Analysis Software Package Research Articles

Training technologies as a means of increasing motivation for creative activity of future nursery teachers

The article investigates the problem of increasing motivation for creative activity of future teachers with the help of training technologies. The studied experience of using training technologies allowed determining their potential to increase the motivation of future teachers to creative activities. Experimental application of training technologies was tested in training courses for future teachers “Psychology,” “General Pedagogy,” “Introduction to the Specialty.” Mathematical data processing methods and a software package for statistical analysis “Statistica” were used to analyze the obtained results and objectively consider the dynamics of change. Socio-psychological training is the most effective way to increase the level of motivation for creative activity of future teachers. Experimental research has shown that training should include a wide range of techniques, namely: icebreaker exercises, feedback games, game of social-perceptual orientation, communication games, psychotechnics aimed at problem solving, meditation, visualization.

Application of mathematical modeling methods to determine the effect of soil on natural vibration frequencies of pipelines

When a pipeline is subjected to an external influence that can affect the frequency of its natural vibrations, the parameters of its natural vibrations change, which increases the measurement error, and often simply distorts the results of vibration control. For pipelines, such an impact may be the influence of the soil when pipelines are laid without a channel. Different types of soil affect the change in the natural vibration frequency of the pipeline in different ways.The purpose of the article is to analyze the influence of various types of soils on the parameters of natural vibrations of the pipeline. The aim of the study was to theoretically confirm the dependence of the change in the frequency of vibration of the pipeline under the influence of soil.A modal analysis of natural oscillations of 5 polyethylene pipelines was performed. As initial data, it is assumed that the design pipeline is laid in a trench with inclined walls, with the slope laid on a flat base at a depth of 2.5 m. The calculations were performed in the ANSYS finite element analysis software package. In order to build a mathematical model, the degree of soil impact on pipelines is determined by studying the vertical and lateral pressure of the soil on the above pipelines, and the natural vibrations of pipelines are analyzed.The results of the modal analysis for polyethylene pipes with a laying scheme with inclined walls and different soils (gravel sands, coarse and medium-sized; heavy clays) are presented. The soils were chosen that are the most common on the territory of Russia.Thus, the obtained dependence of the degree of influence of different soil on the natural frequencies of pipelines significantly increases the reliability of vibration diagnostics of buried communications, can facilitate the work on its organization and allow determining long-term forecasts of pipeline operation.

Stars on the Verge: Investigating Semiregular Light Variations and Changing Multiperiods of the Luminous Red Supergiant μ Cephei from over 175 yr of Photometry

Abstract μ Cephei is a 4th mag semi-regular variable M2Ia star. It is among the largest, most luminous red supergiants in our galactic neighborhood and a probable SN-II core-collapse progenitor. Analyses of ∼175 yr of photometry were conducted. The observations are mostly from the AAVSO database. Period analyses were conducted using the Period Analysis Software (Peranso-3) package. The CLEANest and Wavelet (WWZ) programs were utilized. Two dominant “periods” were found: P = 870 ± 50 days (∼2.39 yr) and a long period of ∼5300 ± 155 days (∼14.5 yr). The long period was prominent during the first ∼90 yr but weakened and was followed by multiple transitory periods ranging from ∼3000 to 4600 days. μ Cephei has interesting features including multiple periods, period-splitting, period-merging and period-decays.

The effectiveness of the implementation of interactive methods in the distance learning system of future primary school teachers

The article identifies that the main problem of distance online learning is the lack of interaction between teacher and student. The study was organized in three stages during 2020-2021. The methods of mathematical data processing and the software package for statistical analysis “Statistica” were used for the analysis of the obtained results and objective consideration of the dynamics of changes in the activity, cognitive and motivational components. The study showed the effectiveness of interactive methods in the distance learning system for the development of all components of the readiness of future primary school teachers to use pedagogical technologies. The author concluded that the most effective methods in the context of professional training of future primary school teachers and adaptation to the features of distance online learning are: microphone, unfinished sentences, brain storm, role play, case method, discussion, take a position, work in pairs, work in threes and small groups.

