bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring Ethical Issues in Pharmaceutical Marketing’s Strategies: A Critical Marketing Perspective
Authors: Malik Dr Fazle , Junaid Dr. Muhammad , Asif Dr. Muhammad
Published: September 2024

This study empirically explores the ethical issues with pharmaceutical marketing, which acts as a transgressor to increase inappropriate prescriptions from physicians. Marketing is used to safeguard the interests of shareholders and indoctrinate materialism in target audiences. The inquiry aims to critically examine the marketing strategies and make some drastic changes to put them on humanistic lines to produce salutary benefits to society and the public health sector. The inquirers deploy qualitative methods to scientifically understand the behaviors of marketers and physicians. They used the stratified purposive sampling technique to get data from those who had it. The constructivist grounded theory is used as a strategy of inquiry to explore the different concepts and ideas that are interconnected to form a social phenomenon. They conducted ten in-depth interviews with the selected samples. The researchers developed categories through initial coding and established relationships among them through axial coding. The analysis and interpretation of data produce a single theme, "Deceptive Marketing Strategies," which has two main categories. Each of them has three sub-categories: (unnecessary prescriptions, drug incentivization, unethical practices) and (non-adherence to clinical practice guidelines, physicians’ materialistic approach, and indiscriminate use of antibiotics) respectively. The consequence of these unethical practices is the emergence of antibiotic resistance. The study found transgressions in pharmaceutical marketing and its deceitful and unscrupulous promotional strategies, which have a compounding effect on the misuse and abuse of pharmaceuticals.
Institutional Quality and Digitalization's Role in Attaining Sustainable Development: Study of G-8 & SAARC Countries
Authors: Zafar Muhammad , Hashmi Dr. Aijaz Mustafa , Ahmed Dr. Ishtiaq
Published: September 2024

The importance of Institutional Quality and Digitalization in sustainable development has led to increased academic research. This study aims to investigate the relationship between Institutional Quality, digitalization, and sustainable development in SAARC and G8 countries. A sample of SAARC and G8 countries was selected for a nineteen-year period from 2004 to 2021. Digitalization is measured through Digital Innovation, E-Governance, ICT Exports, and Internet Users. Panel Regression was used for the analysis. The findings suggest that Institutional Quality and digitalization are crucial factors in achieving sustainable development and that G8 countries have higher levels of Institutional Quality and digitalization than SAARC countries. The study concludes with recommendations for policymakers to efficiently improve institutional quality and digitalization for achieving sustainable development.
Görtler Vortices in the Shock Wave/Boundary-Layer Interaction Induced by Curved Swept Compression Ramp
Authors: Chen Liang , Zhang Yue , Wang Juanjuan , Xue Hongchao , Xu Yixuan , Wang Ziyun , Tan Huijun
Published: September 2024

This study builds on previous research into the basic flow structure of a separated curved swept compression ramp shock wave/turbulence boundary layer interaction (CSCR-SWBLI) at the leading edge of an inward-turning inlet. We employ the ice-cluster-based planar laser scattering (IC-PLS) technique, which integrates multiple observation directions and positions, to experimentally investigate a physical model with typical parameter states at a freestream Mach number of 2.85. This study captures the fine structure of some sections of the flow field and identifies the presence of Görtler vortices (GVs) in the CSCR-SWBLI. It is observed that due to the characteristics of variable sweep angle, variable intensity interaction, and centrifugal force, GVs exhibit strong three-dimensional characteristics in the curved section. Additionally, their position is not fixed in the spanwise direction, demonstrating strong intermittence. As the vortices develop downstream, their size gradually increases while the number decreases, always corresponding to the local boundary layer thickness. When considering the effects of coupling of bilateral walls, it is noted that the main difference between double-sided coupling and single-sided uncoupling conditions is the presence of a large-scale vortex in the central plane and an odd number of GVs in the double-sided model. Finally, the existence of GVs in CSCR-SWBLI is verified through the classical determine criteria Görtler number (GT) and Floryan number (F) decision basis.
Genome-Wide Association Analysis for Submergence Tolerance at the Early Vegetative and Germination Stages in Wild Soybean (Glycine soja)
Authors: Tran Hai Anh , Jo Hyun , Nguyen Thi Cuc , Lee Jeong-Dong , Seo Hak Soo , Song Jong Tae
Published: September 2024

