Reviewerly/exHarmony huggingface dataset:
Cuidados de enfermagem a pacientes com feridas oncológicas

Objective: To analyze the relevance of nursing care in the care of cancer wounds in patients under palliative care. Method: This is an integrative literature review carried out in October 2020, with articles published in the LILACS, MEDLINE and SCIELO databases in Portuguese, English and Spanish using the descriptors: Oncology Nursing; Cutaneous Ulcer; Wounds and Injuries; Oncology; Nursing Evaluation; Nursing care; Neoplastic Invasiveness; Neoplasms and Therapeutics. Results: The results obtained according to the analysis of the published articles indicate that among the 11 studies eligible for interpretation, only 10 fit for the research, in view of the agreement with the theme and objective of the study. Nursing care with oncological wounds minimizes signs and symptoms, promoting quality of life, since these wounds have a negative impact on the patient's self-image and self-acceptance in their health status. Social isolation and feelings of sadness, helplessness and humiliation accompany the patient affected by them, mainly due to the discomfort, pain and characteristic odor. Conclusion: The need for professional preparation during monitoring and assistance to these patients is understood, as technical and scientific knowledge through training is crucial. Being the nurse, the professional who deals with hygiene, skin and skin wounds daily, he must pay attention to the characteristics of the wound, assessing it and guiding patients and their families on the necessary care with it.
ANALYSIS ON STUDENTS’ ENGLISH SPEAKING PERFORMANCE AT UNIVERSITY OF MUHAMMADIYAH SUMATERA UTARA

&lt;p&gt;The lack of students’ English-speaking performance seems to&lt;br /&gt;be common problems found in the department of English&lt;br /&gt;education at the University of Muhammadiyah Sumatera&lt;br /&gt;Utara. Those problems involve the lack of fluency and&lt;br /&gt;proficiency in English speaking skills. This study aimed to&lt;br /&gt;analyze the students’ English-speaking performance and the&lt;br /&gt;challenges faced by them. This research applied a descriptive&lt;br /&gt;qualitative design. The data such as the documents,&lt;br /&gt;observation, and interviews were applied. In analyzing the&lt;br /&gt;data concerning the components of data analysis in the&lt;br /&gt;interactive model, it was proposed by Miles and Huberman&lt;br /&gt;(2016). The data were taken questionnaire from 125 EFL of&lt;br /&gt;second-year students were collected, then the researcher also&lt;br /&gt;conducted the individual interviews with lecturers and class&lt;br /&gt;observation. The result showed that the most challenging&lt;br /&gt;factor faced by the students' speaking performance was related&lt;br /&gt;to the students themselves. Speaking errors were frequently&lt;br /&gt;made. The errors dominantly covered into 3 categories namely&lt;br /&gt;misused forms (44.8 %), incorrect omission (33.6%), and&lt;br /&gt;misplaced and confusing words (21.2 %). Concerning the&lt;br /&gt;external factors, the updated teaching strategies should be&lt;br /&gt;applied in terms of reducing the use of the mother tongue by&lt;br /&gt;combining various speaking performances, collaborating with&lt;br /&gt;other lecturers to organize more English programs, and share&lt;br /&gt;the speaking teaching experience.&lt;/p&gt;
FROM THE PREHISTORY OF BIBLIOMETRICS AND SCIENTOMETRICS

A number of studies that nowadays would be called bibliometric and scientometric and that were performed before the very terms «bibliometrics» and «scientometrics» had been coined are considered. It is shown that researchers who performed such studies from the XVIII to the first half of the XX century did not see any difference between the assessment of documentary flows in order to obtain the characteristics of science and in order to improve the document availability in libraries, and often they carried out both types of assessment simultaneously within the same study. This historical view on the problem of «metricses» indirectly confirms the methodological fruitfulness of not searching for differences between various «metricses», but of getting them together around bibliometrics, and of searching for fundamentally common features of «metricses».
Bitcoin breaks above $20,000 for first time

Bitcoin smashed through $20,000 for the first time on Wednesday, its highest ever.The cryptocurrency
Dimension-Preserving Reductions Between SVP and CVP in Different $p$-Norms