Abstract 2735: Clinical significance of CD4+CD7−helper T-cells and tumoral CD7 expression in colorectal cancer

Abstract CD7 is a transmembrane costimulatory glycoprotein and a member of the immunoglobulin supergene family, which is present on all thymocytes, most mature peripheral blood T-cells, and on natural killer (NK) cells. Studies indicate that the number of CD7 negative (CD7−) T-cells increases with age and in diseases such as chronic inflammation and in T-cell malignancies. To better understand the clinical relevance of CD7 expression in colon cancers and their immune microenvironment, tissue microarrays containing 1719 colorectal cancers were analyzed for CD3, CD4, CD8 and CD7 by multiplex fluorescence immunohistochemistry. Image analysis was performed using a U-net deep learning algorithm for cell detection and the “R” software package for statistical analysis. The density of CD3+CD4+ T-cells ranged from 0 to 8483 cells/mm2 (mean 504±686 cells/mm2) and the density of CD3+CD8+ T-cells ranged from 0 to 1386 cells/mm2 (mean 86±129 cells/mm2) in colorectal cancer. A high density of both, CD3+CD4+ helper T-cells and of CD3+CD8+ cytotoxic T-cells were associated with favorable tumor parameters, such as low tumor stage (p≤0.0004 each), negative nodal stage (p<0.0001 each) or absence of lymphatic vessel invasion (p≤0.0002 each) and high PD-L1 expression in immune cells (p<0.0001 each). In addition, a high density of CD3+CD8+ cytotoxic T-cells was linked to microsatellite instability (p<0.0001) and PD-L1 expression on tumor cells.The average fraction of T-cells lacking CD7 was 22% for CD3+CD4+ T-cells and 1% for CD3+CD8+ T-cells. A low fraction of CD3+CD4+CD7− T-cells was linked to low pT stage (p<0.0001) and microsatellite instability (p=0,0118) and tumor cell PD-L1 expression (p=0.0319) while the fraction of CD3+CD8+CD7− T-cells was unrelated to clinico-pathological parameters. Unequivocal membranous CD7 expression in cancer cells was found in 14 (0.8%) of cases and was significantly linked to lymphatic vessel invasion (p=0.0057) and perineural invasion (p=0.0045).In conclusion, the significant association of the fraction of CD3+CD4+CD7− T helper -cells with favorable clinicopathological features may suggest a clinically relevant role of this cell type. The rare CD7 positive colorectal cancers may potentially benefit from anti-CD7 therapies that are currently considered for T-cell neoplasias. Citation Format: Niclas Christian Blessin, Cheng Yang, Maximilian Lennartz, Katharina Möller, Tim Mandelkow, Ronald Simon, Guido Sauter, Christoph Fraune, Doris Höflmayer, Sarah Minner, Eike Burandt, Sören A Weidemann, Andreas M Luebke. Clinical significance of CD4+CD7−helper T-cells and tumoral CD7 expression in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2735.

Abstract 2773: Deep profiling of the PD-1/PD-L1 pathway in 10000 cancers revealed changes in the immune cell composition between cancer entities

Abstract Immune checkpoint inhibitor (CPI) therapies targeting the PD-1/PD-L1 pathway have shown remarkable results in a rising number of different tumor entities. The likelihood of a positive response rate to CPIs depends - amongst other factors - on the PD-L1 expression level in tumor cells and tumor infiltrating immune cells. PD-L1 expression on different cell types is known to impact both the function and the composition of immune cells in the tumor microenvironment. However, this process is not fully understood. To study the impact of PD-L1 expression on the intratumoral immune environment, a multiplex fluorescence immunohistochemistry approach was used enabling the simultaneous analysis of 15 different antibodies on a set of tissue microarrays containing samples from more than 10000 neoplasms from more than 100 different tumor types and subtypes. Image analysis was performed using a U-net deep learning algorithm for cell detection and the “R” software package for statistical analysis. PD-L1 expression was measured on tumor cells (AE1/AE3+), subsets of macrophages (CD68+CD163+/CD68+iNOS+) and dendritic cells (CD11c+). To address the complexity of the tumor microenvironment, PD-1 expression was measured on B-cells (CD20+) and T-cell subsets, including cytotoxic T-cells (CD3+CD8+), T-helper cells (CD3+CD4+), regulatory T-cells (CD3+CD4+FOXP3+) and their memory (CD45RO+), activated (CD7-) or expanding (ki67+) phenotypes. Although PD-L1 expression varied significantly between cell types, patients and different tumor entities, the number of PD-1+ T-cells was consistently linked to PD-L1 expression. Combined analysis of cell densities, expression patterns, intensity measurements, interaction and distance analysis between immune cells and tumor cells revealed distinct changes in the immune cell infiltration pattern linked to PD-L1 expression. Previously uncharacterized immune cell-composition dynamics in clustered tumor phenotypes, according to the PD-L1 expression, were detected. This included significant associations between PD-L1+ tumor cells and PD-L1+ antigen-presenting cells and various PD-1+ T-cell subsets. In conclusion, deep profiling of 15 biomarkers in 10 000 cancers revealed complex differences in the composition of tumor infiltrating immune cells depending on the PD-L1 expression level of tumor cells and the mononuclear phagocyte system. Citation Format: Niclas Christian Blessin, Cheng Yang, Jonas Raedler, Julia Ebner, Tim Mandelkow, Ronald Simon, Christoph Fraune, Maximilian Lennartz, Andreas M. Luebke, Sarah Minner, Eike Burandt, Doris Höflmayer, Guido Sauter, Katharina Möller, Sören A Weidemann. Deep profiling of the PD-1/PD-L1 pathway in 10000 cancers revealed changes in the immune cell composition between cancer entities [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2773.

