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AbstractOur study described in this paper sought to show that the fibers of the midrib of the leaves of cavendish variety banana plants from Cameroon can be extracted by boiling water and to compare their properties (chemical, physical, thermal, and mechanical) with those obtained by cold water extraction. The standard tests for the various characterizations were respected. This study showed that the fibers extracted with boiling water contained 64.3% cellulose, 18.1% hemicellulose, 4.5% lignin, and 12.9% pectin, while the fibers extracted by the cold water technique contained 65% cellulose, 19% hemicellulose, 5% lignin, and 11% pectin. The extraction of fibers by the boiling water technique gave a 9.35% extraction yield, 0.94 g.cm−3 density, 15.23 tex linear mass, 11.10% water content, 169.78% water absorption degree, and 36.02% humidity at a relative humidity of 75%, while the fibers extracted by the cold water technique had a 12.35% extraction yield, 0.91 g.cm−3 density, 14.23 tex linear mass, 10.73% water content, 102.4% water absorption degree, and 34.45% humidity at a relative humidity of 75%. The boiling water extracted fibers had a thermal stability temperature of 268.5 °C. The student’s t-test showed that the fibers obtained by the boiling water extraction technique and the cold water extraction technique had identical mechanical properties. Thus, we suggest that the fibers of the midrib of the leaves of banana plants can be extracted with boiling water and used in textiles and composite materials. [ABSTRACT FROM AUTHOR]

Global climate change, which has also occurred in the Western Forest-Steppe of Ukraine, has led to early sowing starting from the very beginning of the spring season. In this regard, to provide a scientific basis for spring barley cultivation technology, the issue of investigating the processes of plant growth and development before the onset of the tillering phenomenon, i.e., the second and third stages of organogenesis, is of particular relevance. The purpose of this study was to establish the regularities of dependence of spring barley plant growth and development on the influence of vegetation factors at different sowing dates in the Western Forest-Steppe of Ukraine. To summarise the findings, the following methods were employed: general scientific methods based on objectivity, evidence, reproduction, and mathematical and statistical methods for processing experimental data. The study found the dependence of the processes of growth and development of spring barley plants based on plant biomass, crude biomass, and dry matter content of the root system and aerial parts of plants, as well as leaf area according to the analysis at the beginning of the tillering phase, on the influence of sowing time. The study estimated the significance of the studied factor under the influence of supply conditions for the maximum realisation of spring barley productivity potential. As a result, a regularity was revealed, according to which a substantial decrease in the productivity potential of barley plants was established with a delay for each subsequent 10 days starting from the first sowing date on 10 March. The maximum data values were obtained at the first sowing date, where the plant biomass was 723.6 mg, the crude biomass of the root system was 67.5 mg, the dry matter of the root system was 18.0 mg, the crude biomass of the aerial part of the plant was 656.1 mg, the dry matter of the aerial part of the plant was 130.8 mg and the leaf surface area was 18.1 cm2. As a result of the scientific substantiation, the practical value of the study lies in the favourability of early sowing dates to ensure maximum realisation of plant productivity potential due to vegetation factors. [ABSTRACT FROM AUTHOR]

Global climate change, which has also occurred in the Western ForestSteppe of Ukraine, has led to early sowing starting from the very beginning of the spring season. In this regard, to provide a scientific basis for spring barley cultivation technology, the issue of investigating the processes of plant growth and development before the onset of the tillering phenomenon, i.e., the second and third stages of organogenesis, is of particular relevance. The purpose of this study was to establish the regularities of dependence of spring barley plant growth and development on the influence of vegetation factors at different sowing dates in the Western Forest-Steppe of Ukraine. To summarise the findings, the following methods were employed: general scientific methods based on objectivity, evidence, reproduction, and mathematical and statistical methods for processing experimental data. The study found the dependence of the processes of growth and development of spring barley plants based on plant biomass, crude biomass, and dry matter content of the root system and aerial parts of plants, as well as leaf area according to the analysis at the beginning of the tillering phase, on the influence of sowing time. The study estimated the significance of the studied factor under the influence of supply conditions for the maximum realisation of spring barley productivity potential. As a result, a regularity was revealed, according to which a substantial decrease in the productivity potential of barley plants was established with a delay for each subsequent 10 days starting from the first sowing date on 10 March. The maximum data values were obtained at the first sowing date, where the plant biomass was 723.6 mg, the crude biomass of the root system was 67.5 mg, the dry matter of the root system was 18.0 mg, the crude biomass of the aerial part of the plant was 656.1 mg, the dry matter of the aerial part of the plant was 130.8 mg and the leaf surface area was 18.1 cm2 . As a result of the scientific substantiation, the practical value of the study lies in the favourability of early sowing dates to ensure maximum realisation of plant productivity potential due to vegetation factors

