Stand-alone Tool Research Articles

Reading Patterns, Scanning and the ‘Control F’/Search Icon: How Students Really (Don’t) Read

Purpose: The purpose of this research was to investigate whether digital reading had an impact on reading skills, as well as students’ tendencies to read online or offline in the L2 English speaking classroom. Approach/Methodology/Design: This quantitative-qualitative mixed methods case study involved was comprised of a convenient, purposive sample of 16 participants for semi structured focus group interviews in an English-speaking private university. Findings: The findings seem to suggest that reading digitally prods students not only to adopt skimming patterns, but to use the “Control F” command to bypass reading altogether. Furthermore, students’ reading preferences for online/offline material was also revealed, showing a significant tendency of students to revert to online material “just to understand” or “get an idea” while deep understanding was substantially associated with preference for offline reading. Practical Implications: The findings of this study may serve to guide teachers of English in the L2 classroom how to navigate online texts comprehensively, what skills to promote while reading online and which to forgo. Originality/value: This study sheds light on the possible misuse of “Control F” during online reading exercises and underscores the necessity of using this tool over and above reading strategies and skills, and not as a stand-alone tool in itself,

Phylogenomic analysis supports Mycobacterium tuberculosis transmission between humans and elephants.

Tuberculosis is an infectious disease caused by a group of acid-fast bacilli known as Mycobacterium tuberculosis complex (MTC), which has a major impact on humans. Transmission of MTC across the human-animal interface has been demonstrated by several studies. However, the reverse zoonotic transmission from humans to animals (zooanthroponosis) has often been neglected. In this study, we used Nanopore MinION and Illumina MiSeq approaches to sequence the whole genome of M. tuberculosis strains isolated from two deceased Asian elephants (Elephas maximus) and one human in Chitwan, Nepal. The evolutionary relationships and drug resistance capacity of these strains were assessed using the whole genome data generated by the stand-alone tool Tb-Profiler. Phylogenomic trees were also constructed using a non-synonymous SNP alignment of 2,596 bp, including 94 whole genome sequences representative of the previously described M. tuberculosis lineages from elephants worldwide (lineages 1 and 4) and from humans in Nepal (lineages 1, 2 and 3). The new genomes achieved an average coverage of 99.6%, with an average depth of 55.67x. These M. tuberculosis strains belong to lineage 1 (elephant DG), lineage 2 (elephant PK) and lineage 4 (human), and none of them were found to have drug-resistant variants. The elephant-derived isolates were evolutionarily closely related to human-derived isolates previously described in Nepal, both in lineages 1 and 2, providing additional support for zooanthroponosis or bidirectional transmission between humans and elephants. The human-derived isolate clustered together with other published human isolates from Argentina, Russia and the United Kingdom in the lineage 4 clade. This complex multi-pathogen, multi-host system is challenging and highlights the need for a One Health approach to tuberculosis prevention and control at human-animal interface, particularly in regions where human tuberculosis is highly endemic.

Placenta accreta spectrum in early and late pregnancy from an imaging perspective. A scoping review

Placenta accreta spectrum (PAS) disorders (with increasing order of the depth of invasion: accreta, increta, percreta) are quite challenging for the purpose of diagnosis and treatment. Pathological examination or imaging evaluation are not very dependable when considered as stand-alone diagnostic tools. On the other hand, timely diagnosis is of great importance, as maternal and fetal mortality drastically increases if patient goes through the third phase of delivery in a not well-suited facility. A multidisciplinary approach for diagnosis (incorporating clinical, imaging, and pathological evaluation) is mandatory, particularly in complicated cases. For imaging evaluation, the diagnostic modality of choice in most scenarios is ultrasound (US) exam; patients are referred for MRI when US is equivocal, inconclusive, or not visualizing placenta properly. Herewith, we review the reported US and MRI features of PAS disorders (mainly focusing on MRI), going over the normal placental imaging and imaging pitfalls in each section, and lastly, covering the imaging findings of PAS disorders in the first trimester and cesarean section pregnancy (CSP).

