Comparison Of Different Tools Research Articles

Sarcopenia in cirrhosis of liver - comparison of different tools in diagnosis

BACKGROUND AND AIMS Sarcopenia in liver cirrhosis is a common condition associated with increased mortality and adverse clinical outcome. Early recognition and treatment is essential but challenging. Clinical detection of sarcopenia with various assessment tools gives indirect knowledge of muscle mass and strength. The aim of this study is to find the most easy and applicable assessment tool in daily clinical practice to diagnose sarcopenia. METHODS A retrospective observational study was conducted and data was taken from electronic medical records of patients admitted with cirrhosis and sarcopenia in department of gastroenterology of Tribhuvan university Teaching hospital. A total of 51 cirrhotic patients were included during one and half year study duration. Sarcopenia was assessed using assessment tool like hand grip strength, chair stand test, 400 metre walk test and CT measurement of either skeletal muscle area (SMA) or skeletal muscle index (SMI). RESULTS Among 51 patients assessed with performance based assessment tool to diagnose sarcopenia, taking CT as gold standard test, SARC-F score and chair stand test were found to have highest sensitivity and specificity of 93%, 87.5 % and 93%, 100% respectively. CONCLUSION Diagnosis of sarcopenia with simple clinic based assessment tool SARC-F score and chair stand test is very useful and comparable with more costly and resource-intensive CT scan.

SAFETY CULTURE AND ITS MEASUREMENT METHODS IN THE FIRE SERVICE

The article considers safety culture and discusses its role with regard to risks associated with the fireservice. Attention was drawn to the gap in research on this issue, especially in Poland. The followingresearch problem was formulated: what is and what dimensions does a safety culture conducive tofire services consist of? The cognitive objective was to understand and present the essence of safetyculture and its importance, and the utilitarian objective was to identify possible tools for measuringsafety culture in fire services. A proprietary definition of safety culture in the fire service has beenproposed. An analysis and comparison of different tools for assessing safety culture in the sector werecarried out. Attention was drawn to the need to be systematic in conducting this assessment and thenecessity of providing adequate training and experiences of other sectors.

Comparison of different tools for the evaluation of malnutrition and sarcopenia in patients with liver cirrhosis

Introduction: malnutrition and sarcopenia are frequent in the population with liver cirrhosis and have a negative impact on the performance status and life expectancy of these patients. There are multiple assessment tools for malnutrition and sarcopenia in cirrhosis. Objective: to assess malnutrition and sarcopenia in liver cirrhosis and to compare the accuracy of diagnostic tools in this population. Method: a cross-sectional analytical study was conducted with convenience sampling by using continuous inclusion of patients with liver cirrhosis in a tertiary care center during December 2018 to May 2019. The nutritional assessment was carried out with arm anthropometry, body mass index (BMI), and the algorithm of the Royal Free Hospital Subjective Global Assessment (RFH-SGA). For the evaluation of sarcopenia, the hand grip strength test with a hand dynamometer was applied. The results were reported in measures of central tendency expressed in frequency and percentage. Results: a total of 103 patients were included with a predominance of the male gender (79.6 %) and a mean age of 51 years (± 10). The etiology of liver cirrhosis corresponded more frequently to alcohol consumption (68 %) and most of the patients were Child-Pugh C (57.3 %) with a mean MELD of 21.9 (± 8.9). A mean BMI with dry weight of 25.2 kg/m2 was reported, and with respect to the WHO classification by BMI, 7.8 % were underweight and 59.2 % were malnourished by RFH-SGA. Sarcopenia was present in 88.3 % using the hand grip strength test, for which a mean of 18.99 kg was found. A Kendall's Tau-b rank correlation coefficient was performed between BMI and RFH-SGA, which showed no statistically significant association, as well as between mean arm muscle circumference percentiles and hand grip strength. Conclusions: global assessment in liver cirrhosis should include screening for malnutrition and sarcopenia, for which validated, accessible and safe application tools should be used, such as anthropometric assessment, RFH-SGA, and hand grip strength.

