Reviewerly/exHarmony huggingface dataset:
Using Informatics Framework in Immunosuppressed or Transplanted Patients for a Preferential Care Route at the Emergency Department

For immunosuppressed or transplanted patients, appropriate triage is a timely topic, especially in the Emergency Department (ED) of a high-volume referral center. We implemented a new Program called Rapid Clinical Care by Internal Medicine Specialists, as a preferential care route for these patients, which combines the proposed informatics framework in the field of total quality management in the healthcare units, as an example of digital technologies that can improve processes in the clinical routine. Our study aimed to describe waiting-time and attention-time in ED and to explore the effect on patients’ clinical outcomes after discharge. Findings were: shortened waiting time (median of 8 minutes versus 21, p&lt;0.001), improved ED on-call time (median of 2 hours compared to 4, p&lt;0.001), and greater follow-up after discharge, measured as 1-week scheduled-visits rate (69% with 95%CI 63-75; compared to 43% with 95%CI 35-51; p&lt;0.001).
The degree of availability of professional teaching competencies for physical education teachers in Jordan

The study aimed to identify the degree of availability of professional teaching competencies for physical education teachers in Jordan from their point of view and its relationship to some variables such as gender, academic qualification and years of experience. The study sample consisted of (784) male and female teachers in the second semester of the year (2021/2022); The study concluded that the degree of availability of professional teaching competencies was moderately in all fields of study, in addition to the absence of statistically significant differences that are attributed to the variables of gender and educational qualification, and the presence of statistically significant differences due to the variable years of experience and in favor of teachers with experience of more than 10 years. .
Sentiment Analysis of English Text based on LSTM-RNN

<p style="text-align: justify;"><span style="font-size:16px;font-family: 'Times New Roman','serif'">With the emergence of a large number of text information on the Internet, not only can we learn the user's personal preferences from the emotional mining and analysis of the text, but also can monitor public opinion. So text sentiment analysis has become a new research hotspot for researchers on Web-based information processing. Aiming at the problem of how to analyze the sentiment class from the English text more accurately, this paper selects some user reviews dataset as the sentiment analysis database of the English text dataset by using the corpus that has already completed emotional annotation on the Internet as corpus, and uses the LSTM-RNN algorithm to classify and analyze. The analysis results of this method in this paper are compared with the traditional classification results of other models, the experimental results show that the LSTM-RNN model proposed in this paper compared with other traditional network models is more effective well in classifying sentiment analysis of English texts. The feature selection method of information gain can reach 88.2%, which proves that the model is effective.</span>
Karakteristik struktur dan kebahasaan teks deskripsi siswa di sekolah menengah pertama islam terpadu

The purpose of this research is to describe the characteristics of the structure and language of the description text of the VII grade students of SMP IT Al-Kahfi Pasaman Barat. This type of research is qualitative research using descriptive methods. The results of this research are two, namely (1) characteristics of the structure of the description text of the VII grade students of SMP IT Al-Kahfi Pasaman Barat is the title, identification, and description of the section, and (2) the linguistic characteristics of the description text of the VII grade students of SMP IT Al-Kahfi Pasaman Barat is special words, synonymous words with strong emotions, and personal pronouns.
Bitcoin and Other Opensource Software Protocol Accounting Systems as an Accepted Global Monetary System

Bitcoin, the opensource software protocol accounting system, is a revolutionary metric of finance that has increased in popularly, but more importantly, has increased substantially in value against the Dollar over the previous few years.This paper highlights the fundamentals of valuing Bitcoin by understanding how it is valued as a usable currency and then, helps to guide how it can and is being used as an alternative source of potential equity for global corporate institutions.This paper looks at the challenges faced in maintain and accounting for traditional equity, that is equity backed by the Dollar, and looks at how crypto currency is creating transparency in the financial accounting system.It identifies potential challenges in the use of this new currency against the practices of regulated accounting standards.This research also identifies what future acceptance as an alternative equity might look like with the use of Bitcoin.Cryptocurrency has a significant societal impact now and, in the future, based on the devaluing of the global financial position, the increased availability of communication technologies, and the need for valuing scarcity in a global society.While the technology that embraces Bitcoin and other similar currencies has evolved to create a more understood technology process, the incorporation of these currencies as part of a monetary system is still not understood.Global monetary systems must find a new method of maintaining a financial structure that is universally acceptable but also scarce.Being that we live in an increasingly technological world, digital currency is a natural fit and should be realized as a legal tender.Questions to consider: Cryptocurrency is beginning to be adopted as an alternative to the traditional monetary system.With companies like Coinbase, the largest owner of Bitcoin, looking to value their IPO at $75 billion, the investment community is beginning to pay attention (Roberts, 2021).Can cryptocurrency such as Bitcoin be an effective alternative to a traditional monetary system?If so, how can it be used as an asset for companies as a financial alternative?
General TV Viewing Patterns of Rural School Going Children

