Reviewerly/exHarmony huggingface dataset:
Role of nursing in patients receiving chemotherapy

Introduction: Treatment with chemotherapy is the most widely used in almost all types of neoplasms, however, the side effects that it triggers affect the patient's style and quality of life, for this reason the nursing staff must know what their intervention should be with these patients. Objective: To analyze the role played by the nursing staff in patients receiving chemotherapy. Methodology: A study was carried out with a qualitative, descriptive approach, non-experimental design, the databases used included search engines such as Scopus, PubMed, eJournals, Google Scholar and Trip Database, Scielo, Ocronos). A total of 27 articles are included. Results: Nursing care for patients undergoing cytostatic therapy must be comprehensive from a holistic approach. In which it allows to cope with activities that are of the utmost importance for the patient such as reducing the risk of phlebitis and extravasation, controlling nausea and vomiting, informing about side effects. In this way it provides physical, emotional, psychological, and practical support. Conclusion: The nursing role is one of the most essential pillars when providing the care required by cancer patients, allowing maintaining the integrity of the skin, achieving optimal nutritional status, attending to the emotional spheres of the patient, reducing the degree of duration of diarrhoea, correct medication administration and effective communication.
Autonomous Control Method for Object Grasping of Logistics Sorting Manipulator Considering Changes in Lighting Environment

The autonomous grasping operation is the key to the intelligent logistics sorting manipulators. Since the current logistics sorting manipulators mostly use visual sensors to identify objects, they are extremely vulnerable to the changes in the lighting environment. Therefore, the research considers the influence of complex lighting environment on the autonomous grasping of logistics sorting manipulators. Furthermore, it verifies the effectiveness of SAC-AE-ICM algorithm through simulations and experiments. The experimental results show that SAC-AE-ICM algorithm can quickly achieve convergence in many experiments and can obtain global optimization. In the process of automatic capture, the success rate of SAC-AE-ICM algorithm can reach 90%, which is 25% higher than that of the method without ICM and has better convergence. The success rate was as high as 77% for unknown or irregular targets. In practical experiments, SAC-AE-ICM can effectively capture under good lighting conditions. However, under low light conditions, the probability of capturing unknown targets is about 72.5%. Overall, the success rates for single-object and multi-object capture are 88% and 85%, respectively.
Towards Evolutionary Control Laws for Viability Problems

The mathematical theory of viability, developed to formalize problems related to natural and social phenomena, investigates the evolution of dynamical systems under constraints. A main objective of this theory is to design control laws to keep systems inside viable domains. Control laws are traditionally defined as rules, based on the current position in the state space with respect to the boundaries of the viability kernel. However, finding these boundaries is a computationally expensive procedure, feasible only for trivial systems. We propose an approach based on Genetic Programming (GP) to discover control laws for viability problems in analytic form. Such laws could keep a system viable without the need of computing its viability kernel, facilitate communication with stakeholders, and improve explainability. A candidate set of control rules is encoded as GP trees describing equations. Evaluation is noisy, due to stochastic sampling: initial conditions are randomly drawn from the state space of the problem, and for each, a system of differential equations describing the system is solved, creating a trajectory. Candidate control laws are rewarded for keeping viable as many trajectories as possible, for as long as possible. The proposed approach is evaluated on established benchmarks for viability and delivers promising results.
Suggestions for Improvement in the National History Curriculum-IB as a reference, not as an Alternative-