Comparison of Different Tools and Methods in the Measurement of Leaf Area in Alfalfa

Leaf area measurements in the field are very difficult to determine the yield. Use of the mobile application has come to the fore due to its practical use and ease of transportation. Therefore, in this study, the ease of use and accuracy were tested by determining area of leaf with an automatic leaf area meter and a mobile application called 'PETIOLE'. The leaf area of alfalfa plants (Medicago sativa L. cv Nimet) grown in the field, and measured in the field with the 'PETIOLE' mobile application and in laboratory conditions with automatically leaf area measurement device was measured. The automated leaf area meter mean for total leaf area was 61.65 ± 3.50; meanwhile the mean for the PETIOLE App assessment was 61.56 ± 3.15. As a result, the PETIOLE app measures the area of each leaf separately, more quickly and efficiently than before, particularly in the field.

Importance of videoconferencing in education and comparison of some types of applications

The given article presents information on the topic of videoconferencing and a comparison of different tools for creating effective online lessons. This study aims to determine the demand for videoconferencing and what conferencing applications could be applied in the process of education. The findings indicate that the main distinguishing feature of those applications is the content that is aimed to be shared and the number of participants. Those applications create opportunities for making the lesson more authentic. Particular attention is paid to the analysis of capacities of three applications as Microsoft Teams, Google Meets, and Zoom.

Launch of the FarmConners Wind Farm Control benchmark for code comparison

Careful validation of the modelling and control actions is of vital importance to build confidence in the value of coordinated wind farm control (WFC). The efficiency of flow models applied to WFC should be evaluated to provide reliable assessment of the performance of WFC. In order to achieve that, FarmConners launches a common benchmark for code comparison to demonstrate the potential benefits of WFC, such as increased power production and mitigation of loads. The benchmark builds on available data sets from previous and ongoing campaigns: synthetic data from high-fidelity simulations, measurements from wind tunnel experiments, and field data from a real wind farm. The participating WFC models are first to be calibrated or trained using normal operation periods. For the blind test, both the axial induction and wake steering control approaches are included in the dataset and to be evaluated through the designed test cases. Three main test cases are specified, addressing the impact of WFC on single full wake, single partial wake, and multiple wake. The WFC model outcomes will be compared during the blind test phase, through power gain and wake loss reduction as well as alleviation of wake-added turbulence intensity and structural loads. The probabilistic validation will be based on the median and quartiles of the observations and WFC model predictions. Every benchmark participant will be involved in the final publication, where the comparison of different tools will be performed using the defined test cases. Instructions on how to participate are also provided on farmconners.readthedocs.io.

A Comparison of EDM Tools and Techniques

Several higher educational institutions are adapting the strategy of predicting the student’s performance throughout the academic years. Such a practice ensures not only better academic outcomes but also helps the institutions to reorient their curriculums and teaching pedagogies so as to add to the students’ learning curve. Educational Data Mining (EDM) has risen as a useful technology in this league. EDM techniques are now being used for predicting the enrolment of students in a specific course, detection of any irregular grades, prediction about students’ performance, analyzing and visualizing of data, and providing feedback for overall improvement in the academic spheres. This paper reviews the studies related to EDM, including the approaches, data sets, tools, and techniques that have been used in those studies, and points out the most efficient techniques. This review paper uses true prediction accuracy as a standard for the comparison of different techniques for each EDM applications of the surveyed literature. The results show that the J48 and K-means are the most effective techniques for predicting the students’ performance. Furthermore, the results also cite that Bayesian and Decision Tree Classifiers are the most widely used techniques for predicting the students’ performance. In addition, this paper highlights that the most widely used tool was WEKA, with approximately 75% frequency. The present study’s empirical assessments would be a significant contribution in the domain of EDM. The comparison of different tools and techniques presented in this study are corroborative and conclusive, thus the results will prove to be an effective reference point for the practitioners in this field. As a much needed technological asset in the present day educational context, the study also suggests that additional surveys are recommended to be driven for each of the EDM applications by taking into account more standards to set the best techniques more accurately.

ELECTOR: evaluator for long reads correction methods.