A sample of 150 rural school going children (80 male and 70 female) age ranged between 7-13 yrs were selected by following purposive random sampling method from 6 villages of Parbhani District. The data pertaining to the study were collected by personally interviewing the sample rural school going children based on open ended interview schedule cum checklist after developing rapport with them. Similarly all the sample children’s parents also were interviewed based on the open ended interview schedule cum checklist for obtaining information additionally required for the study. It is clear from the results that relatively a higher percentage of rural school going children (37- 50%) were found to view TV Programmes telecasted on Big Magic channel followed by Channel-2 (28 - 42%) and Channel-3 (24 - 32%). Irrespective of gender, about 98 percent of rural school going children reported that they are more interested in viewing view cartoon serials. More than 70 percent of them had their TV sets in living rooms and a higher percentage of them observed to be maintaining 5-7 ft from TV sets while viewing TV programmes. Irrespective of gender, the findings of the study indicate that significantly a higher percentage of rural school going children (72 – 88%) used to view TV programmes enormously. A higher percent of rural school going children used to view TV programmes by sitting on floor or on cot (47 - 50%). Irrespective of gender, chitchatting (35 - 46%) and eating (38 - 43%) were observed to be the most common concurrently done activities of rural school going children while viewing TV programmes. As compared to the rural school going girls, their counter parts boys used to view TV programmes along with their friends and mothers.
2nd Workshop on Digital Infrastructures for Scholarly Content Objects (DISCO'22)

The goal of the Digital Infrastructures for Scholarly Content Objects (DISCO) workshop is to raise awareness of quality issues, improved discovery, and re-use challenges in digital infrastructures for scholarly content, and to collect potential solutions among an audience of diverse expertise.
Approach for Electronic Medical Record Data Analysis

As the healthcare environment is being digitalized and changed rapidly, research using medical big data is increasing. One of the most applicable data is electronic medical records which can provide a large amount of clinically practical meaning. Electronic medical data include patient’s demographic information, laboratory test results, imaging and biosignal data. In this article, we provide support for a wide variety of researchers in their efforts to use electronic medical record data accurately and usefully in their work. From the basic concept of the research using electronic medical records to challenging aspects like data integration between multiple institutions are described. Also, examples of each type of data are covered; structured such as numeric data and unstructured such as images, biosignals and narrative text. Using these kinds of electronic medical records, analyses are processed by data cleansing, transforming, and reducing in order. Many kinds of variables such as the exposure and outcome of interest, covariate and the research design can be chosen during the preprocessing. As many machine-learning-based studies as well as epidemiologic-based studies have been conducted using electronic medical records, various research frameworks have been proposed. However, data quality management and data standardization for multicenter data analysis are still remaining as challenging tasks.
Implementing Predictive Models Within an Electronic Health Record System: Lessons from an External Validation of a Suicide Risk Model

Over the past 5 years, there has been an increase in the development of EHR-based models for predicting suicidal behaviour. Using the McGinn (2000) framework for creating clinical prediction rules, this study discusses the broad validation of one such predictive model in a context external to its derivation. Along with reporting performance metrics, our paper high-lights five practical challenges that arise when trying to undertake such a project including (i) validation sample sizes, (ii) availability and timeliness of data, (iii) limited or incomplete documentation for predictor variables, (iv) reliance on structured data and (v) differences in the source context of algorithms. We also discuss our study in the context of the current literature.
Opening doors to diversity in leadershipBobbySiuToronto, Canada: University of Toronto Press, 2021, 315 pages, $38.95, hardback

Personnel PsychologyVolume 75, Issue 3 p. 767-769 BOOK REVIEWS Opening doors to diversity in leadership , Bobby Siu, Toronto, Canada: University of Toronto Press, 2021, 315 pages, $38.95, hardback Ashley Pearson, Ashley Pearson Psychology Department, Middle Tennessee State University, Murfreesboro, Tennessee, USASearch for more papers by this author Ashley Pearson, Ashley Pearson Psychology Department, Middle Tennessee State University, Murfreesboro, Tennessee, USASearch for more papers by this author First published: 10 June 2022 https://doi.org/10.1111/peps.12533Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL REFERENCES Abadi, M. (2018, January 10). 5 things that make Canada a very different place to work than the US. https://www.businessinsider.com/differences-canada-us-work-2018-1 Zhao, S. (2021, January 22). Progressive facade: Comparing the U.S. and Canada's treatment of indigenous peoples. https://harvardpolitics.com/a-progressive-facade-comparing-the-u-s-and-canadas-treatment-of-indigenous-peoples/ Volume75, Issue3Autumn (Fall) 2022Pages 767-769 ReferencesRelatedInformation
Predicting immune checkpoint inhibitor-related hepatitis using electronic health records of patients.

