bluuebunny/crossref_metadata_2025_split huggingface dataset:
Parallel, Multi-Zone, Multi-Block Solver to Study Arterial Branches in Human Vascular System
Authors: Tadjfar M. , Himeno R. 
Published: November 2021

Abstract
The unsteady, three-dimensional, incompressible Navier-Stokes equations are solved numerically to study arterial branches in human vascular system. The solver is capable of dealing with moving boundaries and moving grids. It is designed to handle complex, three-dimensional vascular systems. The computational domain is divided into multiple block subdomains. At each cross section the plane is divided into twelve sub-zones to allow flexibility for handling complex geometries and, if needed, appropriate parallel data partitioning. A second-order in time and third-order upwind finite volume method for solving time-accurate incompressible flows based on pseudo-compressibility and dual time-stepping technique is used. For parallel execution, the flow domain is partitioned. Communication between the subdomains of the flow on Riken’s VPP/700E supercomputer is implemented using MPI message-passing library. The code is capable of running on both shared and/or distributed memory architectures.
Instability and Heat Transfer in Mixed Convection Flow in a Horizontal Duct With Discrete Heat Sources
Authors: Wang Qinghua , Jaluria Yogesh 
Published: November 2021

Abstract
Three dimensional mixed convection flow in a horizontal rectangular duct at low Reynolds numbers 5 ≤ Re ≤ 100 has been investigated numerically. Multiple strip heat sources are flushed-mounted on the bottom surface, modeling IC chips on PCBs. Two different flow patterns were observed. For Re ≥ 20, and Gr ≤ 1.5 × 104, only steady longitudinal rolls appear in the channel. The discontinuous deployment of heat sources on the bottom makes the longitudinal rolls expand and shrink periodically. The unsteady flow consists of steady longitudinal rolls near the side walls and traveling transverse rolls at the core region of the channel. The traveling velocity of the transverse rolls was found to be equal to the mean velocity of the forced flow. The implications of these observations to the cooling of electronic equipment are discussed.
Transient Convective Heat Transfer of Air Jet Impinging Onto a Confined Ceramic-Based MCM Disk
Authors: Su W. S. , Liu L. K. , Hung Y. H. 
Published: November 2021

Abstract
Transient heat transfer behavior from a horizontally confined ceramic-based MCM disk with jet impingement has been systematically explored. The relevant parameters influencing heat transfer performance are the steady-state Grashof number, jet Reynolds number, and ratio of jet separation distance to nozzle diameter. In addition, an effective time, ton, representing a certain transient time when the mixed convection effect due to jet impingement and buoyancy becomes significant relative to heat conduction, is introduced. Both the transient chip and average Nusselt numbers on the MCM disk surface decrease with time in a very beginning period of 0 ≤ t &lt; ton, whereas it gradually increases or keeps constant with time and finally approaches the steady-state value in the period of ton ≤ t &lt; ts. As compared with the steady-state results, if the transient chip and average heat transfer behaviors may be considered as a superposition of a series of quasi-steady states, the transient chip and average Nusselt numbers in all the present transient experiments can be properly predicted by the existing steady-state correlations when t ≥ 4 min in the power-on transient period.
Integrated Heterogeneous Design of Semiconductor Heat Sink via Scaled Direct Micro-Modeling, Upper Scale VAT Simulation and Experiment: Comparison and Verification of Properties
Authors: Travkin V. S. , Sergievsky E. D. , Krinitsky E. V. , Catton I. 
Published: November 2021

