Reviewerly/exHarmony huggingface dataset:
Influence of preservation length of the sample on the performance of complete blood count (CBC) in rats

The performance of hematological tests deteriorates with the increase in the length of sample preservation. Therefore it has been an issue to characterize the maximum permissible period spent between blood collection and measurement to have the acceptable test report. From this view point, a study was undertaken to know about the effect of preservation length on complete blood count (CBC) in rat of Long Evans strain. A total of 30 samples were collected from 10 apparently healthy rats aged between 45-48 days and the blood samples were kept in commercial test tubes treated with EDTA. The test tubes containing whole blood samples were divided into three different groups based on preservation length and were allowed to keep at 4ºC for three different lengths of time viz. 2 hours, 4 hours and 6 hours until analysis. The samples were then analyzed for their complete blood count (TEC, TLC, Hb, PCV, DLC, Absolute Leukocyte Count, Red Cell Indices, RDW-SD, RDWCV, Platelet, MPV, PCT and PDW) using Sysmex XT-1800i auto hematological analyzer. Result showed that no significant change in CBC with the variation in preservation length. Based on these findings, it can be concluded that blood samples can be preserved for as long as 6 hours to have the same report obtainable when the samples are preserved at 4ºC in refrigerated condition for 2 or 4 hours.&#x0D; Asian J. Med. Biol. Res. March 2020, 6(1): 22-26
Saliency Prediction Based On Lightweight Attention Mechanism

Abstract Saliency prediction refers to an algorithm that extracts salient regions from natural scenes. In the field of deep learning, receptive field limits the accuracy of pixel classification and thus affects the accuracy of saliency prediction. This study proposes a new saliency prediction method that uses the improved feature pyramid attention (FPA) to gain multi-scale context information to solve the above-mentioned problems. FPA’s number of parameters and cost of calculation are also decreased. Experimental results show that this method can obtain more accurate results than the existing saliency prediction methods without increasing the calculation amount.
Improving the Ability of Deep Neural Networks to Use Information From Multiple Views in Breast Cancer Screening

In breast cancer screening, radiologists make the diagnosis based on images that are taken from two angles. Inspired by this, we seek to improve the performance of deep neural networks applied to this task by encouraging the model to use information from both views of the breast. First, we took a closer look at the training process and observed an imbalance between learning from the two views. In particular, we observed that layers processing one of the views have parameters with larger gradients in magnitude, and contribute more to the overall loss reduction. Next, we tested several methods targeted at utilizing both views more equally in training. We found that using the same weights to process both views, or using modality dropout, leads to a boost in performance. Looking forward, our results indicate improving learning dynamics as a promising avenue for improving utilization of multiple views in deep neural networks for medical diagnosis.
Material Food Probes:Personalized 3D Printed Flavors for Intimate Communication

Interactions with food are complex, integrating rich multisensory experiences within emotionally meaningful social contexts. Yet, the opportunities to explore food as material resource for emotional communication have been less explored. We describe a two-month project with 5 couples centered on the co-design of personalized flavors for intimate communication, which were experienced through an explorative three day study involving a 3D food printer in participants’ homes. We discuss the value of our findings indicating preferences for both remembered and imagined positive flavors and their integration in focal intimacy practices to support emotional coregulation. We also discuss material food probes and their value for exploring and inspiring both design-with and design-around food.
Empathy Profile Based on Gender in IV Graders of Elementary School Students

This study deals with the profile of empathy. The method used survey method. The respondents obtained by using convenience sampling technique. The respondents involved were 643 IV graders of elementary school students consisting of 322 male students and 321 female students. The results obtained from the lowest aspects based on the overall analysis are aspects of cognitive empathy by 62.4% of respondents in the low category, 37.6% in the moderate category, and 0% in the high category. The affective aspect has a fairly average distribution of 39.3% of respondents in the low, 43% in the medium, and 16, 8% in the high category. The most moderate category of prosocial motivation is 50.5%, the low category is 29.9% and the high is 19.6%. The low contribution of cognitive aspects was caused by male respondents 70.2% in the low category while in women only 54.5%. In the affective aspect the contribution of the two is relatively no significant difference. In the aspect of male prosocial motivation 32% of the respondents are in the low category while women are less than 4.3% and 3.8% women are more than men in the high category.
Translation error analysis in Treat