Cultivated soybean is an important legume crop that is generally sensitive to flooding stress, including submergence and waterlogging treatments. Wild soybeans, the ancestor of cultivated soybeans, have been potential genetic resources for resistance to abiotic or biotic stresses. The present study aimed to evaluate 163 wild soybean accessions for foliar damages at the early vegetative stage and 105 accessions for germination rates, normal seedling rates, and electrical conductivity at the germination stage under submergence stress. In addition, a genome-wide association study (GWAS) was conducted to identify genomic regions associated with phenotypic measurements at these two growth stages by using MLM and FarmCPU models with publicly available genotypic data. The phenotypic evaluation revealed six and three accessions were tolerant to submergence at the early vegetative and germination stages, respectively. Notably, only one wild soybean accession showed a tolerance reaction to submergence at two stages. Through GWAS analysis, 16 and 20 SNPs across different chromosomes were determined for the submergence-related traits at the early vegetative and germination stages, respectively. Based on the linkage disequilibrium block on the detected genomic regions, ten and four putative genes were identified at the early vegetative and germination stages, respectively. Of these genes, certain genes may be related to submergence stress in wild soybeans. Further studies should be performed to validate the function of these putative genes in the responses of wild soybeans to submergence stress.
Effects of Ageing on Surface Properties of Biochar and Bioavailability of Heavy Metals in Soil
Authors: Cui Zhengwu , Wang Yang , Wang Nan , Ma Fangfang , Yuan Yuyu
Published: September 2024

This study aims to explore the effects of biochar ageing on its surface properties and the bioavailability of heavy metals in soil. The biochar was subjected to chemical oxidation/dry–wet cycles (CDWs), chemical oxidation/freeze–thaw cycles (CFTs), and natural ageing (NT) to analyze changes in the elemental composition, pH, specific surface area, pore volume, and surface functional groups. Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) were applied to characterize the functional groups and microstructure, and the BCR sequential extraction method was employed to demonstrate the fractionation distribution of Cu, Cd, and Pb. The results showed that the CDWs and CFTs treatments significantly reduced the carbon content of the biochar (with a maximum reduction to 47.70%), increased the oxygen content (up to 49.17%), and notably increased the specific surface area and pore volume. The pH decreased significantly from 9.91 to 4.92 and 4.99 for the CDWs and the CFTs, respectively. The FTIR analysis indicated notable changes in hydroxyl and carboxyl functional groups, and the SEM revealed severe microstructural damage in biochar after the CDWs and CFTs treatments. The heavy metal fractionation analysis indicated that exchangeable Cu, Cd, and Pb significantly increased after the CDWs treatment, reaching 31.40%, 5.25%, and 6.79%, respectively. In conclusion, biochar ageing significantly affects its physicochemical properties and increases the bioavailability of heavy metals, raising concerns about its long-term remediation effectiveness.
A Preliminary Fuzzy Inference System for Predicting Atmospheric Ozone in an Intermountain Basin
Authors: Lawson John R. , Lyman Seth N.
Published: September 2024

High concentrations of ozone in the Uinta Basin, Utah, can occur after sufficient snowfall and a strong atmospheric anticyclone creates a persistent cold pool that traps emissions from oil and gas operations, where sustained photolysis of the precursors builds ozone to unhealthy concentrations. The basin’s winter-ozone system is well understood by domain experts and supported by archives of atmospheric observations. Rules of the system can be formulated in natural language (“sufficient snowfall and high pressure leads to high ozone”), lending itself to analysis with a fuzzy-logic inference system. This method encodes human expertise as machine intelligence in a more prescribed manner than more complex, black-box inference methods such as neural networks, increasing user trustworthiness of our model prototype before further optimization. Herein, we develop an ozone forecasting system, Clyfar, informed by an archive of meteorological and air-chemistry measurements. This prototype successfully demonstrates proof-of-concept despite rudimentary tuning. We describe our framework for predicting future ozone concentrations if input values are drawn from numerical weather prediction forecasts rather than observations as Clyfar initial conditions. We evaluate inferred values for one winter, finding our prototype demonstrates mixed performance but promise after optimization to deliver useful forecast guidance for decision-makers when forecast data are used as input. This early version model is the basis of ongoing optimization through machine learning.
SHS-Hydrogenation, Thermal Dehydrogenation, and Plasma Spheroidization to Produce Spherical Titanium Powders from Titanium Sponge
Authors: Cherezov Nikita , Fadeev Andrey , Samokhin Andrey , Alymov Mikhail
Published: September 2024

Additive manufacturing is a promising and actively developing method for the synthesis of metal products. The development of techniques for the production of spherical powder particles with specified properties from metals and alloys represents a significant challenge in the field of additive manufacturing. A new method for the production of titanium powders with spherical particles has been proposed, including the method of hydrogenation and dehydrogenation with subsequent spheroidization in thermal plasma. Titanium sponge, used as a feedstock, was saturated with hydrogen using the energy-efficient self-propagating high-temperature synthesis (SHS) method. The resulting hydride was then mechanically ground and then dehydrogenated by thermal decomposition in a vacuum furnace. The resulting precursor was subjected to plasma treatment, which resulted in a product (titanium powder) with a high degree of spheroidization. The physical, chemical, and technological parameters of the titanium powders were investigated. It was found that the final product, spherical titanium powder, has the necessary properties for use in additive manufacturing technologies.
A Hybrid System Based on Bayesian Networks and Deep Learning for Explainable Mental Health Diagnosis
Authors: Pavez Juan , Allende Héctor
Published: September 2024