e13564 Background: Immune checkpoint inhibitor (ICI) therapies have shown impressive results in treating oncology patients. However, some patients exhibit immune-related adverse events (irAE-s), one significant irAE is autoimmune hepatitis. Oncologists routinely screen for hepatic toxicity with a complete metabolic panel prior to each ICI administration. Predictive modeling of irAE-s based on patient factors has the potential to help guide treatment selection and monitoring protocols. We have developed a widely usable model based on patient history and routinely collected standard blood panels that can predict whether a patient will experience hepatitis with ICI administration. Methods: We defined irAE hepatitis as any single value of AST, ALT, or alkaline phosphatase three-times the upper limit of normal (ULN) as following ICI treatment. The goal was to determine whether the level of the biomarkers exceed this threshold within certain, pre-defined time-windows, as determined by medical experts. We used feature engineering to compress the time-series of lab panels into single meaningful statistical descriptors, such as mean or maximum of these vectors. The dataset was highly unbalanced with many more negative cases (out of the 3231 patients, depending on the window length used for feature generation, 100-400 positives were found), which warranted the application of synthetic resampling methods. Finally, we trained various ensemble models ( e.g., random forest, gradient boosting), on both the resampled and original dataset, to obtain the final, predictive model for the likelihood of irAE hepatitis. Models were tuned to favor high recall and lower precision (identification of patients for increased monitoring) or moderate recall and moderate precision (maximizing F1-score). Results: We explored several modelling methods, such as KNN, Logistic Regression, Random Forests (RF), Gradient Boosting (GB), and stacking. GB without resampling produced the best model with the moderate recall and precision. To achieve high recall with low precision, we needed to resample the dataset with random majority class under sampling and then use RF (see table below for exact results). Conclusions: In this study, we show contemporary machine learning methods can be used as a screening tool for patients at risk for irAE hepatitis. This method could be used to identify patients who would benefit from additional laboratory monitoring between ICI administrations or guide clinical decisions about therapy cessation in advance of toxicity. Additionally, these methods may be further developed and adapted to improve clinical trial exclusion criteria for patients most likely to develop irAE hepatitis.[Table: see text]
Tensor Networks Meet Neural Networks

Abstract As a simulation of the human cognitive system, deep neural networks have achieved great success in many machine learning tasks and are the main driving force of the current development of artificial intelligence. On the other hand, tensor networks as an approximation of quantum many-body systems in quantum physics are applied to quantum physics, statistical physics, quantum chemistry and machine learning. This talk will first give a brief introduction to neural networks and tensor networks, and then discuss the cross-field research between deep neural networks and tensor networks, such as network compression and knowledge fusion, including our recent work on tensor neural networks. Finally, this talk will also discuss the connection to quantum machine learning.
Designing postures for rehabilitation therapies in a multimodal system based on a 3D virtual environment and movement-based interaction

Abstract Technological advances have facilitated new approaches to support different needs in healthcare environments. In particular, in the field of rehabilitation therapies, we can find software applications that have been developed to support the performance of specific exercises, often with different customization options. However, there are still many gaps that need to be addressed to provide more and better global solutions. In this article, we present a novel system aimed at physiotherapists, which allows them to create new rehabilitation exercises designed to meet the specific needs of their patients. This implies the creation of individualized therapies that contribute to a better and faster recovery of patients. The system consists of a virtual 3D environment with a 3D skeleton representing the patient. The physiotherapist can interact with the skeleton to design the desired postures that the patient should practice according to their personal limitations. The system allows physiotherapists to compose a complete and personalized set of exercises. Alternatively, the physiotherapist may also create the postures by means of a motion sensing device using motion- and voice-based interaction. Both options pose research challenges that the authors have addressed to provide the solution presented in this paper.
DO PRIVATE BANKS AFFECT ETHIOPIA'S ECONOMIC GROWTH?

