Reviewerly/exHarmony huggingface dataset:
Regional Localization of Mouse Brain Slices Based on Unified Modal Transformation

Brain science research often requires accurate localization and quantitative analysis of neuronal activity in different brain regions. The premise of related analysis is to determine the brain region of each site on the brain slice by referring to the Allen Reference Atlas (ARA), namely the regional localization of the brain slice. The image registration methodology can be used to solve the problem of regional localization. However, the conventional multi-modal image registration method is not satisfactory because of the complexity of modality between the brain slice and the ARA. Inspired by the idea that people can automatically ignore noise and establish correspondence based on key regions, we proposed a novel method known as the Joint Enhancement of Multimodal Information (JEMI) network, which is based on a symmetric encoder–decoder. In this way, the brain slice and the ARA are converted into a segmentation map with unified modality, which greatly reduces the difficulty of registration. Furthermore, combined with the diffeomorphic registration algorithm, the existing topological structure was preserved. The results indicate that, compared with the existing methods, the method proposed in this study can effectively overcome the influence of non-unified modal images and achieve accurate and rapid localization of the brain slice.
Qualidade de vida de diabéticos acompanhados pela Estratégia Saúde da Família

Introduction: Diabetes mellitus is a metabolic disease that affects population health and requires quality of life assessment to formulate specific care strategies to minimize or prevent its deterioration. Objective: To assess the quality of life of people with diabetes mellitus monitored by the basic health unit. Methods: Cross-sectional study carried out with 82 diabetic patients in a basic health unit. Questionnaires containing sociodemographic and clinical variables, as well as the problem areas in diabetes, were used to assess quality of life. In the data analysis, the Kruskal-Wallis test, the Mann-Whitney U test, the Student's t test and variance analysis were used. Results: Most of the participants were women, elderlies and had black skin. They were nonsmokers and nonalcoholic patients, had completed primary education and were retired. They had their own homes and a family income of up to a minimum wage. They had type 2 diabetes, apart from two comorbidities associated with diabetes, and between six and ten years of diagnosis. They used oral antidiabetics as a sedentary form of treatment. The total score showed an average of 32.36, which indicates a good quality of life for most of the participants, while those who suffered a negative impact had the emotional factor as the most affected domain. Conclusion: The data obtained from this study will allow planning specific actions targeted at this population to promote better adherence to practices that positively influence quality of life.
Gaussian Representations of K-Means Clusters: Case Study of Educational Process Mining of UCI

The information of data patterns can help determining analytical direction, choosing right tools for analysis, and validating inferential results. However, this argument might not be helpful because of diverse patterns. To disclose inside information, a learning approach about data clustering is proposed by integrating K-means and Gaussian representation from data science. It gets insight of similar and dominant distribution through iterative learning. Its core technique lies in the design of data representation which can carry similarity and dominance characteristics from samples to K-learning. For illustration, it is applied in the educational process mining of UCI. Its results can provide strategic information for educational activities.
An Interpretation of Initiation Theme of Zhang Guixing’s Novels 张贵兴早期小说的青春启蒙成长主题

Since 1970, Zhang Guixing's literary writing can be divided into three periods, that is, in the hometown of Borneo during the first try writing (1970-1976), after graduation from Taiwan University, combined with the colour of Chinese old novel creation transition period (1977-1995), then back to the late return of Borneo's rainforest Writing (1996-2018). Many literary commentators often focus on Zhang Guixing's rainforest writing in their researches, which is relatively neglected the early stages of creation. However, Zhang Guixing's current novel is closely related to his youthful trial in Borneo, leaving a trail of growth and variation in the process. From the perspective of Initiation Story, this thesis will explore the novels of Zhang Guixing's early and transitional period. This research will be focus on his early writing which were published in the local Borneo newspaper Miri Daily, the West Malaysia magazine, Xue Bao，Jiao Feng , as well as his novels as the research object, focused on his literature in the Borneo period.Keywords: Zhang Guixing, Borneo, initiation story, initiation theme张贵兴早期小说的青春启蒙成长主题摘要 从1970年开始创作投稿迄今，张贵兴的创作历程大致可分三个时期，即在故乡婆罗洲时期的初试啼声（1970-1976），留台大学毕业后结合中国旧小说色彩的创作过渡期（1977-1995），再到后期回归婆罗洲的雨林书写（1996-2018）。许多文学评论家论张贵兴时往往集中于其后期的成名作品，即“雨林三部曲”，创作初期作品相对被忽视。然而，张贵兴当下的小说跟他在婆罗洲年少时期的试笔关系紧密，过程中留下了成长的痕迹与变异。因此，本论文将从成长小说的视角，以张贵兴赴台之前发表在婆罗洲当地报章即《美里日报》文艺版，西马刊物《学报》、《蕉风》以及他早期小说为研究对象，集中针对其小说的青春启蒙成长主题进行文本探析。 关键词：张贵兴，婆罗洲，成长小说，成长主题
Implementing the Sparrow laboratory data system in multiple subdomains of geochronology and geochemistry