Recently, a mix of traditional and modern approaches have been proposed to detect brain abnormalities using bio‐signal/bio‐image‐assisted methods. In hospitals, most of the initial/scheduled assessments consider the bio‐signal‐based appraisal, due to its non‐invasive nature and low cost. Further, brain bio‐signal scans can be recorded using a single/multi‐channel electrode setup, which is further evaluated by an experienced doctor, as well as computer software, to identify the nature and severity of abnormality. In this paper, we describe the development of a system for computer supported detection (CSD) of schizophrenia using the electroencephalogram (EEG) signal collected with a 19‐channel electrode array. Schizophrenia is a mental illness that interferes with the way an individual thinks and behaves. It is characterised by psychotic symptoms such as hallucinations or delusions, negative symptoms such as decreased motivation or a lack of interest in daily activities and cognitive symptoms such challenges in processing information to make informed decisions or staying focused. This research has utilized 1142 EEGs (516 normal and 626 schizophrenia) with a frame length of 25 s (6250 samples) for investigation. The work initially converts the EEG signals to images using a spectrogram. Local configuration pattern features were extracted from the images thereafter, and 10‐fold validation technique was used wherein Student's t‐test and z‐score standardization were computed per fold. The highest accuracy of 97.20% was achieved with the K‐nearest neighbour (KNN) classifier. The results obtained confirm that the KNN classifier is helpful in the rapid detection of schizophrenia. This work is one of the first studies to extract local configuration pattern features from spectrogram images, yielding a high accuracy of 97.20%, with reduced computational complexity. [ABSTRACT FROM AUTHOR]

ABSTRACTTo substitute synthetic fibers, which are non-biodegradable and environmentally unfriendly, studies have been carried out to exploit vegetable fibers. Within this concept, this work investigates Sida rhombifolia as a case study. Previous studies showed that the fibers could be extracted only by cold water retting, but this study seeks to show that the boiling water extraction technique can also be used. The objective of this study is to characterize Sida rhombifolia fibers from the Center region of Cameroon, extracted with cold and boiling water, and compare their physico-chemical and mechanical properties with those of other vegetable fibers. The standard tests for the different characterizations have been respected. This study showed that the fibers extracted with cold water retting contained 70.16% cellulose, 16.70% hemicellulose, 10.86% lignin, and 1.47% pectin, while the fibers extracted by boiling water technique contained 68.71% cellulose, 17.48% hemicellulose, 11.26% lignin, and 2.01% pectin. Finally, extraction of fibers from the cold water retting technique gave 38.83% extraction yield, 1.33 g.cm−3 density, 11.23 tex linear mass, 11.73% water content, 118.53% rate of water absorption, and 21.45% humidity at a relative humidity of 75%. While fibers extracted by the boiling water technique had 33.74% extraction yield, 1.35 g.cm−3 density, 13.57 tex linear mass, 13.28% water content, 225.12% rate of water absorption, and 22.06% humidity at a relative humidity of 75%, statistical analysis by Student’s t-test showed a significant difference in the mechanical properties of the fibers depending on the extraction method. Sida rhombifolia fibers can be used in textiles and composites and can be extracted by the boiling water technique.

Copyright of Avances en Ciencias e Ingenierías (ACI) is the property of USFQ Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Air pollution is increasing at a frightening pace due to emissions from industrial plants and manufacturing activities and other anthropogenic activities affecting living beings, property, and environment. This study aims to monitor the impact of COVID-19-induced lockdown and unlock down phases on the air quality of Jaipur city, Rajasthan, India by assessing the change in ambient air quality during pre-COVID-19 (January 2018–December 2019) and COVID-19 (January 2020–December 2021) phases by evaluating air quality parameters (PM10, PM2.5, NO2, O3, Benzene and o-Xylene) using ground station data. Outcome of the study revealed that the ambient air quality improved significantly during lockdown phases (March–May 2020) as the percentage change in concentration of studied parameters declined by more than 100% at different sites. However, the concentrations tend to escalate with the introduction of unlock down phases (June–December 2020) and the onset of winter season (October–December 2020) aggravated the conditions. The AQI touched moderate and poor category many times during study period. Student's t-test was conducted on the dataset. Results revealed significant difference in the concentration of air pollutants between pre-covid and covid period. [ABSTRACT FROM AUTHOR]

Keywords: Socially responsible investing, ESG, Student’s T-test, ARCH, GARCH, performance, GREENEX, SENSEX, CARBONEX This paper aims to examine and compare the effect of black swan events on the performance of companies with strong Environmental, Social, and (Corporate) Governance (ESG) backgrounds with that of other companies. Compared to established firms, companies with ESG backgrounds are perceived to be stable that will help them outperform established companies that are volatile during times of crisis. This research focuses on SENSEX for conventional market index and BSE GREEENEX and S&P BSE CARBONEX for ESG indices. We evaluated performances of the three indices during U.S. Debt Ceiling Crisis (2011- 12), Black Monday China, BREXIT and Demonetization (2015-16), and COVID-19 (2020) crisis. We checked whether ESG indices outperformed conventional index significantly using Student's T-test. We have also compared the volatility of the three indices during the different black swan periods using the GARCH model.

