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2021 ◽  
Vol 12 ◽  
Author(s):  
Matthias Niemann ◽  
Benedict M. Matern ◽  
Eric Spierings ◽  
Stefan Schaub ◽  
Gideon Hönger

Predicted Indirectly ReCognizable Human Leukocyte Antigen (HLA) Epitopes (PIRCHE) are known to be a significant risk factor for the development of donor HLA-specific antibodies after organ transplantation. Most previous studies on PIRCHE limited their analyses on the presentation of the HLA-DRB1 locus, although HLA-DRB3/4/5, -DQ, and -DP are also known for presenting allopeptides to CD4+ T cells. In this study, we analyzed the impact of predicted allopeptides presented by these additional loci on the incidence of HLA-specific antibodies after an immunization event. We considered pregnancy as a model system of an HLA immunization and observed child-specific HLA antibody (CSA) development of 231 mothers during pregnancy by samples being taken at delivery. Our data confirm that PIRCHE presented by HLA-DRB1 along with HLA-DRB3/4/5, -DQ, and -DP are significant predictors for the development of CSA. Although there was limited peptidome overlap observed within the mothers’ presenting HLA proteins, combining multiple presenting loci in a single predictor improved the model only marginally. Prediction performance of PIRCHE further improved when normalizing scores by the respective presenters’ binding promiscuity. Immunogenicity analysis of specific allopeptides could not identify significant drivers of an immune response in this small cohort, suggesting confirmatory studies.


2021 ◽  
Vol 18 (1) ◽  
pp. 107-122
Author(s):  
Miljana Nikolić

The aim of the research was to examine whether the perceived artistic value of the paintings can be predicted by perfectionism and awe, as well as with the modes of aesthetic processing (H - harmony and R - redundancy). The convenience sample was used and it consisted of 92 respondents (Nmale = 10, Nfemale = 82), with average age of 24.65 years (SD = 6.89). Following instruments were used: Scale of Positive and Negative Perfectionism, Awe Experience Scale and semantic differential scales used to assess harmony, redundancy and distance, as well as the perceived artistic value. Stimuli were paintings from nine artistic movements: Renaissance, Romanticism, Impressionism, Expressionism, Post-impressionism, Fauvism, Cubism, Abstract Art and Surrealism. For each of these movements three paintings of one most prominent representative were chosen (omitting the most famous pieces) in order for the quality of artwork to be uniform. Hierarchical linear regression was used for data analysis. Predictors in the first step were modes of aesthetic processing (H and R), perfectionism in the second step, and subscales of awe were added in the third step. The criterion is artistic value. The model composed of H and R explains 26% of the total variance of artistic value (p < .01). The suscales of perfectionism and awe do not make a significant contribution to prediction. A statistically significant single predictor is R, redundancy (β = .39, t = 2.59, p = .01). The potential existence of mediation was also examined; however, the results of the analysis indicate that there is no statistically significant mediator effect. Keywords: perfectionism, awe, modes of aesthetic processing, Harmony, Redundancy


OENO One ◽  
2021 ◽  
Vol 55 (4) ◽  
pp. 209-226
Author(s):  
Carlos Lopes ◽  
Jorge Cadima

Recent advances in machine vision technologies have provided a multitude of automatic tools for recognition and quantitative estimation of grapevine bunch features in 2D images. However, converting them into bunch weight (BuW) is still a big challenge. This paper aims to compare the explanatory power of the number of visible berries (#vBe) and the bunch area (BuA) in 2D images, in order to predict BuW. A set of 300 bunches from four grapevine cultivars were picked at harvest and imaged using a digital RGB camera. Then each bunch was manually assessed for several morphological attributes and, from each image, the #vBe was visually assessed while BuA was segmented using manual labelling combined with an image processing software. Single and multiple regression analysis between BuW and the image-based variables were performed and the obtained regression models were subsequently validated with two independent datasets.The high goodness of fit obtained for all the linear regression models indicates that either one of the image-based variables can be used as an accurate proxy of actual bunch weight and that a general model is also suitable. The comparison of the explanatory power of the two image-based attributes for predicting bunch weight showed that the models based on the predictor #vBe had a slightly lower coefficient of determination (R2) than the models based on BuA. The combination of the two image-based explanatory variables in a multiple regression model produced predictor models with similar or noticeably higher R2 than those obtained for single-predictor models. However, adding a second variable produced a higher and more generalised gain in accuracy for the simple regression models based on the predictor #vBe than for the models based on BuA. Our results recommend the use of the models based on the two image-based variables, as they were generally more accurate and robust than the single variable models. When the gains in accuracy produced by adding a second image-based feature are small, the option of using only a single predictor can be chosen; in such a case, our results indicate that BuA would be a more accurate and less cultivar-dependent option than the #vBe.