Mental illnesses are becoming one of the most common health concerns among the population. Despite the proven efficacy of psychological treatments, mental illnesses are largely underdiagnosed, particularly in developing countries. A key factor contributing to this is the scarcity of mental health providers capable of diagnosing. In this work, we propose a novel method that combines the general capabilities and accuracy of Large Language models with the explainability of Bayesian Networks. Our system analyzes descriptions of symptoms provided by users and written in natural language and, based on these descriptions, asks questions to confirm or refine the initial diagnosis made by the deep learning model. We trained our model on a large-scale dataset collected from various internet sources, comprising over 2.3 million data points. The initial prediction from the Large Language model is refined through symptom confirmation questions derived from a probabilistic graphical model constructed by experts based on the DSM-5 diagnostic manual. We present results from symptom descriptions sourced from the internet and clinical vignettes extracted from behavioral science exams, demonstrating the effectiveness of our hybrid model in classifying mental health disorders. Our model achieves high accuracy in classifying a wide range of mental health disorders, providing transparent and explainable predictions.
Recommender System for University Degree Selection: A Socioeconomic and Standardised Test Data Approach
Authors: Delahoz-Domínguez Enrique J. , Hijón-Neira Raquel
Published: September 2024

This study introduces a novel recommender system that integrates academic performance and socio-demographic variables to provide personalised and contextually relevant recommendations for university degree selection. The system aims to optimise the alignment between students’ profiles and potential academic programmes by utilising advanced machine learning models, including XGBoost, Random Forest, GLMNET, and KNN. The research addresses a critical gap identified in the literature, where most existing systems rely solely on academic data, neglecting the significant impact of socioeconomic factors on educational decision-making. The proposed system demonstrates superior predictive accuracy through rigorous cross-validation and hyperparameter tuning compared to simpler models, such as linear regression. The results show that integrating socio-demographic data enhances the relevance of the recommendations, supporting students in making more informed choices. This approach contributes to educational equity by ensuring that guidance is tailored to each student’s unique circumstances, aligning with the sustainable development goal of quality education. The findings highlight the value of incorporating a comprehensive data-driven approach to improve educational outcomes and support more equitable decision-making processes.
Analysis of the Wear Parameters and Microstructure of High-Carbon Steel in Order to Identify Its Tribological Properties
Authors: Krawczyk Janusz , Frocisz Łukasz , Matusiewicz Piotr , Kopyściański Mateusz , Lech Sebastian
Published: September 2024

Alloyed high-carbon steels are materials primarily intended for components operating under conditions of intense tribological wear. The carbides present in the microstructure of these materials significantly contribute to improving the wear resistance of such alloys. However, changes in the morphology of these precipitates can considerably alter the wear rate, leading to a deterioration in the properties of the materials. Therefore, this study aims to analyze the influence of several factors on the tribological wear of alloyed high-carbon steel. The research included friction tests under various load conditions and different sliding paths. Additionally, the samples were subjected to heat treatment to change the morphology of the observed precipitates. The tribological tests were conducted in a block-on-ring configuration under dry friction conditions. The tribological tests were analyzed statistically using analysis of variance (ANOVA). The results of the statistical analysis indicated that the primary factor influencing the observed differences between the samples was the heat treatment time of the material. Additionally, there were no significant statistical differences when pressure and friction path were varied. These findings, in conjunction with the SEM studies, allowed for the evaluation of the wear mechanism. The results demonstrated that, within the adopted tribological system, no alterations in the wear mechanism were observed with changes in test parameters. The observed differences in wear properties between the samples were found to be related to their heat treatment. The heat treatment resulted in alterations to the particle size distribution, with the annealing of the material at an elevated temperature leading to the dissolution of finer particles within the material. An increase in the average diameter of the carbide present in the material was observed to improve the wear resistance of the alloy tested.
Performance Analysis of Pile Group Installation in Saturated Clay
Authors: Xiong Wenlin , Li Zihang , Hu Dan , Li Fen
Published: September 2024

In offshore pile engineering, the installation of jacked piles generates compaction effects within soil, thus further affecting previously installed adjacent piles. This study proposes a three-dimensional numerical model for pile group installation, soil consolidation, and loading analysis. Subsequently, the effect of pile spacing and pile length-to-diameter ratio on the deformation, internal forces, and vertical bearing capacity of adjacent piles are investigated. The results indicate that with an increase in pile center distance, the peak lateral displacement of the adjacent piles decreases, whereas the peak vertical displacement increases. As the pile length-to-diameter ratio increases, the peak vertical and lateral displacements of the adjacent piles are enhanced. In addition, the peak axial force of the adjacent piles initially decreases and then increases with the penetration depth of the subsequent pile, whereas the peak bending moment initially increases and then decreases. The vertical bearing capacity of the subsequent pile is significantly superior to that of the adjacent piles. Therefore, the effects of pile installation on adjacent piles should be included in pile engineering. The impact of the subsequent pile installation on the bearing capacity of adjacent piles can be significantly reduced by increasing the pile center distance and pile length-to-diameter ratio. The findings provide useful guidance for pile group engineering.
Features of Temporal Variability of the Concentrations of Gaseous Trace Pollutants in the Air of the Urban and Rural Areas in the Southern Baikal Region (East Siberia, Russia)
Authors: Shikhovtsev Maxim Y. , Molozhnikova Yelena V. , Obolkin Vladimir A. , Potemkin Vladimir L. , Lutskin Evgeni S. , Khodzher Tamara V.
Published: September 2024