FLUXestimator: a webserver for predicting metabolic flux and variations using transcriptomics data.

Quantitative assessment of single cell fluxome is critical for understanding the metabolic heterogeneity in diseases. Unfortunately, laboratory-based single cell fluxomics is currently impractical, and the current computational tools for flux estimation are not designed for single cell-level prediction. Given the well-established link between transcriptomic and metabolomic profiles, leveraging single cell transcriptomics data to predict single cell fluxome is not only feasible but also an urgent task. In this study, we present FLUXestimator, an online platform for predicting metabolic fluxome and variations using single cell or general transcriptomics data of large sample-size. The FLUXestimator webserver implements a recently developed unsupervised approach called single cell flux estimation analysis (scFEA), which uses a new neural network architecture to estimate reaction rates from transcriptomics data. To the best of our knowledge, FLUXestimator is the first web-based tool dedicated to predicting cell-/sample-wise metabolic flux and metabolite variations using transcriptomics data of human, mouse and 15 other common experimental organisms. The FLUXestimator webserver is available at http://scFLUX.org/, and stand-alone tools for local use are available at https://github.com/changwn/scFEA. Our tool provides a new avenue for studying metabolic heterogeneity in diseases and has the potential to facilitate the development of new therapeutic strategies.

Analysis of Telestroke Usage in Rural Critical Access Emergency Departments.

Introduction: Telestroke is an effective strategy to increase appropriate stroke treatments among patients in resource-limited environments. Despite the well-documented benefits of telestroke, there is limited literature regarding its utilization. The purposes of this study are: (1) determine the percentage of potential stroke patients who generate a telestroke consult in rural critical access hospitals (CAHs) and (2) validate an electronic medical record (EMR)-derived report as a stroke screen. Methods: This retrospective chart review analyzed patients presenting between September 1, 2020 and February 1, 2021 to three CAHs. Visits with triage complaints suggesting acute ischemic stroke (AIS)/transient ischemic attack (TIA) were pooled for analysis using an EMR-derived report. Patients with confirmed AIS/TIA at discharge over this period were used to validate the EMR tool. Results: The EMR report pooled 252 possible AIS/TIA visits out of 12,685 emergency department visits for analysis. It had a specificity of 98.78% and sensitivity of 58.06%. Of the 252 visits, 12.7% met telestroke criteria and 38.89% received telestroke evaluation. Among these, a definite diagnosis of AIS/TIA was made in 92.86%. Of the remaining population who met criteria but didn't undergo consultation, 61.11% were diagnosed with AIS/TIA at discharge. Conclusion: This study provides novel characterization of stroke presentations and telestroke in rural CAHs. The EMR-derived report is a reasonable tool to concentrate potential AIS/TIA cases for review and resource allocation but is not sensitive enough to detect stroke as a stand-alone tool. The majority (56%) of eligible patients did not undergo telestroke consultation. Future studies are critical to further understand reasons contributing to this.

Golgi_DF: Golgi proteins classification with deep forest.

Golgi is one of the components of the inner membrane system in eukaryotic cells. Its main function is to send the proteins involved in the synthesis of endoplasmic reticulum to specific parts of cells or secrete them outside cells. It can be seen that Golgi is an important organelle for eukaryotic cells to synthesize proteins. Golgi disorders can cause various neurodegenerative and genetic diseases, and the accurate classification of Golgi proteins is helpful to develop corresponding therapeutic drugs. This paper proposed a novel Golgi proteins classification method, which is Golgi_DF with the deep forest algorithm. Firstly, the classified proteins method can be converted the vector features containing various information. Secondly, the synthetic minority oversampling technique (SMOTE) is utilized to deal with the classified samples. Next, the Light GBM method is utilized to feature reduction. Meanwhile, the features can be utilized in the penultimate dense layer. Therefore, the reconstructed features can be classified with the deep forest algorithm. In Golgi_DF, this method can be utilized to select the important features and identify Golgi proteins. Experiments show that the well-performance than the other art-of-the state methods. Golgi_DF as a standalone tools, all its source codes publicly available at https://github.com/baowz12345/golgiDF. Golgi_DF employed reconstructed feature to classify the Golgi proteins. Such method may achieve more available features among the UniRep features.