Abstract
The thermal and hydrodynamic characteristic of straight-channel longitudinal fin heat sink under forced air-cooling is studied experimentally and numerically using a Phoenics 3.3 (CHAM, UK) CFD software. The aim of the study is to simulate and compare the viability of employing Phoenics code as effective and efficient means gathering the vast amount of data required to adequately quantify heat sink characteristics on the lower scale with the two scale experimental data reduced according to requirements of VAT. For this case is analyzed the basic homogeneous heat transfer performance features and shown insolvency of using heat transfer and effectiveness parameter. A number of data reduction parameters and procedures were developed using scaling heterogeneous formulation by volume averaging theory (VAT). Analysis brought in this work supports the procedures used to connect the two scale VAT experiment with the full lower scale direct numerical modeling for the semiconductor heat sink.
Application of a Two-Color Laser Induced Fluorescence (LIF) Technique for Temperature Mapping
Authors: Kim H. J. , Kihm K. D. 
Published: November 2021

Abstract
Two-color laser induced fluorescence (LIF) technique has been developed and examined to use for full-field temperature mapping of a micro-scale field-of-view in water. The technique uses two fluorescence dyes with different emission characteristics — one is the temperature sensitive dye (Rhodamine-B) and the other is the temperature insensitive dye (Rhodamine-110). The ratio of the two fluorescence emission intensities, therefore, provides a formidable correlation with temperature that does not depend on the laser illumination intensity variation and is free from the possible bias occurring from background noise. In considering the technique for applications to micro-scale field-of-view, the first question that may be asked will be if the technique ensures acceptable accuracy in temperature readings with sufficiently small spatial resolution. In order to explore answers to this question, an extensive calibration for the intensity ratio versus temperature has been performed using a constant-temperature bath and the calibration results have been statistically analyzed to estimate measurement uncertainties. The developed technique measures thermally stratified fields with known temperature distributions that are established inside 10-mm and 1-mm path cuvettes to ensure measurement accuracy and spatial resolution for potential microscale applications.
Measurement of Specific Heat of Biological Tissue Using IR Imaging and Spectroscopy
Authors: Abel Joshua C. , Krishnan S. S. , Xu Lisa X. , Gore Jay P. 
Published: November 2021

Abstract
This paper presents a device for the measurement of the heat capacity of small biological samples in the physiological temperature range (34–40C°) using infrared (IR) thermometry. Conventional calorimetry is unsatisfactory for this purpose due to the relatively large size of the sample required and the changes in the specific heat induced by temperature changes in the measurement process. The present device design and calibration is discussed, along with preliminary experimental results. Auxiliary IR spectroscopy has been used to check the biological samples. Preliminary results show that the present method can be used for the measurement of the thermal properties of small samples.
Processing, Understanding, and Application of Piezoelectric Materials for an Artificial Neural System
Authors: Schulz M. J. , Chattopadhyay S. , Sundaresan M. J. , Ghoshal A. , Martin W. N. , Pratap P. R. 
Published: November 2021

Abstract
Piezoelectric materials are opening the door for the design of large smart structures. To explore what possibilities there might be for building practical smart structures, a review of the characteristics and methods of processing piezoelectric active materials is given. The advantages and limitations of using the different forms of piezoelectric materials for sensors and actuators are then discussed. One area where piezoceramic sensors can have a large impact is structural condition monitoring. Structural condition monitoring refers to using in-situ sensors to monitor the internal loads and the health of a structure in real-time. This will allow a structure to be operated at its maximum performance and efficiency while minimizing the fatigue damage. To achieve this on a large structure, a new highly distributed sensor concept is discussed in which piezoceramic fibers and microelectronic components are used to mimic the biological nervous system. A simplified simulation and experiment are presented to show how this artificial neural system can measure dynamic strains and acoustic emissions caused by damage in structures.
Radiation Beam Modeling and Intelligent Signal Interpretation for Phased Array Ultrasonic Inspection
Authors: Song Sung-Jin , Shin Hyeon Jae , Kwon Jeong-Rock 
Published: November 2021

