Reliability of Donor Lung Sampling in Lung Transplantation

Introduction: Ex vivo lung perfusion (EVLP) is a normothermic platform used to assess donor lungs. Many have studied biomarkers in lung injury, but it is unclear whether samples taken from one location are representative of the organ. Our objective was to investigate the uniformity of cytokine expression in tissue biopsies and in EVLP perfusates from various locations. Methods: In the tissue study, eight donor lungs were partitioned from apex to base. In each lung, three biopsies were taken from the third, sixth, and ninth slices, while two were taken from the lingula and an injury site. In the perfusate study, four samples were taken from four lobes in eight donors during EVLP. Expressions of IL-6, IL-8, IL-10, and IL-1β were measured using qPCR and ELISA. Results: In the tissue study, the mean intra-biopsy equal-variance F-value was 0.53. The median intra-biopsy coefficient of variation (CV) was 18%. In donors without gross focal injury, the mean comparisons of biopsies in each donor showed that the three consistent slices showed no differences and had a CV of 20%, which was similar to the intra-biopsy CV (p=0.80). Both the lingula and injury biopsies demonstrated larger differences from the rest. The median intra-lung CV of perfusates from different lobes was 4.9%. Conclusion: Intra-biopsy variances were consistent across biopsies. Lungs without gross focal injury demonstrated more consistent gene expression. The lingula is not a representative site due to high signal variability. The consistent measurements in EVLP perfusates provided a uniform picture of the inflammation.

Pengaruh Penerapan Pendekatan Saintifik Melalui Model Discovery Learning Terhadap Hasil Belajar IPA

<p><em>This research started with doubts </em><em>whether the application of the scientific approach through the Discovery Learning model in science learning in elementary schools was appropriate.</em><em> The research conducted is experimental research with the type of Quasi Experimental Design, while the research design used in this study is non equivalent control group design. </em><em> </em><em>Based on the results of the study, it can be seen from the analysis using the Independent Sample Test. From the results of the Independent Sample t-Test test for the Equal variance assumed column, it was obtained that the t-count coefficient was 2.672 with a significance value in the Sig (2-tailed) column of 0.01. 87.7273 and for the control class of 80.88 with the average difference in learning outcomes is 6.8472. These results indicate that there is a significant difference in influence between learning with a scientific approach through Discovery Learning and PBL in science subjects.</em></p>

Generalized Linear Models

This chapter revisits a regression analysis to explore the normal least squares assumption of approximately equal variance. It also considers some of the data transformations that can be used to achieve this. A linear regression of transformed data is compared with a generalized linear-model equivalent that avoids transformation by using a link function and non-normal distributions. Generalized linear models based on maximum likelihood use a link function to model the mean (in this case a square-root link) and a variance function to model the variability (in this case the gamma distribution, where the variance increases as the square of the mean). The Box–Cox family of transformations is explained in detail.

Public Perceptions Associated with Barriers to Climate Change Adaptation in Kurdistan Region (KRG): Sulaymaniyah as a Case Study

The aim of this study was to highlight the challenges facing climate change adaptation from the householders’ perceptions in the Sulaymaniyah city. For this purpose, a descriptive analysis method was used with quantitative and qualitative data. Using the SPSS program, several statistical tests were used such as Percentage, the Person-Correlation Coefficient-Partial and Bivariate, T-test Two Sample Equal Variance. The sample of the study consisted of (675) citizens of all components (age, gender, level of education, occupation) who were randomly selected, of which (10) were interviewed. As a result, the study found that participants have faced some barriers such as lack of knowledge about adaptation measures, lack of responsibility for the implementation of the adaptation strategies, and lack of behavioral adaption. In addition, the study identified the most important barriers that limit the willingness of citizens to participate in adaption strategies such as costs, lack of guidance and policies by the local and central government, unbelievable in climate change. Finally, the researcher proposes to conduct more scientific research on climate change adaptation and its barriers in order to prevent the Kurdistan region and its population from the adverse impacts of climate change. Key Words: Adaptation, Climate Change, Barriers to Climate Change Adaptation, Public Perceptions

ROC Asymmetry Is Not Diagnostic of Unequal Residual Variance in Gaussian Signal Detection Theory

Signal detection theory (SDT) is used to analyze yes/no judgment accuracy in many research domains of psychology. SDT yields separate estimates for response bias/criterion (c) and for sensitivity/discriminability (d'). Discrimination performance can be displayed in Receiver Operating Characteristics (ROCs) plotting hit and false alarm rates at various levels of confidence. We provide formal proof and simulations showing that asymmetric ROCs in Gaussian SDT are not exclusively diagnostic of unequal residual variance but may as well result from equal-variance models with c and d' systematically varying across subjects and/or items. Falsely attributing zROC slopes to unequal residual variance while neglecting true group-level variability introduces systematic and unsystematic statistical error. We show that ordinal regression models minimize such errors while estimating all SDT parameters and statistical criteria in a single model.