The error rates of third-generation sequencing data have been capped >5%, mainly containing insertions and deletions. Thereby, an increasing number of diverse long reads correction methods have been proposed. The quality of the correction has huge impacts on downstream processes. Therefore, developing methods allowing to evaluate error correction tools with precise and reliable statistics is a crucial need. These evaluation methods rely on costly alignments to evaluate the quality of the corrected reads. Thus, key features must allow the fast comparison of different tools, and scale to the increasing length of the long reads. Our tool, ELECTOR, evaluates long reads correction and is directly compatible with a wide range of error correction tools. As it is based on multiple sequence alignment, we introduce a new algorithmic strategy for alignment segmentation, which enables us to scale to large instances using reasonable resources. To our knowledge, we provide the unique method that allows producing reproducible correction benchmarks on the latest ultra-long reads (>100 k bases). It is also faster than the current state-of-the-art on other datasets and provides a wider set of metrics to assess the read quality improvement after correction. ELECTOR is available on GitHub (https://github.com/kamimrcht/ELECTOR) and Bioconda.

Non-listed Nias Exposure Assessment: Comparison of Different Tools

Food contact materials (FCMs) can contain Non-intentionally added substances (NIAS) as a result of break down, side product or impurities. NIAS can migrate into food and this might cause a risk for human health. Thus, their presence has to be evaluated, but currently there are no protocols to establish how to perform a risk assessment. Then, in this work, three different strategies to make a NIAS exposure assessment were compared: the European Food Agency Authority (EFSA) food consumption database, the Matrix Tool and the FACET tool. 2,4-Di-tert-butylphenol (2,4-DTB), an identified and quantified NIAS, was used as the case study. Differences between these tools were highlighted, but for all the strategies tested the estimated exposure to 2,4-DTB was lower than its threshold value indicating that there are no risk for the consumers.

Comparison of different tools for pain assessment following ovariohysterectomy in bitches

BACKGROUND: Accurate identifying and assessment of the degree of pain that the animal is suffering can be a challenge, and, control of painful condition is becoming an increasingly important part of veterinary medicine. OBJECTIVES: This study was carried out to compare different tools for postoperative pain assessment in bitches. METHODS: Ten adult mixed breed bitches were selected and randomly divided into two equal treatment and control groups. Anaesthesia was premedicated with acepromazine (0.03 mg/kg, IM) and induced with Sodium thiopental (6-10 mg/kg, IV). Halothane was used for maintenance of the anesthesia. Ovariohysterectomy performed in the two groups. Treatment group received 3 mg/kg of tramadol intramuscularly (i.m.) and control group received normal saline (equal volume with tramadol, i.m.) before the anesthetic induction. After operation the injections of tramadol and normal saline were repeated for every 6 hours in 7 days. The animals were monitored at hour 2, 3 and 4 after each injection and they were scored for signs of pain by two trained assessors who were blinded to the groups. The measured variables were pain assessment with different methods including Simple Descriptive Scale (SDS), Visual Analogue Scale (VAS), and University Melbourne Pain Scale (UMPS). Duration of anesthesia and duration of surgery, were also recorded. RESULTS: There were no significant differences between the two groups in regard to analgesia that were measured based on VAS and SDS methods, but in UMPS method, analgesia was significantly better in treatment group. Among simple clinical criteria body temperature and respiratory rate did not show any significant alterations, but heart rate had significant changes between the groups. CONCLUSIONS: The ability to quantify the degree of pain experienced by animals is an important aspect in the assessment of animal welfare; in addition, we concluded, that the great challenge for the veterinarians is the evaluation of postoperative pain in dogs

HiC-bench: comprehensive and reproducible Hi-C data analysis designed for parameter exploration and benchmarking