This study aims to examine a content selecting and organizing method of IB history to use it as a reference for improving the national history curriculum. The introduction of IB into public education incurs opportunity costs such as enormous expenses, unequal distribution of educational budgets and human resources, imbalances in educational opportunities, and educational excellence on the premise of discrimination. To solve this problem, educational administrators insist on developing and distributing the 'Korean Baccalaureate'. However, the Korean Baccalaureate is unsubstantial, and neither the DLDP discussed in that way nor the dual system of the national curriculum and DLDP do not solve this problem. Therefore, rather than introducing IB into our public education, it is much more useful to study IB as a reference to improve our curriculum. For this, I examined the selection and organizing of the contents of IBDP history. To apply this to the national history curriculum, three points must be preceded. First, the content sequence should be structured to learn specific themes or facts after learning the chronicle. Second, when organizing contents, it should be allowed to selectively structure the contents. Third, enough time should be given to learn a subject. But IBDP's content selecting and organizing method have both strengths and weaknesses, detailed follow-up studies should follow. On the other hand, it is necessary to consider the development of systematic and practical teacher training programs and the training of scorers to improve teachers' professionalism. To improve classes, in addition to developing teachers' abilities, environment conditions and the paradigm of curriculum construction must be changed together.
Dietary Practices, Physical Activity, and Sleep Habits in Adults during the COVID-19

© 2023. Brazilian Sleep Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
A Stereo Vision-Based Flexible Deflection Measurement System

This paper aims at measuring deflection of mainly beam structures in a non-contact, installation-free and marker-less way with the aid of stereo vision, edge detecting, projection transformation, spline interpolation among other data processing methods. A measurement scheme covering the hardware system design and data analyzing is proposed. Things relevant to stereo vision mainly convert a position in image to a real world position. The edge detection is used to recognize features in images that are essential for measuring deflection. The projection to a certain plane is a reasonable design due to the structure of the targeted structures. And spline interpolation compensates for the loss of obtaining the coordinates of discrete points of the target object. Then an experiment is carried out. And the result proves the feasibility of the proposed method.
Closing the Loop for Software Remodularisation - REARRANGE: An Effort Estimation Approach for Software Clustering-based Remodularisation

Software remodularisation through clustering is a common practice to improve internal software quality. How-ever, the true benefit of software clustering is only realized if developers follow through with the recommended refactoring suggestions, which can be complex and time-consuming. Simply producing clustering results is not enough to realize the benefits of remodularisation. For the recommended refactoring operations to have an impact, developers must follow through with them. However, this is often a difficult task due to certain refactoring operations' complexity and time-consuming nature.
Patchmatch: A Tool for Locating Patches of Open Source Project Vulnerabilities

With the rapid development of open source projects, the continuous emergence of vulnerabilities in the project brings great challenges to the security of the project. Security patches are one of the best ways to deal with vulnerabilities, but are not well applied currently. Although there are sites like CVE/NVD that provide information about vulnerabilities, many of the vulnerabilities disclosed by CVE/NVD are not accompanied by security patches. This makes it difficult for developers to apply patches. In the present study, a sorting method based on extracting multidimensional features from auxiliary information in CVE/NVD was proposed. And we made a further step, we proposed VCMATCH, a model for mining semantic information in vulnerability description and code commit messages, which has good recall rate and applicability across projects. On this basis, we established Patchmatch, a tool for helping developers to quickly locate patches. Given a vulnerability, Patchmatch can forecast the implicit patches in the code repository's commits. Patchmatch also has a visual webpage for information statistics and a display web page to help developers manage all kinds of information in the code repository. A demo video of Patch-match is at https://www.youtube.com/watchvnOBSMFtZV8A. Patchmatch is in https://github.com/Sklud1456/patchmatch
Empirical Evaluation of Self-Sovereign Identity Technology

Self-sovereign identity (SSI) enables the creation of user-centric applications where the user has complete control over his data. This research evaluates the performance of SSI-based applications. This work proposed an architecture based on the Hyperledger Indy and Hyperledger Aries frameworks, deployed it in a cloud environment, and executed its empirical evaluation. The results indicate that the bottleneck is the CPU; a simple setup can support up to 80 concurrent users without relevant errors and 120 simultaneous users before system degradation. Finally, we discuss the system bottlenecks and possible optimization techniques.
Analyzing Africa's Economic Challenges: Assessing the Suitability of Cryptocurrency as a Solution through Occam's Razor Test

