bluuebunny/crossref_metadata_2025_split huggingface dataset:
Three‐dimensional weakly compressible moving particle simulation coupled with geometrically nonlinear shell for hydro‐elastic free‐surface flows
Authors: Amaro Junior Rubens Augusto , Gay Neto Alfredo , Cheng Liang‐Yee 
Published: March 2022

AbstractA three‐dimensional fluid–structure interaction solver based on an improved weakly compressible moving particle simulation (WC‐MPS) method and a geometrically nonlinear shell structural model is developed and applied to hydro‐elastic free‐surface flows. The fluid–structure coupling is performed by a polygon wall boundary model that can handle particles and finite elements of distinct sizes. In WC‐MPS, a tuning‐free diffusive term is introduced to the continuity equation to mitigate nonphysical pressure oscillations. Discrete divergence operators are derived and applied to the polygon wall boundary, of which the numerical stability is enhanced by a repulsive Lennard–Jones force. Additionally, an efficient technique to deal with the interaction between fluid particles placed at opposite sides of zero‐thickness walls is proposed. The geometrically nonlinear shell is modeled by an unstructured mesh of six‐node triangular elements. Finite rotations are considered with Rodrigues parameters and a hyperelastic constitutive model is adopted. Benchmark examples involving free‐surface flows and thin‐walled structures demonstrate that the proposed model is robust, numerically stable and offers more efficient computation by allowing mesh size larger than that of fluid particles.
High‐order implicit‐explicit additive Runge–Kutta schemes for numerical combustion with adaptive mesh refinement
Authors: Christopher Joshua , Guzik Stephen M. , Gao Xinfeng 
Published: March 2022

AbstractThe objective of this study is to develop and apply efficient solution techniques for numerical modeling of combustion with stiff chemical kinetics in practical combustors. The new technique combines a fourth‐order implicit‐explicit (IMEX) additive Runge‐Kutta scheme (ARK) with adaptive mesh refinement (AMR). The IMEX component treats the stiff reactions implicitly but integrates convection and diffusion explicitly in time, and thus permits the solution to advance with larger time‐step sizes than that of explicit time‐marching methods alone. The AMR further adds computational efficiency by effectively placing high spatial resolution meshes in regions with strong gradients, such as flame fronts. The novelty of this study is in the integration of a fourth‐order IMEX ARK method with AMR for a high‐order finite‐volume scheme and the application to solving complex reacting flows governed by the compressible Navier–Stokes equations with very stiff chemistry in a practical combustor geometry. The effectiveness and performance of the adaptive ARK4 is assessed for complex reacting flows by examining properties, such as the presence of shock waves, the time‐scale changes in response to AMR levels, and the size and stiffness of reaction mechanisms for various fuels such as , , and . The new adaptive ARK4 method is verified and validated using a convection‐diffusion‐reaction problem and shock‐driven combustion, respectively. The validated algorithm is then applied to solve the stiff ‐air combustion in a bluff‐body combustor. A significant speedup of three orders of magnitude is achieved in comparison to the standard ERK4 method at the given solution accuracy.
Deep learning with regularized robust long‐ and short‐term memory network for probabilistic short‐term load forecasting
Authors: Jiang He , Zheng Weihua 
Published: March 2022

AbstractShort‐term electricity load forecasting plays an essential role in power system operation and energy trading. However, the strong volatility, seasonality, and uncertainly of the load series pose challenges to accurate short‐term load forecasting using existing forecasting models. To tackle these challenges, in this paper, we investigate a novel deep learning‐based probabilistic short‐term load forecasting model to predict the hourly ahead electricity load accurately. The proposed deep learning forecasting model embeds nonconvex minimax concave penalty in the robust long‐ and short‐term memory (LSTM) network to simplify its complex structure while extracting the important information. The model parameters in the proposed regularized and robust LSTM network are fine‐tuned using whale optimization algorithm which is a meta‐heuristic approach. For empirical applications, electricity load data collected from New York Independent System Operator and ISO New England are considered, and numerical results show that the proposed method outperforms other state‐of‐the‐art competitors in terms of both point and interval forecasting accuracy.
Brain signatures based on structural MRI: Classification for MCI, PMCI, and AD
Authors: Gonuguntla Venkateswarlu , Yang Ehwa , Guan Yi , Koo Bang‐Bon , Kim Jae‐Hun 
Published: March 2022

