bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimizing solar collector efficiency through nanofluid analysis and investigating the impact of particle concentration, and stability
Authors: Sivaraman Prabhakaran , Kolandaivel Visagavel , Murugesan Senthil , Rajendran Silambarasan 
Published: August 2023

AbstractThe emission of greenhouse gases contributes to global warming, and adopting renewable energy can mitigate the reliance on fossil fuels, which currently account for 84.3% of global energy production. Solar thermal energy represents a significant renewable energy source, with solar collectors contributing 54.1% of the world's solar energy. However, the thermal properties of the liquids used in these collectors are suboptimal, and adding particles to the fluid can enhance absorption and thermal characteristics. Nanofluids refer to solid particles reduced to nanoscale sizes, and this study focuses on producing an Ag nanofluid through mechanical exfoliation and its comparative analysis with a GO nanofluid regarding radiation absorption. The results indicate that the Ag nanofluid outperforms pure water and performs similarly at lower concentrations. Specifically, temperature differences of 4–7°C were observed for a simulated power of 1 unit, while the evaporation efficiency reached up to 40.8% for 200 and 500 ppm concentrations, compared to 28.6% for pure water. Moreover, under a radiation intensity of 60 units, the Ag nanofluid achieved the boiling temperature of the water after 85 s. In contrast, GO required at least 250 s, and pure water did not reach the boiling temperature within the 6‐min study period. Thus, the Ag nanofluid holds promise as an effective nanofluid for direct absorption solar collectors due to its affordability, low toxicity, and comparable benefits to graphene.
Analysis of purification in radioactively contaminated ocean water near the Fukushima nuclear accident site
Authors: Lee Boong Joo , Jang Kyung Bae , Woo Tae Ho 
Published: August 2023

AbstractThe nuclear‐contaminated water in the seawater near the site of the Fukushima nuclear power plant (NPP) accident is being investigated for treating the radioactive material. One of the most important considerations in the treatment is the management of the vast aquatic area of the oceanic scale. There are two methods in the application of osmosis and filtration for the modeling. There is the molecule quantity by the water volume where the list of transition of quantities is shown, where it decreases to 10% from the reversed osmosis method and to 0.01% from the filtration method in 9 days. In the filtrations, the discharge variations in the sea are described as the maximum and minimum values within 100 square velocities. A design for the general radioactive contaminated seawater treatment facility is introduced.
Simple parameterization method using differential evolution algorithm to estimate state of charge for Li‐ion batteries and packs for electric vehicles
Authors: Sandoval‐Chileño Marco A. , Cortez Ricardo , Castañeda Luis A. , Lozada‐Castillo Norma , Vazquez‐Arenas Jorge , Luviano‐Juárez Alberto 
Published: August 2023

AbstractAn accurate method is proposed to measure the electrical parameters describing the experimental charge‐discharge curves of Li‐ion batteries and a pack through an equivalent electric dynamic model based on heuristic optimization algorithms (eg, differential evolution approach). The accuracy of these parameters is critical for on‐board state of charge and Health (SOH) estimations of numerous applications and devices. The procedure is constructed, based on the simple Thévenin electrical model. Charge‐discharge experimental curves collected for different chemistry and capacity batteries are described with the model, revealing better estimation results with respect to other algorithms such as impedance‐based methodologies (decreasing the error until 64.19%) and particle swarm optimization based approaches (decreasing the error until 94.02%). The proposal was assessed with different chemistries, capacities and with a 28 battery pack (LiFeMnPO, 100 Ah) used in an electric vehicle.
Quinoa (Chenopodium quinoa Willd.) supplemented cafeteria diet ameliorates glucose intolerance in rats
Authors: Ozcaliskan Ilkay Hatice , Karabulut Derya , Kamaci Ozocak Gonca , Mehmetbeyoglu Ecmel , Kaymak Emin , Kisioglu Betul , Cicek Betul , Akyol Asli 
Published: August 2023