Background. Wild irises are promising for cultivation and use in breeding practice. Many of them are included in Red Lists, as they disappear under the impact of anthropogenic factors. It is biologically important to study their morphometric and reproductive parameters, so that the most stable and highly ornamental species could be recommended for expanding the range of flower plants.Materials and methods. Biological features of four Iris L. species rarely occurring in the Southern Urals: I. pseudacorus L., I. pumila L., I. scariosa Wild. ex Link, and I. humilis Georgi, were studied in 2012–2017 in 23 natural and 4 introduced cenopopulations. Individual parameters were compared for 25 medium-age plants from each cenopopulation in their mass-flowering and fruiting phase according to 11 biometric parameters using conventional methods. Statistical significance of the differences was assessed using Student’s t-test.Results. Comparison of morphometric parameters of four rare Iris spp. naturally occurring and introduced in Bashkortostan during six years of research showed significant differences between cenopopulations at a 5% significance level for most traits of I. pumila and I. pseudacorus. As for I. scariosa and I. humilis, differences were mostly insignificant (at tfact< 2.064). Mean values of most reproductive parameters for I. scariosa, I. humilis and I. pseudacorus were significantly lower under introduction conditions than in natural populations. Under cultivation, seed productivity of I. pumila increased. Variability of most morphometric features of the studied irises was within normal response limits for the studied species. When cultivated in the environments of the Bashkir Cis-Urals, they bloom and bear fruit every year, except for I. humilis.Conclusion. Of the four rare Iris spp., I. pumila is recommended for landscaping settlements in the South Urals as the most stable species.

This paper proposes a new THL bearing design method based on an improved version of a precedent method. The precedent method used a model expression prepared in advance to easily and quickly find a crucial predicted data of the maximum bearing temperature. Three expressions were prepared for three different values of journal eccentricity ratio, 0.25, 0.50, and 0.75. Which one of the three should be used was determined, based on the preliminarily obtained value of journal eccentricity ratio derived from the initially analysis and t–test, for the crucial temperature for any value of journal eccentricity ratio. Furthermore, the new expression explicitly includes the four well-known dimensionless numbers used in THL analysis, that is, Sommerfeld number, bearing width-to-dimeter ratio, Peclet number and Khonsari number. The model expressions for other bearing characteristic performances were obtained in the same way. Compared with some measurements in test rigs of cylindrical bearings, the new improved method is confirmed to predict reasonably accurate bearing performances of cylindrical bearings faster and more easily than the precedent method over a wide range of operating conditions.

The topic's relevance is based on solving the problems of the influence of preschool education experience on the multidimensional non-cognitive abilities and personality development of adolescents. The purpose of the article was to analyse the problems of the formation of multidimensional non-cognitive processes, substantiating and determining the non-cognitive abilities of preschool children: highly developed personality, giftedness, intelligence, soft skills and conducting an experiment using the basic survey of the 2013-2014 school years conducted by the Chinese Expert Research on Education (CEPS) at Renmin University (China). The methodological approach of the research was based on the methods of analysis, synthesis, comparison, generalisation of literary sources on the problem of researching the formation of multidimensional non-cognitive abilities, graphic methods for visual illustration and comparison of the results of the ascertaining and formative stages of the research. The content of the main concepts of "abilities" and "non-cognitive abilities" is determined, and their features and features are revealed. The identified non-cognitive abilities and their indicators, as well as the methods of their formation, can be used as methodical material for universities and for the personal development of individual preschool education specialists in near and far foreign countries. [ABSTRACT FROM AUTHOR]

Aims: The inertial measurement unit (IMU), as a sensor-based assessment tool, could provide objective and quantitative data for evaluating a patient with adhesive capsulitis (AC). The IMUs have advantages in simplification of implementation, cost, and computation complexity. We aimed to propose an IMU-based approach to extract statistical features for the assessment of AC in daily activity. Methods: Nine healthy subjects and nine AC patients participate in this experiment. The accelerometers are placed on the wrist and arm to measure the movement performance. Each subject is asked to perform three basic shoulder motions, including flexion, extension, and abduction. Eight types of features are extracted from the norm of accelerometer signals, including mean, standard deviation (SD), variation, maximum, minimum, range, kurtosis, and skewness. These features are explored to distinguish the differences in the movement performance between healthy subjects and AC patients. Statistical Analysis Used: Student's t-test and effect size (Cohen's d) are calculated to assess the reliability of the proposed evaluation approach. Results: The results show that the feature of SD extracted from the wrist can achieve significant differences and large effect sizes between healthy subjects and AC patients. Conclusion: We demonstrate the feasibility of the proposed IMU-based functional evaluation for the AC assessment using statistical features.