AbstractStructural MRI (sMRI) provides valuable information for understanding neurodegenerative illnesses such as Alzheimer's Disease (AD) since it detects the brain's cerebral atrophy. The development of brain networks utilizing single imaging data—sMRI is an understudied area that has the potential to provide a network neuroscientific viewpoint on the brain. In this paper, we proposed a framework for constructing a brain network utilizing sMRI data, followed by the extraction of signature networks and important regions of interest (ROIs). To construct a brain network using sMRI, nodes are defined as regions described by the brain atlas, and edge weights are determined using a distance measure called the Sorensen distance between probability distributions of gray matter tissue probability maps. The brain signatures identified are based on the changes in the networks of disease and control subjects. To validate the proposed methodology, we first identified the brain signatures and critical ROIs associated with mild cognitive impairment (MCI), progressive MCI (PMCI), and Alzheimer's disease (AD) with 60 reference subjects (15 each of control, MCI, PMCI, and AD). Then, 200 examination subjects (50 each of control, MCI, PMCI, and AD) were selected to evaluate the identified signature patterns. Results demonstrate that the proposed framework is capable of extracting brain signatures and has a number of potential applications in the disciplines of brain mapping, brain communication, and brain network‐based applications.
Throwing caution to the wind: How hurricanes affect COVID‐19 spread
Authors: Tracey Marlon , Plemmons Alicia , Belasen Ariel 
Published: March 2022

AbstractThis study exploits the pathway of Hurricane Laura to assess its impact on the spread of COVID‐19. Using US hospital data on confirmed and suspected adult COVID‐19 cases, we find average daily cases per week rose by more than 12% primarily in tropical storm‐affected counties in subsequent weeks. We suspect the key mechanisms involve constraints on social distancing for two reasons. First, there is significant evidence of storm‐induced mobility. Second, lower income areas endured higher growth in hospital cases during the post‐hurricane period. These findings provide crucial insights for policy‐makers when designing natural disaster protocols to adjust for potential respiratory viral illnesses.
MicroRNA‐132 is overexpressed in fetuses with late‐onset fetal growth restriction
Authors: Morales‐Roselló José , Loscalzo Gabriela , García‐Lopez Eva María , García‐Gimenez José Luis , Perales‐Marín Alfredo 
Published: March 2022

AbstractBackground and AimsTo evaluate the expression of microRNA 132 (miR‐132) in fetuses with normal growth and in fetuses with late‐onset growth restriction (FGR).MethodsIn a prospective cohort study, 48 fetuses (24 with late‐onset FGR and 24 with normal growth) were scanned with Doppler ultrasound after 34 weeks to measure the umbilical artery and middle cerebral artery pulsatility indices and followed until birth. Subsequently, blood samples from the umbilical cord were collected to evaluate the expression of miR‐132 by means of Real‐time quantitative polymerase chain reaction, determining the existence of normality cut‐offs and associations with birth weight (BW) centile, cerebroplacental ratio multiples of the median (CPR MoM), and intrapartum fetal compromise (IFC).ResultsIn comparison with normal fetuses, late‐onset FGR fetuses showed upregulation of miR‐132 (33.94 ± 45.04 vs. 2.88 ± 9.32 2−ddCt, p < 0.001). Using 5 as a cut‐off we obtained a sensitivity of 50% and a specificity of 96% for the diagnosis of FGR, while for IFC these values were respectively 27% and 73%. Expression of miR‐132 was associated with BW centile but not with CPR MoM. Finally, the best detection of IFC was achieved combining miR‐132 expression and CPR MoM (AUC = 0.69, p < 0.05).ConclusionFetuses with late‐onset FGR show upregulation of miR‐132. Further studies are needed to investigate the role of miR‐132 in the management of late‐onset FGR.
Sero‐prevalence of SARS‐CoV‐2 in certain cities of Kazakhstan
Authors: Smagul Manar , Esmagambetova Aizhan , Nusupbaeva Gauhar , Kirpicheva Ulyana , Kasabekova Lena , Nukenova Gauhar , Saliev Timur , Fakhradiyev Ildar , Tanabayeva Shynar , Zhussupov Baurzhan 
Published: March 2022