Abstract
Flaw characterization with ultrasonic phased array technique involves to key issues, such as obtaining the high quality flaw images and determining the quantitative flaw information (such as location, type and size). This paper deals with these two key issues. For obtaining the high quality images, it is necessary to optimize the parameters of array transducers. To address such a need, a very computationally efficient radiation beam model is developed based on the boundary diffraction wave model, and the 3-D radiation beam fields from array transducers were simulated to investigate their characteristics in detail. From the sectorial images provided by the ultrasonic phased array technique, flaw size can be determined very successfully, if the type of the scatters is identified in advance. For the determination of the type of scatters, an intelligent signal interpretation scheme based on ultrasonic pattern recognition approach is studied, and the variation of features according to the steering angle is found to be a very sensitive feature for this purpose. The performance of the proposed approach is demonstrated with the initial experiments.
Design Point Performance Trends for Water Vapor Compressors
Authors: D’Orsi Nicholas C. , Wight Sharon E. , Yoshinaka Tsukasa 
Published: November 2021

Abstract
A design study of various water vapor compressor configurations — including single and multistage centrifugal compressors and multistage axial compressors — is used to determine geometry and performance trends as a function of design speed, compressor configuration, and intercooling method. The intercooled multistage centrifugal machines led to the lowest required power levels, though the large outer diameter of these machines and the addition of an intercooler may reduce their appeal. The non-intercooled multistage axial configurations offered high design point performance and a much smaller outer diameter than the centrifugal machines, though at the expense of large overall axial length and limited flow range. Ultimately, the selection of the right machine for a given application is a tradeoff between the performance and geometry trends illustrated in this paper, as well as the cost of the machine.
Curving Analysis of Modified Designs of Passenger Railway Vehicle Trucks
Authors: Dukkipati Rao V. , Narayanaswamy S. 
Published: November 2021

Abstract
In this paper, modified truck designs were studied with an objective to achieving better compatibility between high speed stability and curving behaviour compared to the conventional truck. The analysis has shown that USD truck can be designed to achieve better over all performance compared to other truck designs. The results of steady state curving program were validated using the commercial software package NUCARS. The comparison of steady state curving behaviour of different truck designs using NUCARS also showed that USD truck has the potential to achieve superior performance compared to other truck designs.
The research reported in this paper has dealt with steady state curving behaviour. To look into the safety implications of the new designs, transient behaviour in curves must be studied. The response of the railway cars in entry and exit spirals should be evaluated. The effects of track irregularities on the response of these modified designs need to be analyzed.
Access to mental healthcare in the year after first fit note: a longitudinal study of linked clinical records
Authors: Dorrington Sarah , Carr Ewan , Stevelink Sharon , Ashworth Mark , Broadbent Matthew , Madan Ira , Hatch Stephani , Hotopf Matthew 
Published: November 2021

ObjectivesSickness absence is strongly associated with poor mental health, and mental disorders often go untreated. In this population-based cohort study, we identified people receiving fit notes from their general practitioner (GP) and determined access to mental health treatment stratified by health complaint and demographic variables.DesignLongitudinal study of health records.SettingPrimary care and secondary mental health care in the borough of Lambeth, South London. Forty-five GP practices in Lambeth and the local secondary mental healthcare trust.ParticipantsThe analytical sample included 293 933 working age adults (16–60 years) registered at a Lambeth GP practice between 1 January 2014 and 30 April 2016.Primary and secondary outcome measuresThree indicators of mental healthcare in the year after first fit note were antidepressant prescription, contact with Improving Access to Psychological Therapy (IAPT) services and contact with secondary mental health services.Results75% of people with an identified mental health condition at first fit note had an indicator of mental healthcare in the following year. Black Caribbean and Black African groups presenting with mental disorders were less likely to have a mental healthcare indicator compared with White British groups.ConclusionsThe majority of those with an identified mental health need receive some treatment in the year following a fit note; however, our results suggest Black African and Black Caribbean groups with an identified mental healthcare need have less complete access compared to the White British group.
Deep learning-based facial image analysis in medical research: a systematic review protocol
Authors: Su Zhaohui , Liang Bin , Shi Feng , Gelfond J , Šegalo Sabina , Wang Jing , Jia Peng , Hao Xiaoning 
Published: November 2021