BackgroundChromatin conformation capture techniques have evolved rapidly over the last few years and have provided new insights into genome organization at an unprecedented resolution. Analysis of Hi-C data is complex and computationally intensive involving multiple tasks and requiring robust quality assessment. This has led to the development of several tools and methods for processing Hi-C data. However, most of the existing tools do not cover all aspects of the analysis and only offer few quality assessment options. Additionally, availability of a multitude of tools makes scientists wonder how these tools and associated parameters can be optimally used, and how potential discrepancies can be interpreted and resolved. Most importantly, investigators need to be ensured that slight changes in parameters and/or methods do not affect the conclusions of their studies.ResultsTo address these issues (compare, explore and reproduce), we introduce HiC-bench, a configurable computational platform for comprehensive and reproducible analysis of Hi-C sequencing data. HiC-bench performs all common Hi-C analysis tasks, such as alignment, filtering, contact matrix generation and normalization, identification of topological domains, scoring and annotation of specific interactions using both published tools and our own. We have also embedded various tasks that perform quality assessment and visualization. HiC-bench is implemented as a data flow platform with an emphasis on analysis reproducibility. Additionally, the user can readily perform parameter exploration and comparison of different tools in a combinatorial manner that takes into account all desired parameter settings in each pipeline task. This unique feature facilitates the design and execution of complex benchmark studies that may involve combinations of multiple tool/parameter choices in each step of the analysis. To demonstrate the usefulness of our platform, we performed a comprehensive benchmark of existing and new TAD callers exploring different matrix correction methods, parameter settings and sequencing depths. Users can extend our pipeline by adding more tools as they become available.ConclusionsHiC-bench consists an easy-to-use and extensible platform for comprehensive analysis of Hi-C datasets. We expect that it will facilitate current analyses and help scientists formulate and test new hypotheses in the field of three-dimensional genome organization.

PTH-225 Paediatric malnutrition screening on admission: a comparison of different tools and their association with body composition and clinical outcomes: Abstract PTH-225 Table 1

Introduction The aim of the study was to evaluate associations between currently available paediatric malnutrition screening tools (MSTs), baseline body composition (BC) measurements and clinical outcomes (length of stay-LOS; nutrition status on discharge-NS) in children admitted to a tertiary referral hospital. Method 128 children (mean age 10.7yr; 49.2% male; 54.7% surgical) admitted to Great Ormond Street Hospital (GOSH) under any specialty and expected stay >3 days were enrolled. 3 MSTs (Paediatric Yorkhill Malnutrition Score-PYMS; Screening Tool for the Assessment of Malnutrition in Paediatrics-STAMP; Screening Tool for Risk of Impaired Nutritional Status and Growth-STRONG) were implemented on admission. Weight (WT) and BC measurements (lean (LM) and fat mass (FM) by dual Energy X-ray Absorptiometry) were obtained within 48 h of admission and SD scores (SDS) calculated from UK BC reference data. 1 WT and LOS were recorded on discharge. Results STAMP classified more patients as high risk (HR) compared to PYMS and STRONG. Most patients were identified as moderate risk (MR) by both STAMP and STRONG, and low risk (LR) by PYMS. STAMP and STRONG classified more surgical patients in HR and MR categories respectively. STAMP and STRONG showed the best agreement (60.9% agreement, 0.427 kappa), followed by STRONG and PYMS (48.4% agreement; 0.321 kappa) and STAMP and PYMS (46.1% agreement; 0.284 kappa). Children classified HR by STRONG had significantly lower WT, LM and FM SDS compared to LR and MR patients. The HR category in STAMP also had significantly lower LM SDS. MSTs did not correlate significantly with LOS and discharge NS (WT change), although there was a tendency for HR patients to stay longer than predicted. Conclusion STAMP and STRONG seem to show the best agreement, and identify HR patients with abnormal BC (especially low LM). GOSH patients are generally short and have multiple and chronic diagnoses, possibly explaining the proportion of patients classified as LR by PYMS, which used body mass index scores and does not consider underlying diagnosis. Although HR patients showed a tendency for worse clinical outcomes, these were not significant, probably reflecting the limitations of these generic outcomes for this heterogeneous group. Thus, further research is needed in specific patient groups to establish the usefulness of each MST in different conditions. Disclosure of interest None Declared. Reference Wells JC et al . AJCN 2012;96:1316–26

An overview of the prediction of protein DNA-binding sites.

Interactions between proteins and DNA play an important role in many essential biological processes such as DNA replication, transcription, splicing, and repair. The identification of amino acid residues involved in DNA-binding sites is critical for understanding the mechanism of these biological activities. In the last decade, numerous computational approaches have been developed to predict protein DNA-binding sites based on protein sequence and/or structural information, which play an important role in complementing experimental strategies. At this time, approaches can be divided into three categories: sequence-based DNA-binding site prediction, structure-based DNA-binding site prediction, and homology modeling and threading. In this article, we review existing research on computational methods to predict protein DNA-binding sites, which includes data sets, various residue sequence/structural features, machine learning methods for comparison and selection, evaluation methods, performance comparison of different tools, and future directions in protein DNA-binding site prediction. In particular, we detail the meta-analysis of protein DNA-binding sites. We also propose specific implications that are likely to result in novel prediction methods, increased performance, or practical applications.