The present study is envisaged with an aim to highlight a novel approach of applying the statistical factorial design analysis (FDA) technique in radiation shielding design. In FDA, the estimated total dose rate (TDR) and concentration of elements in shielding material are termed as "Response" and "Factors." The impact on the response due to the change in the level of factors is defined as "Effects." Monte Carlo simulation (MCS) is performed using the MCNP4A code to compute the surface TDRs due to the coupled neutron-gamma field arising from the 740-GBq 241Am-Be source housed inside a shielding container made of composite polymer (CP). The composition of CP is hydrogen, carbon, and oxygen with lead and natural boron as fillers. In the present work, the weight percent of hydrogen, carbon, and lead is optimized in the CP by minimizing the surface TDR at the exit of the shield, and a proposed CP (PCP) is obtained. For the first time, a detailed regression analysis is performed to develop a model linking TDR and the three factors, namely, hydrogen weight percent, carbon weight percent, and lead weight percent. Three levels of each factor are considered, and the impact due to the linear, quadratic, and interaction effects of the factors that influences the TDR is investigated using Student's t-test analysis. The results from the statistical analysis indicate that the weight percent of hydrogen and lead have a greater influence on TDR. The interaction effects arising out of the combination of hydrogen, carbon, and lead are observed to be negligible. Hence, the regression model is modified by dropping the statistically insignificant terms from the equation, and the new model has shown excellent correlation within ±1% of the estimated TDRs using MCS. The R2 and R2Adj values are found to be 0.99970 and 0.99966, which explains the computation power of the model. The model can be applied to compute the TDRs for any combinations of factors within the range of variability as studied in the present work. The shielding container made of PCP obtained from the present study provides a minimum of 20% reduction in volume and mass compared to the conventional high-density polyethylene and other polymer-based materials. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Educational Sciences (2520-2634) is the property of Al-Farabi Kazakh National University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Background Null hypothesis significance testing (NHST) is among the most frequently employed methods in the biomedical sciences. However, the problems of NHST and p-values have been discussed widely and various Bayesian alternatives have been proposed. Some proposals focus on equivalence testing, which aims at testing an interval hypothesis instead of a precise hypothesis. An interval hypothesis includes a small range of parameter values instead of a single null value and the idea goes back to Hodges and Lehmann. As researchers can always expect to observe some (although often negligibly small) effect size, interval hypotheses are more realistic for biomedical research. However, the selection of an equivalence region (the interval boundaries) often seems arbitrary and several Bayesian approaches to equivalence testing coexist. Methods A new proposal is made how to determine the equivalence region for Bayesian equivalence tests based on objective criteria like type I error rate and power. Existing approaches to Bayesian equivalence testing in the two-sample setting are discussed with a focus on the Bayes factor and the region of practical equivalence (ROPE). A simulation study derives the necessary results to make use of the new method in the two-sample setting, which is among the most frequently carried out procedures in biomedical research. Results Bayesian Hodges-Lehmann tests for statistical equivalence differ in their sensitivity to the prior modeling, power, and the associated type I error rates. The relationship between type I error rates, power and sample sizes for existing Bayesian equivalence tests is identified in the two-sample setting. Results allow to determine the equivalence region based on the new method by incorporating such objective criteria. Importantly, results show that not only can prior selection influence the type I error rate and power, but the relationship is even reverse for the Bayes factor and ROPE based equivalence tests. Conclusion Based on the results, researchers can select between the existing Bayesian Hodges-Lehmann tests for statistical equivalence and determine the equivalence region based on objective criteria, thus improving the reproducibility of biomedical research.

March 2020 has become a moment of change in communication mode and quality. Previously, the media paid attention to the current affairs, however, never earlier the journalistic discourse has been so influentially affected by the ongoing phenomenon as in the case of COVID-19. Almost overnight the new terminological phenomena with specific legal or medical reference were introduced into everyday language mainly via mass media and become an important part of a pandemic related narration. The strong influence on the shape of the mentioned linguistic changes has mainly the adoption of new legal regulations due to the unexpected outbreak of the pandemic. The aim of the following paper is to investigate how COVID-19 pandemic affected the specialisation of the journalistic discourse and how different domains (law, medicine) are being influenced by new terminology and in other way round, how for example law and medicine influence new "COVID language". In order to take the interdisciplinary nature of the issue into account, the degree of hybridity of the selected texts will be examined by means of selected material analysis. The methodology applied in the paper uses an empirical approach and comparative analysis. The material used for the analysis comes from the selected Polish quality and boulevard press. The paper concerns the linguistic influence of the "invisible enemy" on the language presented in press. The main findings reveal the intense use of neologisms, borrowings, and it shows that the discourse was changed linguistically thanks to Student's t-test. [ABSTRACT FROM AUTHOR]