This article presents the results of the automatic monitoring of the concentrations of gaseous impurities of sulfur and nitrogen oxides in the ground-level atmosphere of the urban and rural areas in the Southern Baikal region (East Siberia, Russia). The study was conducted from 2020 to 2023 at the urban Irkutsk station and the rural Listvyanka station located at a distance of 70 km from each other. We calculated the main statistical characteristics of the variations in the concentrations of nitrogen oxides and sulfur dioxide in the ground-level atmosphere and determined a nature of variability in their concentrations on various time scales: annual, weekly, and daily. Annual variabilities of gaseous pollutants in the ground-level atmosphere above the Irkutsk city and the Listvyanka settlement were similar and showed the highest values in winter and the lowest in summer. The daily and weekly dynamics of the nitrogen oxide concentrations in the urban area clearly depended on the increase in the road traffic during rush hours (morning and evening). In the rural area, there was no such dependence. In this area, the daily and weekly variability in the concentrations of nitrogen oxides and sulfur dioxide mainly depended on natural meteorological processes. The work systematizes the meteorological parameters at which the largest amount of anthropogenic impurities enters the air basin of Lake Baikal. The maximum values of acid-forming gas concentrations were observed when the air masses were transferred from the northwest direction, which corresponds to the location of sources in the territory of the Irkutsk–Cheremkhovo industrial hub—the largest concentration of anthropogenic objects in the Irkutsk region.
Long-Term Monitoring and Management of Genetically Modified Canola in Natural Environments: A 15-Year Study
Authors: Lim Hye Song , Choi Wonkyun , Jung Young Jun , Yoon A-Mi , Noh Donghyeon , Lee Jeong Hwan , Kim Chul Min , Lee Jung Ro
Published: September 2024

The unintentional release of living modified organisms (LMOs) into natural environments poses potential ecological risks, particularly in terms of gene flow and biodiversity loss. Since 2009, the Ministry of Environment (MOE) in South Korea has conducted an extensive monitoring project to detect and manage LMOs, with a primary focus on LM canola. This study evaluates the outcomes of the LMO monitoring project over the past 15 years (2009–2023), analyzing the distribution, persistence, and management of LM canola across various environments. Our findings reveal that LM canola predominantly proliferates along roadsides, with occasional occurrences at festival and planting sites. Out of 10,571 monitored sites, 4326 suspicious samples were collected, with a significant increase observed in 2017, underscoring the ongoing risk of accidental releases. This study highlights the critical role of specific environments in the spread of LM canola, and assesses the effectiveness of post-management strategies in controlling these populations. The National Institute of Ecology (NIE) has developed and implemented advanced monitoring protocols and post-management systems tailored to the characteristics of the monitoring sites and the nature of the LMOs. These efforts have been effective in controlling the spread of LM canola, thereby helping to preserve the biodiversity of South Korea’s natural environments. In conclusion, the proactive and adaptive strategies employed by the NIE are essential for mitigating the ecological risks associated with LMOs. Our study emphasizes the importance of on-going vigilance and the continuous refinement of monitoring and management practices to safeguard biodiversity and ecosystems.
Real-Time Optimization of Ancillary Service Allocation in Renewable Energy Microgrids Using Virtual Load
Authors: Abed Amir , Dobric Goran
Published: September 2024

The stability of global economies relies heavily on power systems (PS) that have sufficient operating reserves. When these reserves are insufficient, power systems become vulnerable to issues such as load shedding or complete blackouts. Maintaining grid stability becomes even more challenging with a high penetration of renewable energy sources (RES). However, RES, connected through power electronic devices, offer significant potential as ancillary service (AS) sources. Renewable energy-based microgrids (MG), which aggregate various RES resources and have substantial load control potential, further enhance the capability of AS provision from RES. The presence of diverse AS resources raises the question of how to dispatch ancillary service signals optimally to all resources. Most of the previous research work related to AS allocation relied on single-bus MG models. This paper proposes a detailed MG model for the optimal dispatching of ASs among the resources using Virtual Load, along with an optimization procedure to achieve the best results. The model incorporates voltage profiles and power losses for AS dispatching, and a comparative analysis is conducted to quantify the significance of grid modeling. The model and proposed procedure are tested using the CIGRE microgrid benchmark model. The results indicate that detailed modeling of MG can impact the results by 11%, compared to single-bus modeling, which qualifies detailed MG modeling for all future research work and shows the impact that modeling can have on technical and economic indicators of MG operation.
A Comparison of Local and Global Strategies for Exploiting Field Inversion on Separated Flows at Low Reynolds Number
Authors: Muscarà Luca , Cisternino Marco , Ferrero Andrea , Iob Andrea , Larocca Francesco
Published: September 2024