$ \newcommand{\SVP}{\textsf{SVP}} \newcommand{\CVP}{\textsf{CVP}} \newcommand{\eps}{\varepsilon} $We show a number of reductions between the Shortest Vector Problem and the Closest Vector Problem over lattices in different $\ell_p$ norms ($\SVP_p$ and $\CVP_p$ respectively). Specifically, we present the following $2^{\eps m}$-time reductions for $1 \leq p \leq q \leq \infty$, which all increase the rank $n$ and dimension $m$ of the input lattice by at most one: $\bullet$ a reduction from $\widetilde{O}(1/\eps^{1/p})\gamma$-approximate $\SVP_q$ to $\gamma$-approximate $\SVP_p$; $\bullet$ a reduction from $\widetilde{O}(1/\eps^{1/p}) \gamma$-approximate $\CVP_p$ to $\gamma$-approximate $\CVP_q$; and $\bullet$ a reduction from $\widetilde{O}(1/\eps^{1+1/p})$-$\CVP_q$ to $(1+\eps)$-unique $\SVP_p$ (which in turn trivially reduces to $(1+\eps)$-approximate $\SVP_p$). The last reduction is interesting even in the case $p = q$. In particular, this special case subsumes much prior work adapting $2^{O(m)}$-time $\SVP_p$ algorithms to solve $O(1)$-approximate $\CVP_p$. In the (important) special case when $p = q$, $1 \leq p \leq 2$, and the $\SVP_p$ oracle is exact, we show a stronger reduction, from $O(1/\eps^{1/p})\text{-}\CVP_p$ to (exact) $\SVP_p$ in $2^{\eps m}$ time. For example, taking $\eps = \log m/m$ and $p = 2$ gives a slight improvement over Kannan's celebrated polynomial-time reduction from $\sqrt{m}\text{-}\CVP_2$ to $\SVP_2$. We also note that the last two reductions can be combined to give a reduction from approximate-$\CVP_p$ to $\SVP_q$ for any $p$ and $q$, regardless of whether $p \leq q$ or $p > q$. Our techniques combine those from the recent breakthrough work of Eisenbrand and Venzin (which showed how to adapt the current fastest known algorithm for these problems in the $\ell_2$ norm to all $\ell_p$ norms) together with sparsification-based techniques.
Quantum Chaos-Based Encryption Technique for Transmission of Medical Images

With the fast advancement of networked devices and growth in usage of digital data transmission, hawk-eye attention is needed to provide the secured transmission for various vital data such as medical images and digital signatures. Even though many encryption algorithms were proposed, achieving high-security transmission remains in the darker side of the research because of its low sensitivity and less complexity. Recently, usage of quantum chaos has gained more insight in the encryption world due to its complex nature. A new encryption scheme quantum chaos-based network-centric encryption for data transmission (Q-CNEST) is proposed to integrate with the network characteristics as its initial conditions for generation of high complex encrypted data. As a first step, cipher keys are generated by the quantum chaotic logistic maps using the random network parameters. Following that, diffusion and permutation of each pixel with the high randomness cipher keys have been performed. Finally, sensitivity analysis is done. Simulation has been implemented in the Qiskit packages, and its results have proven that the proposed algorithm has good randomness which will be more suitable for the prevention of conventional attacks over the medical information. Moreover, the proposed encryption algorithms can provide more limelight for the secure transmission of medical image transmissions.
Machine Learning Based Neighbor Path Selection Model in a Communication Network

Neighbor path selection is to pre-select alternate routes in case geographically correlated failures occur simultaneously on the communication network. Conventional heuristic-based algorithms no longer improve solutions because they cannot sufficiently utilize historical failure information. We present a novel solution model for neighbor path selection by using machine learning technique. Our proposed machine learning neighbor path selection (ML-NPS) model is composed of five modules- random graph generation, data set creation, machine learning modeling, neighbor path prediction, and path information acquisition. It is implemented by Python with Keras on Tensorflow and executed on the tiny computer, Raspberry PI 4B. Performance evaluations via numerical simulation show that the neighbor path communication success probability of our model is better than that of the conventional heuristic by 26% on the average.
Implementasi Arsitektur Web Server Cluster Menggunakan Single Board Computer untuk Menunjang Kebutuhan High Availability System

Untuk mewujudkan ketahanan pangan, diperlukan mekanisme pengumpulan data secara real-time dari produsen bahan pangan, pendisitribusi bahan pangan sampai pengolah bahan pangan. Namun tidak semua organisasi yang berkecimpung dalam distribusi pangan memiliki infrastruktur sistem informasi yang cukup baik. Untuk mengatasi kendala infrastruktur, penelitian ini mengusulkan untuk membangun arsitektur web server cluster yang dapat menunjang kebutuhan high availability system menggunakan single board computer. Komponen arsitektur terdiri dari dua tier yaitu: frontend dan backend. Untuk menjamin kehandalan sistem, arsitektur yang diusulkan didukung dengan komponen load balancing, mekanisme failover dan replikasi database. Sistem telah diuji berasarkan kebutuhan fungsional dan kebutuhan non-fungsional yang sudah didefinisikan sesuai kebutuhan organisasi. Dari hasil pengujian, tingkat availabilitas yang dihasilkan sebesar 95.83%. AbstractTo achieve food security, a real-time data collection mechanism is needed from food producers, food distribution to food processing. However, not all organizations involved in food distribution have adequate information system infrastructure. To overcome infrastructure constraints, this study proposes to build a web server cluster architecture that can support the needs of a high availability system using a single board computer. The architectural component consists of two tiers, namely: frontend and backend. To ensure system reliability, the proposed architecture is supported by load balancing components, failover mechanisms, and database replication. The system has been tested based on functional requirements and non-functional requirements that have been defined according to organizational requirements. From the test results, the resulting availability level is 95.83%.
Conservatorium Wind Orchestra: Second Winds

