bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Improved Model Predictive Current Control of BLDC Motor With a Novel Adaptive Extended Kalman Filter–Based Back EMF Estimator and a New Commutation Duration Approach for Electrical Vehicle
Authors: Inan Remzi 
Published: December 2024

ABSTRACTAs a result of the increasing use of electric vehicles, ensuring high‐performance speed and torque control of brushless direct current (BLDC) motors has become of great importance for energy efficiency. In order to prevent the torque ripple of the finite control set model predictive current control (FCS‐MPCC), commutation moments are detected by Hall effect sensors in conventional methods. However, this method cannot exhibit a long‐life structure because of physical strain damaging the sensors and electrical connections. In this study, commutation moments and durations are captured and determined with a new approach. Commutation moments are captured with zero crossing detectors and commutation durations are determined by using the position information obtained from the encoder. Moreover, three‐phase back electromotive forces (EMFs) of the BLDC motor applied to FCS‐MPCC to predict the stator phase currents are estimated with a novel adaptive extended Kalman filter (AEKF) which has the estimation capability without any speed sensor. Furthermore, another improvement is implemented in the calculation of the cost function of FCS‐MPCC by taking into account the difference between the predicted and the reference torque of the BLDC motor different from the conventional MPCC methods. The proposed drive system is tested under different scenarios at various speeds under load torque, stator resistance, and leakage inductance variations in simulation. It is proven by simulation results that phase commutations can be achieved stably with the proposed phase commutation determination method. In addition, the simulation results show that the proposed novel AEKF estimator and the FCS‐MPCC in which the cost function is calculated by regarding not only the current error but also the moment error have impressive prediction and control performance, respectively.
CARNet: An Efficient Cascaded and Attention‐Based RNN Architecture for Modulation Classification in Cognitive Radio Network Using Improved Kookaburra Optimization Strategy
Authors: N Venkateswara Rao , Krishna B. T. 
Published: December 2024

ABSTRACTIn cognitive radio (CR) networks, the automatic modulation classification (AMC) is considered as the significant role in smart wireless communications. Due to the high growth of deep learning in the modern days, neural network‐aided automated modulation categorization tasks have become highly demanded. Nevertheless, an enormous amount of attributes and the neural network's complexity make them complex to adopt in various scenarios. Moreover, the receiver systems are limited by the latency and less storage resources. Additionally, the detection system of the signal modulation is mostly hampered by overfitting issues and insufficient information. Therefore, a robust AMC model based on adaptive deep learning is implemented to determine the type of modulation used at the transmitter by observing the received signal. Initially, the necessary raw data for the suggested model is garnered from benchmark dataset. Also, the optimal features from the raw data are selected with the help of the fitness‐revised position updating in Kookaburra optimization (FPUKO) for minimizing the computation time and enhancing the accuracy rates in the classification process. Moreover, this optimal feature selection makes the modulation selection process quick and efficient. Finally, the optimal features are fed to a cascaded and attention‐based recurrent neural network (CA‐RNN) in the modulation classification, which is designed to classify the type of modulation used on the transmitter side. Various experiments are conducted for the designed framework by comparing it with the existing models to view its efficiency.
Tea Tree Oil Delays Kiwifruit Ripening Through Regulating Energy Metabolism
Authors: Fu Changchun , Zhu Shiyan , Ni Ying , Chen Hangjun , Han Yanchao 
Published: December 2024

ABSTRACTKiwifruit is easy to ripen and soften after harvest. Tea tree oil (TTO) has important application value in postharvest fruit preservation. However, the effect of TTO on kiwifruit fruit ripening, quality maintenance and energy metabolism, has not been studied. In this research, we found that TTO could delay ‘Xuxiang’ kiwifruit ripening, and keep good quality even after 18 days of storage. In three different concentrations of TTO treatments, 2.0 mL L−1 TTO has the best preservation effect on kiwifruit. TTO slowed down the softening and degreening, reduced the respiration intensity and delayed the peak of respiration. Moreover, TTO also delayed the decrease of total sugar, titratable acid (TA) and vitamin C (Vc). The fruit treated with TTO kept higher levels of ATP, ADP and energy charge (EC), and higher activities of succinate dehydrogenase (SDH), cytochrome C oxidase (CCO) and ATPase. Correlation analysis results showed that kiwifruit ripening was closely related to nutritional quality and energy metabolism. To summarize, TTO could delay kiwifruit ripening and keep fruit quality by maintaining higher energy level and activities of energy metabolism‐related enzymes during the late storage. This study will provide theoretical and technical support for kiwifruit preservation.
Analysis of Volatile Substances Difference in Hazelnut Soy Sauce at Different Fermentation Stages Based on HS‐SMPE‐GC/MS
Authors: Fu Miao , Zou Chenyang , Lyu Chunmao , Tian Chuan , Wu Yanyan , Chen Le , Jiang Han 
Published: December 2024