The prediction of separated flows at low Reynolds numbers is crucial for several applications in aerospace and energy fields. Reynolds-averaged Navier–Stokes (RANS) equations are widely used but their accuracy is limited in the presence of transition or separation. In this work, two different strategies for improving RANS simulations by means of field inversion are discussed. Both strategies require solving an optimization problem to identify a correction field by minimizing the error on some measurable data. The obtained correction field is exploited with two alternative strategies. The first strategy aims to the identification of a relation that allows to express the local correction field as a function of some local flow features. However, this regression can be difficult or even impossible because the relation between the assumed input variables and the local correction could not be a function. For this reason, an alternative is proposed: a U-Net model is trained on the original and corrected RANS results. In this way, it is possible to perform a prediction with the original RANS model and then correct it by means of the U-Net. The methodologies are evaluated and compared on the flow around the NACA0021 and the SD7003 airfoils.
Ecological and Cost Advantage from the Implementation of Flight Simulation Training Devices for Pilot Training
Authors: Maciejewska Marta , Kurzawska-Pietrowicz Paula , Galant-Gołębiewska Marta , Gołębiewski Michał , Jasiński Remigiusz
Published: September 2024

The paper discusses a case study of obtaining an airline pilot license in integrated training—the so-called “from zero to Airline Transport Pilot License”. The environmental implications of simulator-based training were examined across multiple dimensions. Key areas of research include the reduction of harmful exhaust gases pollution associated with traditional flight training activities. Based on our analysis, it can be stated that increasing the use of Flight Simulation Training Devices in pilot training should be significant consideration. This approach brings many benefits, especially ecological ones. Changing the training program and increasing the use of flight simulators can result in a reduction of CO2 emissions by up to 70%. Based on country specific electricity factors, CO2 emissions during flight training in each EU country were calculated. Using Levelized Cost of Electricity average value to calculate training costs in EU countries depends on the mix of energy sources (wind, photovoltaics, carbon and gas). The findings highlight the significant ecological advantages of simulator-based training methods in mitigating the environmental footprint of aviation operations. By seeking to minimize environmental disruption and increase training efficiency, the adoption of simulators is a sustainable approach to pilot training that is consistent with global efforts to mitigate climate change and protect natural ecosystems.
Specific Synbiotic Sugars Stimulate Streptococcus salivarius BLIS K12 and BLIS M18 Lantibiotic Production to Expand Bacterial Inhibition Range and Potency
Authors: Harold Liam K. , Jones Nicola C. , Barber Sarah L. , Voss Abigail L. , Jain Rohit , Tagg John R. , Hale John D. F.
Published: September 2024

Synbiotics are mixtures of prebiotics and probiotics that enhance the activity of probiotic bacteria when co-administered to provide greater benefits to the host. Traditionally, the synbiotics that have been discovered enhance gut probiotic strains and are nutritionally complex molecules that survive digestive breakdown until they reach the later stages of the intestinal tract. Here, we screened and identified sugars or sugar substitutes as synbiotics for the oral probiotic strains Streptococcus salivarius BLIS K12 and BLIS M18. Using a modified deferred antagonism assay, we found that 0.5% (w/v) galactose and 2.5% (w/v) raffinose were the best candidates for use as synbiotics with BLIS K12 and M18, as they trigger enhanced antimicrobial activity against a range of bacteria representing species from the mouth, gut, and skin. Using reverse transcriptase quantitative PCR, we found that this enhanced antimicrobial activity was caused by the upregulation of the lantibiotic genes salA, salB, and sal9 in either K12 or M18. This led to the conclusion that either 2.5% (w/v) raffinose or 0.5% (w/v) galactose, respectively, are suitable synbiotics for use in conjunction with BLIS K12 and M18 to enhance probiotic performance.
Evaluation of the Performance of Neural and Non-Neural Methods to Classify the Severity of Work Accidents Occurring in the Footwear Industry Complex
Authors: da Silva Jonhatan Magno Norte , da Silva Braz Maria Luiza , da Silva Joel Gomes , Bispo Lucas Gomes Miranda , dos Santos Leite Wilza Karla , de Araujo Vieira Elamara Marama
Published: September 2024