IntroductionDeep learning techniques are gaining momentum in medical research. Evidence shows that deep learning has advantages over humans in image identification and classification, such as facial image analysis in detecting people’s medical conditions. While positive findings are available, little is known about the state-of-the-art of deep learning-based facial image analysis in the medical context. For the consideration of patients’ welfare and the development of the practice, a timely understanding of the challenges and opportunities faced by research on deep-learning-based facial image analysis is needed. To address this gap, we aim to conduct a systematic review to identify the characteristics and effects of deep learning-based facial image analysis in medical research. Insights gained from this systematic review will provide a much-needed understanding of the characteristics, challenges, as well as opportunities in deep learning-based facial image analysis applied in the contexts of disease detection, diagnosis and prognosis.MethodsDatabases including PubMed, PsycINFO, CINAHL, IEEEXplore and Scopus will be searched for relevant studies published in English in September, 2021. Titles, abstracts and full-text articles will be screened to identify eligible articles. A manual search of the reference lists of the included articles will also be conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework was adopted to guide the systematic review process. Two reviewers will independently examine the citations and select studies for inclusion. Discrepancies will be resolved by group discussions till a consensus is reached. Data will be extracted based on the research objective and selection criteria adopted in this study.Ethics and disseminationAs the study is a protocol for a systematic review, ethical approval is not required. The study findings will be disseminated via peer-reviewed publications and conference presentations.PROSPERO registration numberCRD42020196473.
What influences people’s responses to public health messages for managing risks and preventing infectious diseases? A rapid systematic review of the evidence and recommendations
Authors: Ghio Daniela , Lawes-Wickwar Sadie , Tang Mei Yee , Epton Tracy , Howlett Neil , Jenkinson Elizabeth , Stanescu Sabina , Westbrook Juliette , Kassianos Angelos P , Watson Daniella , Sutherland Lisa , Stanulewicz Natalia , Guest Ella , Scanlan Daniel , Carr Natalie , Chater Angel , Hotham Sarah , Thorneloe Rachael , Armitage Christopher J. , Arden Madelynne , Hart Jo , Byrne-Davis Lucie , Keyworth Christopher 
Published: November 2021

BackgroundIndividual behaviour changes, such as hand hygiene and physical distancing, are required on a population scale to reduce transmission of infectious diseases such as COVID-19. However, little is known about effective methods of communicating risk reducing information, and how populations might respond.ObjectiveTo synthesise evidence relating to what (1) characterises effective public health messages for managing risk and preventing infectious disease and (2) influences people’s responses to messages.DesignA rapid systematic review was conducted. Protocol is published on Prospero CRD42020188704.Data sourcesElectronic databases were searched: Ovid Medline, Ovid PsycINFO and Healthevidence.org, and grey literature (PsyarXiv, OSF Preprints) up to May 2020.Study selectionAll study designs that (1) evaluated public health messaging interventions targeted at adults and (2) concerned a communicable disease spread via primary route of transmission of respiratory and/or touch were included. Outcomes included preventative behaviours, perceptions/awareness and intentions. Non-English language papers were excluded.SynthesisDue to high heterogeneity studies were synthesised narratively focusing on determinants of intentions in the absence of measured adherence/preventative behaviours. Themes were developed independently by two researchers and discussed within team to reach consensus. Recommendations were translated from narrative synthesis to provide evidence-based methods in providing effective messaging.ResultsSixty-eight eligible papers were identified. Characteristics of effective messaging include delivery by credible sources, community engagement, increasing awareness/knowledge, mapping to stage of epidemic/pandemic. To influence intent effectively, public health messages need to be acceptable, increase understanding/perceptions of health threat and perceived susceptibility.DiscussionThere are four key recommendations: (1) engage communities in development of messaging, (2) address uncertainty immediately and with transparency, (3) focus on unifying messages from sources and (4) frame messages aimed at increasing understanding, social responsibility and personal control. Embedding principles of behavioural science into public health messaging is an important step towards more effective health-risk communication during epidemics/pandemics.
Integrating expert knowledge for dementia risk prediction in individuals with mild cognitive impairment (MCI): a study protocol
Authors: Wang Meng , Smith Eric E , Forkert Nils Daniel , Chekouo Thierry , Ismail Zahinoor , Ganesh Aravind , Sajobi Tolulope 
Published: November 2021

