Examination of Nutritional Knowledge Levels and Nutritional Attitudes of Badminton Athletes

Aim: This study aimed to examine the nutritional knowledge levels and nutritional attitudes of badminton athletes in Turkey. Method: The screening model was used in our research. After giving preliminary information about the survey to the participants, a total of 207 volunteer athletes (92 (44.4%) female and 115 (55.6%) male athletes) participated in the study voluntarily. In the research, a personal information form was used in the first part, and a nutrition questionnaire consisting of two main parts was applied in the nutrition-related part. The first part of the nutrition questionnaire measured the nutritional knowledge level of the participants, and the second part measured their nutritional attitudes. The data obtained for the research were first transferred to the computer environment and then analyzed through the SPSS 22.0 package program. Results: According to the results of the study, it was observed that the nutritional attitude values of the female participants were higher than the males, and this difference was found to be statistically significant (p<0.05). Considering the nutritional attitudes of the national athletes according to the being national athlete status variable of the participants, it was determined that the mean scores were higher than the non-national athletes and this situation was statistically significant (p<0.05). Conclusion: When the results were examined, it was observed that the athletes who took nutrition lessons had higher nutritional knowledge and attitudes than those who did not, and national athletes had higher nutritional knowledge and attitudes than non-national athletes. The fact that national athletes can be in the camp environment at an early age and work with experts was inevitably beneficial for their nutritional knowledge and attitude. Keywords: Badminton, Nutrition Knowledge and Attitude

Spatial Plan of Wisma Athletes as A Defense in The Era of The Covid-19 Pandemic

In this era of the COVID-19 pandemic, there are many things that need to be watched out for and also need to be prepared. The role of the government as one of the leaders of a country needs to have a plan to overcome these problems. One of the efforts made by the government is to create a Covid-19 emergency hospital by converting the Kemayoran and Pademangan Wisma Athletes. The selection of this athlete's home is considered to be able to accommodate patients affected by COVID-19. But not only that, every room in this emergency hospital is a shield for every patient. Each room in the athlete's house has its own role and function, not least as a means of defense for every patient, to support this, the use of descriptive and narrative analysis is to explain how the architectural layout in the athlete's house and also use narrative analysis techniques to focus on an idea that can be developed into a related part. From the results of this analysis, it is also expected to get results to provide new knowledge, about how patients in the athlete's house become a means of defense for themselves.

Structure Model of Foresightful Export Oriented Strategies for Iran Pharmaceutical Industry: Using a Fuzzy DEMATEL Method

Background: Export orientation is one of the main approaches in developing Iran's pharmaceutical industry as a key health-related part of industries. It is necessary to identify, formulate and implement some foresightful strategies and strategic plans toward adopting the export approach in the Iran pharmaceutical industry. Objectives: This paper aims to identify, prioritize and develop a structure model of foresightful export-oriented strategies and strategic plans for Iran's pharmaceutical industry. Methods: Data gathering for identifying strategies conducted through literature review and some interviews with pharmaceutical industry experts analyzed through qualitative content analysis. Then fuzzy DEMATEL technique is used to prioritize and develop cause and effect and structure the model of identified strategies. Results: Policy modification, privatization, smart self-sufficiency in production, knowledge management in both national policy and industry firm's levels, and quality improvement in all aspects of production and products were identified as foresightful export-oriented strategies and plans for Iran pharmaceutical industry. Conclusion: Privatization is the most effective and important foresightful export-oriented strategy in Iran's pharmaceutical industry.

Training Visual Pattern Recognition in Ophthalmology Using a Perceptual and Adaptive Learning Module

Background: To evaluate the efficacy of a perceptual and adaptive learning module (PALM) for teaching the identification of five optic nerve findings.Methods: In this prospective trial at a single academic institution, second- through fourth-year medical students were randomized, by class, to the PALM or a video didactic lecture. The PALM presented the learner with a short classification task consisting of an optic nerve image with all five possible findings. Learner accuracy and response time were used to guide the sequencing of successive classification tasks. Mastery for each finding was defined as three consecutive correct identifications within a target response time of eight seconds. The lecture intervention was a narrated video designed to simulate the related part of a traditional medical school didactic lecture. Accuracy and fluency on a pre-test, post-test, and delayed test (one month after the learning intervention) were compared within and between groups using the t-test. Cohen’s d was used to estimate effect size.Results: Eighty-three students participated. Accuracy and fluency improved significantly (P < 0.001) from pre-test to immediate post-test for both the PALM (accuracy d = 2.94, fluency d = 3.39) and lecture (accuracy d = 2.32, fluency d = 1.06). At the delayed test, PALM performance remained significantly (P < 0.001) greater than the pre-test in both accuracy (d = 0.89) and fluency (d = 1.16), while lecture performance remained greater in accuracy only (d = 0.44, P = 0.02). The PALM induced greater improvements than the lecture in both accuracy and fluency on the immediate post-test and delayed test.Conclusions: The PALM is an effective modality for training identification of common optic nerve findings.

The Music in Berlin: Musical Networks

This chapter is a detailed discussion of the sophisticated network relations at play in Berlin’s klezmer and Yiddish music scene. Drawing on the work of Howard Becker and Mark Granovetter, it lays out the connections that bring different musicians together, including an analysis of important network hubs and significant weak ties that enable creative links across different musical and social territories. The historical context for these networks is also discussed in detail, including the earlier roles of venues, organizations, and personalities in uniting musicians, audiences, and enthusiasts. The second half of the chapter then offers a detailed breakdown of current musical styles, positing four overlapping stylistic (and in some senses social) categories that help the reader to navigate different expressions and groupings of Berlin klezmer: pioneers, modernists, fantasists, and transformers. Each one of the taxonomies is analyzed in terms of musical approach, repertoire, and relation to other groups. These are enriched in each case by a wealth of ethnographic detail, thick descriptions of particular performances (including the author’s own reactions and responses), and informative musical examples and transcriptions. The chapter concludes by placing the city of Berlin’s klezmer musical networks within the wider international scene of which they are a distinct but related part.