&amp;lt;p&amp;gt;Data sharing between laboratories is critical for building repeatable, comparable, and robust geochronology and geochemistry workflows. Meanwhile, in the broader geosciences, there is an increasing need for standardized access to aggregated geochemical data tied to basic geological context. Such data can be used to enrich sample and geochemical data repositories (e.g., EarthChem, Geochron.org, publisher archives), align geochemical context with other datasets that capture global change (e.g., Neotoma, the Paleobiology Database), and calibrate digital Earth models (e.g., Macrostrat) against geochronology-driven assessments of geologic time.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;A typical geochemical lab manages a large archive of interpreted data; standardizing and contributing data products to community-level archives entails significant manual work that is not usually undertaken. Furthermore, without widely accepted&amp;amp;#160; interchange formats, this effort must be repeated for each intended destination.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Sparrow (https://sparrow-data.org), in development by a consortium of geochronology labs, is a standardized system designed to support labs&amp;amp;#8217; efforts to manage, contextualize, and share their geochemical data. The system augments existing analytical workflows with tools to manage metadata (e.g., projects, sample context, embargo status) and software interfaces for automated data exchange with community facilities. It is extensible for a wide variety of geochemical methods and analytical processes.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this update, we will report on the implementation of Sparrow in the Arizona Laserchron Center detrital zircon facility, and how that lab is using the system to capture geological context across its data archive. We will review similar integrations underway with U-Pb, &amp;lt;sup&amp;gt;40&amp;lt;/sup&amp;gt;Ar/&amp;lt;sup&amp;gt;39&amp;lt;/sup&amp;gt;Ar, SIMS, optically stimulated luminescence, thermochronology, and cosmogenic nuclide dating. We will also discuss preliminary efforts to aggregate the output of multiple chronometers to refine age calibrations for the Macrostrat stratigraphic model.&amp;lt;/p&amp;gt;
Flouting of Conversational Maxims in Comments on Social Media Instagram

The name Instagram is short for the word instant-telegram hence when viewed from the combination of the two words insta and gram, Instagram means the ease of taking and viewing photos that can be sent or shared with others, and the users of Instagram can comment in the photo that other users share. People in Instagram uses ambiguous, slang, or any other forms of language to comment in other users post for various reasons. During this comment process, they exchange meanings, which calls for both message senders and receivers to understand and interpret the messages in the same perspectives. In interpreting the meanings or messages people convey through a conversation, the intension of the utterances they make are aimed to socialize within the society well, but often people misunderstanding the meanings of utterances in comment section. Therefore this research was conducted with the objective to identify flouted maxims in comments on Instagram posts and to find out the implied meanings intended by speakers in conveying messages to the readers (hearers). The data were taken from the comments section on Instagram posts which indicate flouting maxims. And this research uses qualitative descriptive to describe and give an overview of the data found in this research using Pragmatic approach. Five data are discussed in this paper based on the conversation implicature and cooperative principle. The results show that the flouted maxims are those of Relation and of Manner. The analysis performed on the data has also shown that the reason behind the implied meanings intended by speakers are that the speakers want to show friendly impression and familiarity. Keywords: Instagram, conversation implicature, cooperative principle, meanings, flouting maxims
Graph-based variational auto-encoder for generalized zero-shot learning.

Zero-shot learning has been a highlighted research topic in both vision and language areas. Recently, generative methods have emerged as a new trend of zero-shot learning, which synthesizes unseen categories samples via generative models. However, the lack of fine-grained information in the synthesized samples makes it difficult to improve classification accuracy. It is also time-consuming and inefficient to synthesize samples and using them to train classifiers. To address such issues, we propose a novel Graph-based Variational Auto-Encoder for zero-shot learning. Specifically, we adopt knowledge graph to model the explicit inter-class relationships, and design a full graph convolution auto-encoder framework to generate the classifier from the distribution of the class-level semantic features on individual nodes. The encoder learns the latent representations of individual nodes, and the decoder generates the classifiers from latent representations of individual nodes. In contrast to synthesize samples, our proposed method directly generates classifiers from the distribution of the class-level semantic features for both seen and unseen categories, which is more straightforward, accurate and computationally efficient. We conduct extensive experiments and evaluate our method on the widely used large-scale ImageNet-21K dataset. Experimental results validate the efficacy of the proposed approach.
Synthesis of academic and modern practices of learning sculpture in creative universities of kazakhstan