El espectro de placenta acreta en la etapa temprana y final del embarazo. Un repaso a través de la imagen

Placenta accreta spectrum (PAS) disorders (with increasing order of the depth of invasion: accreta, increta, percreta) are quite challenging for the purpose of diagnosis and treatment. Pathological examination or imaging evaluation are not very dependable when considered as stand-alone diagnostic tools. On the other hand, timely diagnosis is of great importance, as maternal and fetal mortality drastically increases if patient goes through the third phase of delivery in a not well-suited facility. A multidisciplinary approach for diagnosis (incorporating clinical, imaging, and pathological evaluation) is mandatory, particularly in complicated cases. For imaging evaluation, the diagnostic modality of choice in most scenarios is ultrasound (US) exam; patients are referred for MRI when US is equivocal, inconclusive, or not visualizing placenta properly. Herewith, we review the reported US and MRI features of PAS disorders (mainly focusing on MRI), going over the normal placental imaging and imaging pitfalls in each section, and lastly, covering the imaging findings of PAS disorders in the first trimester and cesarean section pregnancy (CSP).

Low Specificity of Rapid Eye Movement Sleep Behavior Disorder Questionnaires: Need for Better Screening Methods.

Correct diagnosis of rapid eye movement sleep behavior disorder (RBD) is critical due to its link to α-synucleinopathies and risk of injuries and requires video-polysomnography (V-PSG). Usefulness of screening questionnaires outside the context of validation studies is limited. The aim was to assess the performance of three validated RBD screening questionnaires compared with gold-standard V-PSG. In this bicentric prospective study, 400 consecutive subjects referred to a sleep center for the first time filled three RBD questionnaires (RBD Screening Questionnaire, RBD Single Question, and Innsbruck RBD Inventory) in random order before sleep experts' interview. Subjects positive for at least one questionnaire were invited to undergo V-PSG. Data from patients negative for all questionnaires undergoing V-PSG for other reasons were also evaluated. Questionnaire performances were compared to gold-standard V-PSG RBD diagnosis. Three hundred ninety-nine patients (median age: 51 [interquartile range: 37-64] years, 54.9% men) participated. Two hundred thirty-eight (59.6%) were positive for at least one questionnaire, and RBD was diagnosed using V-PSG in 30 patients (7.5%). Questionnaire specificity was 48.1% to 67.4%, sensitivity 80% to 92%, accuracy 51% to 68.3%, negative predictive value 94.2% to 98%, and positive predictive value 14.1% to 20.7%, with no relevant differences in performances among the evaluated questionnaires. RBD questionnaires have low specificity and low positive predictive value and should not be used as a standalone tool for the diagnosis of RBD. Further development of RBD screening methods is needed, particularly for upcoming neuroprotective trials. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

AntiSMASH 7.0: new and improved predictions for detection, regulation, chemical structuresand visualisation.

Microorganisms produce small bioactive compounds as part of their secondary or specialised metabolism. Often, such metabolites have antimicrobial, anticancer, antifungal, antiviral or other bio-activities and thus play an important role for applications in medicine and agriculture. In the past decade, genome mining has become a widely-used method to explore, access, and analyse the available biodiversity of these compounds. Since 2011, the 'antibiotics and secondary metabolite analysis shell-antiSMASH' (https://antismash.secondarymetabolites.org/) has supported researchers in their microbial genome mining tasks, both as a free to use web server and as a standalone tool under an OSI-approved open source licence. It is currently the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in archaea, bacteria, and fungi. Here, we present the updated version 7 of antiSMASH. antiSMASH 7 increases the number of supported cluster types from 71 to 81, as well as containing improvements in the areas of chemical structure prediction, enzymatic assembly-line visualisation and gene cluster regulation.