Inappropriate prescribing to older patients admitted to hospital: A comparison of different tools of misprescribing and underprescribing

PurposeThis study aims to assess inappropriate prescribing (IP) to elderly patients during the month prior to hospitalization and to compare different IP criteria. MethodsAn observational, prospective and multicentric study was carried out in the internal medicine services of seven Spanish hospitals. Patients aged 75years and older were randomly selected after hospital admission for a year. To assess potentially inappropriate medicines (PIMs), the Beers and STOPP criteria were used and to assess potentially prescribing omissions (PPOs), the START criteria and ACOVE-3 medicine quality indicators were used. An analysis to assess factors associated with IP was performed. Results672 patients [median age (Q1–Q3) 82 (79–86) years, 55.9% female] were included. Median prescribed medicines in the month prior to hospitalization were 10(Q1–Q3 7–13). The prevalence of IP was 87.6%, and 54.3% of patients had PIMs and PPOs concurrently. A higher prevalence rate of PIMs was predicted using the STOPP criteria than with the Beers criteria (p<0.001) and a higher prevalence of PPOs using the ACOVE-3 criteria than using the START criteria (p<0.001) was observed. Polypharmacy (≥10 medicines) was the strongest predictor of IP [OR=11.34 95% confidence interval (CI) 4.96–25.94], PIMs [OR=14.16, 95% CI 6.44–31.12], Beers-listed PIMs [OR=8.19, 95% CI 3.01–22.28] and STOPP-listed PIMs [OR=8.21, 95% CI 3.47–19.44]. PIMs was the strongest predictor of PPOs [OR=2.79, 95% CI 1.81–4.28]. ConclusionsA high prevalence of polypharmacy and PIMs and PPOs were reported. More than half the patients had simultaneous PIMs and PPOs. The related factors to PIMs and PPOs were different.

Influence of Organizational Factors on Management Tools Usage in Slovenian Organizations

Purpose – In the global competitive environment, managers of organizations must permanently rethink and renew their work, especially about the use of different managerial tools. A selection of suitable management tools for organization requires consideration of characteristics of the known tools, comparison of different tools, and consideration of demands and conditions of the organizations. But direct comparison of different management tools is not possible because of their content-related and methodological differences. In management theory, various authors tried to consider the use of management tools more deeply. The main purpose of this paper is to examine the influence of important organizational factors on usage of single management tools in Slovenian organizations. Thus, we consider: 1) usage patterns of management tools in different areas worldwide, 2) the influence of single organizational factors – i.e. education, position, and working years, on the usage of management tools in Slovenian organizations, and 3) the influence of a linear combination of selected factors on usage of management tools in Slovenian organizations. Design/methodology/approach – A qualitative analysis is applied on the basis of the selected cognitions from Management, and Organization. The quantitative analysis includes desk research about the management tools, and analysis of the results from a survey about management tools in Slovenian organizations in 2010. In examining the impact of the considered organizational factors (separately and in combination) on management tools we use linear regression analysis to predict the influence of single factors and linear combination of the selected factors on the use of selected management tools. AMOS 17.0 was used for analysis. Findings – Intensity of management tools usage in Slovenian organizations is similar to the global patterns, while patterns of their usage are rather different. Examination of factors influencing usage of the top five management tools in Slovenian organizations reveal: education has the strongest impact on the usage of management tools, the impact of employees’ position in organization is weaker, and the impact of working years is very weak. When we take into consideration all three predictors simultaneously, the impact of education and position becomes weaker, while the impact of working years becomes insignificant. We apply a deeper approach to gauge the influence of organizational factors on usage of the selected management tools. The impact of other considered factors, we find, is not significant. Research limitations/implications – Research is limited to a hypothesis, broader qualitative aspects encountered during desk research, and some quantitative analysis of results from our survey. We test our hypotheses and the chosen model on the top five management tools most used by employees in Slovenian organizations. Practical implications – Authors try to overcome the prevailing practice of very general consideration of management tools usage, especially regarding organizational factors, which influence the usage of management tools. Authors suggest a new approach, hardly known in the main-stream literature. They propose a more specific and target-oriented approach to consideration of management tools usage in business. Originality/value – Available management literature does not provide a similar solution for considering and researching the usage of management tools in business. This is useful for business practice in organizations, for advancing the usage of management tools, since the most important organizational factors on management tools usage are outlined. DOI: http://dx.doi.org/10.5755/j01.ee.23.3.1933