2021 ◽  
Author(s):  
Mathew Wheto ◽  
Nkiruka Goodness Chima ◽  
Henry T Ojoawo ◽  
Matthew A Adeleke ◽  
Sunday O Peters ◽  
...  

Abstract This study aimed to assess the relationship among carcass traits of meat line FUNAAB Alpha chicken genotype, to identify the components that defined bled weight in them using multivariate principal component regression. A total of 14 different carcass traits from sixty-eight birds were recorded and subjected to one-way analysis of variance to vet for sex effect. Phenotypic relationships among the carcass traits were also established to pave way for the principal component analysis. The results reveal significant effects between the traits measured. The male significantly (P<0.05) had greater mean values for the traits measured. Correlations among the considered carcass traits were found to be positive and significant ranging from r = 0.406 (LrWt) - 0.981 (EdWt) for the female chicken; r = 0.330 (Head Wt) - 0.978 (BdWt) for the male chicken. The extracted components PC1 to PC7 contributed 95.66% with PC1 accounting for 68.68% of the variability in the original parameters. Communality estimates varied from 0.466 (thigh weight) to 0.983 (liver weight). In the principal component regression models, Eviscerated weight accounted for 95% of the variation observed in bled weight. The use of PC1 as a single predictor, explained 96.4% of the variability, whilst combining PC1 and PC4 showed improvements in the variance explained (R2 = 96.7%) with a lower Mallow's cp (5.31). Using the principal components scores from the chicken morphometric traits was more appropriate than using the original traits in bled weight prediction.


2021 ◽  
Vol 5 (9) ◽  
pp. 56
Author(s):  
Amal Abdulrahman ◽  
Deborah Richards

Conversational agents offer promise to provide an alternative to costly and scarce access to human health providers. Particularly in the context of adherence to treatment advice and health behavior change, they can provide an ongoing coaching role to motivate and keep the health consumer on track. Due to the recognized importance of face-to-face communication and establishment of a therapist-patient working alliance as the biggest single predictor of adherence, our review focuses on embodied conversational agents (ECAs) and their use in health and well-being interventions. The article also introduces ECAs who provide explanations of their recommendations, known as explainable agents (XAs), as a way to build trust and enhance the working alliance towards improved behavior change. Of particular promise, is work in which XAs are able to engage in conversation to learn about their user and personalize their recommendations based on their knowledge of the user and then tailor their explanations to the beliefs and goals of the user to increase relevancy and motivation and address possible barriers to increase intention to perform the healthy behavior.


2021 ◽  
Vol 8 ◽  
Author(s):  
Anling Xiao ◽  
Huijuan Zhao ◽  
Jianbing Xia ◽  
Ling Zhang ◽  
Chao Zhang ◽  
...  

Background: The coronavirus disease 2019 (COVID-19) pandemic has lasted much longer than an influenza season, but the main signs, symptoms, and some imaging findings are similar in COVID-19 and influenza patients. The aim of the current study was to construct an accurate and robust model for initial screening and differential diagnosis of COVID-19 and influenza A.Methods: All patients in the study were diagnosed at Fuyang No. 2 People's Hospital, and they included 151 with COVID-19 and 155 with influenza A. The patients were randomly assigned to training set or a testing set at a 4:1 ratio. Predictor variables were selected based on importance, assessed by random forest algorithms, and analyzed to develop classification and regression tree models.Results: In the optimal model A, the best single predictor of COVID-19 patients was a normal or high level of low-density lipoprotein cholesterol, followed by low level of creatine kinase, then the presence of &lt;3 respiratory symptoms, then a highest temperature on the first day of admission &lt;38°C. In the suboptimal model B, the best single predictor of COVID-19 was a low eosinophil count, then a normal monocyte ratio, then a normal hematocrit value, then a highest temperature on the first day of admission of &lt;37°C, then a complete lack of respiratory symptoms.Conclusions: The two models provide clinicians with a rapid triage tool. The optimal model can be used to developed countries/regions and major hospitals, and the suboptimal model can be used in underdeveloped regions and small hospitals.