In the footwear industry, occupational risks are significant, and work accidents are frequent. Professionals in the field prepare documents and reports about these accidents, but the need for more time and resources limits learning based on past incidents. Machine learning (ML) and deep learning (DL) methods have been applied to analyze data from these documents, identifying accident patterns and classifying the damage’s severity. However, evaluating the performance of these methods in different economic sectors is crucial. This study examined neural and non-neural methods for classifying the severity of workplace accidents in the footwear industry complex. The random forest (RF) and extreme gradient boosting (XGBoost) methods were the most effective non-neural methods. The neural methods 1D convolutional neural networks (1D-CNN) and bidirectional long short-term memory (Bi-LSTM) showed superior performance, with parameters above 98% and 99%, respectively, although with a longer training time. It is concluded that using these methods is viable for classifying accidents in the footwear industry. The methods can classify new accidents and simulate scenarios, demonstrating their adaptability and reliability in different economic sectors for accident prevention.
Model-Based Design of LFP Battery Thermal Management System for EV Application
Authors: Sophy-Mahfoudi Nadjiba , Sekharam Sai-Vandhan , Boutaous M’hamed , Xin Shihe
Published: September 2024

This study uses an equivalent circuit model (ECM) and real-time data to model lithium iron phosphate (LFP) batteries to accurately represent their thermo-electrical behavior. In particular, the focus is on a thermal management perspective in high-performance electric vehicles (EVs). The ECM-based battery management system, which effectively captures the non-linear behavior of Li-ion batteries, is developed to optimize the safety, lifespan and overall performance of the EV battery management system. The ECM-based battery model is validated using real-time drive cycle data to enhance the understanding of battery management systems, contributing to improved overall performance and reliability. In addition, advanced estimation algorithms, such as the extended Kalman filter, are integrated to further improve the predictive capabilities of battery parameters. Battery terminal voltage prediction with an average RMSE error of 0.015% is achieved, highlighting the critical role of ECMs and advanced numerical simulation methods in optimizing the performance of automotive battery management systems. The achieved results provide important guidance for model-based design validation and functional development of battery management for mobility applications.
SAAZ—Fine Aroma Hop Pedigree: A Review of Current Knowledge
Authors: Olšovská Jana , Straková Lenka , Nesvadba Vladimír , Vrzal Tomáš , Malečková Michaela , Patzak Josef , Donner Pavel
Published: September 2024

The hop variety Saaz is well known over the world and is usually used for brewing of lager beers. Recently, the new related varieties Saaz Late, Brilliant, Comfort, and Shine were registered. Information about these varieties is splintered and often available only in the Czech language in regional journals. This review (i) summarizes previously published data (breeding history, genetic data, basic parameters such as yield, sensory profile, concentrations of key technologically important hop compounds), (ii) presents long-term data (2004–2021), and (iii) shows similarities/differences among these varieties. All Saaz varieties are typically fine aroma hops with a relatively low content of alpha bitter acids ranging from 5 to 7 wt%, cohumulone amounts lower than 30% rel., and hop oil content of about 1.0 wt%. Even though the new varieties have no identical chemical parameters to the original Saaz, they can substitute this established standard as well. Furthermore, the varieties Saaz Comfort and Saaz Shine show high resistance to Pseudoperonospora humuli as well as very good tolerance to drought.
Deciphering the Potentials of Cardamom in Cancer Prevention and Therapy: From Kitchen to Clinic
Authors: Bano Shabana , Majumder Avisek , Srivastava Ayush , Nayak Kasturi Bala
Published: September 2024

Cardamom (cardamum) is a spice produced from the seeds of several Elettaria and Amomum plants of the Zingiberaceae family. Cardamom has been demonstrated to offer numerous benefits, including its antioxidant, antimicrobial, anti-inflammatory, and other metabolic (anti-diabetic) properties, and its potential to reduce cancer risk. Recently, researchers have extracted and tested multiple phytochemicals from cardamom to assess their potential effectiveness against various types of human malignancy. These studies have indicated that cardamom can help overcome drug resistance to standard chemotherapy and protect against chemotherapy-induced toxicity due to its scavenging properties. Furthermore, chemical compounds in cardamom, including limonene, cymene, pinene, linalool, borneol, cardamonin, indole-3-carbinol, and diindolylmethane, primarily target the programmed cell death lignin-1 gene, which is more prevalent in cancer cells than in healthy cells. This review provides the medicinal properties and pharmacological uses of cardamom, its cellular effects, and potential therapeutic uses in cancer prevention and treatment, as well as its use in reducing drug resistance and improving the overall health of cancer patients. Based on previous preclinical studies, cardamom shows significant potential as an anti-cancer agent, but further exploration for clinical use is warranted due to its diverse mechanisms of action.
Inhalation Anesthetics Play a Janus-Faced Role in Self-Renewal and Differentiation of Stem Cells
Authors: Hao Xiaotong , Li Yuan , Gao Hairong , Wang Zhilin , Fang Bo
Published: September 2024