AbstractQuinoa (Chenopodium quinoa Willd.) is a pseudocereal with rich nutritional composition, gluten free, and organoleptic. The primary aim of this study was to elucidate the possible protective roles of quinoa in glucose homeostasis in a model of cafeteria diet‐induced obesity. Male Wistar rats (3 weeks of age) were randomly allocated to be fed by; control chow (CON; n = 6), quinoa (QUI; n = 6), cafeteria (CAF; n = 6), or quinoa and cafeteria (CAFQ; n = 6) for 15 weeks. CAFQ resulted in decreased saturated fat, sugar, and sodium intake in comparison with CAF. Compared to CON, CAF increased body weight gain, plasma insulin, plasma glucose, decreased liver IRS‐1, AMPK mRNA expressions, and pancreatic β‐cell insulin immunoreactivity, and developed hepatocyte degeneration and microvesicular steatosis. Compared to CAF, QUI lowered body weight, plasma glucose, and plasma insulin, increased liver IRS‐1 and AMPK mRNA expressions, and pancreatic β‐cell insulin immunoreactivity. Compared to CAF, CAFQ lowered plasma glucose, increased liver IRS‐1 mRNA expressions, increased pancreatic β‐cell insulin immunoreactivity, and lowered hepatocyte degeneration and microvesicular steatosis. Dietary treatments did not influence IRS‐2, AKT2, and INSR mRNA expressions. HOMA‐IR, HOMA‐β, and QUICKI were also similar between groups. Restoration of insulin in CAFQ islets was as well as that of CON and QUI groups. In conclusion, as a functional food, quinoa may be useful in the prevention of obesity and associated metabolic outcomes such as glucose intolerance, disrupted pancreatic β‐cell function, hepatic insulin resistance, and lipid accumulation.
Rethinking the Ethics of the Covid‐19 Pandemic Lockdowns
Authors: Miller Daniel , Moss Alvin 
Published: August 2023

AbstractPublic health responses to the Covid‐19 pandemic included various measures to mitigate the spread of the virus. Among these, the most restrictive was a broad category referred to as “lockdowns.” We argue that the reasoning offered in favor of extended lockdowns—those lasting several months or longer—did not adequately account for a host of countervailing considerations, including the impact on mental illness, education, employment, and marginalized communities as well as health, educational, and economic inequities. Furthermore, justifications offered for extended lockdowns set aside a basic tenet of public health ethics: restrictions on liberty and autonomy should be the least intrusive means of achieving the desired end. Since it is now clear that extended lockdowns cause severe harm to many vulnerable populations, the burden of proof is on those who would advocate for them, and there must be a much higher bar to implement an extended lockdown, with high‐quality evidence that the benefit would substantially exceed its harm.
The Moral Value of Telemedicine to the Physician‐Patient Relationship
Authors: Wilfond Benjamin S. 
Published: August 2023

AbstractCovid‐19 heralded a natural experiment with telemedicine. My experience as a clinician was very positive, and learning how to use telemedicine has made me a better doctor. Telemedicine has flipped the medical service paradigm; families do not need to conform their busy lives to the medical office workflow. An appointment can be a virtual house call that takes less time for my patient's family and allows me to learn even more about their home. While there are limitations of telemedicine, there are good ethical reasons for clinicians to support the broader use of telehealth, including equity, efficiency, effectiveness, and respecting preferences. Empirical health‐services research that assesses satisfaction, quality, and health outcomes will be necessary to determine the impact of telehealth on a population level to ensure that is used in a way that promotes equity in care.
Inequalities in access to paid sick leave among workers in England and Wales
Authors: Patel Parth , Beale Sarah , Nguyen Vincent , Braithwaite Isobel , Byrne Thomas E. , Erica Fong Wing Lam , Fragaszy Ellen , Geismar Cyril , Hoskins Susan , Navaratnam Annalan M. D. , Shrotri Madhumita , Kovar Jana , Aryee Anna , Hayward Andrew C. , Aldridge Robert W. 
Published: August 2023