AbstractBackground and AimsSeroprevalence studies are needed to determine the cumulative prevalence of SARS‐CoV‐2 infection and to develop pandemic mitigation strategies. Despite the constant monitoring and surveillance, the true level of infection in the population of Kazakhstan remains unknown. The aim of this study was to determine the sero‐prevalence of SARS‐CoV‐2 in the main cities of Kazakhstan.MethodsThe research was conducted as a cluster‐randomized cross‐sectional national household study in three cities of Kazakhstan. The study covered the period: from October 24, 2020, to January 11, 2021. A total of 5739 people took part in the study. All participants agreed to be tested for antibodies to IgM/IgG. Demographic characteristics were analyzed. The presence of symptoms of respiratory diseases and the results of polymerase chain reaction (PCR) testing were determined. The antibodies to the SARS‐CoV‐2 virus were detected using the method of enzyme‐linked immunosorbent assay (ELISA).ResultsThere was significant geographic variability with a higher prevalence of IgG/IgM antibodies to SARS‐CoV‐2 in Almaty 57.0%, in Oskemen 60.7% than in Kostanay 39.4%. There were no significant differences in prevalence between men and women (p ≥ 0.05). In Almaty, only 19% of participants with antibodies reported the presence of respiratory symptoms during a pandemic. At the same time, the percentage of patients with antibodies who had respiratory symptoms was 36% in Oskemen and 27% in Kostanay.ConclusionThe findings indicate that despite reasonable level of seroprevalence, the country has not yet reached the baseline minimum of herd immunity scores. The prevalence estimates for asymptomatic or subclinical forms of the disease ranged from 64% to 81%. Thus, given that almost half of the population of Kazakhstan remains vulnerable, the importance of preventive strategies such as social distancing, the use of medical masks, and vaccination to protect the population from the transmission of SARS‐CoV‐2 is highly critical.
Influences of Soret and Dufour numbers on mixed convective and chemically reactive Casson fluids flow towards an inclined flat plate
Authors: Ramzan Muhammad , Saeed Anwar , Kumam Poom , Ahmad Zubair , Junaid Muhammad S. , Khan Dolat 
Published: March 2022

AbstractThe purpose of this study is to examine the magnetohydrodynamic mixed convection Casson fluid flow over an inclined flat plate along with the heat source/sink. The present flow problem is considered under the assumption of the chemical reaction and thermal radiation impacts along with heat and mass transport. The leading nonlinear partial differential equations of the flow problem were renovated into the nonlinear ordinary differential equations (ODEs) with the assistance of appropriate similarity transformations and then we solved these ODEs with the employment of the bvp4c technique using the computational software MATLAB. The consequences of numerous leading parameters such as thermophoretic parameter, local temperature Grashof number, solutal Grashof number, suction parameter, magnetic field parameter, Prandtl number, chemical reaction parameter, Dufour number, Soret number, angle of inclination, radiation parameter, heat source/sink, and Casson parameter on the fluid velocity, temperature, and concentration profiles are discoursed upon and presented through different graphs. Some important key findings of the present investigation are that the temperature of the Casson fluid becomes lower for local temperature Grashof number and solutal Grashof number. It is initiated that the Casson fluid parameter increases the velocity of the fluid whereas the opposite effect is noticed in the temperature profile. Higher estimation of Prandtl number and magnetic parameter elevated the Casson fluid concentration. Finally, the skin friction coefficient, Nusselt number, and Sherwood number are calculated and tabulated. It is also examined that the Nusselt number is weakened for both the Dufour number and Soret number but the skin fraction coefficient is greater for both the Dufour number and Soret number.
An integrated analysis of hypoxic–ischemic encephalopathy‐related cell sequencing outcomes via genes network construction
Authors: Zhou Hong‐Su , Chen Ting‐Bao 
Published: March 2022