AN RBF BASED HIGH-DIMENSIONAL MODEL REDUCTION APPROACH IN BUILDING OPTIMIZATION

Building optimization has gained importance with the recent push to create the most economical and efficient buildings possible. As the effects of optimization are a function of the building size, it is crucial to understand and further develop optimization techniques for large-scale building structures. Practical structural optimization of buildings requires the use of a structural analysis software package and an iterative optimization procedure. As a result, finite element (FE) software shall be linked with an optimization solver. It is an expensive process which requires extensive computer coding. Alternative methods are available, including metamodeling methods, which are used to create simple and approximate functions based on complex FE simulations. In this study, the approximate functions are generated using a high-dimensional model representation (HDMR) framework. The HDMR framework is a model reduction approach and is found to be very accurate for different functions. The component functions of HDMR are expressed using augmented radial basis functions (RBFs). To further improve the numerical efficiency of the metamodels and reduce the total required number of structural analyses, a few different HDMR sampling approaches are investigated, including one static approach and two iterative strategies. An existing nonlinear programming (NLP) solver is employed in the design process. To illustrate the proposed approach, a three-dimensional building structure is selected as a numerical example. The numerical optimization is conducted to reduce the torsional response of the building. The proposed optimization method works very well and the results from different HDMR techniques are compared.

Modeling: ratio between means of teaching and motor training in junior school physical education classes

Background and Study Aim. The purpose of the study was to determine the ratio between means of teaching and motor training in junior school physical education classes.
 Materials and methods. The study involved 32 boys who were 8 years old at the beginning of the experiment. They were randomly divided into four groups of eight people each. A pedagogical experiment was conducted using a 22 full factorial design. The study recorded the following indicators: number of repetitions required to teach exercises; grade for a unidirectional movement coordination exercise (test 1); grade for a multidirectional movement coordination exercise (test 2); error in time accuracy of performing the squat thrust (test 3); error in time accuracy of 5 jumps on marks in 5 s (test 4); error in assessing muscular effort with visual control (test 5); vestibular stability, error (test 6). The obtained experimental material was processed statistically using statistical analysis software packages (SPSS 20).
 Results. According to the logistic function analysis, the achievement of an optimal result in differentiating temporal characteristics of movement requires 8.5 months, strength characteristics of movement – 8 months, movement coordination – 8 months, vestibular analyzer stability – 10 months. It takes 3 to 5 months to obtain positive increases in testing results in boys aged 8-9. The ratio of time allotted for strength training (ST) and coordination training (CT) to teaching motor actions (TMA) varies as 1:4 (ST: TMA) and 1:4.5 (CT: TMA).
 Conclusions. The ratio of time allotted for strength training, coordination training, and teaching to the time of the main part of the class ranges between 14.3-23.5% (strength training), 17.1-23.5% (coordination training), and 53.0-68.6% (teaching). As exercises become more complicated, the time allotted for strength and coordination training increases.

Perceptions, Awareness, and Attitudes of Primary Health Care Workers Towards Management of Type-2 Diabetes in Jordan: A Qualitative Study

OBJECTIVE: This study aimed to explore health care workers’ perceptions, awareness and attitudes towards the factors that contribute to poor glycemic control among patients with Type-2 diabetes in Jordan. 
 
