating multiple data sources and feature extraction techniques, such as fundamental analysis, technical indicators, global economic data, and sentiment analysis, generative AI constructs a comprehensive deep learning framework that significantly enhances financial data management efficiency and market forecasts' accuracy. Specifically, technologies like generative adversarial networks (Gans) and variational autoencoders (VAE) demonstrate substantial data augmentation and model optimisation potential. The application value of the model in real-time market prediction and trading strategy optimization is further amplified through reinforcement learning methods.
Revealing the Impact of Understory Fires on Stem Survival in Five Palm Species (Arecaceae): An Experimental Approach Using Predictive Models
Authors: Liesenfeld Marcus Vinicius de Athaydes
Published: July 2024

Amid increasing deforestation, surface fires reaching the forest understory are one of the primary threats to Amazonian ecosystems. Despite extensive research on post-fire mortality in woody species, literature on palm resilience to fire is scant. This study investigates post-fire mortality in four understory palms—Bactris maraja Mart., Chamaedorea pauciflora Mart., Geonoma deversa (Poit.) Kunth, Hyospathe elegans Mart., and juvenile individuals of Euterpe precatoria Mart. Objectives included: a) comparing post-fire responses; b) developing mortality models based on severity variables; and c) evaluating if diameter protects bud stems from heat flux. Conducted at the edge of an Ombrophylous Forest in Alto Juruá Acre, Brazil (7°45'S, 72°22'W), the experiment subjected 85 individuals to controlled burning in a 1 m² area near the stipe, with temperature sampling using K thermocouples. Results showed varying mortality rates among species, with larger stipe diameter correlating to reduced mortality. Canopy burning patterns significantly influenced mortality, especially for Euterpe precatoria. Species exhibited diverse regrowth capacities, with B. maraja showing the highest number and tallest basal resprouts. This study underscores post-fire plant mortality as a critical indicator of fire severity, essential for understanding its ecological impacts.
Deciphering Factors Contributing to Cost-Effective Medicine Using Machine Learning
Authors: Long Bowen , Zhou Jinfeng , Tan Fangya , Bellur Srikar
Published: July 2024

This study uses machine learning to identify key factors influencing the cost-effectiveness of over-the-counter (OTC) medications. By developing a novel cost-effectiveness rating (CER) from user ratings and prices, we analyzed data from Amazon. The findings indicate that FSA/HSA eligibility, symptom treatment range, safety warnings, special effects, active ingredients, and packaging size significantly impact cost-effectiveness across cold, allergy, digestion, and pain relief medications. Medications eligible for FSA or HSA funds, treating a broader range of symptoms, and having smaller packaging are perceived as more cost-effective. Cold medicines with safety warnings were found to be cost-effective due to their lower average price and effective ingredients like phenylephrine and acetaminophen. Allergy medications with kid-friendly features showed higher cost-effectiveness, and ingredients like calcium, famotidine, and magnesium boosted the cost-effectiveness of digestion medicines. These insights help consumers make informed purchasing decisions and assist manufacturers and retailers in enhancing product competitiveness. Overall, this research supports better decision-making in the pharmaceutical industry by highlighting factors that drive cost-effective medication purchases.
Dispensing Error Rate in an App-Based, Semaglutide-Supported Weight-Loss Service: A Retrospective Case Study
Authors: Talay Louis , Vickers Matt
Published: July 2024

Digital weight-loss services (DWLSs) combining pharmacotherapy and health coaching have the potential to make a major contribution to the global struggle against obesity. However, there is currently no evidence to counter the widespread concern that these services enable large numbers of unsuitable patients to obtain Glucagon-like peptide-1 receptor agonists (GLP-1 RA). This study retrospectively analysed the rate at which the partner pharmacy network of Australia’s largest DWLS provider committed GLP-1 RA dispensing errors over a 6-month period. The analysis found that 191 (0.14%) of the 135131 dispensed Semaglutide orders contained an error. Non-compliant dose escalation (44.5%) and dispatch errors (32.5%) were the two most common error types. Most errors (89%) were deemed to have been of medium urgency, with 6.8% considered high urgency. A disproportionate number of high urgency cases were from wrong medication (31%) and general complaint errors (15%). A Chi-square test revealed a statistically higher dispensing error rate among orders to female patients (0.16%) compared to males (0.076%). The results lay an important foundation in digital pharmacy literature and suggest that comprehensive DWLSs have the potential to safely collaborate with third-party pharmacies in dispensing GLP-1 RAs.
Intraperitoneal Administration of 17-DMAG as an Effective Treatment Against Leishmania braziliensis Infection in BALB/c Mice: A Preclinical Study
Authors: Cruz Kercia P. , Petersen Antonio L. O. A. , Amorim Marina F. , Pinho Alan G. S. F. , Palma Luana C. , Dantas Diana A. S. , Silveira Mariana R. G. , Silva Carine S. A. , Cordeiro Ana Luiza J. , Oliveira Izabella G. , Pita Gabriella B. , Souza Bianca C. A. , Bonfim Gilberto C. , Brodskyn Claudia I. , Fraga Deborah B. M. , Lima Isadora S. , de Santana Maria B. R. , Teixeira Helena M. P . , Menezes Juliana P. B. , Santos Washington L. P. , Veras Patricia S. T.
Published: July 2024