IntroductionTo date, there is no broadly accepted dementia risk score for use in individuals with mild cognitive impairment (MCI), partly because there are few large datasets available for model development. When evidence is limited, the knowledge and experience of experts becomes more crucial for risk stratification and providing MCI patients with prognosis. Structured expert elicitation (SEE) includes formal methods to quantify experts’ beliefs and help experts to express their beliefs in a quantitative form, reducing biases in the process. This study proposes to (1) assess experts’ beliefs about important predictors for 3-year dementia risk in persons with MCI through SEE methodology and (2) to integrate expert knowledge and patient data to derive dementia risk scores in persons with MCI using a Bayesian approach.Methods and analysisThis study will use a combination of SEE methodology, prospectively collected clinical data, and statistical modelling to derive a dementia risk score in persons with MCI . Clinical expert knowledge will be quantified using SEE methodology that involves the selection and training of the experts, administration of questionnaire for eliciting expert knowledge, discussion meetings and results aggregation. Patient data from the Prospective Registry for Persons with Memory Symptoms of the Cognitive Neurosciences Clinic at the University of Calgary; the Alzheimer’s Disease Neuroimaging Initiative; and the National Alzheimer’s Coordinating Center’s Uniform Data Set will be used for model training and validation. Bayesian Cox models will be used to incorporate patient data and elicited data to predict 3-year dementia risk.DiscussionThis study will develop a robust dementia risk score that incorporates clinician expert knowledge with patient data for accurate risk stratification, prognosis and management of dementia.
Social inequalities and dynamics of the early COVID-19 epidemic: a prospective cohort study in France
Authors: Bajos Nathalie , Counil Emilie , Franck Jeanna-eve , Jusot Florence , Pailhé Ariane , Spire Alexis , Martin Claude , Lydie Nathalie , Slama Remy , Meyer Laurence , Warszawski Josiane 
Published: November 2021

ObjectiveAlthough social inequalities in COVID-19 mortality by race, gender and socioeconomic status are well documented, less is known about social disparities in infection rates and their shift over time. We aim to study the evolution of social disparities in infection at the early stage of the epidemic in France with regard to the policies implemented.DesignRandom population-based prospective cohort.SettingFrom May to June 2020 in France.ParticipantsAdults included in the Epidémiologie et Conditions de Vie cohort (n=77 588).Main outcome measuresSelf-reported anosmia and/or ageusia in three categories: no symptom, during the first epidemic peak (in March 2020) or thereafter (during lockdown).ResultsIn all, 2052 participants (1.53%) reported anosmia/ageusia. The social distribution of exposure factors (density of place of residence, overcrowded housing and working outside the home) was described. Multinomial regressions were used to identify changes in social variables (gender, class and race) associated with symptoms of anosmia/ageusia. Women were more likely to report symptoms during the peak and after. Racialised minorities accumulated more exposure risk factors than the mainstream population and were at higher risk of anosmia/ageusia during the peak and after. By contrast, senior executive professionals were the least exposed to the virus with the lower rate of working outside the home during lockdown. They were more affected than lower social classes at the peak of the epidemic, but this effect disappeared after the peak.ConclusionThe shift in the social profile of the epidemic was related to a shift in exposure factors under the implementation of a stringent stay-at-home order. Our study shows the importance to consider in a dynamic way the gender, socioeconomic and race direct and indirect effects of the COVID-19 pandemic, notably to implement policies that do not widen health inequalities.