AbstractBackgroundIt is poorly understood which workers lack access to sick pay in England and Wales. This evidence gap has been of particular interest in the context of the Covid‐19 pandemic given the relationship between presenteeism and infectious disease transmission.MethodThis cross‐sectional analysis (n = 8874) was nested within a large community cohort study based across England and Wales (Virus Watch). An online survey in February 2021 asked participants in work if they had access to paid sick leave. We used logistic regression to examine sociodemographic factors associated with lacking access to sick pay.ResultsOnly 66% (n = 5864) of participants reported access to sick pay. South Asian workers (adjusted odds ratio [OR] 1.40, 95% confidence interval [CI] 1.06–1.83) and those from Other minority ethnic backgrounds (OR 2.93, 95% CI 1.54–5.59) were more likely to lack access to sick pay compared to White British workers. Older workers (OR range 1.72 [1.53–1.93]–5.26 [4.42–6.26]), workers in low‐income households (OR 2.53, 95% CI 2.15–2.98) and those in transport, trade, and service occupations (OR range 2.03 [1.58–2.61]–5.29 [3.67–7.72]) were also more likely to lack access to sick pay compared respectively to workers aged 25–44, those in high income households and managerial occupations.DiscussionUnwarranted age and ethnic inequalities in sick pay access are suggestive of labour market discrimination. Occupational differences are also cause for concern. Policymakers should consider expanding access to sick pay to mitigate transmission of Covid‐19 and other endemic respiratory infections in the community, and in the context of pandemic preparation.
Monthly precipitation prediction at regional scale using deep convolutional neural networks
Authors: Ni Lingling , Wang Dong , Singh Vijay P. , Wu Jianfeng , Chen Xiaoyan , Tao Yuwei , Zhu Xiaobin , Jiang Jianguo , Zeng Xiankui 
Published: August 2023

AbstractVariations in monthly precipitation are associated with climate extremes having significant socio‐economic and eco‐environmental impacts. Knowledge of monthly precipitation information is therefore valuable for policy making. Extensive research has been conducted on dynamic prediction using state‐of‐the‐art coupled climate models. However, the skilful prediction of monthly precipitation with dynamical models remains a challenge. With the development of machine learning tools, statistical predictions show comparable performance with dynamic models, but they are limited to at‐site monthly prediction, due to the lack of ability for processing spatially connected geophysical data. To improve monthly precipitation forecasting and provide regional forecasts, we propose a model termed UNet‐RegPre based on convolutional neural network and U‐net architecture. The model shows comparable prediction skills with recurrent state‐of‐the‐art dynamic forecasts (CFSv2), and has the capability to capture spatiotemporal patterns of precipitation and reproduce the main process of representative droughts. The key precursors for rainfall development identified by UNet‐RegPre shows that the constructed model can detect the climatic connection between rainfall in eastern China and summer monsoon, showing the potential to advance hydrometeorological understanding with a deep learning‐based model. These results suggest that the proposed model can be a potential tool for precipitation prediction.
Population attributable proportion and number of cancer cases attributed to potentially modifiable risk factors in Iran in 2020
Authors: Nemati Saeed , Mohebbi Elham , Toorang Fatemeh , Hadji Maryam , Hosseini Bayan , Saeedi Elnaz , Abdi Sepideh , Nahvijou Azin , Kamangar Farin , Roshandel Gholamreza , Ghanbari Motlagh Ali , Pourshams Akram , Poustchi Hossein , Haghdoost Ali Akbar , Najafi Farid , Sheikh Mahdi , Malekzadeh Reza , Zendehdel Kazem 
Published: August 2023