The aim of this research paper is to conduct a thorough analysis of inter-annotator agreement in the process of error analysis, which is well-known for its subjectivity and low level of agreement. Since the process is tiresome in its nature and the available user interfaces are pretty distinct from what the average annotator is accustomed to, a user-friendly Windows 10 application offering a more attractive user interface is developed with the aim to simplify the process of error analysis. Translations are performed with Google Translate engine and English-Croatian is selected as the language pair. Since there has been a lot of dispute on inter-annotator agreement and the need for guidelines has been often been emphasized as crucial, the annotators are given a very detailed introduction into the process of error analysis itself. They are given a presentation with a list of the MQM guidelines enriched with tricky cases. All annotators are native speakers of Croatian as the target language and have a linguistic background. The results demonstrate that a stronger agreement indicates more similar backgrounds and that the task of selecting annotators should be conducted more carefully. Furthermore, a training phase on a similar test set is deemed necessary in order to gain a stronger agreement.
A Study on Comparision of Quality of Life of Asthma Patient with PFT and Mini AQLQ Scoring in SRMC

Asthma is one of the chronic respiratory conditions.A large Number of patients still experience a high level of morbidity .Much of the morbidity from Asthma is believed to be due to factors such as a chronic condition, poor knowledge of the disease process and medication understanding on the use of and poor self-management.Patient education is becoming an essential area of service provision.In this study30 Patients who were diagnosed as asthma with PFT and attending Pulmonology OPD at SRMC were included and were given a mini AQLQ questionnaire containing 15 questions regarding the level of asthma and limitations of activities, to test their knowledge about Asthma and quality of life, with particular reference to the knowledge about the disease and answers were analyzed to test the knowledge of the Patients about Asthma.It was done twice, first visit and after 3 weeks.These patients were prescribed with bronchodilators (SABA or LABA), Breathing exercises were explained and Inhaler technique was checked and proper technique is taught to the patient.Results showed Educating the patient about disease and teaching inhaler technique, breathing exercise resulted in more improvement in both PFT and quality of life of asthma patients with significant improvement in lung function.
Using Artificial Intelligence System for Pattern Identification Based on Features Extracted from Gel Electrophoresis Images

Artificial intelligence has many branches of image processing-based applications in terms of classification and identification, error back-propagation neural network is a great match for such applications as long as linear vector quantization (LVQ) and pattern recognition is another great match for recognition of digital images based on their features. The dataset used in this paper are gel electrophoresis images where 6 features had been extracted from the images and used as input to a neural network for learning and then checked for recognition purposed and the system managed to recognize all the 6 images. Six features had been used: average, standard deviation, smoothness, skewness, uniformity, and entropy. A tiny error rate where allowed in the recognition program to cover the variation of the dataset and the test data (gel-electrophoresis images). The proposed system had successfully managed to identify all of the learned data in both LVQ and error-back-propagation. Error-back-propagation proved itself as a great tool in terms of learning time compared with LVQ, which was very slow in terms of learning time and recognition.
Research on Optimization of Informatization Talents Training Mode in Colleges Under the Background of “Innovation 3.0”

The innovation paradigm has evolved from innovation 1.0 and innovation 2.0 to innovation 3.0.In the period of Innovation 3.0, the institutions are required to cultivate talents with innovative consciousness, innovative thinking and innovative ability.Using the RETAIN model, the optimization path of innovation and entrepreneurship education in colleges and universities can be designed from six aspects: relevance, embedding, translation, adaptation, immersion, naturalization; enhancing the correlation between educational content and demand; increasing the embedding of ecosystem construction; promoting learners Application of knowledge and skill transfer; use school-enterprise cooperation to help learners adapt to economic and social needs; create learning situations to help learners immerse themselves in the continuous learning process; promote the process of innovation and entrepreneurship to naturalize, and guide learners to shift staged learning to lifelong learning.
Effective Knowledge Distillation for Human Pose Estimation

Most existing human pose estimation approaches focus on improving the model performance, but putting aside the significant efficiency problem. It makes the model not practical. Therefore, it is meaningful to explore how to keep high precision on a smaller model. This paper investigates the knowledge distillation strategy for training small network by making use of large network and try to keep high performance at the same time. Experiments on COCO dataset demonstrates the effectiveness of the proposed approach which can improve network accuracy without increasing network complexity.
Comparison Analysis with Huffman Algorithm and Goldbach Codes Algorithm in File Compression Text Using the Method Exponential Comparison