Research background: Collaboration between wind orchestra, film and electronic sonic art.Research contribution: This project engaged existing knowledge in a new and creative way so at generate new concepts, methodologies and understandings, by taking existing source material (Alex Shapiro's 'Immersion Symphony') and adding an entire new layer of electronic sounds in live performance. The project also added visual element of film footage not originally intended for this work. The performance was quasi-improvisatory, so different each time it was performed.Research significance: This was a public performance at QCGU, documented via archival video. It was important in supporting the inclusion of electronic sonic art as a collaborative option for modern performance practice. An image of the performance was used for the cover of 2021 GU Research and Innovation Plan 2021-2025:https://www.griffith.edu.au/__data/assets/pdf_file/0023/1213961/Research-and-Innovation-Plan-2021-25.pdf
DEVELOPING DIFFERENTIATED ELECTRONIC SUPPLEMENTARY READING EXERCISE FOR THE SLOW LEARNERS OF SEVENTH YEAR STUDENTS AT SMP N 2 SINGARAJA

Self-regulated learning (SRL) becomes one of the crucial skill in nowadays era. The ability to regulate their own learning, helps students to achieve better. In order to prove that, this study aimed at investigate the correlation between SRL strategies and the student’s English achievement by using expost facto research design. 152 students were involved to be the sample of this study and asked to fill Motivated Strategies for Learning Questionnaire (MSLQ) developed by Pintrich (1991) as the data of their SRL strategies. For the achievement, the record keeping document were used. As the result, it was found that there is a significant correlation between SRL strategies and the student’s English achievement.
China in the Global Market of Higher Education Services

The article intends to refer to China as to an outstanding example of dynamic development. The Chinese Republic is now perceived almost exclusively as a country that has been highly successful in implementing market reforms. This helps to define the reasons and essence of the successful measures taken in China, which have provided powerful dynamic processes, including in the field of higher education. The paper proceeds to the description of quite competitive global markets for educational services, where the service providers have found ways to retain each potential client through practicing individual approach, when it is necessary to attract and engage prospective students to the bachelor’s, master’s and postgraduate programs. The main objectives of any university are described in the article, They include not only informing public about the offered educational programs and training opportunities, but also promoting their educational services in the domestic and international markets.
Security Properties as Nested Causal Statements

Thinking in terms of causality helps us structure how different parts of a system depend on each other, and how interventions on one part of a system may result in changes to other parts. Therefore, formal models of causality are an attractive tool for reasoning about security, which concerns itself with safeguarding properties of a system against interventions that may be malicious. As we show, many security properties are naturally expressed as nested causal statements: not only do we consider what caused a particular undesirable effect, but we also consider what caused this causal relationship itself to hold. We present a natural way to extend the Halpern-Pearl (HP) framework for causality to capture such nested causal statements. This extension adds expressivity, enabling the HP framework to distinguish between causal scenarios that it could not previously naturally tell apart. We moreover revisit some design decisions of the HP framework that were made with non-nested causal statements in mind, such as the choice to treat specific values of causal variables as opposed to the variables themselves as causes, and may no longer be appropriate for nested ones.
Systematic DCG Evaluations of Search Algorithm Components

Many of the search algorithms used in LexisNexis applications are composed of individual components that each contribute to the relevance scores assigned to the members of result sets. In Lexis Advance, there are several such components called Levers, which can be enabled or disabled via query plans to alter the behavior of the search engine. Thirteen Levers are currently enabled in the Production search engine. These Levers were largely implemented and deployed before the current era of search accuracy testing using the STF tool. To determine how much each Lever individually contributes to the overall accuracy of the search engine, a series of experiments were conducted in STF in which the results of turning off each lever were compared with the system as it is configured now. From these experiments, we were able to determine which Levers had the most impact (whether positive or negative) and thus we able to target future efforts in improving the overall search algorithm. One of the major outcomes of this effort was obtaining the query-document pairs that needed to be rated by human testers in order to improve the coverage of tests. An overview of the testing apparatus is provided so that other organizations within the RELX Group may conduct similar assessments.
Pengaruh Kerjasama antara Orang Tua dengan Guru dan Keaktifan Belajar terhadap Keberhasilan Belajar Siswa Kelas atas di SD Negeri Kleco 1 Surakarta