Background: Leishmaniasis is a significant global public health issue that is caused by parasites from Leishmania genus. With limited treatment options and rising drug resistance, there is a pressing need for new therapeutic approaches. Molecular chaperones, particularly Hsp90, play a crucial role in parasite biology and are emerging as promising targets for drug development.
Objective: This study evaluates the efficacy of 17-DMAG in treating BALB/c mice from cutane-ous leishmaniasis through in vitro and in vivo approaches.
Materials and Methods: We assessed 17-DMAG cytotoxic effect on bone marrow-derived mac-rophages (BMMΦ) and its effects against L. braziliensis promastigotes and intracellular amastigotes. Additionally, we tested the compound's efficacy in BALB/c mice infected with L. braziliensis via intraperitoneal administration to evaluate the reduction of lesion size and de-crease of parasite load in the ears and lymph nodes of infected animals.
Results: 17-DMAG showed selective toxicity [selective index=432) towards Leishmania amastigotes, causing minimal damage to host cells. The treatment significantly reduced lesion sizes in mice and results in parasite clearance from ears and lymph nodes. It also diminished in-flammatory responses and reduced the release of pro-inflammatory cytokines (IL-6, IFN-g, TNF) and the regulatory cytokine, IL-10, underscoring its dual leishmanicidal and anti-inflammatory properties.
Conclusion: Our findings confirm the potential of 17-DMAG as a viable treatment for cutaneous leishmaniasis and support further research into its mechanisms and potential applications against other infectious diseases.
Multi-Link Prediction for mmWave Wireless Communication Systems using Liquid Time-Constant Networks, Long Short-term Memory, and Interpretation using Symbolic Regression
Authors: Pendyala Vishnu , Patil Milind
Published: July 2024

A significant challenge encountered in mmWave and Sub-terahertz systems used in 5G and 1 the upcoming 6G networks is the rapid fluctuation in signal quality across various beam directions. Extremely high-frequency waves are highly vulnerable to obstruction, making even slight adjustments in device orientation or the presence of blockers capable of causing substantial fluctuations in link quality along a designated path. This issue poses a major obstacle because numerous applications with low-latency requirements necessitate precise forecasting of network quality from many directions and cells. The method that is proposed in this research demonstrates an avant-garde approach for assessing the quality of multi-directional connections in mmWave systems by utilizing the Liquid Time Constant network (LTC) instead of the conventionally used Long Short-Term Memory (LSTM) technique. The method’s validity was tested through an optimistic simulation involving the monitoring of multi-cell connections at 28 GHz in a scenario where humans and various obstructions were moving arbitrarily. The results with LTC are significantly better than those obtained by conventional approaches such as LSTM. The latter resulted in a test Root Mean Squared Error (RMSE) of 3.44 dB, while the former, 0.25 dB, demonstrating a 13-fold improvement. For better interpretability and to illustrate the complexity of prediction, an approximate mathematical expression is also fitted to the simulated signal data using Symbolic Regression.
Evaluation of Neutralizing Antibodies on Respiratory Syncytial Virus in Japanese Mother-Infant Pairs after COVID-19 Pandemic
Authors: Oishi Tomohiro , Yoshioka Daisuke , Ono Sachie , Yasui Yuto , Kato Atsushi , Ogita Satoko , Tokutomi Tomoaki , Miura Mazumi , Eitoku Takahiro , Enoki Hideo , Shimoya Koichiro , Nakano Takashi
Published: July 2024