2021 ◽  
Vol 11 (8) ◽  
pp. 980
Author(s):  
Pietro Manuel Ferraro ◽  
Viola D’Ambrosio ◽  
Andrea Di Paolantonio ◽  
Valeria Guglielmino ◽  
Paolo Calabresi ◽  
...  

Objective: Hereditary transthyretin amyloidosis (ATTRv) represents a diagnostic challenge considering the great variability of clinical presentation and multiorgan involvement. In the present study, we report the prevalence of kidney involvement and kidney function over time in a cohort of ATTRv patients with different transthyretin gene mutations. Patients and Methods: For this study, we systematically collected data from all patients with a diagnosis of ATTRv followed at the Neurology Unit of Fondazione Policlinico Universitario A. Gemelli IRCCS. Kidney involvement was defined as presence of estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 obtained with CKD-EPI equation, abnormal urinary protein excretion (UPE) (>150 mg/24 h) and/or albuminuria >30 mg/24 h (or mg/g creatinine). The analysis included data from 46 patients with 122 measurements of serum creatinine. Results: Among the 46 patients included in the analysis, kidney involvement was present in 37%, with 15% showing reduced eGFR and 22% abnormal UPE (63% of patients with available UPE data). No single predictor was associated with either eGFR values or its slope over time. Conclusions: Kidney involvement is quite common in patients with ATTRv regardless of the underlying genetic variant. In particular, abnormal UPE appears to be a common feature of the disease.


2021 ◽  
Author(s):  
Lun Li ◽  
Stephen X. Zhang ◽  
Lorenz Graf-Vlachy

Background: There is limited research focusing on publicly available statistics on the Coronavirus disease 2019 (COVID-19) pandemic as predictors of mental health across countries. Managers are at risk of suffering from mental disorders during the pandemic because they face particular hardship. Objective: We aim to predict mental disorder (anxiety and depression) symptoms of managers across countries using country-level COVID-19 statistics. Methods: A two-wave online survey of 406 managers from 26 countries was finished in May and July 2020. We used logistic panel regression models for our main analyses and performed robustness checks using ordinary least squares regressions. In the sample of 406 managers from 26 countries, 26.5% of managers reached the cut-off levels for anxiety (General Anxiety Disorder-7; GAD-7) and 43.5% did so for depression (Patient Health Questionnaire-9; PHQ- 9) symptoms. Findings: We found that cumulative COVID-19 statistics (e.g., cumulative cases, cumulative cases per million, cumulative deaths, and cumulative deaths per million) predicted managers' anxiety and depression symptoms positively, whereas daily COVID-19 statistics (daily new cases, smoothed daily new cases, daily new deaths, smoothed daily new deaths, daily new cases per million, and smoothed daily new cases per million) predicted anxiety and depression symptoms negatively. In addition, the reproduction rate was a positive predictor, while stringency of governmental lockdown measures was a negative predictor. Individually, we found that the cumulative count of deaths is the best single predictor of both anxiety and depression symptoms. Conclusions: Cumulative COVID-19 statistics predicted managers' anxiety and depression symptoms positively, while non-cumulative daily COVID-19 statistics predicted anxiety and depression symptoms negatively. Cumulative count of deaths is the best single predictor of both anxiety and depression symptoms. Reproduction rate was a positive predictor, while stringency of governmental lockdown measures was a negative predictor.


2021 ◽  
Vol 1 (1) ◽  
pp. 27-35
Author(s):  
Cahya Agung Nugraha ◽  
Ikin Asikin ◽  
Asep Dudi Suhardini