Aims: The inertial measurement unit (IMU), as a sensor-based assessment tool, could provide objective and quantitative data for evaluating a patient with adhesive capsulitis (AC). The IMUs have advantages in simplification of implementation, cost, and computation complexity. We aimed to propose an IMU-based approach to extract statistical features for the assessment of AC in daily activity. Methods: Nine healthy subjects and nine AC patients participate in this experiment. The accelerometers are placed on the wrist and arm to measure the movement performance. Each subject is asked to perform three basic shoulder motions, including flexion, extension, and abduction. Eight types of features are extracted from the norm of accelerometer signals, including mean, standard deviation (SD), variation, maximum, minimum, range, kurtosis, and skewness. These features are explored to distinguish the differences in the movement performance between healthy subjects and AC patients. Statistical Analysis Used: Student's t-test and effect size (Cohen's d) are calculated to assess the reliability of the proposed evaluation approach. Results: The results show that the feature of SD extracted from the wrist can achieve significant differences and large effect sizes between healthy subjects and AC patients. Conclusion: We demonstrate the feasibility of the proposed IMU-based functional evaluation for the AC assessment using statistical features. [ABSTRACT FROM AUTHOR]

The twenty-first century has brought the growing use of information and communication technologies in many spheres of human life. Also in education. In the learning process, students are increasingly focused on the use of modern technologies and software packages. Exploring the quality of maths teaching in primary school, we found students' knowledge of using modern technologies but also the lack of visual-logical approach in solving mathematical problems. In this paper, we show how the establishment of figurative numbers and selected examples that demonstrate the observation of legality, can direct students to a visual-logical approach to solving tasks with sets of numbers. We organized a three-hour exercise in experimental and control group, during which the experimental group was working with figurative numbers and the control group with selected examples. On the pre-test both groups showed a low degree of ability to observe legality among the numbers. On the post-test, both groups achieved progress compared to the pre-test, although the experimental group achieved greater progress. The research has shown that dealing with figurative numbers and selected examples that demonstrate the observation of legality, contributes to the development of pupils' abilities to perceive the laws of numbers and to apply the laws observed to solving problems with sets and arrays of numbers.

Copyright of Revista Venezolana de Gerencia (RVG) is the property of Revista de Filosofia-Universidad del Zulia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Metabolomic biomarkers play a vital role in the early identification and prediction of cancer. It is possible to save numerous lives if biomarkers are used to assist medical providers in diagnosing their patients faster. Many researchers have been trying to identify the crucial biomarkers in the early diagnosis of diseases. This paper presents several steps divided into two phases for determining the most important metabolomic biomarkers in the blood for lung cancer prediction using Plasma and Serum samples. We used the Shapiro–Wilk Test, Bartlett’s Test, Levene’s Test, Student’s t-Test, and Kruskal–Wallis Test in the first phase to determine the potential biomarkers. Recursive Feature Elimination with Random Forest was used to identify the final most dominant metabolomic biomarker at the second phase. Lastly, we ended with Ridge Classifier and XGBoost Classifier to assess the consistency of our approaches. Despite the declining number of metabolites up to a greater level, our prediction accuracy was 100% and 90.91% for Plasma and Serum samples, respectively which is higher than the state-of-the-art method. Finally, we made some analysis using the most dominant metabolites that can serve as a source of inspiration for our work.

Testing for differences between two groups is one of the scenarios most often faced by scientists across all domains and is particularly important in the medical sciences and psychology. The traditional solution to this problem is rooted inside the Neyman–Pearson theory of null hypothesis significance testing and uniformly most powerful tests. In the last decade, a lot of progress has been made in developing Bayesian versions of the most common parametric and nonparametric two‐sample tests, including Student's t‐test and the Mann–Whitney U test. In this article, we review the underlying assumptions, models and implications for research practice of these Bayesian two‐sample tests and contrast them with the existing frequentist solutions. Also, we show that in general Bayesian and frequentist two‐sample tests have different behavior regarding the type I and II error control, which needs to be carefully balanced in practical research. This article is categorized under:Statistical and Graphical Methods of Data Analysis > Bayesian Methods and TheoryStatistical and Graphical Methods of Data Analysis > Monte Carlo MethodsStatistical and Graphical Methods of Data Analysis > Markov Chain Monte Carlo [ABSTRACT FROM AUTHOR]

Student's two-sample t-test is often used in medical research like randomized controlled trials. To control type I errors, normality of the observed data needs to be assessed. In practice, a two-stage procedure is acknowledged: First, a preliminary test for normality is conducted. If the test is not significant, the two-sample t-test is applied, and else a nonparametric test like Mann–Whitney's U is conducted. It is unknown how Bayesian tests behave under this procedure. A simulation study was conducted to study the error rates of these Bayesian alternatives under preliminary assessment of normality in balanced and unbalanced designs. Results show that Bayesian counterparts yield 50–60% fewer type I errors at the cost of slightly increased type II error rates, and that the two-stage procedure is not recommended in unbalanced Bayesian designs. This makes them an attractive alternative for biomedical research, as decreased power can be overcome by increasing sample size. [ABSTRACT FROM AUTHOR]