The Effectiveness Of Multimodal Approaches In Learning

This study aims to test the effectiveness of a multimodal approach in learning. The method used in this study is an experimental research method whose implementation uses a quasi experiment type. The steps of implementing the effectiveness test, namely (1) determining the control group and the experimental group, (2) conducting the pretest, (3) carrying out learning in the control and experimental class, (4) conducting the postest, and (5) analyzing the experimental test results. The multimodal approach has been tested through the t-test to measure its effect on improving students' literary psychological analysis skills. The results of the effectiveness test showed that there was a significant difference in the psychological analysis abilities of students in general between the post-test scores of the control class and the experimental class (p = 0.00 <0.05). This shows that the two variances are not the same, so the use of the variance to compare the population average (t-test for Equality of Means) in the t-test test must be on the basis of equal variance not assumed. At the equal variance not assumed, a t value of 8.114 was obtained and a significance level of Sig. (2-tailed) of 0.000 <0.05, p = 0.000. These results indicate that p <0.05, means that there is a significant difference between groups of students who get treatment using a multimodal approach. Thus it can be said that there is a significant difference in student learning outcomes between the experimental class with the multimodal approach compared to the control class with conventional methods. From the results of the above analysis shows that Ho is rejected, because the significance level of Sig. (2-tailed) of 0.000 <0.05, while H1 was accepted because there was a significant difference between the increase in student learning outcomes in the experimental class and the control class.

Using Statistical Model to Study the Daily Closing Price Index in the Kingdom of Saudi Arabia (KSA)

Classification in statistics is usually used to solve the problems of identifying to which set of categories, such as subpopulations, new observation belongs, based on a training set of data containing information (or instances) whose category membership is known. The article aims to use the Gaussian Mixture Model to model the daily closing price index over the period of 1/1/2013 to 16/8/2020 in the Kingdom of Saudi Arabia. The daily closing price index over the period declined, which might be the effect of corona virus, and the mean of the study period is about 7866.965. The closing price is the last regular deal that took place during the continuous trading period. If there are no transactions on the stock during the day, the closing price is the previous day’s closing price. The closing auction period comes after the continuous trading period (from 3 : 00 PM to 3 : 10 PM), during which investors can enter by buying and selling the stocks at this period. The experimental results show that the best mixture model is E (equal variance) with three components according to the BIC criterion. The expectation-maximization (EM) algorithm converged in 2 repetitions. The data source is from Tadawul KSA.

A Hierarchical Unequal-Variance Signal Detection Model for Binary Data

Gaussian signal detection models with equal variance are typically used for detection and discrimination data whereas models with unequal variance rely on data with multiple response categories or multiple conditions. Here a hier- archical signal detection model with unequal variance is suggested that requires only binary responses from a sample of participants. Introducing plausible constraints on the sampling distributions for sensitivity and response criterion makes it possible to estimate signal variance at the population level. This model was applied to existing data from memory and reasoning tasks and the results suggest that parameters can be reliably estimated, allowing a direct comparison of signal detection models with equal- and unequal-variance.

Statistical Estimates of the Pulsar Glitch Activity

A common way to calculate the glitch activity of a pulsar is an ordinary linear regression of the observed cumulative glitch history. This method however is likely to underestimate the errors on the activity, as it implicitly assumes a (long-term) linear dependence between glitch sizes and waiting times, as well as equal variance, i.e., homoscedasticity, in the fit residuals, both assumptions that are not well justified from pulsar data. In this paper, we review the extrapolation of the glitch activity parameter and explore two alternatives: the relaxation of the homoscedasticity hypothesis in the linear fit and the use of the bootstrap technique. We find a larger uncertainty in the activity with respect to that obtained by ordinary linear regression, especially for those objects in which it can be significantly affected by a single glitch. We discuss how this affects the theoretical upper bound on the moment of inertia associated with the region of a neutron star containing the superfluid reservoir of angular momentum released in a stationary sequence of glitches. We find that this upper bound is less tight if one considers the uncertainty on the activity estimated with the bootstrap method and allows for models in which the superfluid reservoir is entirely in the crust.

UJI PERBANDINGAN MOTIVASI BELAJAR SISWA KELAS XI MIPA 2 DAN XII MIPA 2 DI SMA NEGERI 1 MUARO JAMBI

Penelitian ini bertujuan untuk melihat perbandingan motivasi belajar siswa kelas XI dan kelas XII. Penelitian ini menggunakan metode penelitian kuantitatif deskriptif dengan menggunakan instrumen berupa angket motivasi belajar siswa. Sampel penelitian ini yaitu siswa kelas XI MIPA 2 dan kelas XII MIPA 2 di SMA NEGERI 1 MUARO JAMBI tahun ajaran 2020/2021 yang berjumlah 60 responden. Teknik analisis data yang digunakan peneliti yaitu menggunakan software IBM SPSS 23, dengan melakukan Uji Normalitas, Uji Homogenitas, dan Uji Perbandingan. Data yang didapatkan peneliti telah terdistribusi normal dan homogen, sehingga peneliti dapat menggunakan uji perbandingan. Adapun hasil uji perbandingan ini yaitu nilai signifikan pengujian dua arah Sig.(2-tailed) sebesar 0,207 pada Equal variance not assumed, dan nilai signifikan pengujian dua arah Sig.(2-tailed) untuk Equal variance assumed dan nilai untuk Equal variance not assumed sebesar 0,208. Hasil penelitian menunjukkan tidak terdapat perbedaan yang signifikan pada hasil motivasi belajar siswa antara siswa kelas XI MIPA 2 dan XII MIPA 2.