The article put attention on the need for a methodological collaboration analysis of the academic and modern types of teaching sculpture in the specialized creative colleges and universities of the Republic of Kazakhstan in the modern educational and aesthetic discourse. The main research problem focuses on identifying and characterizing the most relevant educational theoretical and practical methods that can significantly increase the level of domestic art education in the art of sculpture. The author believes that a comprehensive scientific analysis of the educational potential of the Kazakhstani aesthetic originality of modern sculpture, its history and technical and technological features will give a possibility to understand deeply and see the big picture of the art education role in the general socio-cultural canvas of sovereign Kazakhstan. At the moment, the Kazakhstani art education system is on a peripeteia and it is necessary to clear the choice between academic and contemporary art practices or their harmonious synthesis. This work is devoted to these question’s analysis and the author's research work disclosure.
Quality of Online Learning Participation in a Context of Crisis (Journal Pre-Proof)

Objectives: The COVID-19 pandemic has forced educational institutions to adopt online tools in order to conduct emergency remote teaching and make efficient use of virtual learning contexts. However, although these contexts may serve to improve teaching processes, a number of issues must be taken into consideration in order to ensure quality student learning. The purpose of our study is to examine types of participation in virtual learning processes by analyzing the level of information contained in message posts and the depth of contributions made by students Method: We analyze a computer programming module taught online using a learning management system during the first year of a computer science degree program at a Chilean university. We conducted a content analysis of the messages posted in the forums, followed by a statistical analysis of the codified data. For the latter, we used quantitative methods to identify relationships between the level of information contained in student contributions (information level) and a series of covariates, such as message length, perception of achieved learning, final grade, and message depth. Results: Results show that Number of Words (B = 0.02, SE = 0.002), Final Grade (B = 0.45, SE = 0.22), and Student Self-Perceived Learning (B = -0.82, SE = 0.40) predict higher Information Level. Conclusions: Greater clarity as to the relationship that exists between forms of participation in online collaborative environments and the quality of participants’ contributions would support the generation of activity models that are conducive to improved quality of participant learning. Implication for Practice: Results reveal the need for guidelines that define online classroom activities, as these have a considerable influence on the generation of dialogue that is conducive to the construction of new knowledge.
A Study on the Effect of Heart rate based Left Ventricular Global Function on the Time of Contrast Enhancement

A Study on the Effect of Heart rate based Left Ventricular Global Function on the Time of Contrast Enhancement 의 이용 수, 등재여부, 발행기관, 저자, 초록, 목차, 참고문헌 등 논문에 관한 다양한 정보 및 관련논문 목록과 논문의 분야별 BEST, NEW 논문 목록을 확인 하실 수 있습니다.
AuraEN: Autonomous Resource Allocation for Cloud-Hosted Data Processing Pipelines

Ensuring cost-effective end-to-end QoS in an IoT data processing pipeline (DPP) is a non-trivial task. A key factor that affects the overall performance is the amount of computing resources allocated to each service in the pipeline. In this demo paper, we present AuraEN, an Autonomous resource allocation ENgine that can proactively scale the resources of each individual service in the pipeline in response to predicted workload variations so as to ensure end-to-end QoS while optimizing the associated costs. We briefly describe the AuraEN system architecture and its implementation and demonstrate how it can be used to manage the resources of a DPP hosted on the Amazon EC2 cloud.
Perancangan Sistem Informasi Rental Sepeda Berbasis Web Pada Toko Linkz Cycle Pontianak

Linkz Cycle is a bike rental located in Pontianak City. This rental provides services in the form of hourly bike rental. Linkz Cycle Store is located at Kedah Street No.76 Pontianak City. In this effort, there are still many problems that occur in the Admin section, namely in the process of recording bike rental bookings that take a lot of time because it is still recorded through books. Problems also occur when consumers place an order over the phone, because the consumer can not see the picture of the bike to be rented. The process of data processing and report making that occurs in Linkz Cycle is still using data processing that is recorded in the form of bookkeeping. With the increasing number of products and transactions that occur every day, it turns out that it makes it difficult for companies in the process of searching for data, causing delays and even errors in obtaining the desired information. Also on the issue of bike rental security, in the absence of a bike feeding tracking system can not be monitored medium position where, and it can certainly harm the store in case of theft. With some of the above problems, it is necessary to create a bike rental application and equipped with a GPS tracking system at the Linkz Cycle Store so that it can facilitate and maximize the performance of employees, and reduce the risk of losses in the end the application analyzed in this research is expected to support the required information process quickly and accurately. The application is created with PHP and MySQL programming languages.
Video Resolution Enhancement