 MATERIAL & METHODS: A qualitative study was conducted to seek rich, in-depth data about health care workers’ perceptions and attitudes regarding Type-2 diabetes. Ten semi-structured interviews were conducted with primary health care workers: four nurses, physician, dietitian, pharmacist, lab technician, dentist and receptionist who were recruited using purposive sampling. All interviews were audio recorded, transcribed and uploaded to the qualitative data analysis software package NVivo 12. Thematic analysis was used to analyze the data. 
 
 RESULTS: Four themes were derived from the interview analysis: lack of knowledge of patients regarding diabetes and its management; influence of socio-cultural factors on patients’ diabetes management behaviors included eating pattern and physical activity; challenges related to the health care system including medication insecurity and health insurance policies and challenges related to staff shortages and poor patient-staff communication. 
 
 CONCLUSION: The findings suggest that medical and nursing practice could usefully move away from a task-oriented medical model towards a more holistic approach in diabetes management. Health promotion should be delivered in a wider context to target the population in different age groups to raise awareness of diabetes amongst the general population in Jordan. Nurses’ skills and knowledge could be utilized to rectify patients’ misconceptions and beliefs regarding diabetes treatment.

External function for GOTHIC code to estimate critical heat flux conditions for in-vessel retention assessment

GOTHIC is an integrated, general purpose thermal hydraulic software package for design, licensing, safety and operating analysis of Nuclear Power Plant containments, confinement buildings and system components. It bridges the gap between the lumped parameter codes frequently used for containment analysis (such as MELCOR, MAAP, COCOSYS, ASTEC codes) and Computational Fluid Dynamics codes. Within a single model, GOTHIC can include regions treated in conventional lumped parameter mode and regions with three-dimensional flows in complex geometries. The heat transfer correlations built into GOTHIC cover the portion of the boiling curve which spans single phase heat transfer up to pre-Critical Heat Flux (CHF) heat transfer. The implemented boiling curve is truncated to exclude post-CHF heat transfer as it has not been adequately verified and was considered by the developers to have little application in general containment analysis. As such, one area that the code is not currently qualified for is post-CHF heat transfer, which could occur for example in the case of In-Vessel Corium Retention, where cooling water enters in contact with the high temperature of the Reactor Pressure Vessel wall. The presented research focuses on creating an external subroutine that solves this limitation, enabling the GOTHIC code to account for CHF phenomena. The modeling of CHF would be very useful in order to enable the code to simulate the external Reactor Pressure Vessel (RPV) Cooling , as well as other types of severe accidents or analyses where post-CHF simulation is required. Several subroutine function switches were implemented in order to facilitate its usage for different types of heat structures and correlations. The subroutine determines the CHF values based on either: the 2006 Groeneveld Look-up Tables, Lookup Tables for Large Diameter Vertical Tubes, Look-up Tables for Large Diameter Horizontal Tubes, or the correlation used by the MELCOR code for critical heat flux situations. It shall be noted that the developed subroutine and its implementation were performed without the need to have access to the GOTHIC source code. In a previous paper, the GOTHIC code was used to perform a containment safety analysis for the Atucha-I NPP (CNA-I) for an in-vessel retention type of analysis. Highly conservative vapour generating boundary conditions were used in order to simulate the boiling between the cavity water and the RPV surface, and to bypass the GOTHIC limitation. The newly developed subroutine was used for the analysis of two postulated Atucha-I in-vessel retention scenarios, a Large Break Loss Of Coolant Accident (LBLOCA) and a Station Black-Out (SBO), with the simulation of heat transfer between RPV and cavity water. Specifically for in-vessel retention situations, a separate user selectable option for the subroutine was developed, in which the Critical Heat Flux is determined based on experiments performed at the ULPU facility from the University of California, Santa Barbara, USA, which were combined with the 2006 Groeneveld Look-up Tables primarily in order to have a pressure dependence. This was performed because for the Atucha-I analysis, the pressure was higher than in the ULPU facility.

Identify the triple-negative and non-triple-negative breast cancer by using texture features of medicale ultrasonic image: A STROBE-compliant study.