MembIT – A Tool to Calculate Solute Membrane Insertions and Deformations in Molecular Dynamics Simulations

In molecular dynamics simulations of membrane systems, it is very important to evaluate the interactions between membrane bilayers and other molecules like small compounds, peptides, or proteins. When these interactions lead to local deformations in the membrane, it is essential to fully understand and accurately characterize them, since these deformations can impact the calculation of membrane properties. Here, we introduce MembIT, a simple standalone tool that calculates several membrane properties that are very useful to gauge system equilibration and quality control in molecular dynamics simulations. It has implemented a distinction between local and bulk lipids, which corrects the local deformations, that are often overlooked by other tools. We show examples of MembIT calculations of membrane insertion and deformation values in systems containing POPC and a small drug (sunitinib), a transmembrane peptide (pHLIP), and a transmembrane protein (ADP/ATP carrier). We hope that this tool will be adopted by the scientific community and that the analyses that it provides become good practices in MD simulations of membrane systems.

A novel method for the automated simulation of various vehicle collisions to estimate crash severity

Objective: Vehicle collisions are described with the help of collision severity parameters such as energy equivalent speed (EES) and the collision-based change of velocity (delta-v). These serve as an input for injury outcome estimations through injury risk functions (IRF) or for the virtual assessment of active safety systems in case of a modified collision. A novel method was developed with the aim of simulating various vehicle collisions within a short time frame while ensuring the accuracy of the collision severity parameters. Methods: Previously developed three-dimensional EES models were used in this study. They were used to compute 2 D vehicle substitute models, which are deformed during a new, time-discrete method. By using fundamentals of mechanical impact calculation and vehicle kinematics, relevant collision severity parameters are calculated. These steps are executed in an own developed standalone tool named impactEES. The results obtained were verified against measured crash test data from the European New Car Assessment Programme (Euro NCAP) and the Technical Center of Allgemeiner–Deutscher–Automobil-Club (ADAC). Results: The novel method enables the automated computation of various car-to-car and car-to-object collisions. The output of impactEES includes the deformation area, EES, and delta-v. Furthermore, it includes the following time-discrete data for each vehicle: translational and angular accelerations, translational and angular velocities, and the position of the center of gravity in addition to the heading of the vehicle. Finally, without the need of highly sophisticated hardware, a single simulation of a collision between two vehicles can be calculated within only a few seconds including collision severity parameters. Based on the comparison of measured crash test data and results obtained from impactEES the mean percentage error (MPE) and its standard deviation (SD) were calculated for EES (MPE= − 2.0%, SD = 8.4%, n = 14) and delta-v (MPE= − 1.2%, SD = 14.2%, n = 18). Conclusions: The novel method allows for the 2 D computation of various car-to-car and car-to-object collisions. Using predefined IRF allows the assessment of injury probabilities relative to the change of collision severity parameters. Both can be used for the virtual assessment of injury mitigation capabilities of active safety systems and thus represent an important contribution to its targeted development.

VirClust-A Tool for Hierarchical Clustering, Core Protein Detection and Annotation of (Prokaryotic) Viruses.

Recent years have seen major changes in the classification criteria and taxonomy of viruses. The current classification scheme, also called "megataxonomy of viruses", recognizes six different viral realms, defined based on the presence of viral hallmark genes (VHGs). Within the realms, viruses are classified into hierarchical taxons, ideally defined by the phylogeny of their shared genes. To enable the detection of shared genes, viruses have first to be clustered, and there is currently a need for tools to assist with virus clustering and classification. Here, VirClust is presented. It is a novel, reference-free tool capable of performing: (i) protein clustering, based on BLASTp and Hidden Markov Models (HMMs) similarities; (ii) hierarchical clustering of viruses based on intergenomic distances calculated from their shared protein content; (iii) identification of core proteins and (iv) annotation of viral proteins. VirClust has flexible parameters both for protein clustering and for splitting the viral genome tree into smaller genome clusters, corresponding to different taxonomic levels. Benchmarking on a phage dataset showed that the genome trees produced by VirClust match the current ICTV classification at family, sub-family and genus levels. VirClust is freely available, as a web-service and stand-alone tool.