Inhalation anesthesia stands as a pivotal modality within clinical anesthesia practices. Beyond its primary anesthetic effects, inhaled anesthetics have non-anesthetic effects, exerting bidirectional influences on the physiological state of the body and disease progression. These effects encompass impaired cognitive function, inhibition of embryonic development, influence on tumor progression, and so forth. For many years, inhaled anesthetics were viewed as inhibitors of stem cell fate regulation. However, there is now a growing appreciation that inhaled anesthetics promote stem cell biological functions and thus are now regarded as a double-edged sword affecting stem cell fate. In this review, the effects of inhaled anesthetics on self-renewal and differentiation of neural stem cells (NSCs), embryonic stem cells (ESCs), and cancer stem cells (CSCs) were summarized. The mechanisms of inhaled anesthetics involving cell cycle, metabolism, stemness, and niche of stem cells were also discussed. A comprehensive understanding of these effects will enhance our comprehension of how inhaled anesthetics impact the human body, thus promising breakthroughs in the development of novel strategies for innovative stem cell therapy approaches.
Deep Learning-Based Biomimetic Identification Method for Mask Wearing Standardization
Authors: Yan Bin , Li Xiameng , Yan Wenhui
Published: September 2024

Deep learning technology can automatically learn features from large amounts of data, with powerful feature extraction and pattern recognition capabilities, thereby improving the accuracy and efficiency of object detection. [The objective of this study]: In order to improve the accuracy and speed of mask wearing deep learning detection models in the post pandemic era, the [Problem this study aimed to resolve] was based on the fact that no research work has been reported on standardized detection models for mask wearing with detecting nose targets specially. [The topic and method of this study]: A mask wearing normalization detection model (towards the wearing style exposing the nose to outside, which is the most obvious characteristic of non-normalized style) based on improved YOLOv5s (You Only Look Once v5s is an object detection network model) was proposed. [The improved method of the proposed model]: The improvement design work of the detection model mainly includes (1) the BottleneckCSP (abbreviation of Bottleneck Cross Stage Partial) module was improved to a BottleneckCSP-MASK (abbreviation of Bottleneck Cross Stage Partial-MASK) module, which was utilized to replace the BottleneckCSP module in the backbone architecture of the original YOLOv5s model, which reduced the weight parameters’ number of the YOLOv5s model while ensuring the feature extraction effect of the bonding fusion module. (2) An SE module was inserted into the proposed improved model, and the bonding fusion layer in the original YOLOv5s model was improved for better extraction of the features of mask and nose targets. [Results and validation]: The experimental results indicated that, towards different people and complex backgrounds, the proposed mask wearing normalization detection model can effectively detect whether people are wearing masks and whether they are wearing masks in a normalized manner. The overall detection accuracy was 99.3% and the average detection speed was 0.014 s/pic. Contrasted with original YOLOv5s, v5m, and v5l models, the detection results for two types of target objects on the test set indicated that the mAP of the improved model increased by 0.5%, 0.49%, and 0.52%, respectively, and the size of the proposed model compressed by 10% compared to original v5s model. The designed model can achieve precise identification for mask wearing behaviors of people, including not wearing a mask, normalized wearing, and wearing a mask non-normalized.
Consumer Readiness for Microtransactions in Digital Content Business Models
Authors: Chaudhary Pankaj , DaSouza Richelle Oakley
Published: September 2024

As digital content increasingly moves away from free access, microtransactions may provide an alternative. There is a need for research on microtransactions as a general digital content payment mechanism. Businesses can capitalize on this technological advancement by expanding their paid digital content offerings without resorting to subscription-based services. This study examines a taxonomy for microtransactions based on consumer buying behavior, presents business models for microtransaction payment processing, and examines issues with its implementation. Data collected from 180 consumers were analyzed using quantitative and qualitative analyses to assess the receptiveness and perception of microtransactions. The results indicate that consumers are receptive to the concept of microtransactions and are willing to spend on five distinct digital content categories. This study concludes with a discussion of issues that consumers foresee with digital content microtransactions and implications for interested businesses.
Progress in the Application of Bronchoscopic Cryotherapy in Pediatric Pulmonary Diseases
Authors: Tao Xiaofen , Li Shuxian , Wu Hujun , Jin Fang , Jin Guoping , Wu Lei
Published: September 2024

Cryotherapy in interventional bronchoscopy is a new treatment modality which has recently been made available for the pediatric airway. Lack of experience and safety concerns have led to hesitant adaptation. The aim of this work was to elaborate on the application progress of cryotherapy in pediatric pulmonary diseases and also to assess indications, success rates, and complications of airway cryotherapy in children. In summary, cryotherapy via flexible bronchoscopy is a safe and feasible method. The application scope in pediatrics is similar to that in adults, and it is mainly used in airway obstructive diseases. However, it is primarily caused by benign conditions, and the interventional treatment mainly seeks to provide long-lasting symptomatic alleviation. Thus, prevention, treatment, and prognosis of long-term complications are issues that should be carefully considered in pediatric applications.
Delphi/AHP-Based Method for Biomass Sustainable Assessment in the Sugar Industry
Authors: Jiménez Borges Reinier , Alvarez-Gonzalez Andres Lorenzo , Iturralde Carrera Luis Angel , Bravo Amarante Edelvy , Castillo Alvarez Yoisdel , Rodríguez Pérez Berlan , Álvarez-Alvarado José M. , Rodríguez-Reséndiz Juvenal
Published: September 2024