With the development of technology at this time many people know about compression. In simple compression is a process to shrink the file from its original size. At this time compression applications that are often used are WinZip, WinRar, and 7-Zip, namely with the aim of compressing documents and saving space on memory or data transmission. Compressed data can be in the form of images, audio, video and text. The use of the Huffman algorithm and the Goldbach Codes algorithm in compressing text files is intended to provide enormous benefits in the sending and storage process and requires less memory space compared to uncompressed text. The algorithm starts by providing a string of inputs as input, how to produce an algorithm output in the form of a binary string or code that translates each input string, so that the string has a small number of bits compared to strings that are not compressed. Thus, the problem is how to obtain the code with sorted characters and frequency tables as input and shorter binary code as output. In applying the Huffman algorithm and the Goldbach Codes algorithm in compressing text files is very good, the results were not reduced from the original file or there was no reduction
CONSTRUCTION OF A NETWORK MODEL OF CIVIC CONSCIOUSNESS OF PEDAGOGICAL UNIVERSITY STUDENTS BASED ON THE INTERDISCIPLINARY APPROACH

In the article, the authors propose a project to develop a new approach to the study of the personality characteristics of pedagogical university students based on building a network model of civic consciousness using an integrated interdisciplinary approach. The concept of civic consciousness is used as the basic one for studying the personality characteristics of teachers in training in connection with the high level of social activity of contemporary young people, its impact on professional and pedagogical features, and also because this scientific concept remains unrevealed from the point of view of its semantic content, network modeling and the inclusion of this model into the elements of the educational process and system-forming factors of personality.
Industrial Internet of Things: practical study based on a computerized multifunctional laboratory

In article are considering the education-methodical aspects of organization on a base of multifunctional computerized lab of practice learning by students of specialty 151 "Automation and computer-integration technologies" of the fundamental IIoT information technologies and its using in MES.
Character Segmentation Of Degraded Odia Script

Optical Character Recognition (OCR) is a field which converts printed text into computer understandable format that is editable in nature. Odia is a regional language used in Odisha, West Bengal &amp; Jharkhand. It is used by over forty million people and still counting. With such large dependency on a language makes it important, to preserve its script, get a digital editable version of odia script. We propose a framework that takes computer printed odia script image as an input &amp; gives a computer readable &amp; user editable format of same, which eventually recognizes the characters printed in input image. The system uses various techniques to improve the image &amp; perform Line segmentation followed by word segmentation &amp; finally character segmentation using horizontal &amp; vertical projection profile.
2SPD-013 Application of the ABC analysis method for optimising the stock management of medical devices in common use

<h3>Background and importance</h3> One of the hospital pharmacist’s main tasks is to optimise the inventory management of pharmaceutical products to keep costs under control in the supply chain and guarantee a minimal storage cost. A number of tools exist to allow the categorisation of products to be managed in order to focus on those considered most strategic. <h3>Aim and objectives</h3> To use the ABC analysis method to optimise the economic management of common medical device stocks at the pharmacy level of our hospital and the importance criteria set in the value of annual consumption. <h3>Material and methods</h3> On an Excel board, we calculated the accumulated stock value, accumulated value rate, rank and rank percentage of each medical device intended for common use. This made it possible to draw the cumulative value percentage curve according to the percentage of rank and the ‘Pareto histogram’. <h3>Results</h3> A total of 234 references were analysed, the total amount of which was 774 888.36€. We distinguished three categories of products: ‘Category A’: representing 85% of the total value of the stock and 20% of the total number of items. It included articles such as universal kits, sterile gloves or infusers. According to our criteria of importance, this group of articles was considered the most important. ‘Category B’: the items represented about 12% of the total value of stock and 30% of the total number of items, including products such as penis cases or plaster strips. ‘Category C’: the items represented 2% of the total value of stock and more than 50% of the total number of items, such as the case of Guedel cannulas or Y fittings. <h3>Conclusion and relevance</h3> The data collected confirmed Pareto’s law, according to which 20% of the products stored represent 80% of the value of the stock. This allows better efficiency in decision making and the implementation of actions adapted for each category, such as reducing the value of stocks and the cost of storage, to adapt the ordering method and fix the number of permanent inventories to be made. <h3>References and/or acknowledgements</h3> No conflict of interest.
Implementing On-line Scientific Collaboration Editing to Increase Lecturer’s Research Publication