AbstractHypoxic–ischemic encephalopathy (HIE) is one of the main causes of morbidity and severe neurological deficits in neonates. This study aimed to find core genes and their potential roles in HIE with the help of single‐cell sequencing (SCS) technology and genes network construction. We collected and screened an HIE genes data set from the Pubmed database to analyze differential expression, and the differential values of genes were ≥3 or ≤−3 in gene expression. We constructed a protein–protein interaction (PPI) network by the string, which was also verified by Cytoscape 3.8.2. Functional enrichment analysis was performed to determine the characteristics and pathways of the core genes. We examined two meaningful papers and integrated all genes by SCS, which were classified into 12,093 genes without duplicates, 217 shared genes, and 11,876 distinct genes. Among 217 genes, the signal transducer and activator of transcription (STAT) family was the most targeted gene in the PPI network. Moreover, Gene Ontology and Kyoto encyclopedia of genes and genome analysis showed that the process in response to virus and the JAK‐STAT signaling pathway play significant roles in HIE. We also found that 54 screened genes were highly expressed, while three genes (B2M, VIM, and MRPS30) were different in the heat map and differential genes expression exhibition. VIM, as an essential portion of the brain's cytoskeleton, is closely linked to STAT and neurologic development. From the findings of SCS and bioinformatics predictive analytics model, our outcomes provided a better understanding of the roles of STAT, the JAK‐STAT signaling pathway, and VIM, which can pave an alternative avenue for further studies on HIE progression.
Extracellular vesicles released by steatotic hepatocytes alter adipocyte metabolism
Authors: Mleczko J.E. , Royo F. , Samuelson I. , Clos‐Garcia M. , Williams C. , Cabrera D. , Azparren‐Angulo M. , Gonzalez E. , Garcia‐Vallicrosa C. , Carobbio S. , Rodriguez‐Cuenca S. , Azkargorta M. , van Liempd S. , Elortza F. , Vidal‐Puig A. , Mora S. , Falcon‐Perez J.M. 
Published: March 2022

AbstractThe composition of extracellular vesicles (EVs) is altered in many pathological conditions, and their molecular content provides essential information on features of parent cells and mechanisms of crosstalk between cells and organs. Metabolic Syndrome (MetS) is a cluster of clinical manifestations including obesity, insulin resistance, dyslipidemia and hypertension that increases the risk of cardiovascular disease and type 2 diabetes mellitus. Here, we investigated the crosstalk between liver and adipocytes by characterizing EVs secreted by primary hepatocytes isolated from Zucker rat model, and studied the effect they have on 3T3‐L1 adipocytes. We found that steatotic hepatocytes secrete EVs with significantly reduced exosomal markers in comparison with their lean counterpart. Moreover, proteomic analysis revealed that those EVs reflect the metabolic state of the parent cell in that the majority of proteins upregulated relate to fat metabolism, fatty acid synthesis, glycolysis, and pentose phosphate pathway. In addition, hepatocytes‐secreted EVs influenced lipolysis and insulin sensitivity in recipient 3T3‐L1 adipocytes. Untargeted metabolomic analysis detected alterations in different adipocyte metabolic pathways in cells treated with hepatic EVs. In summary, our work showed that steatosis has a significant impact in the amount and composition of EVs secreted by hepatocytes. Moreover, our data point to the involvement of hepatic‐EVs in the development of pathologies associated with MetS.
A counterexample to the lights out problem
Authors: Nagy János , Pach Péter Pál 
Published: March 2022

AbstractIn this note we present a counterexample to the “lights out problem”, that is, for every odd prime we construct a simple graph with vertex set such that there does not exist elements such that for each . On the other hand, in the positive direction, we show that if a certain quadratic form is associated to the graph and the prime is positive definite, then the conjecture holds.
Magnetic Resonance Elastography of Intervertebral Discs: Spin‐Echo Echo‐Planar Imaging Sequence Validation
Authors: Co Megan , Dong Huiming , Boulter Daniel J. , Nguyen Xuan V. , Khan Safdar N. , Raterman Brian , Klamer Brett , Kolipaka Arunark , Walter Benjamin A. 
Published: March 2022