Abstract Background The replication crisis hit the medical sciences about a decade ago, but today still most of the flaws inherent in null hypothesis significance testing (NHST) have not been solved. While the drawbacks of p-values have been detailed in endless venues, for clinical research, only a few attractive alternatives have been proposed to replace p-values and NHST. Bayesian methods are one of them, and they are gaining increasing attention in medical research, as some of their advantages include the description of model parameters in terms of probability, as well as the incorporation of prior information in contrast to the frequentist framework. While Bayesian methods are not the only remedy to the situation, there is an increasing agreement that they are an essential way to avoid common misconceptions and false interpretation of study results. The requirements necessary for applying Bayesian statistics have transitioned from detailed programming knowledge into simple point-and-click programs like JASP. Still, the multitude of Bayesian significance and effect measures which contrast the gold standard of significance in medical research, the p-value, causes a lack of agreement on which measure to report. Methods Therefore, in this paper, we conduct an extensive simulation study to compare common Bayesian significance and effect measures which can be obtained from a posterior distribution. In it, we analyse the behaviour of these measures for one of the most important statistical procedures in medical research and in particular clinical trials, the two-sample Student’s (and Welch’s) t-test. Results The results show that some measures cannot state evidence for both the null and the alternative. While the different indices behave similarly regarding increasing sample size and noise, the prior modelling influences the obtained results and extreme priors allow for cherry-picking similar to p-hacking in the frequentist paradigm. The indices behave quite differently regarding their ability to control the type I error rates and regarding their ability to detect an existing effect. Conclusion Based on the results, two of the commonly used indices can be recommended for more widespread use in clinical and biomedical research, as they improve the type I error control compared to the classic two-sample t-test and enjoy multiple other desirable properties.

It has not been established yet that the cancer stem cell genes have any relation with the non-stem cell cancer genes. It could be interesting to find which non-stem cancer genes are more prone to be affected by cancer stem cell genes. In this paper, an in-silico model has been developed to find out the breast cancer non-stem cell genes which have shown a strong relationship with the breast cancer stem cell genes. First, a set of genes (appearing at antecedent) having a high association with the class labels (as consequent) have been computed using the Apriori algorithm. Then, the cancer non-stem cell genes are identified from the association where one of the genes is cancer stem cell gene. Finally, these cancer non-stem cell genes are optimized according to their differential ability. The experiment has been done on a publicly available Breast Cancer data set. The resultant genes are cross-validated, and accuracy has been reported.

Background: Null hypothesis significance testing (NHST) is among the most frequently employed methods in the biomedical sciences. However, the problems of NHST and p-values have been discussed widely and various Bayesian alternatives have been proposed. Some proposals focus on equivalence testing, which aims at testing an interval hypothesis instead of a precise hypothesis. An interval hypothesis includes a small range of parameter values instead of a single null value and the idea goes back to Hodges and Lehmann. As researchers can always expect to observe some (although often negligibly small) effect size, interval hypotheses are more realistic for biomedical research. However, the selection of an equivalence region (the interval boundaries) often seems arbitrary and several Bayesian approaches to equivalence testing coexist.Methods: A new proposal is made how to determine the equivalence region for Bayesian equivalence tests based on objective criteria like type I error rate and power. Existing approaches to Bayesian equivalence testing in the two-sample setting are discussed with a focus on the Bayes factor and the region of practical equivalence (ROPE). A simulation study derives the necessary results to make use of the new method in the two-sample setting, which is among the most frequently carried out procedures in biomedical research.Results: Bayesian Hodges-Lehmann tests for statistical equivalence differ in their sensitivity to the prior modeling, power, and the associated type I error rates. The relationship between type I error rates, power and sample sizes for existing Bayesian equivalence tests is identified in the two-sample setting. Results allow to determine the equivalence region based on the new method by incorporating such objective criteria. Importantly, results show that not only can prior selection influence the type I error rate and power, but the relationship is even reverse for the Bayes factor and ROPE based equivalence tests.Conclusion: Based on the results, researchers can select between the existing Bayesian Hodges-Lehmann tests for statistical equivalence and determine the equivalence region based on objective criteria, thus improving the reproducibility of biomedical research. [ABSTRACT FROM AUTHOR]