Abstract. The educational process will run conducive if aspects of communication between students and teachers are harmoniously established. Communication between students and teachers cannot be assessed only in terms of quantity or intensity but rather quality in this case communication ethics. One of the problems faced in the field of education is the decline in ethics of student communication to teachers. Communication ethics is a procedure for someone to convey information that is in accordance with moral values so that they can judge the good or bad behavior of a person. For this reason, a program or forum that accommodates students is needed to actualize themselves and to provide guidance related to religious values in order to improve the quality of students' communication ethics to teachers. The purpose of this study is to find out: 1) How active students are in participating in the KRI; 2) How is the ethics of student communication to the teacher; 3) The effect of the students' activeness in following the KRI on communication ethics to the teacher. This research is a quantitative correlational research approach. The population of this study was students of KRI members with a sample of 42 students. The analysis technique used is a single predictor regression analysis. The results showed that there was no influence between the activeness of students in joining the KRI program with the ethics of student communication to teachers in SMA PGII 2 Bandung. Correlation coefficient value of 0.080 with a significance of 0.069 where p> 0.05. This means that students 'activeness in joining the KRI program has not shown a significant influence on the quality of students' communication ethics to teachers, so the work hypothesis is rejected. Regression test results obtained R-square 0.08 or 8% and the remaining 92% is influenced by variables that have not been revealed in this study. In conclusion, the KRI program has not yet led to an improvement in the quality of students' communication ethics to teachers. This is evidenced from the final assessment of the KRI program which is more oriented towards students' cognitive aspects in Islamic insight and vision and mission which are still normative and has not led to an increase in the quality of students' communication ethics to teacher. Abstrak. Proses pendidikan akan berjalan dengan kondusif jika aspek komunikasi antar siswa dengan guru terjalin secara harmonis. Komunikasi antar siswa dengan guru tidak dapat diniliai hanya dari segi kuantitas atau intensitas melainkan kualitas dalam hal ini etika komunikasi. Salah satu masalah yang dihadapi dalam bidang pendidikan yaitu adanya penurunan etika komunikasi siswa kepada guru. Etika komunikasi adalah tata cara seseorang dalam menyampaikan informasi yang sesuai dengan nilai moral sehingga dapat menilai baik atau buruk perilaku seseorang. Untuk itu dibutuhkan program atau wadah yang menampung para siswa dalam mengaktualisasikan diri serta dalam memberikan pengarahan terkait nilai-nilai keagamaan guna meningkatkan kualitas etika komunikasi siswa kepada guru. Tujuan dari penelitian ini adalah untuk mengetahui: 1) Bagaimana keaktifan siswa dalam mengikuti KRI; 2) Bagaimana etika komunikasi siswa kepada guru; 3) Pengaruh keaktifan siswa dalam mengikuti KRI terhadap etika komunikasi kepada guru. Penelitian ini merupakan penelitian dengan pendekatan kuantitatif korelasional. Populasi penelitian ini adalah siswa anggota KRI dengan sampel 42 siswa. Teknik analisis yang digunakan adalah analisis regresi satu prediktor. Hasil penelitian menunjukan bahwa tidak terdapat pengaruh antara keaktifan siswa dalam mengikuti program KRI dengan etika komunikasi siswa kepada guru di SMA PGII 2 Bandung. Nilai koefisien korelasi sebesar 0,080 dengan signifikansi sebesar 0,069 dimana p > 0,05. Hal ini berarti keaktifan siswa dalam mengikuti program KRI belum menunjukan pengaruh yang signifikan terhadap kualitas etika komunikasi siswa kepada guru, sehingga hipotesis kerja ditolak. Hasil uji regresi diperoleh R-square 0,08 atau sebesar 8% dan sisanya 92 % dipengaruhi oleh variabel yang belum terungkap dalam penelitian ini. Kesimpulannya program KRI masih belum mengarah kepada peningkatan kualitas etika komunikasi siswa kepada guru hal ini dibuktikan dari penilaian akhir tentang program KRI yang lebih berorientasi pada aspek kognitif siswa dalam wawasan keislaman serta visi dan misi yang masih normative dan belum mengarah kepada peningkatan kualitas etika komunikasi siswa kepada guru.


2021 ◽  
pp. 103-138
Author(s):  
Justin C. Touchon

What are normal data? What are non-normal data? How do you tell them apart and how do you know what sort of data you have? Chapter 5 begins teaching statistical analysis with a focus on understanding the shape of one’s data and how to measure it. The RxP dataset is explored and the principal focus in this chapter is on normal data and on conducting an Analysis of Variance (ANOVA), although classic non-parametric statistics such as a Kruskal-Wallis test and Mann-Whitney U test are also introduced. Readers are taught how to test for data normality, assess model fit, interpret the summary output from the model, calculate summary statistics and p-values, and how to conduct post-hoc tests (Tukey’s HSD) to compare different levels of a single predictor.


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