BackgroundMagnetic resonance elastography (MRE) is an imaging technique that can noninvasively assess the shear properties of the intervertebral disc (IVD). Unlike the standard gradient recalled echo (GRE) MRE technique, a spin‐echo echo‐planar imaging (SE‐EPI) sequence has the potential to improve imaging efficiency and patient compliance.PurposeTo validate the use of an SE‐EPI sequence for MRE of the IVD compared against the standard GRE sequence.Study TypeCross‐over.SubjectsTwenty‐eight healthy volunteers (15 males and 13 females, age range: 19–55).Field Strength/Sequence3 T; GRE, SE‐EPI with breath holds (SE‐EPI‐BH) and SE‐EPI with free breathing (SE‐EPI‐FB) MRE sequences.AssessmentMRE‐derived shear stiffnesses were calculated via principal frequency analysis. SE‐EPI derived shear stiffness and octahedral shear strain signal‐to‐noise ratios (OSS‐SNR) were compared against those derived using the GRE sequence. The reproducibility and repeatability of SE‐EPI stiffness measurements were determined. Shear stiffness was evaluated in the nucleus pulposus (NP) and annulus fibrosus (AF) regions of the disc. Scan times between sequences were compared.Statistical TestsLinear mixed models, Bland–Altman plots, and Lin's concordance correlation coefficients (CCCs) were used with P < 0.05 considered statistically significant.ResultsGood correlation was observed between shear stiffnesses derived from the SE‐EPI sequences with those derived from the GRE sequence with CCC values greater than 0.73 and 0.78 for the NP and AF regions, respectively. OSS‐SNR was not significantly different between GRE and SE‐EPI sequences (P > 0.05). SE‐EPI sequences generated highly reproducible and repeatable stiffness measurements with CCC values greater than 0.97 in the NP and AF regions and reduced scan time by at least 51% compared to GRE. SE‐EPI‐BH and SE‐EPI‐FB stiffness measurements were similar with CCC values greater than 0.98 for both regions.Data ConclusionSE‐EPI‐based MRE‐derived stiffnesses were highly reproducible and repeatable and correlated with current standard GRE MRE‐derived stiffness estimates while reducing scan times.Level of Evidence1Technical Efficacy Stage1
The relationship between spiritual leadership and human engineering among university employees: The mediating role of mindfulness
Authors: Mohammed Sanaa Mostafa Mohammed , El‐Ashram Reda Ebrahim Mohamed , Abosaif Mahmoud Sayed Ali 
Published: March 2022

AbstractThis study explores whether, and how, mindfulness mediates the relationship between spiritual leadership and human engineering. Based on data from a sample of 335 members of faculty and administrative staff from Imam Mohammad Ibn Saud Islamic University in Saudi Arabia, the paper provides insights into how mindfulness affects the relationship between spiritual leadership and human engineering. The authors believe that it is the first time that mindfulness as a mediator in this relationship has been studied. They also believe that it is the first time such a study has been conducted in an Arab environment. By studying the relationship between spiritual leadership and human engineering, and by studying mindfulness as a mediating variable in this relationship in a non‐Western environment, the study expands the external validity of the notions of spiritual leadership and human engineering. The results indicate a significant relationship between spiritual leadership and human engineering, and show that mindfulness has an indirect effect on this relationship. The article highlights the implications for dealing with stress in the work environment by using mindfulness as a driver for developing spiritual leadership, as well as understanding and practicing the values of spiritual leadership in promoting spirituality.
Evaluation of oral anticoagulant prescribing patterns and associated hospital acquired complications – a single centre Australian study
Authors: Khalil Viviane 
Published: March 2022

AbstractBackgroundOral Anticoagulants (OACs) are widely prescribed for various chronic conditions. Inappropriate prescribing has been reported in various settings.AimsThe primary aim of this study was to assess the proportion of inpatients who were prescribed OACs concordant with prescribing recommendations. The secondary aims were to assess predictors of inappropriate prescribing and evaluate the number of related hospital‐acquired complications (HAC).MethodA retrospective audit was conducted in a multisite 650‐bed Australian Hospital from January to March 2019 to fulfil the study objectives. Consecutive patients who were discharged on OAC were included. Patients’ demographics, OAC prescribed and comorbidities data were collected. Appropriateness of OAC use was evaluated according to the manufacturer’s recommendations. HAC data were retrieved from the hospital coding unit from January to June 2019 to evaluate the impact of inappropriate OAC prescribing.ResultsA total of 322 patients were eligible to be included in the study. Of this cohort, 185 (57%) were prescribed appropriate therapy. There was a total of 78 HAC reported cases over the study period. Predictors of inappropriate prescribing included those with HASBLED scores > 3 (OR = 0.205 (0.127–0.331), p < 0.0001), discharged from surgical units (OR = 0.522 (0.312–0.875), p = 0.014) or prescribed warfarin (OR = 0.236 (0.106–0.524), p < 0.001). [Correction added on 19 April 2022: “CHA2DS2‐VASc > 3 (OR = 0.668 (0.426–1.049), p = 0.079),” was removed from before “HASBLED scores > 3…” in the preceding sentence.]ConclusionInappropriate OAC prescribing is prevalent among inpatients. Strategies should be developed to assist clinicians to improve OAC prescribing in an evidence‐based approach.