Respiratory syncytial virus (RSV) is the most common cause of acute lower respiratory tract infection in young children globally. Following the COVID-19 pandemic, RSV infections have become more prevalent. Consequently, a new vaccine targeting RSV infections in pregnant women has been introduced worldwide. To estimate the effectiveness of this new vaccine for pregnant women, we investigated neutralizing antibodies against RSV in samples taken from 51 mothers and their babies. The prevalence rate of neonatal antibodies, defined as a titer of ≥16, was 39.2%. We found no significant differences in neonatal neutralizing antibodies based on factors, such as sex, gestational age at birth, birth weight, presence of siblings, neonatal problem, and usage of palivizumab. Neonatal neutralizing antibodies were equal to or higher than those of their mother. A new RSV vaccine targeting all pregnant women is promising, as approximately 60% of neonates had low antibody titers against RSV. However, predicting low antibody titer against RSV remains challenging. Moreover, our findings indicate efficient transmission of RSV antibodies from babies to their mothers.
Self-Cleaning Solar Mirrors Coatings: From the Laboratory Scale to Prototype Field Tests
Authors: Castaldo Anna , Gambale Emilia , Vitiello Giuseppe , Cara Giuseppe
Published: July 2024

A low cost, scalable and robust process has been proposed as innovative method for coating solar mirrors with a self-cleaning, transparent in the full solar range and versatile material based on auxetic aluminium nitrides, previously obtained on the laboratory scale. This work presents the scaling-up of fabrication process from laboratory to prototypal scale and pre-liminary results of outdoor self-cleaning solar mirror prototypes testing in the demonstrative CSP plant ENEASHIP located in Casaccia (Rome) ENEA research centre.
Prototypes 50x40cm have shown stability in external conditions: no degradation occurs during the test campaign. Their washing restores the initial reflectance affected by soiling and the self-cleaning performance allows the utilization of a reduced quantity of water for cleaning operations with respect to uncoated glass of back surface mirrors. A similar self-cleaning AlN coating could be utilized on other solar components affected by soiling, such as glass envelopes of heat collecting elements, PV panels and everywhere are required self-cleaning performance combined to optical ones.
Assessing irrigation water demand and pumping operations for rice farming in the Bengawan Solo River, Indonesia
Authors: Trinugroho Muchamad Wahyu , Arif Sigit Supadmo , Susanto Sahid , Nugroho Bayu Dwi Apri
Published: July 2024

Owing to population growth, the rice demand in Indonesia has been increasing, which has led to an increase in rice consumption. One way to boost rice production is to enhance pump irrigation in rainfed fields. The aim of this study is to evaluate irrigation water usage and water pumping practices in the Bengawan Solo River, focusing on enhancing rice production. Data were sourced from governmental entities, which include the Indonesian Bureau of Meteorology, Climatology, and Geophysics and the Ministry of Public Works and Housing. Water requirement was calculated using the FAO Penman–Monteith equation. The study highlights that throughout the three distinct growing seasons (GS), the water requirements for irrigating rainfed rice fields vary, with the most substantial demand observed during the first growing season (GS I), followed by the third growing season (GS III), and the second growing season (GS II). In dry years, a consistent pattern of low water balances occurs, which persists below 500 mm across all months. Compared with the other two scenarios, the dry year shows higher variability in rainfall, as evidenced by its higher coefficient of variation of 0.620 compared with 0.347 and 0.416 for the wet and normal years, respectively. The electricity cost rate peaks in GS I, trailed by GS II and GS III, with rates of IDR 2,400, 1,180, and 1,028 per kilowatt-hour, respectively. The findings play a pivotal role in shaping regional planning decisions regarding the utilization and necessity of river water resources and the development of cropping calendars.
Soil fertility based on mineralogical properties to support sustainable agriculture management
Authors: Hidayat Wahyu , Suryaningtyas Dyah Tjahyandari , Mulyanto Budi
Published: July 2024

Detailed information on soil mineral composition has been crucial in providing the basis for designing sustainable agricultural practices, as this information offers long-term insights into natural soil fertility. This research aimed to further investigate the characteristics of soil mineral composition as a basis for managing soil fertility. Three soil profiles representing three different parent materials have been examined in the field, and soil samples have been collected for laboratory analysis. Profile 1 originates from the Raung Volcano Rock Formation (Qhvr). Profile 2 originates from the Sukamade Formation (Toms). Profile 3 originates from Puger Formation (Tmp). The presence of Mount Raung volcanic influence results in distinct soil characteristics in Profiles 2 and 3 compared to typical sedimentary and karst rock soils. The sand fraction minerals in all three profiles are predominantly composed of opaque minerals, followed by rock fragments, ferromagnesian mineral series (olivine, augite, hypersthene, and hornblende), plagioclase minerals (anorthite, biotite, and labradorite), iron concretions, epidote, and tourmaline. The clay fraction minerals in all three profiles consist of illite, kaolinite, and quartz. The minerals illite and ferromagnesian groups in all three profiles play a significant role in increasing the availability of potassium, calcium, and magnesium nutrients, thereby reducing the need for fertilizers for these elements. The soils in all three profiles naturally possess good fertility; however, designing a sustainable agricultural system requires consideration of the morphology, landform, and climate of all three profiles.
Examining the Negative Impact of TikTok Usage on Elementary Students' Learning Motivation
Authors: Mariyati Lely Ika , Wilmar Muhammad Pascal
Published: July 2024