The The Relationship between Speaking and Writing Performance in an Indonesian Senior High English Foreign Language (EFL) Classroom

Purpose - This research aims to figure out the relationship between those two productive skills focusing on four aforementioned crucial aspects in language learning. Design/methodology/approach - This study used a cross-sectional quantitative method with 32 English Education Department students in the 6th semester at Universitas Islam Negeri Sunan Ampel Surabaya who have already been experienced in spoken and written class to be the participants. In terms of gaining the data, It used pictured cued interviews and answer the open-ended question related to the best way in finding a job and give their opinion within 30 minutes. Both of the tests were adapted from the TOEIC sample test from the Educational Testing Service (ETS). Finally, use SPSS 2.2 for the data analysis. Findings - The result shows that the organization gains the highest rate or simply as the most related part among the other language learning. Furthermore, the correlation between the two productive skills also shows a moderate correlation. Originality/value - It simply said that speaking and writing show an insignificant correlation with the organization as the most related part of language learning. Paper type – Research paper

Physics of parameter correlations around the solar-scale enhancement in neutrino theory with unitarity violation

We discuss the physics of the three neutrino flavor transformation with non-unitary mixing matrix, with particular attention to the correlation between the $\nu$SM- and the $\alpha$ parameters which represent the effect of unitarity-violating (UV) new physics. Towards this goal, a new perturbative framework is created to illuminate the effect of non-unitarity in the region of the solar-scale enhanced oscillations. We refute the skepticism about the physical reality of the $\nu$Standard Model CP phase $\delta$–$\alpha$ parameter phase correlation by analysis with the SOL convention of $U_{{\tiny MNS}}$, in which $e^{\pm i \delta}$ is attached to $s_{12}$. Then, a comparative study between the solar- and atmospheric-scale oscillation regions allowed by the framework reveals a dynamical $\delta$–(blobs of the $\alpha$ parameters) correlation in the solar oscillation region, in sharp contrast to the “chiral”-type phase correlation $[e^{- i \delta} \bar{\alpha}_{\mu e},\ e^{- i \delta} \bar{\alpha}_{\tau e},\ \bar{\alpha}_{\tau \mu}]$ in the Particle Data Group convention seen in the atmospheric oscillation region. An explicit perturbative calculation to the first order in the $\nu_{\mu} \rightarrow \nu_{e}$ channel allows us to decompose the UV related part of the probability into the unitary evolution part and the genuine non-unitary part. We observe that the effect of non-unitarity tends to cancel between these two parts, as well as between the different $\alpha_{\beta \gamma}$ parameters.

The design of the study

The third chapter discusses the case selection of the study and more broadly, its research design. As the subtitle of the book already indicates, two cases are selected here: France (FN) and the Netherlands (PVV). These different cases are highly interesting as they allow pin-pointing the key differences between and similarities among types of radical right-wing voters across various national contexts, as well as improving the specificity and validity of the causal claims. In terms of the research design, the remainder of the chapter follows the same structure as the previous theory chapter, Chapter 2. Accordingly, it first discusses the data and methods used in the supply-side-oriented part of the book, which relies on a content analysis of the tweets of Marine Le Pen and Geert Wilders. The demand-side-related part, by contrast, relies on multiple data sources and methods. This chapter explains why a sequential mixed-methods approach is followed, using multiple correspondence analysis (MCA) to investigate the structural heterogeneity among radical right voters and life-history interviews to assess ideal-typical forms of radical right support within this structural heterogeneity.

Copula Model Selection for Vehicle Component Failures Based on Warranty Claims

In the automotive industry, it is important to know whether the failure of some car parts may be related to the failure of others. This project studies warranty claims for five engine components obtained from a major car manufacturer with the purpose of modeling the joint distributions of the failure of two parts. The one-dimensional distributions of components are combined to construct a bivariate copula model for the joint distribution that makes it possible to estimate the probabilities of two components failing before a given time. Ultimately, the influence of the failure of one part on the operation of another related part can be described, predicted, and addressed. The performance of several families of one-parameter Archimedean copula models (Clayton, Gumbel–Hougaard, survival copulas) is analyzed, and Bayesian model selection is performed. Both right censoring and conditional approaches are considered with the emphasis on conditioning to the warranty period.

MemCap: Memorizing Style Knowledge for Image Captioning

Generating stylized captions for images is a challenging task since it requires not only describing the content of the image accurately but also expressing the desired linguistic style appropriately. In this paper, we propose MemCap, a novel stylized image captioning method that explicitly encodes the knowledge about linguistic styles with memory mechanism. Rather than relying heavily on a language model to capture style factors in existing methods, our method resorts to memorizing stylized elements learned from training corpus. Particularly, we design a memory module that comprises a set of embedding vectors for encoding style-related phrases in training corpus. To acquire the style-related phrases, we develop a sentence decomposing algorithm that splits a stylized sentence into a style-related part that reflects the linguistic style and a content-related part that contains the visual content. When generating captions, our MemCap first extracts content-relevant style knowledge from the memory module via an attention mechanism and then incorporates the extracted knowledge into a language model. Extensive experiments on two stylized image captioning datasets (SentiCap and FlickrStyle10K) demonstrate the effectiveness of our method.