Systems methods for analyzing trade-offs between food security and conserving biodiversity

The endeavor for greater food security has caused trade-offs between increasing agricultural production and conserving habitat of threatened species. We take a novel approach to analyze these trade-offs by applying and comparing three systems methods (systems diagrams, influence matrices, and land use modeling) in a case study of Uganda. The first two methods were used to scope out the trade-off system and identify the most important variables influencing trade-offs. These variables were agricultural yield, land governance processes, and change in land use and land cover. The third method was used to quantify trade-offs and evaluate policy scenarios to alleviate them. A reference scenario indicated that increasing agricultural production by expanding agricultural land provided food for 79% more people in 2050 (compared to 2005) but with a 48% loss of habitat of threatened species. A scenario assuming strong investments to augment agricultural yield increased the number of people fed in 2050 up to 157%, while reducing the loss of habitat down to 27%. We use a novel “trade-off coefficient” for a consistent comparison of scenario results. A scenario assuming yield improvement and ring-fencing protected areas reduced the trade-off coefficient from − 0.62 in the reference case to − 0.15. This coefficient can be used as a common basis to compare results from different trade-off studies. It was found that the three systems methods are useful, but have limitations as stand-alone tools. Combining the methods into a single methodology increases their collective utility by maximizing the transparency and comprehensiveness and potential stakeholder engagement of a trade-off analysis.

How Interactive Visualizations Compare to Ethical Frameworks as Stand-Alone Ethics Learning Tools for Health Researchers and Professionals

Background Despite the bourgeoning of digital tools for bioethics research, education, and engagement, little research has empirically investigated the impact of interactive visualizations as a way to translate ethical frameworks and guidelines. To date, most frameworks take the format of text-only documents that outline and offer ethical guidance on specific contexts. This study’s goal was to determine whether an interactive-visual format supports frameworks in transferring ethical knowledge by improving learning, deliberation, and user experience. Methods An experimental comparative study was conducted with a pre-, mid-, and post-test design using the online survey platform Qualtrics. Participants were university based early-stage health researchers who were randomly assigned to either the control condition (text-only document) or the experimental condition (interactive-visual). The primary outcome variables were learning, (measured using a questionnaire), deliberation (using cases studies) and user experience (measured using the SED/UD Scale). Analysis was conducted using descriptive statistics and mixed-effects linear regression. Results Of the 80 participants, 44 (55%) used the text-only document and 36 (45%) used the interactive-visual. Results of the knowledge-test scores showed a statistically significant difference between participants’ post-test scores, indicating that the interactive-visual format better supported understanding, acquisition, and application of the framework’s knowledge. Findings from the case studies showed both formats supported ethical deliberation. Results further indicated the interactive-visual provided an overall better episodic and remembered user experience compared with the text-only document. Conclusions Our findings show that ethical frameworks formatted with interactive and visual qualities provide a more pleasing user experience and are effective formats for ethics learning and deliberation. These findings have implications for practitioners developing and deploying ethical frameworks and guidelines (e.g., in educational or employee-onboarding settings), in that the knowledge generated can lead to more effective dissemination practices of normative guidelines and health data ethics concepts.

Diagnostic accuracy of the PMcardio smartphone application for artificial intelligence–based interpretation of electrocardiograms in primary care (AMSTELHEART-1)