ABSTRACTHazelnut meal, as a by‐product of hazelnut oil extraction, is not only rich in protein but also has the potential to become a high‐quality plant protein source. In this study, we innovatively developed a novel hazelnut soy sauce product using hazelnut meal as the main raw material. The volatile components of hazelnut soy sauce in different fermentation stages were analysed by HS‐SPME‐GC/MS technique. The results of the analysis showed that 127 different volatile substances were identified in the samples tested, including alcohols, aldehydes, acids, esters, ketones, phenols, furans, pyrazines and other categories. In addition, we found that there were significant differences in the volatile components of hazelnuts soy sauce at different fermentation stages, and these differences were mainly driven by eight key volatile substances such as isoamyl acetate, phenylethanol, 1‐octene‐3‐ol, phenylacetaldehyde, benzaldehyde, ethyl acetate, isoamylaldehyde and 2,6‐dimethylpyrazine. This study not only provides a preliminary insight into the dynamic changes of volatile substances in hazelnut soy sauce during fermentation but also opens up a new way for high‐value utilisation of hazelnut meal.
Money Matters: Broad Divisia Money and the Recovery of the US Nominal GDP From the COVID‐19 Recession
Authors: Bordo Michael D. , Duca John V. 
Published: December 2024

ABSTRACTThe rise of inflation in 2021 and 2022 surprised many macroeconomists who ignored the earlier surge in money growth because of past instability in the demand for simple‐sum monetary aggregates. We find that the demand for more theoretically based Divisia aggregates can be modeled and that these aggregates provide useful information about nominal GDP. Unlike M2 and Divisia‐M2, whose velocities do not internalize shifts in liabilities across commercial and shadow banks, the velocities of broader Divisia monetary aggregates are stable and can be empirically modeled through the Covid‐19 pandemic. In the long run, these velocities depend on regulation and mutual fund costs that affect the substitutability of money for other financial assets. In the short run, we control for swings in mortgage activity and use vaccination rates and the stringency of government pandemic restrictions to control for the unusual pandemic effects. The velocity of broad Divisia money declines during crises like the Great and COVID Recessions but later rebounds. In these recessions, monetary policy lowered short‐term interest rates to zero and engaged in quantitative easing of about $4 trillion. Nevertheless, broad money growth was more robust in the COVID Recession, reflecting a less impaired banking system that promoted rather than hindered deposit creation. Our framework implies that nominal GDP growth and inflation rebounded more quickly from the COVID Recession versus the Great Recession. Our different scenarios for future Divisia money growth and the unwinding of the pandemic have different implications for medium‐term nominal GDP growth and inflationary pressures.
Guidelines for establishing models of immunomodulatory in Caenorhabditis elegans
Authors: Ouyang Boya 
Published: December 2024

AbstractCaenorhabditis elegans is a popular model for studying the interaction between bacterial pathogens, viruses, fungi, and the innate immune system of metazoans. When exposed to a pathogenic organism, a clear response is elicited in the C. elegans which is characterized by specific alterations on the transcriptional and translational levels. In this guideline, we describe the current use of pathogens as media to infect C. elegans and study host immune regulation, and elaborate on how to accurately establish pathogenic models of innate immunity and host–pathogen interactions, which is conducive to researchers to establish corresponding models and effective killing methods according to their own research directions, and then conduct more in‐depth research on immune regulatory mechanisms at biological and molecular levels.
Alcohol and the Medical Community: A Cocktail for Exclusion
Authors: Ellythy Luqman M. , Michel Ian M. , Farkouh Elizabeth K. , Padela Aasim I. 
Published: December 2024