In this period of advanced correspondence, video has become a significant aspect of our everyday life. Additionally, video enhancement being a functioning exploration subject in PC vision has gotten more consideration in these ongoing years. Video enhancement manages the accompanying issue: Given an inferior quality info video, how might we make yield video more understood and better. There are essentially two strategies for video enhancement: 1-Spatial - based space video enhancement, 2-Transform - based area video enhancement. Spatial - put together area video enhancement works with respect to pixels. The essential restrictions of this model remember need of giving sufficient heartiness. The fundamental thought behind change-based video enhancement is that to improve the video by controlling the change coefficients. These strategies can't do all the upgrade of the image well overall, and it is hard to mechanize the image enhancement method. Aside from this, actualizing video enhancement utilizing these strategies costs high and is perplexing as well. Perform video enhancement utilizing a solitary image super resolution utilizing four diverse imaging procedures, in particular Super Resolution Convolutional Neural Network (SRCNN), Fast Super Resolution Convolutional Neural Network (FSRCNN), Super Resolution Generative Adversarial Networks (SRGAN), Fast Super Resolution Generative Adversarial Networks (FSRGAN).
CONTENT ANALYSIS OF STUDENT BOOK “WHEN ENGLISH RINGS A BELL” FOR GRADE VIII JUNIOR HIGH SCHOOL

The purpose of this study is to analyze the relationship between inner material student book “ When English Rings a Bell “ for grade VIII SMP with Core Competenicies and Basic Cognitive Field 2013 Curriculu and the realm of psychomotor learning. This research uses descriptive qualitative content analysis as a research method. Data collected from English student book “When English Rings a Bell” for eighth graders of junior high school. The school was written by the writing team of the Ministry of Education and Culture Indonesia. In this study the material in the textbook is classified based on basic competence three as cognitive domain and basic competence four as psychomotor domain.  Data is extracted from the data source and entered into checklist table to make comparisons between material in textbooks and the material needed in the 2013 English syllabus for grade VIII students Junior high school.
THEORETICAL PROBLEM OF STUDYING THE PROFESSIONAL QUALITIES OF SCHOOL PSYCHOLOGISTS

A competent, qualified psychologist becomes in the process of education and formation of professionally important qualities and, observing the moral and ethical standards of behavior when working with clients, which have been developed by psychological practice. Professionally important qualities (PVK) are individual qualities of the subject of activity that affect the effectiveness of the activity and the success of its development. The professional competence of a psychologist, their compliance with moral and ethical norms of behavior in professional activity is one of the indicators of professional competence assessment, ensure their social adaptation, ability to self-regulation and multi-level reflection
Directional Bias Amplification

Mitigating bias in machine learning systems requires refining our understanding of bias propagation pathways: from societal structures to large-scale data to trained models to impact on society. In this work, we focus on one aspect of the problem, namely bias amplification: the tendency of models to amplify the biases present in the data they are trained on. A metric for measuring bias amplification was introduced in the seminal work by Zhao et al. (2017); however, as we demonstrate, this metric suffers from a number of shortcomings including conflating different types of bias amplification and failing to account for varying base rates of protected attributes. We introduce and analyze a new, decoupled metric for measuring bias amplification, $\text{BiasAmp}_{\rightarrow}$ (Directional Bias Amplification). We thoroughly analyze and discuss both the technical assumptions and normative implications of this metric. We provide suggestions about its measurement by cautioning against predicting sensitive attributes, encouraging the use of confidence intervals due to fluctuations in the fairness of models across runs, and discussing the limitations of what this metric captures. Throughout this paper, we work to provide an interrogative look at the technical measurement of bias amplification, guided by our normative ideas of what we want it to encompass. Code is located at this https URL
Self-educational Competence as an Integral Part of the Professional Competence of Future Agricultural Students

The author analyses the content of the development of selfeducational competence of students of agricultural educational institutions with the help of interactive computer technologies. High speed of science development quickly renders any knowledge acquired by students in high school obsolete and reveals the urgent need for the development of self-educational competence. In conditions of widespread computerisation and active use of the latest modern technical developments in everyday life, the use of interactive computer technology appears to be the most effective and promising line of self-educational competence development among university students. Four components of self-educational competence are identified: knowledge; motivation; activity; communication. In accordance with these components, criteria, indicators, and tools were developed to determine the self-educational competence development of university students through interactive computer technology. The pedagogical experiment took place from 2017-2019 based on Chernyatyn College of Vinnytsia National Agrarian University. The survey covered 87 students of four faculties, 26 people were in the control group and 61 people in the experimental group. To standardise the initial results of diagnostic tests and questionnaires, percentiles were used. After calculating percentiles for each component of self-educational competence, a table of standardisation was composed. Four levels of component development of self-educational competence were identified: low, below average, above average, and high. The purpose of the formative phase of the experiment was the model testing of self-educational competence development in university students through interactive computer technology. The analysis of indicators of transition of students to a high level of development of self-educational competence demonstrated that the process of development of self-educational competence of students of experimental group passes more effectively than at students of control group. The reason was the experimental work performance to implement structural and functional models for self-educational competence development of university students through interactive computer technology