The Rough Guide to In Silico Function Prediction, or How To Use Sequence and Structure Information To Predict Protein Function

Choosing the right function prediction tools The vast majority of known proteins have not yet been characterized experimentally, and there is very little that is known about their function. New unannotated sequences are added to the databases at a pace that far exceeds the one in which they are annotated in the lab. Computational biology offers tools that can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history, and their association with other proteins. In this contribution, we attempt to provide a framework that will enable biologists and computational biologists to decide which type of computational tool is appropriate for the analysis of their protein of interest, and what kind of insights into its function these tools can provide. In particular, we describe computational methods for predicting protein function directly from sequence or structure, focusing mainly on methods for predicting molecular function. We do not discuss methods that rely on sources of information that are beyond the protein itself, such as genomic context [1], protein–protein interaction networks [2], or membership in biochemical pathways [3]. When choosing a tool for function prediction, one would typically want to identify the best performing tool. However, a quantitative comparison of different tools is a tricky task. While most developers report their own assessment of their tool, in most cases there are no standard datasets and generally agreed-upon measures and criteria for benchmarking function prediction methods. In the absence of independent benchmarks, comparing the figures reported by the developers is almost always comparing oranges and apples (for discussion of this problem see [4]). Therefore, we refrain from reporting numerical assessments of specific methods. For those cases in which independent assessment of performance is available, we refer the reader to the original publications. Finally, we discuss only methods that are either accessible as Web servers or freely available for download (relevant Web links can be found in Table S1).

A framework for describing and understanding mining tools in software development

We propose a framework for describing, comparing and understanding tools for the mining of software repositories. The fundamental premise of this framework is that mining should be done by considering the specific needs of the users and the tasks to be supported by the mined information. First, different types of users have distinct needs, and these needs should be taken into account by tool designers. Second, the data sources available, and mined, will determine if those needs can be satisfied. Our framework is based upon three main principles: the type of user, the objective of the user, and the mined information. This framework has the following purposes: to help tool designers in the understanding and comparison of different tools, to assist users in the assessment of a potential tool; and to identify new research areas. We use this framework to describe several mining tools and to suggest future research directions.

Overview of popular benchmark sets

One of the most difficult tasks CAD users face is the evaluation and comparison of different tools and algorithms. For commercial software purchasers, it is vital to understand how well a given tool does the required job and which of many possible choices is best for the kinds of problems a user will face. For the tool developer, whether in academia or industry, the efficiency of critical algorithms must be measured and compared to understand both tool behavior and progress over time. Over the years, there have been many attempts to create and use neutral benchmarks for tool evaluation and comparison. Typically, a benchmark set consists of a collection of circuits in a common format, which attempt to represent a range of problems for evaluating algorithms and tools within an important problem domain. In principle, if everyone uses the same test cases to evaluate similar tools, it should be straightforward to compare results-although this is rarely true in reality. Several benchmark sets are widely used. The paper summarises briefly some of the more important ones. In addition, advanced research is under way to develop synthetic benchmarks with carefully controlled properties, with the objective of studying scaling and perturbation effect.

A comparison of tools for strategic simulation and scenario generation with special emphasis on ‘soft factors’

This paper describes a comparison of different tools for strategic simulation and scenario generation. Techniques and tools, namely GAMMA, a causal network editor, a connectance modeller allowing linear analysis and CRIMP, a tool based on dynamic cross-impact modelling and simulation, are presented and applied to a sample company specialised in technological breakthroughs. The results of tools are compared to identify strengths and weaknesses of these approaches.