AbstractAlcohol is a class 1 carcinogen, and its use, at any level, is not safe for health. Despite this, alcohol remains strongly mixed into medical culture and is often served free at medical‐community events. This presents numerous ethical concerns. First, the funding of alcohol‐centered events by the medical community reinforces alcohol consumption as a coping mechanism for stress, perpetuates the perceived need for alcohol for socialization, and falsely implies that it is a safe substance. Additionally, the medical community is increasingly diverse, including Muslims, Mormons, those in recovery from substance use disorders, pregnant individuals, and individuals from homes and communities damaged by alcohol. Due to their moral or safety concerns, these individuals may miss opportunities to network and engage in professional development when alcohol is present. Therefore, alcohol acts as a barrier to diversity, equity, and inclusion efforts and can result in pernicious downstream effects for minority patient populations.
The Insidious Foreseeability Revolution
Authors: Appel Jacob M. 
Published: December 2024

AbstractThe laws of medical malpractice have historically differed in significant ways from general liability laws. Until the mid‐twentieth century, physician liability in the United States was limited to cases in which the doctor and patient had an established professional relationship. In the 1970s, courts and legislatures began carving out exceptions when patients posed an imminent threat to identifiable third parties. Recently, a series of cases involving circumstances such as curbside consultation, threats of violence, and automotive accidents have led some state courts to abandon the requirement of a preexisting physician‐patient relationship. Instead, the courts now focus on whether foreseeable reliance is present. While these developments may significantly impact clinical practice, the connections between these cases have gone largely overlooked by both the medical and bioethics communities. This essay aims to highlight these parallel developments and to suggest that this evolution reflects a broader trend with implications far beyond the individual cases themselves.
Incentives, Health, and Retirement: Evidence From a Finnish Pension Reform
Authors: Ollonqvist Joonas , Kotakorpi Kaisa , Laaksonen Mikko , Martikainen Pekka , Pirttilä Jukka , Tarkiainen Lasse 
Published: December 2024

ABSTRACTThis paper examines, using exogenous variation generated by a Finnish pension reform implemented in 2005, the interplay between health and financial incentives to postpone retirement. Based on detailed administrative data on individual health and retirement behavior, we focus on whether individual reactions to incentives vary according to health status and analyze whether individuals with ill health are also able to take advantage of the potential monetary benefits of delayed retirement created by the reform. We find that on average, individuals react to the financial incentives created by the reform as expected. This result holds for most of the health‐related subgroups we analyze. However, those with a long period of sickness absence are less likely to respond to changes in the financial incentives to postpone retirement.
Prevalence, Predictors, and Outcomes of HIV Care in HIV‐Positive Clients Entering HIV Care With Advanced HIV Disease in Sub‐Saharan Africa 2010–2022: Systematic Review and Meta‐Analysis
Authors: Haumba Samson , Arora Shreya , Williams Victor , Maseko Thokozani , Mafukidze Arnold , Ojoo Sylvia 
Published: December 2024