Scientific publications have become a trend in the field of academics. As the development of trends in publications turns into a necessity. Lecturers are required to conduct scientific publications as a form of implementation of the Tridarma of Higher Education. Lecturers have a community that needs a vehicle to construct knowledge in the style of collaborative scientific writing. Management of scientific paper is essential, one form is collaboration. Collaboration has the opportunity to achieve significant improvements in the scientific publications of lecturers at Universitas Negeri Malang (UM). The online collaboration concept is felt to provide facilities that allow lecturers at UM to create, publish works that are rich in digital content in new or existing communities. The goal is to increase the scientific publications of lecturers with a collaborative system of writing scientific work among lecturers at UM based online.
Self-Assessment on Integrated Listening-Writing Skills for Human Puppets Preservation

This study examines the application of self-assessment concerning students writing skills using integrated CLLA (Cultural Language Learning Approach), BLM (Blended Learning Method) and HOTS (High Order Thinking Skills) with human puppets serial stories what so-called Wayang Orang (WO) as the learning discourses.This was intended to implement Self-Assessment to the students' listening-writing skills development using integrated CLLA, BLM and HOTS as WO preservation efforts for the sake of finding the concept of implementing Self-Assessment on Listening-Writing Skills (SALWS) using such three methods.The Mixed Methods Study was conducted by involving 30 students of the English Education Program Faculty of Teachers Training and Education.The main data was a portfolio of documentation of SALWS assignments analyzed using the Eberly Center for Teaching Excellence Carnegie Mellon Model (ECTECM).The results were interpreted as findings regarding the SALWS implementation integrated with CLLA, BLM and HOTS containing with various WO serial stories.The study reveals that SALWS can be used as a self-assessment guide by students for the average score spreads between 0% for A(sophisticated) scores, 6% B scores (very competent), 71% C scores (competent), and the remaining 11% get scores D (Not yet competent).WO preservation efforts conducted in the Paragraph-Writing class could attract a majority of 89% of students.The rest neither were interested in WO nor increased such language skills since they came from foreign countries which were still in the process of adaptation in using both their English and Indonesian.
Understanding Perception and Motivation in Sharing Information by Digital Natives in Social Media

Background of the study: The phenomenon of sharing information by all members of the public, especially digital natives. The phenomenon of sharing information is most visible done on social media such as WhatsApp, Instagram and line. Information sharing activities seem easy to do, especially on social media with a variety of features that have been provided and a variety of information that is spread. Even sharing information can have an impact, both positive like increasing knowledge or negative impacts such as creating information hoaxes.Purpose: Not yet known explicitly actually what lies behind someone, especially the digital generation natives share information on social media. To find out what is the background of someone sharing information on social media, therefore this study wants to find out from the aspect of perception and motivation regarding information sharing activities carried out by digital natives on social media.Method: This research uses quantitative methods, while the test carried out is path analysis. The population and sample of this study were S2 students in Information Management and Library and S1 Faculty of Social and Politics UGM. The population was chosen because they want to know the differences in perceptions and motivations of digital generations from the perspective of the level of education and age, apart from the social aspects of each student in sharing information on social media.Findings: The results of this study found that the perception of MIP students' information sharing was higher than that of FISIPOL students, but on the contrary, the motivation to share information on FISIPOL students was higher than MIP students. The difference is based on the age difference of MIP students who are more mature than FISIPOL students so that their perceptions about sharing information are wiser, but the motivation of FISIPOL students is higher because sharing information is not only for formal matters but also for informal matters such as finding one's reputation and pursuing prizes.Conclusion: Digital natives' perception in sharing information on social media is sharing information because it is seen to be beneficial to other individuals, sharing information is fun and can invite others to jointly understand and discuss together the latest information. For digital natives motivation in sharing information on social media, intrinsically to meet self-satisfaction. Examples such as being able to add insight and can discuss with other individuals. Whereas extrinsically is the motivation to share information because it can help others, especially when the information they have is useful and worth sharing. In terms of information sharing activities themselves, the digital natives really understand and pay attention to the type of information and the quality of information that will be shared before they share it with a wide audience.
A Study on the Construction of Data Mining Course-Oriented Data Literacy Training

The data literacy training is becoming important in the big data era and data mining course has been one of the key courses to cultivate data literacy in universities.After analyzing the problems in the actual teaching, the paper discusses the construction of data mining course oriented data literacy training and proposes a new project-driven teaching scheme that includes the case-based classroom teaching and flipped-classroom practice teaching with a multilevel practice system.The new scheme can offer an individualized teaching and promote the learning enthusiasm and initiative of students efficiently.