The use of 12-lead electrocardiogram (ECG) is common in routine primary care, however it can be difficult for less experienced ECG readers to adequately interpret the ECG. To validate a smartphone application (PMcardio) as a stand-alone interpretation tool for 12-lead ECG in primary care. We recruited consecutive patients who underwent 12-lead ECG as part of routinely indicated primary care in the Netherlands. All ECGs were assessed by the PMcardio app, which analyzes a photographed image of 12-lead ECG for automated interpretation, installed on an Android platform (Samsung Galaxy M31) and an iOS platform (iPhone SE2020). We validated the PMcardio app for detecting any major ECG abnormality (MEA, primary outcome), defined as atrial fibrillation/flutter (AF), markers of (past) myocardial ischemia, or clinically relevant impulse and/or conduction abnormalities; or AF (key secondary outcome) with a blinded expert panel as reference standard. We included 290 patients from 11 Dutch general practices with median age 67 (interquartile range 55-74) years; 48% were female. On reference ECG, 71 patients (25%) had MEA and 35 (12%) had AF. Sensitivity and specificity of PMcardio for MEA were 86% (95% CI: 76%-93%) and 92% (95% CI: 87%-95%), respectively. For AF, sensitivity and specificity were 97% (95% CI: 85%-100%) and 99% (95% CI: 97%-100%), respectively. Performance was comparable between Android and iOS platform (kappa = 0.95, 95% CI: 0.91-0.99 and kappa = 1.00, 95% CI: 1.00-1.00 for MEA and AF, respectively). A smartphone app developed to interpret 12-lead ECGs was found to have good diagnostic accuracy in a primary care setting for major ECG abnormalities, and near-perfect properties for diagnosing AF.

Systematic Review and Meta-Analysis: Clinical Utility of Continuous Performance Tests for the Identification of Attention-Deficit/Hyperactivity Disorder

We aimed to quantify the clinical utility of continuous performance tests (CPTs) for the diagnosis of attention-deficit/hyperactivity disorder (ADHD) compared to a clinical diagnosis in children and adolescents. Four databases (MEDLINE, PsycINFO, EMBASE, and PubMed) were screened until January 2023. Risk of bias of included results was judged with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). We statistically pooled the area under the curve, the sensitivity, and the specificity of 3 commonly used CPTs subscales: omission/inattention, commission/impulsivity, and total number of errors/ADHD subscales (PROSPERO registration: CRD42020168091). A total of 19 studies using commercially available CPTs were identified. Results from up to 835 control individuals and 819 cases were combined in the summary receiver operating characteristic (ROC) curve analyses (sensitivity and specificity pooling), and up to 996 cases and 1,083 control individuals in the area under the curve (AUC) analyses. Clinical utility as measured by AUCs could be considered as barely acceptable (between 0.7 and 0.8) for the most part, with the best results for the total/ADHD score, followed by omissions/inattention, and poorest for commission/impulsivity scores. A similar pattern was found when pooling sensitivity and specificity: 0.75 (95% CI= 0.66-0.82) and 0.71 (0.62-0.78) for the total/ADHD score; 0.63 (0.49-0.75) and 0.74 (0.65-0.81) for omissions; and 0.59 (0.38-0.77) and 0.66 (CI= 0.50-0.78) for commissions. At the clinical level, CPTs as a stand-alone tool have only a modest to moderate ability to differentiate ADHD from non-ADHD samples. Hence, they should be used only within a more comprehensive diagnostic process. A systematic review of screening tools for ADHD in children and adolescents; https://www.crd.york.ac.uk/prospero/; CRD42020168091.

CellTrackVis: interactive browser-based visualization for analyzing cell trajectories and lineages

BackgroundAutomatic cell tracking methods enable practitioners to analyze cell behaviors efficiently. Notwithstanding the continuous development of relevant software, user-friendly visualization tools have room for further improvements. Typical visualization mostly comes with main cell tracking tools as a simple plug-in, or relies on specific software/platforms. Although some tools are standalone, limited visual interactivity is provided, or otherwise cell tracking outputs are partially visualized.ResultsThis paper proposes a self-reliant visualization system, CellTrackVis, to support quick and easy analysis of cell behaviors. Interconnected views help users discover meaningful patterns of cell motions and divisions in common web browsers. Specifically, cell trajectory, lineage, and quantified information are respectively visualized in a coordinated interface. In particular, immediate interactions among modules enable the study of cell tracking outputs to be more effective, and also each component is highly customizable for various biological tasks.ConclusionsCellTrackVis is a standalone browser-based visualization tool. Source codes and data sets are freely available at http://github.com/scbeom/celltrackvis with the tutorial at http://scbeom.github.io/ctv_tutorial.