ABSTRACTBackground and AimsSub‐Saharan Africa drives global HIV‐related mortality, and patients continuously present with advanced HIV disease (AHD) at diagnosis. We describe prevalence, predictors, and treatment outcomes in HIV clients with AHD.MethodsWe systematically reviewed PUBMED, SCOPUS, Web of Science, JSTOR, and CINAHL for relevant studies conducted in Sub‐Saharan Africa from 2010 to 2022. We used a narrative synthesis to describe included studies and a random effect meta‐analysis to determine AHD pooled prevalence. The Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) checklist guided the reporting, while the Joanna Briggs Institute's quality assessment checklist assessed the quality of included articles. Cochrane's Q and the I2 tests assessed heterogeneity between included studies.ResultsWe included 24 studies with a sample size of 322,676. Prevalence of AHD ranged from 11.0% to 89.7% with an overall pooled prevalence of 58.7% (95% CI: 51.3%, 66.0%): 66.1% (95% CI: 58.8%, 73.4%) between 2010 and 2016, and 51.2% (95% CI: 37.7%, 64.6%) from 2017 to 2022. Predictors of AHD include male sex, older age (≥ 35), widowed or divorced, unemployment, gap in care of ≥ 12 months before antiretroviral therapy (ART) initiation, no history of HIV testing, and seeking care from a traditional healer before presenting for HIV care. Loss to follow‐up ranged from 6.7%–58.3%, while the proportion of death ranged from 1.8%–13.1%. Predictors of death were being male, advanced age (≥ 50 years), advanced clinical stages, late ART initiation, higher mean log viral load, CD4+ cell count < 50 cells/mm3 and severe anaemia.ConclusionsThe high baseline prevalence of AHD suggests the need for targeted, people‐centred HIV testing in Sub‐Saharan Africa. Country HIV programs should accelerate the implementation of comprehensive HIV services that identify clients at risk of AHD for early enrolment with systems for monitoring the WHO care package for preventing, diagnosing, and treating AHD and associated comorbid conditions.PROSPERO number: 2022 CRD42022336487.
Cervical Cancer Screening Practice and Associated Factors Among School Teachers in Bahir Dar City, North West Ethiopia: A Cross‐Sectional Study
Authors: Nega Bezawit Getachew , Yadita Zemenu Shiferaw , Misker Agernesh Dereje , Ebrahim Ammar Bishaw , Asresie Melash Belachew 
Published: December 2024

ABSTRACTBackground and AimsDespite its prioritization by the World Health Organization, improving access to cervical cancer screening remains a challenge in Ethiopia. Educated individuals, particularly teachers, are viewed as key influencers in promoting healthy lifestyles among youth and can significantly contribute to cervical cancer prevention. However, there is a notable gap in research regarding cervical cancer screening practices among female educators in the studied region. This study aimed to assess the cervical cancer screening practices and associated factors among female school teachers in Bahir Dar, Ethiopia, 2024.MethodsA school‐based cross‐sectional study was conducted from May 27 to June 28, 2024, involving 561 female school teachers in Bahir Dar City, using a stratified multistage sampling method. Data were gathered through a pretested structured questionnaire, entered in Epi‐data version‐4.6, and analyzed with SPSS version‐23. Bi‐variable and multivariable binary logistic regression analyses were performed, considering variables with p values < 0.05 as statistically significant. Multicollinearity was assessed, and the Hosmer–Lemeshow test evaluated the model's fit.ResultsThe proportion of female school teachers practicing cervical cancer screening was 14.6% (95% CI: 11.57%–17.66%). Significant factors associated with screening included having more than one lifetime sexual partner (AOR = 2.96, 95% CI: 1.48–4.92), a history of gynecological examinations (AOR = 2.59, 95% CI: 1.28–5.23), a fair understanding of cervical cancer (AOR = 2.16, 95% CI: 1.12–4.17), a positive attitude toward screening (AOR = 3.23, 95% CI: 1.65–6.33), and a high perceived susceptibility to cervical cancer (AOR = 2.57, 95% CI: 1.34–4.93).ConclusionsCervical cancer screening rates among female school teachers in Bahir Dar City fall short of the HSTP‐II target. Independent predictors of screening include having multiple sexual partners, a history of gynecological exams, knowledge of cervical cancer, attitudes toward screening, and perceived susceptibility. To improve these rates, initiatives should focus on raising awareness and fostering positive attitudes among teachers about cervical cancer and health‐seeking behavior.
Food Safety Knowledge, Attitudes, Practices, and Associated Factors Among Adult Consumers in Bangladesh: Findings From a Nationwide Cross‐Sectional Survey
Authors: Roy Nitai , Aktarujjaman Mohammad , Siddiky Aysha , Mollick Kakali , Rosby Raphyel , Rogers Bryan T. , Hossain Ekhtear , Al Mamun Firoj , Mamun Mohammed A. 
Published: December 2024