Introduction: Major activities of private sector banks promote changes in a country's economic progress. Many studies have concentrated on the general policy of customer service. As a result, the goal of the study is to look into the impact of private banks on Ethiopia's Gross Domestic Product (GDP) growth.&#x0D; Methods: Time-series data of the National Bank from 2011 to 2020 is studied using a dynamic-factor model that is flexible for multi-variable autoregressive data.&#x0D; Results: The result indicates that mobilization of deposits and domestic investment have a strong positive impact on Gross Domestic Product (GDP), whereas foreign exchange and credit services have a significant negative impact.&#x0D; Conclusion and suggestion: Private banks play an important role in Ethiopia's GDP growth. Therefore, in order to boost economic growth, banks should collect deposits from all over Ethiopia and use them to fund viable investment initiatives.
Result-Set Management for NDP Operations on Smart Storage

Current data-intensive systems suffer from scalability as they transfer massive amounts of data to the host DBMS to process it there. Novel near-data processing (NDP) DBMS architectures and smart storage can provably reduce the impact of raw data movement. However, transferring the result-set of an NDP operation may increase the data movement, and thus, the performance overhead. In this paper, we introduce a set of in-situ NDP result-set management techniques, such as spilling, materialization, and reuse. Our evaluation indicates a performance improvement of 1.13 × to 400 ×.
E-Healthcare Privacy Data Sharing with Fine-Grained Access Control

The E-Healthcare Cloud system has shown that it can improve healthcare quality as well as individual quality of life. Unfortunately, concerns about security and privacy prevent it from being widely adopted and used. Several studies have been carried out in order to protect the privacy of electronic health record (EHR) data. We start with a two-layer encryption scheme. We create first-layer encryption to ensure efficient and fine-grained access control over EHR data, in which we create a highly specialised access policy for each data attribute in the EHR and encrypt them individually with high efficiency. To protect the privacy of role attributes and access policies used in the first-layer encryption, we construct the second-layer encryption systematically. We made a recommendation. User revocation is commonly supported in such schemes, as users' group memberships may change for a variety of reasons. Prior to now, the computational overhead for Auto user revocation. Binary key generation is included for file storage. We proposed enabling file encryption alongside proxy re encryption.
PENGARUH MEDIA BIG BOOK TERHADAP KEMAMPUAN BERBICARA ANAK USIA 5-6 TAHUN DI TK HIJRIAH III PALEMBANG

This research is entitled "The influence of big book media on the speaking ability of children aged 5-6 years at Kindergarten Hijriah III Palembang". This type of research is a quantitative Experimental Design One Group Pre-test Post-test (one class). The research sample used in this study was group B1 in Tk Hijriah III Palembang, totaling 10 children, namely 5 boys and 5 girls. The sampling technique was carried out using Simple Random Sampling or the children were called one by one to the front of the class to retell the story. The data collection method uses observation tests and documentation with data analysis using normality tests and homogeneity tests. The results of the study and discussion of the average pre-test score that did not use treatment was 51, while the typical post-test score utilizing the big book or treatment media was 79. There was an effect when not using the media and after using the big book media. The results obtained by testing the hypothesis using the T-test obtained 16.667 with a significant level of 5% so that it can be 2,262. Because = 16,667 &gt; = 2,262. So the conclusion is that the null hypothesis (Ho) is rejected and the alternative hypothesis (Ha) is accepted, meaning that there is an influence of the media on the speaking ability of children at Hijriah III Kindergarten in Palembang.
When Technology Becomes a Policing Agent: Effects of Raids on Restaurants in Leading Crime Shows on the Youth of Pakistan

Objectives: To explore the effects of raids on restaurants shown in crime/investigation shows of Pakistan on the behaviors of youth.Sample: Respondents were selected from University of the Punjab (PU) and Lahore University of Management Sciences (LUMS).Method: The methodology used by the study is survey and the questionnaire are of structured pattern and comprised of close ended questions endorsing both Nominal and Likert scales.This study has surveyed among 150 students who were living in hostels in their respective universities.Theoretical Framework: Cognitive Dissonance was the theoretical framework for the study which explains about the difference between the beliefs and actions.Findings: The results show that the raids on restaurants shown in different crime shows of Pakistan are disseminating information, but that information is not yielded into the behavioral change as expected from the information.Implication: These programs are widening the gap between action and thoughts of the youth.The epitome of the study is that unveiling restaurants in crime/investigations shows are creating awareness among the students about food items and their hygiene condition, but the awareness is not yielded into the behavioral change by the students.The study suggests that informing the youth is also necessary, but it is the need of the time to pay more attention towards cleanliness of the restaurants environment than just to inform the youth about not to go on those kinds of restaurants for eating.