This study aims to find out: 1) cooperation between parents and teachers on the success of learning. 2) active learning towards learning success. 3) collaboration between parents and teachers and learning activeness towards the successfullearning of upper-class students in Kleco 1 Surakarta Elementary School. This research includes quantitative research with survey research design. Data collectionis done through questionnaires and documentation. The population was 128 students and their parents and 56 samples were taken using the proportionate stratified random sampling technique. Data were analyzed using simple linear regression analysis and multiple regression. Based on data analysis, there is an effect of 40.53% with a significance level of 5% cooperation between parents and teachers onthe success of learning, there is an effect of 34.72% with a significance level of 5% learning activeness towards learning success and there are joint influences at 42.1%with a significance level of 5% cooperation between parents and teachers and active learning together towards learning success. The results showed that there was a positive and significant influence of collaboration between parents and teachers on the success of learning, there was a positive and significant effect of learning activeness on learning success, there was a positive and significant influencebetween parent cooperation with teachers and learning activeness towards the success of classroom learning at SD Kleco 1 Surakarta.
The effective use of media as being an analytical linguistic phenomenon with the case of COVID 19: A literature review

Available social media archives publicly are seen to facilitate further studies regarding the social sciences as well as provide corpora to test and then train a wide range of machine learning as well as some methods of natural language processing. In regard to the recent COVID-19 outbreak, online platforms reflecting public opinions and perceptions associated COVID 19 and the societal impact such pandemic has. Indeed, the understanding of such discourse, its evolutions, and inter-dependencies with the events of the real world or misinformation can foster further valuable insights. Accordingly, the main objective of this study is to review the literature that investigated the case of COVID 19 as being a discourse to be analyzed using linguistic studies. As COVID-19 is seen to be, on social media, as one of the most topics that has been widely talked about; it is then significant to investigate such social issue and see how people react. This study concludes that COVID 19 as being a discourse in social media has received researchers’ attention in many regards.However, the idea of studying as well as analyzinglinguistically any social platform e.g., Twitter, Facebook, News Headlinescan add more value. More precisely, this is true in Arab context as the nature of political language used has been shifted completely and differently after Arab Spring and more specifically in areas that face challenges including Jordan, Saudi Arabia, Iraq, Syria and many of other Arab countries.In fact, this review of literature has the possibility to help researchers to evaluate the current presence of the nature of the discourse used in political, social, and language research fields and hence, recommends further research directions.
New Deep Neural Networks for Unsupervised Feature Learning on Graph Data

Graph data are ubiquitous in the real world, such as social networks, biological networks. To analyze graph data, a fundamental task is to learn node features to benefit downstream tasks, such as node classification, community detection. Inspired by the powerful feature learning capability of deep neural networks on various tasks, it is important and necessary to explore deep neural networks for feature learning on graphs. Different from the regular image and sequence data, graph data encode the complicated relational information between different nodes, which challenges the classical deep neural networks. Moreover, in real-world applications, the label of nodes in graph data is usually not available, which makes the feature learning on graphs more difficult. To address these challenging issues, this thesis is focusing on designing new deep neural networks to effectively explore the relational information for unsupervised feature learning on graph data. First, to address the sparseness issue of the relational information, I propose a new proximity generative adversarial network which can discover the underlying relational information for learning better node representations. Meanwhile, a new self-paced network embedding method is designed to address the unbalance issue of the relational information when learning node representations. Additionally, to deal with rich attributes associated to nodes, I develop a new deep neural network to capture various relational information in both topological structure and node attributes for enhancing network embedding. Furthermore, to preserve the relational information in the hidden layers of deep neural networks, I develop a novel graph convolutional neural network (GCN) based on conditional random fields, which is the first algorithm applying this kind of graphical models to graph neural networks in an unsupervised manner.
The nature of development of the education system during the transformation of Indian and Pakistani society

This article discusses the education systems of India and Pakistan to show that education is a resource that is readily available to some but not to others. The evolution of formal education in India and Pakistan has been strongly influenced by colonial history. Access to education is also strongly influenced by social differences such as religion, caste and gender. The article provides examples of the most significant educational reforms in India and Pakistan. It also explores issues that remain unresolved, such as learning outcomes. The Indian government ultimately recognized education as a fundamental right for a free person in today’s world through the Right to Education Act. India and Pakistan have made significant progress in education and literacy through education development measures. Education is the foundation of the political, social and economic development of any country. India and Pakistan have faced difficult education challenges since their founding as developing countries, so the education system could not be implemented according to the preferences of the nation. This situation was caused by various factors. Experiments to overcome the difficulties inherent in India and Pakistan, which previously lagged significantly in their socio-economic development, were in colonial dependence and experienced serious contradictions in the development of society, are of particular interest in the scientific community. The main purpose of this research work is to compare the problems of the education system in India and Pakistan, based on a critical examination of the available literature, the need and importance of education, we will try to show recommendations for solving the problems of the education system of these two countries. Key words: India, Pakistan, education system, educational problems.
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