ABSTRACTAimThis study aimed to evaluate the food safety knowledge, attitudes, and practices (KAP) of Bangladeshi consumers and investigate their associations with various demographic factors.MethodsThis national cross‐sectional study utilized a face‐to‐face survey using a structured questionnaire to recruit 1400 adult consumers between September 2022 and November 2022. Multiple linear regression analysis was employed to determine the factors associated with the food safety KAP.ResultsThe current findings revealed that consumers had moderate knowledge (overall correct response rate of 65.3% with a mean score of 13.06 ± 2.88 on a scale of 0 to 20), excellent attitudes (overall correct response rate for food safety knowledge was 81.8% with a mean score of 14.72 ± 2.72 on a scale of 0 to 18), and relatively poor practices (overall correct response rate was 51.7% with a mean score of 35.17 ± 11.2 on a scale of 0 to 68). Participants who were male, had higher education, were employed, were familiar with the Bangladesh Food Safety Authority, and residing outside the Mymensingh division, demonstrated greater food safety knowledge. However, participants from Barisal, Rangpur, and Dhaka, who were less educated, had fewer children, and only occasionally cooked, had negative attitudes about food safety. Additionally, individuals from all administrative divisions except Mymensingh and Chittagong, who were employed, had fewer children, had experienced food poisoning, and had inadequate food safety practices.ConclusionThese findings suggest that the Bangladeshi government should intensify efforts to enhance consumer awareness regarding food safety.
Hybrid Drought Forecasting Framework for Water‐Scarce Regions Based on Support Vector Machine and Precipitation Index
Authors: Alsumaiei Abdullah A. 
Published: December 2024

ABSTRACTDrought is a natural event that slowly deteriorates water reserves. This study aims to develop a machine learning–based computational framework for monitoring drought status in water‐scarce regions. The proposed framework integrates the precipitation index (PI) with support vector machine models to forecast drought occurrences based on an autoregressive modelling scheme. Due to the suitability of the PI for drought analysis in arid climates, the developed hybrid model is appropriate in regions with limited rainfall. This study used a historical precipitation dataset from 1958 to 2020 at the Kuwait International Airport, Kuwait City. The study area is characterised by scarce rainfall and is vulnerable to severe water shortages owing to limited water resources. Initially, historical PI time‐series datasets were examined for stationarity to validate the utility of the autoregressive model. The autocorrelation function test was significantly associated with the PI time series at the 12‐ and 24‐month drought‐monitoring scales. Predictive drought forecasting models were constructed to predict drought occurrences up to 3 months in advance. Statistical evaluation metrics were used to assess model performance for the 12‐ and 24‐month drought‐monitoring scales. The results showed a strong association between the observed and predicted drought events, with coefficients of determination (R2) ranging between 0.865 and 0.925 for the 12‐ and 24‐month drought‐monitoring scales. The proposed computational framework aims to provide water managers in arid and water‐scarce regions with efficient and reliable drought‐monitoring tools to assist in preparing appropriate water management plans. This study provides guidance for improving water resource resilience under water shortage scenarios in the study area and other climatic regions by applying suitable drought indices in conjunction with robust data‐driven models. The results provide a baseline for water resource policymakers worldwide to establish sustainable water conservation strategies and provide crucial insights for drought disaster preparation.
ESG Ratings and Investment Returns at the Country Level: Does Higher Mean Better?
Authors: Asteriou Dimitrios , Pilbeam Keith , Litsios Ioannis , Pouliot William 
Published: December 2024

ABSTRACTWe examine whether U.S. dollar‐based investors can do better investing in highly rated ESG countries than in medium and lower rated ESG countries using both cross sectional and panel data estimations. In general, we find evidence that investment in ESGLow scoring countries leads to better returns than investing in ESGHigh scoring countries which in turn provide better returns than investing in ESGMedium scoring countries. We also examine the issue of risk‐adjusted excess returns using a variety of country risk‐adjusted returns including the country‐level Sharpe ratio, Treynor ratio and Alpha. In general, we find that ESGLow countries still outperform ESGHigh countries who in turn outperform ESGMedium countries. We also find that countries that have improved their ESG scores over the period 2000–2021 have tended to provide the best returns for international investors and this group is mainly made up of ESGLow countries, although this is likely driven mainly by their higher economic growth rates. Finally, we examine the performance within the groups of ESGHigh, ESGMedium and ESGLow countries. In each case, we find that there is a positive relationship of returns with ESG scores within the group, and that GDP per capita in levels has a negative impact on returns using both the market exchange rate and purchasing power parity measures.