Copyright of Retos, Revista de Ciencias Administrativas y Económicas is the property of Universidad Politecnica Salesiana and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Highway Development and Management (HDM-4) is an internationally recognised tool to analyse pavement management and investment alternatives. The HDM-4 pavement deterioration models help to predict the initiation and progression of various pavement distresses under the different combinations of traffic, climate, pavement structure, and composition. Since the rate of initiation and propagation of each pavement distress is strongly dependent on local conditions, it is essential to calibrate and validate the HDM-4 models for local conditions before their use. Validation of the calibrated HDM-4 pavement deterioration models is needed to check the adequacy of the calibration factors before the model is put to use for future applications. Time series data collected consecutively for three years of 23 high-speed corridors sections constructed with modified binders in India was used to calibrate the HDM-4 distress models. The main aim of this paper is to discuss the validation aspects of the calibrated HDM-4 models, to compare the distresses predicted to those observed on test sections. In this study, a novel technique termed the “proximity to the line of equality” approach is used to validate the HDM-4 models. In addition, Student’s t-test is also used as a conventional validation technique. The advantage of the “proximity to the line of equality” approach is that it removes subjectivity associated with judging the nearness of best-fit straight line of predicted-observed data to the line of equality. Validation results show that distresses predicted by HDM-4 are statistically similar to those observed on the sections. Therefore, the calibrated HDM-4 models can be adopted for planning future maintenance strategies for flexible pavement sections with modified asphalt binder road surfacing.

Purpose - The study aims to explore the particularities of religious tourists' attitudes and behaviors with different demographic profiles. Therefore, this work aims to verify if there are differences between the attitudes and behaviors of Brazilian and Portuguese religious tourists in terms of gender, nationality, and religiosity. Design/methodology/approach - A survey was carried out with 396 religious tourists residing in Brazil and Portugal, who have visited religious destinations in their country or abroad, to carry out a comparative analysis between groups, according to gender, nationality, and religiosity through Student's t-test. Findings - The results show significant differences in tourists' attitudes and behaviors who visit sacred places divided between women and men, Brazilians and Portuguese, and finally, between those who consider themselves religious and non-religious. Research limitations/implications - The study's limitations involve the use of an instrument with a particularly Christian bias. Practical implications - The practical implications of this study include contributions to improving local infrastructure related to hotels, commerce, and tourist services. Originality/value - From a theoretical perspective, this study contributes to the advancement of administrative sciences as it engenders the intersection between religious tourism and public and non-profit marketing, placing the discussion in two countries with a strong religious tradition in the West, Brazil and Portugal. [ABSTRACT FROM AUTHOR]

The quality of the scanning electron microscope (SEM) images can be estimated using the signal-to-noise ratio (SNR). SNR is defined as the ratio of the desired signal to background noise. The noise which appeared in the SEM image is called Gaussian noise. Thus, if the SNR value is high, the image will have better quality since there is more useful information (the signal) than unwanted data (the noise). However, existing SNR estimation methods such as Nearest Neighbourhood (NN), Linear Interpolation (LI), and combination of Nearest Neighbourhood and Linear Interpolation unable to provide satisfactory results in estimating the SNR value. So, to prevent the loss of important information of SEM images, the novel SNR estimation method named Cubic Spline Hermite Interpolation with Linear Least Square Regression (CSHILLSR) has been proposed and formulated. The proposed method is compared with existing methods in terms of absolute error of SNR values, F-test, and Student's t-test. The result shows that the proposed method having a lower absolute error as compared to other methods and there is no significant difference between the actual and estimated SNR value at a 95% confidence level. This indicates that the proposed CSHILLSR able to provide better accuracy in estimation of SNR value as compare to the existing methods. [ABSTRACT FROM AUTHOR]

The situation on the labour market in the field of transport and logistics is strongly undersized by offering the necessary quality human resources. Acquiring and maintaining these resources creates one of the main prerequisites for the competitiveness of companies. Knowing their preferences can help not only solve the problem of gaining, retaining quality employees, but also more efficiently spend funds in this area. The aim of the article is to determine the motivational preferences of employees in the field of transport and logistics and to identify the main areas that are least fulfilled by their employers.. The article is based on the results of a questionnaire survey on a sample of 2363 respondents. Data are processed using basic descriptive statistics and Student's T-test. The results provide an overview of the employees’ preferences of transport and logistics companies and problem areas in terms of satisfaction. In addition to enriching the knowledge base for the next stage of the issue, the conclusions provide companies in the field of transport and logistics with the opportunity to take a more sophisticated approach to motivating their employees and also to help acquire new ones.

Air pollution is one of the most important global environmental issues. Taiwan Environmental Protection Agency (EPA) is currently using an Air Quality Index (AQI) to measure and monitor its national air quality. The main objective of this study is to assess the air quality per hour every month in Taichung City of Taiwan from 2014 to 2016 based on the nonconformance probability of the AQI index. The nonconformance probability is defined as the probability that a characteristic of interest falls outside of an acceptance region. A lower confidence bound for the nonconformance probability is applied to test whether the AQI index value exceeds a warning threshold, and then the government could issue warnings according to the decision made by such statistical inference. An unbalanced two-way random effects model is presented for fitting the AQI index values. We evaluate three different lower confidence bound construction methods, including a t-based, an adjusted t-based and a generalized pivotal quantity (GPQ) based methods, through a detailed simulation study. Finally, a hybrid method of the t-based and the adjusted t-based estimators is recommended for practical use. [ABSTRACT FROM AUTHOR]