The study aimed to explore the value of ultrasound (US) texture analysis in the differential diagnosis of triple-negative breast cancer (TNBC) and non-TNBC.Retrospective analysis was done on 93 patients with breast cancer (35 patients with TNBC and 38 patients with non-TNBC) who were admitted to Taizhou people's hospital from July 2015 to June 2019. All lesions were pathologically proven at surgery. US images of all patients were collected. Texture analysis of US images was performed using MaZda software package. The differences between textural features in TNBC and non-TNBC were assessed. Receiver operating characteristic curve analysis was used to compare the diagnostic performance of textural parameters showing significant difference.Five optimal texture feature parameters were extracted from gray level run-length matrix, including gray level non-uniformity (GLNU) in horizontal direction, vertical gray level non-uniformity, GLNU in the 45 degree direction, run length non-uniformity in 135 degree direction, GLNU in the 135 degree direction. All these texture parameters were statistically higher in TNBC than in non-TNBC (P <.05). Receiver operating characteristic curve analysis indicated that at a threshold of 268.9068, GLNU in horizontal direction exhibited best diagnostic performance for differentiating TNBC from non-TNBC. Logistic regression model established based on all these parameters showed a sensitivity of 69.3%, specificity of 91.4% and area under the curve of 0.834.US texture features were significantly different between TNBC and non-TNBC, US texture analysis can be used for preliminary differentiation of TNBC from non-TNBC.

Evaluating the fishery of tropical reservoirs using surplus production models: A case study of Aliyar Reservoir, Tamil Nadu, India

AbstractReservoir fisheries support the livelihood needs of socio‐economically deprived fishers and ensure the nutritional security of rural populations. To sustain community food safety and economic needs, a basic understanding of the prevailing biological and economic conditions, as well as a comprehensive evaluation of the fishery is essential. To this end, the present study focused on evaluating the fisheries of the small Aliyar Reservoir located in the Coimbatore District of the state of Tamil Nadu, India, utilizing surplus production models. The maximum recorded fish catch was 51.3 MT in 2015, with the minimum catch of 10.89 MT obtained in 1991, and the average production during 1985 to 2018 being 30.80 MT from the reservoir. The peak catch season was during the months of February to May. The MSY (Maximum Sustainable Yield) and other key fish population parameters, including the carrying capacity (K), catchability coefficient (q), intrinsic population growth rate (r) and coefficient of variation (CV), using catch and effort data (CEDA) analysis and ASPIC (a surplus production model incorporating covariates) computer software packages. Using CEDA software, the estimated MSY was 36.92 MT (CV = 0.47) using the Fox model and 36.68 MT (CV = 0.307) using the Schaefer model. An integrated surplus production model (CYP) of Clarke et al. (Marine Research Economics, 1992, 7, 115) was also fitted to the data and found to be the best fit with the MSY, an estimated optimum effort of 51.20 MT and 5110 nets/year. The results indicated the need for increasing the fishing effort with appropriate standard gears for exploiting the fish stock. Further economic optimization with the CYP model indicates increasing the fishing effort by 34% will lead to a 40% increase in the annual profits for the fishermen.

Comparing International Communication of Corporate Social Responsibility by Chinese and Korean Firms on Social Media

Background: More and more multinational corporations (MNCs) based in East Asia are adopting international social media to communicate messages on corporate social responsibility (CSR), but little research has investigated their content qualitatively. Literature review: I reviewed the literature related to the convergence and divergence of corporate behaviors under the framework of the institutional theory. Comparative studies on web-based CSR communication (CSRC) were also addressed, and CSR development in China and Korea was described as the research context to develop hypotheses and research questions. Research questions: 1. How do Chinese and Korean CSRCs resemble each other in international social media? 2. What are the differences between Chinese and Korean CSRCs in international social media? Research methodology: I selected six Chinese companies and six Korean firms from the 2019 Forbes 2000 world's-largest-corporations ranking, and analyzed the content of their English-language Facebook accounts using “Leximancer,” a powerful textual analysis software package. Results: Results indicated that the CSR messages of Chinese and Korean firms resembled each other at a macrolevel but differed at a microlevel. In addition, the CSR messages of Chinese companies were more likely to reflect national strategic agendas, while Korean firms placed greater emphasis on short-term events and legal compliance. Conclusions: Chinese and Korean corporations have adopted an approach of “global topics, native framing” in their CSRCs to achieve a balance between internal and external legitimacy.