AbstractIn the current study, we aimed to calculate the fraction of cancer attributable to modifiable risk factors in Iran in 2020. Population attributable fractions (PAFs) were calculated for established cancer risk factors using three data sources: the national cancer incidence reports, relative risks extracted from global and national meta‐analyses, and exposure prevalence from national/subnational population‐based surveys. In addition to overall cancers, the PAFs were estimated separately for each cancer site among men and women. Overall, 32.6% of cancers in 2020 in Iran were attributable to known risk factors. The PAF in men (40.2%) was twice as high as in women (21.1%). Cigarette smoking (15.4%), being overweight (5.0%), opium use (3.9%) and H. pylori infection (3.8%) were the leading causes of cancers. For men, the highest PAFs belonged to cigarette smoking (26.3%), opium use (6.8%) and being overweight (3.1%), while for women, the highest PAFs belonged to being overweight (7.2%), H. pylori infection (2.7%) and cigarette smoking (2.7%). Among Iranian men and women, the PAFs of waterpipe smoking were 2% and 0.9%, respectively. A third of incident cancers in Iran are due to modifiable exposures, mainly cigarette smoking, being overweight, and H. pylori infection. Opium consumption and waterpipe smoking collectively accounted for 8.8% of cancer occurrence in men and 1.3% in women in Iran. These emerging risk factors should be taken into consideration in future PAF studies.
Advances in Mass Spectrometry‐Based Structural Proteomics: Development of HDX‐MS and XL‐MS Techniques from Recombinant Protein to Cellular Systems
Authors: Courouble Valentine V. , Mann Matthew D. , Griffin Patrick R. 
Published: August 2023

AbstractMass spectrometry (MS) is a central analytical technique used to study proteins and biomolecules. It measures mass‐to‐charge ratio of ions to identify and quantify molecules in simple and complex mixtures. Technological advancement in instrumentation, sample preparation methodologies, and data analysis workflows continue to push the capabilities of MS to answer more complicated questions and vice versa. Structural proteomics uses MS‐based methodologies to characterize protein structure. Specifically, but not limited to, hydrogen deuterium exchange MS (HDX‐MS) and crosslinking MS (XL‐MS) are complementary techniques that capture the structural plasticity inherent to proteins in solution. This review is intended to present recent progress in HDX‐MS and XL‐MS that have allowed these techniques to be used not only for simple recombinant protein systems but with complex cellular systems.
Remarks on a copula‐based conditional value at risk for the portfolio problem
Authors: Molina Barreto Andres Mauricio , Ishimura Naoyuki 
Published: August 2023

SummaryWe deal with a multivariate conditional value at risk. Compared with the usual notion for the single random variable, a multivariate value at risk is concerned with several variables, and thus, the relation between each risk factor should be considered. We here introduce a new definition of copula‐based conditional value at risk, which is real valued and ready to be computed. Copulas are known to provide a flexible method for handling a possible nonlinear structure; therefore, copulas may be naturally involved in the theory of value at risk. We derive a formula of our copula‐based conditional value at risk in the case of Archimedean copulas, whose effectiveness is shown by examples. Numerical studies are also carried out with real data, which can be verified with analytical results.
Machine learning‐based establishment and validation of age‐related patterns for predicting prognosis in non‐small cell lung cancer within the context of the tumor microenvironment
Authors: Ma Zeming , Han Haibo , Zhou Zhiwei , Wang Shijie , Liang Fan , Wang Liang , Ji Hong , Yang Yue , Chen Jinfeng 
Published: August 2023

AbstractLung cancer (LC) is a leading cause of cancer‐related mortality worldwide, with non‐small cell lung cancer (NSCLC) accounting for over 80% of cases. The impact of aging on clinical outcomes in NSCLC remains poorly understood, particularly with respect to the immune response. In this study, we explored the effects of aging on NSCLC using 307 genes associated with human aging from the Human Ageing Genomic Resources. We identified 53 aging‐associated genes that significantly correlate with overall survival of NSCLC patients, including the clinically validated gene BUB1B. Furthermore, we developed an aging‐associated enrichment score to categorize patients based on their aging subtypes and evaluated their prognostic and therapeutic response values in LC. Our analyses yielded two aging‐associated subtypes with unique profiles in the tumor microenvironment, demonstrating varying responses to immunotherapy. Consensus clustering based on transcriptome profiles provided insights into the effects of aging on NSCLC and highlighted the potential of personalized therapeutic approaches tailored to aging subtypes. Our findings provide a new target and theoretical support for personalized therapeutic approaches in patients with NSCLC, offering insights into the potential impact of aging on cancer outcomes.
The influence of professional identity on perceptions of substance use harm reduction among professional counselors
Authors: Jordan Justin R. , Welfare Laura E. , Fullen Matthew C. 
Published: August 2023