Background: The replication crisis hit the medical sciences about a decade ago, but today still most of the flaws inherent in null hypothesis significance testing (NHST) have not been solved. While the drawbacks of p-values have been detailed in endless venues, for clinical research, only a few attractive alternatives have been proposed to replace p-values and NHST. Bayesian methods are one of them, and they are gaining increasing attention in medical research, as some of their advantages include the description of model parameters in terms of probability, as well as the incorporation of prior information in contrast to the frequentist framework. While Bayesian methods are not the only remedy to the situation, there is an increasing agreement that they are an essential way to avoid common misconceptions and false interpretation of study results. The requirements necessary for applying Bayesian statistics have transitioned from detailed programming knowledge into simple point-and-click programs like JASP. Still, the multitude of Bayesian significance and effect measures which contrast the gold standard of significance in medical research, the p-value, causes a lack of agreement on which measure to report.Methods: Therefore, in this paper, we conduct an extensive simulation study to compare common Bayesian significance and effect measures which can be obtained from a posterior distribution. In it, we analyse the behaviour of these measures for one of the most important statistical procedures in medical research and in particular clinical trials, the two-sample Student's (and Welch's) t-test.Results: The results show that some measures cannot state evidence for both the null and the alternative. While the different indices behave similarly regarding increasing sample size and noise, the prior modelling influences the obtained results and extreme priors allow for cherry-picking similar to p-hacking in the frequentist paradigm. The indices behave quite differently regarding their ability to control the type I error rates and regarding their ability to detect an existing effect.Conclusion: Based on the results, two of the commonly used indices can be recommended for more widespread use in clinical and biomedical research, as they improve the type I error control compared to the classic two-sample t-test and enjoy multiple other desirable properties. [ABSTRACT FROM AUTHOR]

Objective: The minimum detectable difference (MDD) of computed tomography (CT) scanned images was quantified and optimized according to an indigenous hepatic phantom, line group gauge and Taguchi L 1 8 optimization analysis in this work. Methods: Optimal combinations of CT scan factors in every group with the level organization were judged using the Taguchi analysis, in which every factor was organized into only 18 groups, creating evaluated outcomes with the same confidence as if every factor was analyzed independently. The five practical factors of the CT scan were (1) kVp, (2) mAs, (3) pitch increment, (4) field of view (FOV) and (5) rotation time for one loop of CT scan. Insofar as each factor had two or three levels, the total number of 162 (i.e., 2 × 3 × 3 × 3 × 3) combinations was considered. Results: The optimal setting was 120 kVp, 300 mAs, 0.641 pitch, 320 mm FOV and 1.0 s of rotation time of CT scan. The minimal MDD was 2.65 mm under 0.39 mm of the slit depth from the revised Student's t -test with a 95% confidence level. In contrast, the MDD of conventional and the best one (no. 7) among all original 18 groups were 3.27 mm and 2.93 mm for 0.43 mm and 0.41 mm slit depths, respectively. Conclusion: The Taguchi analysis was found very lucrative for the design of imaging analysis in practical diagnosis. The indigenous line group gauge and hepatic phantom also proved to be suitable in simulating the human body in real hepatic carcinoma examination. [ABSTRACT FROM AUTHOR]

Objective: To optimize the minimum detectable difference (MDD) of a cardiac X-ray imaging system using the Taguchi L8(27) analysis and a precise line pair (LP) gauge. Methods: The optimal combination of the four critical factors of the cardiac X-ray imaging system, namely X-ray focus, kilovoltage (kVp), milliamper-seconds (mAs) and source image distance (SID), providing the MDD was calculated via the Taguchi analysis and experimentally verified. Two (low and high) levels were assigned for each factor, and eight combinations of four factors were used to acquire instant X-ray images using an NDT commercial LP gauge (with a gauge length of 64 mm and a width of 3. 5 mm). The latter had five lines and was split gradually from top to bottom for the inspection of X-ray images, whose quality was ranked by three well-trained radiologists according to the double-blind criterion. The ranking grade was given by sharp contrast, low noise and precision to distinguish the LP. Accordingly, the MDD was derived to represent the spatial resolution of instant X-ray images by the revised Student's t -test analysis. The optimal combination of factors was experimentally identified and clinically verified in the follow-up inspections. Results: For the conventional setting, Group No. 7 (which obtained the highest grade among eight groups) and the optimal setting, the obtained MDD values were 0. 1 8 3 , 0. 1 6 7 and 0. 1 5 7 mm, respectively, while the LP (line pair/mm) interpolated from the gauge scale amounted to 2. 7 , 3. 1 and 3. 2 LP/mm, respectively. Conclusion: The Taguchi L8 analysis was proved to be instrumental in optimizing the cardiac X-ray imaging system MDD and is recommended to be used jointly with the revised Student's t -test analysis for improving the spatial resolution of instant X-ray images. [ABSTRACT FROM AUTHOR]