Stakeholders’ perceptions of how nurse-physician communication may impact patient care: protocol for a concept mapping study

ABSTRACT Effective nurse-physician interprofessional communication is important to ensure that patients receive evidence-based care and treatment. There is a gap in knowledge about how nurse-physician communication impacts patient care. We propose using concept mapping to develop an in-depth understanding of patients, nurses, and physicians’ perspectives on how physician-nurse communication affects patient care. There are six phases to concept mapping: determining the focus, generating statements, structuring statements, producing the map, interpretating the map, and map utilization. We will use ‘Ariadne’, a concept mapping software package for data collection and analysis. The study outcome will be a two-dimensional concept map providing a visual representation of how nurse-physician communication influences patient care. We will report similarity and differences among three stakeholder groups. Our research will inform the development of testable hypotheses about nurse-physician communication and patient care.

Benchmarking association analyses of continuous exposures with RNA-seq in observational studies.

Large datasets of hundreds to thousands of individuals measuring RNA-seq in observational studies are becoming available. Many popular software packages for analysis of RNA-seq data were constructed to study differences in expression signatures in an experimental design with well-defined conditions (exposures). In contrast, observational studies may have varying levels of confounding transcript-exposure associations; further, exposure measures may vary from discrete (exposed, yes/no) to continuous (levels of exposure), with non-normal distributions of exposure. We compare popular software for gene expression-DESeq2, edgeR and limma-as well as linear regression-based analyses for studying the association of continuous exposures with RNA-seq. We developed a computation pipeline that includes transformation, filtering and generation of empirical null distribution of association P-values, and we apply the pipeline to compute empirical P-values with multiple testing correction. We employ a resampling approach that allows for assessment of false positive detection across methods, power comparison and the computation of quantile empirical P-values. The results suggest that linear regression methods are substantially faster with better control of false detections than other methods, even with the resampling method to compute empirical P-values. We provide the proposed pipeline with fast algorithms in an R package Olivia, and implemented it to study the associations of measures of sleep disordered breathing with RNA-seq in peripheral blood mononuclear cells in participants from the Multi-Ethnic Study of Atherosclerosis.

Automated Nanoparticle Analysis in Surface Plasmon Resonance Microscopy.

The unique capability of surface plasmon resonance microscopy (SPRM) in single nanoparticle analysis has found use in various chemical and biological applications. While SPRM offers exceptional sensitivity, the statistical analysis of numerous nanoparticles has been extremely laborious and time-consuming. Herein, we presented an image processing software package for nanoparticle analysis in SPRM, which is empowered by a deep learning algorithm. This package enabled fully automated nanoparticle identification, digital counting, three-dimensional tracking of particle locations, and quantification of dwell time and Brownian motion properties. With a built-in image filtering process to improve the contrast, robust identification and analysis have been achieved from SPRM images of low refractive index nanoparticles. This software tool would largely promote the translation of SPRM technology into the digital sensing platform for high throughput sample screening.

GEInter: an R package for robust gene-environment interaction analysis.

For understanding complex diseases, gene-environment (G-E) interactions have important implications beyond main G and E effects. Most of the existing analysis approaches and software packages cannot accommodate data contamination/long-tailed distribution. We develop GEInter, a comprehensive R package tailored to robust G-E interaction analysis. For both marginal and joint analysis, for data without and with missingness, for continuous and censored survival responses, it comprehensively conducts identification, estimation, visualization and prediction. It can fill an important gap in the existing literature and enjoy broad applicability. TCGA data is analyzed as demonstrating examples. It is well known that such data is publicly available https://cran.r-project.org/web/packages/GEInter/. Supplementary data are available at Bioinformatics online.

Thermal-striping analysis methodology for sodium-cooled reactor design

Computational fluid dynamics simulations have been performed to study the applicability of engineering CFD methods for thermals striping analysis. Thermal striping is the fluctuating temperature profile in a solid caused by fluctuating fluid temperature, and the resulting thermal stresses cause high cycle fatigue and eventual material failure. This study presents the methodology for thermal striping analysis, including a transient conjugate heat transfer RANS simulation benchmarked against a sodium triple jet experiment. Multiphysics calculations are implemented to analyze the thermal stresses in the solid domain caused by the coupled heat transfer between the fluid and solid domains. Validation data from a liquid sodium triple jet experiment include time-averaged temperature measurements and power spectra of the temperature signal. The numerical results agree well with these experimental measures, demonstrating key features such as the dominant frequency of temperature fluctuations. The applicability of a low-cost wall treatment method is demonstrated, enabling key computational savings. Finally, the performance of two finite element stress analysis software packages is compared, and the validity of the lower-cost method is confirmed. These results demonstrate the applicability of engineering methods for computational thermal striping calculations, enabling thermal striping estimations in large fluid systems such as the core of a liquid metal-cooled nuclear reactor.