This correlational quantitative study investigates the impact of TikTok social media usage intensity on academic learning motivation among elementary school students. Using a sample of 80 students from grades 4, 5, and 6, selected through accidental sampling, the research employed TikTok usage intensity scales and an academic learning motivation scale based on self-determination theory. Data analysis with Pearson correlation in JASP software revealed a significant negative relationship between TikTok usage intensity and students' learning motivation, supporting the hypothesis. Recommendations include implementing social media regulations in educational settings and promoting awareness among students, parents, and educators about the potential adverse effects of excessive TikTok use. Future research could explore this topic further with more sophisticated methodologies to enhance understanding.
Highlight:

Quantitative approach reveals significant negative correlation.
Accidental sampling used for diverse grade representation.
Recommendations advocate media regulation for academic focus.

 
Keywoard: TikTok, Elementary students, Learning motivation, Social media impact, Correlational study
Root Rot Disease in Association with Common Bean Stem Maggot (Ophyiomia phaseoli) and Evaluation of Insecticides for Management of Stem Maggot on Common Bean (Phaseolus vulgaris L.) at West Hararghe, Ethiopia
Authors: Beyene Gelana Keno , Heji Ahmed Beyan , Tsegaye Tilahun
Published: July 2024

Bean stem maggot (BSM) and root rot disease are economically important pests of common beans. The wounds caused by BSM feeding act as entry points for root rot-causing pathogens. The objective of this paper was to assess root rot disease associated with stem maggots and evaluate insecticides for managing stem maggots on common beans in west Hararghe, Ethiopia. This study included a two-part survey and field experiment. The survey was conducted at different common bean growing agro-ecologies of the west Hararghe zone, namely, the Oda Bultum, Habro, and Chiro districts, while the field experiment was conducted at the Habro district, Bareda, Oda bultum University farm site. Twenty farms in four kebeles were randomly selected for each district to determine the occurrence and incidence of bean root rot and bean stem maggot alone and their interactions. Each bean root was examined for the presence of bean stem maggot and root rot disease-causing pathogens. The results showed that the occurrence and incidence of bean root rot diseases and bean stem maggots were significant (p<0.05) in the surveyed areas. Rhizoctonia solani, Pythium spp.and Fusarium spp. were the major root rot pathogens isolated. Ophyiomia phaseoli was the dominant bean stem maggot in the surveyed districts. The incidence of common bean fly and root rot computed was significantly different (P< 0.05) among the surveyed districts. The highest disease and bean fly interaction incidence (50.85%) was obtained from the Chiro district, followed by the Habro district (36.04%). The lowest incidence of disease and bean fly interaction (26.97%) was recorded in the Oda Bultum district. For the field experiment, six different insecticides, namely, confidor SL 200, Karate 5% EC, Dimeto 40% EC, Alpha guard, Apron star 42 WS, and Bravo 5% EC (W/V), were evaluated and compared to the control, which was not sprayed to determine the differences among insecticides. Common bean agronomic parameters showed significant differences (P< 0.0001 to 0.05) among the treatments compared to those of the control. The grain yield ranged from 1095 to 2950 kg/ha among the treatments. The addition of Confidor SL 200, followed by Apron Star 42 WS and dimethoate (40%) significantly reduced the number of bean stem maggots and increased common bean agronomic yield and yield component parameters.
Wave sources of the 17th-century tsunami deposits in western Hokkaido, Japan using sediment transport modeling
Authors: Nakanishi Ryo , Kimura Tatsuto , Kanno Takeshi
Published: July 2024

Sediment transport modeling is a powerful tool for identifying wave sources of paleo-tsunami deposits because it can reproduce not only the thickness distribution but also the sediment features. The giant earthquakes in the Kuril Trench have uncertainties in the magnitude depending on the extent to which tsunami deposits widely distributed along the Pacific coast of Hokkaido can be correlated with each other. Multiple tsunami deposits have been found in Kabari, northern Hidaka, Hokkaido, and their wave sources are expected to provide a significant constraint on the tsunami magnitude. We reproduce two layers of tsunami deposits around the 17th century with sediment transport modeling using possible wave source candidate models. The Mt. Komagatake collapse and Kuril Trench earthquake models reproduce the two layers of tsunami deposits, indicating the tsunami distributions along the Pacific coast of Hokkaido are reproduced without Mw > 9 earthquake models.