Role of MRI in the evaluation of acute pyelonephritis in a high-risk population with renal dysfunction: a prospective study

This study aims to evaluate the (a) accuracy of conventional and diffusion-weighted-imaging (DWI) sequences in the diagnosis of acute pyelonephritis and (b) minimum apparent diffusion coefficient (ADC) values for the diagnosis of acute pyelonephritis and the differentiation of renal abscesses from acute pyelonephritis. Ultrasound, conventional MRI sequences, and DWI were used to evaluate the kidneys in 68 patients suspected to have acute pyelonephritis. Multiple similar regions of interest (ROIs) were placed over the renal parenchyma with visually identifiable diffusion restriction, over the non-diffusion-restricted renal parenchyma of affected kidneys and over the normal kidneys. Corresponding minimum ADCs were noted for analysis. Pyelonephritis was confirmed based on clinical criteria, laboratory findings, and by resolution/development of known complications of pyelonephritis. DWI showed the highest sensitivity(100%), while DWI read with T2-weighted imaging (both being positive) showed the highest specificity(100%) for the diagnosis of acute pyelonephritis in our population with a high baseline creatinine. The minimum-ADC of the nephritic diffusion-restricted area in patients with confirmed pyelonephritis was significantly lower than the minimum-ADC in patients without pyelonephritis [(0.934 ± 0.220, mean ± SD) vs (1.804 ± 0.404) × 10-3s/mm2] (p < 0.001). ROC cut-off of minimum-ADC for the diagnosis of acute pyelonephritis was 1.202 × 10-3s/mm2 (area under curve 0.978). The minimum-ADC of the abscesses were significantly lower when compared to the minimum-ADC of the nephritic diffusion-restricted portion of the same kidney [(0.633 ± 0.248) vs (0.850 ± 0.191) × 10-3s/mm2] (p < 0.001). DWI is an excellent stand-alone imaging tool that can be combined with conventional sequences for the diagnosis of APN even in patients with high serum-creatinine or other contraindications to intravenous contrast. Further, ADC values can be used to differentiate between renal abscesses and uncomplicated pyelonephritis.

Application of Machine Learning Methods for Data Analytics in Social Sciences

This article addresses the challenges in the application of artificial intelligence methods such as machine learning, computational intelligence and/or soft computing methods in social sciences. The literature review is performed in order to give a review of different approaches and methods that have been applied so far. The most used method in social sciences and management is the SWOT method, for the identification of strengths, weaknesses, opportunities, and threats when making strategic decisions. Two fundamental characteristics of previous approaches are the development of numerical models of utility functions and the possibility of upgrading these models by formalizing the intuition of strategic decision-makers. There are several shortcomings of the existing approaches. The application of computational intelligence and machine learning methods in social sciences is identified as one of the most challenging and promising areas, which could overcome identified shortcomings. The principles of one popular machine learning method, the decision tree, are explained and a demonstration is performed on the case study of churn prediction. Benchmarking data set from the publicly available repository is used to demonstrate the suggested approach Evaluation results measured through model accuracy and reliability gave promising results for further analysis. A developed predictive model could serve as a standalone tool or as support for decision-making in social sciences.

Modeling simultaneous momentum and passive scalar transfer in turbulent annular Poiseuille flow

AbstractSimultaneous momentum and passive scalar transfer in weakly heated pressure‐driven turbulent concentric annular pipe flow is numerically investigated using the cylindrical formulation of the stochastic one‐dimensional turbulence (ODT) model, which is utilized here as standalone tool. In the present study, we focus on the model calibration for heated annular pipes based on recent reference direct numerical simulations (DNS) from Bagheri and Wang (Int. J. Heat Fluid Flow 86, 108725, 2020; Phys. Fluids 33, 055131, 2021). It is shown that the model is able to individually capture scalar and momentum transfer, but not both equally well at the same time. We attribute this to less dissimilar scalar and momentum transport in the model at the low Reynolds number investigated. It is argued that the model prefers a fully developed turbulent state due to its construction. Nevertheless, it is demonstrated that ODT is able to reasonably capture the radial inner‐outer asymmetry of the scalar and momentum boundary layers which yields better predictive capabilities than wall‐function‐based approaches.