AbstractHarm reduction (HR) approaches to substance use show promising efficacy, but limited research exists exploring professional counselors’ perceptions of HR. An online survey gathered data from 395 substance use providers, including 128 professional counselors. In measuring HR acceptance, t‐tests compared this sample to prior samples, an analysis of variance compared counselors to other providers, and multiple regression explored the influence of counselor identity factors. Empathic responsiveness and positive social justice attitudes were predictors of HR acceptance. Counselors’ perceptions of HR were similar to other providers. Results indicated that counselor identity influences HR perceptions, with implications for practice and training considered.
Impact of microsampling on toxicological evaluation in rodent safety studies
Authors: Takahashi Kazuaki , Hattori Norimichi , Yokoyama Hideaki , Jinno Fumihiro , Ohtsuka Hirohiko , Nakai Keiko , Takumi Asuka , Shibui Yusuke , Yamaguchi Koki , Shimazaki Taishi , Tanaka Yoichi , Saito Kosuke , Kobayashi Akio , Saito Yoshiro 
Published: August 2023

AbstractRecently, animal welfare has been attracting worldwide attention, and implementation of 3Rs (replacement, reduction, and refinement) is prioritized in every way possible in the drug development. Microsampling, in which small amounts of blood are collected, is attracting attention in this context. ICH S3A Q&A focused on microsampling was published in November 2017 to help accelerate the application of microsampling for toxicokinetic assessment. The increased sensitivity of drug measurement apparatuses such as mass spectrometers has made it possible to measure drug concentrations with small amounts of blood samples. In this review, we summarized the reports on toxicological influence of microsampling in rodents (rats and mice) with or without drug administration or recovery period after blood collection and influences that may arise from differences in the blood sampling site or blood sampling volume. We also summarized some perspectives on further implementation of microsampling in toxicology studies. The use of microsampling in regulatory toxicology studies has gradually increased, although at a lower rate than in discovery studies. Since more animals are used in GLP toxicology studies than in discovery studies, the effect of reducing the number of animals by microsampling is expected to be greater in the toxicology studies. This report aims to promote the application of microsampling to nonclinical studies, as it is beneficial for improving animal welfare and can contribute to the 3Rs.
Advances in laser speckle imaging: From qualitative to quantitative hemodynamic assessment
Authors: Qureshi Muhammad Mohsin , Allam Nader , Im Jeongmyo , Kwon Hyuk‐Sang , Chung Euiheon , Vitkin I. Alex 
Published: August 2023

AbstractLaser speckle imaging (LSI) techniques have emerged as a promising method for visualizing functional blood vessels and tissue perfusion by analyzing the speckle patterns generated by coherent light interacting with living biological tissue. These patterns carry important biophysical tissue information including blood flow dynamics. The noninvasive, label‐free, and wide‐field attributes along with relatively simple instrumental schematics make it an appealing imaging modality in preclinical and clinical applications. The review outlines the fundamentals of speckle physics and the three categories of LSI techniques based on their degree of quantification: qualitative, semi‐quantitative and quantitative. Qualitative LSI produces microvascular maps by capturing speckle contrast variations between blood vessels containing moving red blood cells and the surrounding static tissue. Semi‐quantitative techniques provide a more accurate analysis of blood flow dynamics by accounting for the effect of static scattering on spatiotemporal parameters. Quantitative LSI such as optical speckle image velocimetry provides quantitative flow velocity measurements, which is inspired by the particle image velocimetry in fluid mechanics. Additionally, discussions regarding the prospects of future innovations in LSI techniques for optimizing the vascular flow quantification with associated clinical outlook are presented.