Workplace Violence Among Healthcare Workers in a Tertiary Medical City in Riyadh: A Cross-Sectional Study.

IntroductionWorkplace violence is a common problem that is encountered by healthcare workers worldwide; however, it is still under-studied in Saudi Arabia. This study aims to determine the prevalence of workplace violence and to explore reasons for not reporting it among healthcare workers in a tertiary medical city in Riyadh.MethodsThis cross-sectional study was conducted among 404 healthcare workers who had direct contact with patients or their relatives in a tertiary care medical city in Riyadh, Saudi Arabia. Data were analyzed using Statistical Analysis Software Package (SPSS; IBM, Armonk, NY, USA).ResultsMost participants (81.4%) had experienced verbal, physical, academic, or sexual violence. Approximately 39.6% of those who experienced workplace violence did not report the incident, and the most common reason for not reporting was identified as “reporting would not accomplish anything” (49.4%). About 27.5% of violence victims did not know how to report the incidents. Patients or their relatives were the main sources of violence across all violence categories except academic violence, in which consultant physicians were the main source.ConclusionsThe prevalence of workplace violence in the population studied was higher than anticipated compared to similar studies both in Saudi Arabia and globally. Almost half of those who were subjected to violence did not report the incident, believing that reporting would not change anything. There is arguably an urgent need to develop strategies that reduce workplace violence and facilitate reporting it in hospitals. Moreover, awareness programs regarding the negative impacts of violence against healthcare workers on the quality of care are necessary.

QIIME 2 Automation for Microbiome Analysis: An Opportunity to Reduce Barriers to Entry While Improving Analytic Speed and Reliability

The cost of next-generation sequencing has significantly reduced since its arrival in 2004, allowing metagenomic research to flourish with applications in medicine, genetics, agriculture, and environment. QIIME 2 is an open-source microbiome analysis software package that converts raw sequence data into interpretable visualizations and statistical results. Most common analyses include classifying sequences taxonomically, analyzing alpha and beta diversity, assessing phylogenetic relationship between features, and identifying features with differential abundances in various treatment groups. Third parties can contribute functionality such as longitudinal analysis and machine-learning analysis, making it a robust microbiome tool that is widely used. However, there exist several barriers in using QIIME 2. There is a steep learning curve for users with limited technical computer skill. The high volume of user inputs increases risk for user error and inefficient reproducibility among collaborators. However, these issues with efficiency, accessibility, and consistency can be addressed through automation. Using LINUX shells, we developed a robust QIIME 2 automation pipeline that automates the core functions of QIIME 2 metagenomic analysis. The process covers raw sequence data importing, demultiplexing, and denoising. It also automates data subset filtering, taxonomic classification, and alpha and beta diversity analyses. Files created with standardized nomenclature are organized into a simple folder structure comprising of data, visualizations, and metadata. QIIME 2 parameters are saved into accessible text files for transparency. The pipeline was trialed with 3 novices to both data science and metagenomic research: one PhD principal investigator, one 2nd year medical student and one 1st year medical student. They were given our scripts and tutorial, and they recorded the time and keystrokes to reach 3 endpoints: 1) construct a PCOA plot of an entire dataset, 2) perform ADONIS test on a distance matrix subset, and 3) compare alpha diversity using the Shannon metric on a metadata subset feature table. 2 out of 3 trials were successful in meeting these endpoints within 2 weeks, requiring 7 (PhD) and 9 hours (2nd year medical student) to do so. Using the fewest possible keystrokes, this analysis would have taken 11,594 characters over roughly 40 hours if done manually. Using our QIIME 2 automation, these endpoints were completed with 228 user keystrokes. The limitations of QIIME 2 can be diminished by automation and clarification of steps at decision points within a metagenomic analysis. The goal of this project was to reduce risk of error and time spent, limiting the obstacles facing a new user using QIIME 2. With growing popularity in metagenomic research, our automation tool can help computer novices navigate through the technical barriers of metagenomic analysis.