Multi-criteria methods are highly attractive tools to address the inherent complexity of evaluating problems in various scientific areas. The combination of methods such as Delphi/AHP is emerging as a robust alternative to evaluate the sustainability of renewable energy sources. In this theoretical-descriptive research, the use of the Delphi method is proposed to select criteria and sub-criteria to obtain a high level of reliability, while the AHP method is used to establish an order of preference among the alternatives analyzed. This process requires the support of a committee of experts, whose role is to identify the various biomass alternatives that can be used in the sugar industry, considering aspects related to sustainability. The selected experts have identified energy, exergy, and emergetic indicators, in which economic, environmental, and social aspects are integrated. The multi-criteria analysis shows that the V1 variant was the most satisfactory in terms of biomass sustainability, representing 45% and 53% of the overall priorities in the evaluated case studies. In addition, the sensitivity analysis under an equal-weighted scenario for both study cases evidenced that variant V1 acquired the highest score (38.17%) among all alternatives. Variant V4 achieved the second highest score (31.79%), while alternative V2 achieved only 29.04%, respectively. The integration of Delphi/AHP methods emerges as a novel tool to assess sustainability in different industries of the energy sector.
Alcohol Consumption and Cancer Risk: Two Sample Mendelian Randomization
Authors: Jee Yongho , Ryu Mikyung , Sull Jae-Woong
Published: September 2024

Although numerous observational studies have reported on the association between alcohol consumption and cancer, insufficient studies have estimated the causality. Our study evaluated the causal relationship between various types of cancer according to the frequency of drinking and the amount of alcohol consumed. The research data were obtained from the publicly available MR-Base platform. The frequency and amount of drinking were selected as the exposure, and 16 cancer types were selected as the outcome. Two-sample summary data Mendelian randomization (2SMR) was conducted to examine the causality between alcohol consumption and cancer type. Additionally, for cancers suspected of pleiotropy, outliers were removed and re-analyzed through radial MR. The MR results using the inverse variance weighted (IVW) method were different before and after removing outliers. The biggest differences were found for esophageal cancer and biliary tract cancer. For esophageal cancer, after removing outliers (rs13102973, rs540606, rs650558), the OR (95% CI) was 3.44 (1.19–9.89), which was statistically significant (p = 0.02172). Even in biliary tract cancer, after removing outliers (rs13231886, rs58905411), the OR (95% CI) was 3.86 (0.89–16.859), which was of borderline statistical significance (p = 0.07223). The strongest association was found for esophageal cancer. For other cancers, the evidence was not sufficient to draw conclusions. More research is needed to understand the causality between drinking and cancer.
Development of Potentially Probiotic Mead from Co-Fermentation by Saccharomyces cerevisiae var. boulardii and Kombucha Microorganisms
Authors: Souza Handray Fernandes de , Freire Eduardo Novais Souza , Monteiro Giovana Felício , Bogáz Lorena Teixeira , Teixeira Ricardo Donizete , Junior Fabiano Vaquero Silva , Teixeira Felipe Donizete , Santos João Vitor dos , Carvalho Marina Vieira de , Rocha Ramon da Silva , da Cruz Adriano Gomes , Bell Juliana Maria Leite Nobrega de Moura , Brandi Igor Viana , Kamimura Eliana Setsuko
Published: September 2024

Mead is a fermented alcoholic beverage produced from a diluted solution of honey and yeast activity. The objectives of this study were to produce a potentially probiotic mead through mixed fermentation by Saccharomyces cerevisiae var. boulardii and kombucha microorganisms and to evaluate fermentation kinetics, microbial cell survival and their in vitro resistance to simulated gastrointestinal transit, color parameters and the phenolic and antioxidant potential of the product. The main results of this study show that in order to develop a potentially probiotic mead utilizing the mixed fermentation of S. boulardii and kombucha microorganisms, the best condition was a concentration of 25 mL/L (v/v) of kombucha and 0.75 g/L (w/v) of S. boulardii with fermentation for 9 days at a temperature of 25 °C. In addition, at the end of fermentation, mead with kombucha and S. boulardii presented physicochemical characteristics with a pH of 3.48, 0.67% total acidity, 18.76 °Brix soluble solids and 4.77% alcohol content. The S. boulardii and lactic acid bacteria (LAB) present in the mead survived conditions reproducing those of the gastrointestinal tract, with counts of more than 6 Log10 CFU/mL for both microorganisms after the intestinal phase. In the color analysis, the mead with kombucha and S. boulardii had a yellow color with the b* parameter corresponding to 35.93, luminosity (L*) equal to 76.09 and 1.82 for a*. In addition, the mead we produced contains quantities of phenolics and antioxidants. In conclusion, kombucha and S. boulardii are presented as alternative microbial sources for obtaining potentially probiotic mead.