The African continent faces a myriad of economic challenges, including limited access to financial services, currency instability, and barriers to cross-border trade. Cryptocurrencies, with their innovative features and decentralised nature, have emerged as a potential solution to these problems. However, their applicability and effectiveness in the African context need to be scrutinized through the lens of Occam's razor. This article delves into the exploration of the potential of cryptocurrencies in addressing African economic challenges by applying the principle of Occam's razor. Occam's razor, a fundamental tenet of modern science, advocates for simplicity and economy of assumptions in problem-solving. By analysing the complex landscape of African economies, marked by diverse challenges and opportunities, this article aims to uncover the role of cryptocurrencies in addressing these issues.
Online Peer-To-Peer Teaching Practice as a Tool to Advance Professional Competence in Distant Learning Format

The article describes peer-to-peer online practice as a new format of online teaching. The aim of the research is to develop this concept to define its linguistic and methodology value for contemporary educational environment and to identify additional professional skills, enabled through peer-to-peer online practice. Methodology basis of the research includes works on cooperative learning, e-learning, linguodidactics, as well as academic papers on digital technologies integration with methods used to teach Russian as a foreign language. We also rely on recent developments in e-learning methodology, online resources and tools for teachers. Identifying, describing and implementing a new type of teaching practice links independent learning and authentic interaction using a foreign language to promote professional satisfaction among future educators, working in cross-cultural information environment. Individualized teaching technology relying on online resources justifies the theoretical relevance of our research. Peer-to-peer online practice is teacher–student interaction, allowing to adapt knowledge acquisition to the student’s individual psychology and particular practical needs, while maintaining standard methodology of teaching. This type of interaction (peer-to-peer) hasn’t been described in detail among contemporary methods of teaching Russian as a foreign language, especially as a tool to train future specialists.
Research on Unsupervised Domain Adaptation System for Machine Translation

With the intensive research on neural networks and deep learning, neural machine translation proposed in recent years has greatly improved translation quality and gradually replaced traditional statistical-based machine translation. Although neural machine translation can achieve very high translation accuracy with translation models trained on resource-rich outer domains, it tends to perform poorly in other inner domains where resources are scarce. Domain adaptation is one approach to enhance its performance, which uses resource-rich domains to help improve the translation quality of machine translation in resource-scarce domains. In this paper, we try to build a parallel corpus in the inner domain by using the parallel corpus in the outer domain to better train the translation model, which is eventually invoked by the system to realize the translation. The experimental results show that the accuracy of the machine translation system is significantly improved when translating data from the inner domain after applying this method.
Corpus Research

This chapter provides an overview of research into L3/Ln that is based on corpus data, and provide the reader with information on publicly available L3/Ln corpora. As both L3/Ln corpus-based research and corpora are quite scarce to date, I devote the better part of this chapter to describing the outcome of a survey I conducted to gather colleagues’ needs and preferences regarding future L3/Ln corpus compilations.
50 Shades of Gray Matter

Intelligence appears to involve many areas across the brain and specific neural circuits are identified based on both structural and functional connectivity. Data support the PFIT model and the idea that intelligence is related to efficient information flow in brain networks.
Video Corpus Moment Retrieval via Deformable Multigranularity Feature Fusion and Adversarial Training

As a new emerging task, video corpus moment retrieval (VCMR) aims to find the video segments relevant to a given natural language query from a large number of untrimmed videos. It mainly includes two subtasks, finding the most relevant video based on the query text (video retrieval), and locating the segment most relevant to a given query in a video (moment localization). At the same time, since videos often contain rich multi-modal information such as audio, text, and images, how to align and interact with the multi-modal information of videos and the text information of natural language queries across modalities is the core issue of this task. This article proposes a Deformable Multigranularity Feature Fusion with Adversarial Training Network (DMFAT), first inputs the subtitle and frame multi-modal information of the video into our Multi-Scale Deformable Attention module and performs multi-granularity feature fusion through Deformable Attention respectively. Then, guided by the query, adaptive weights are generated to fuse the two multi-granularity modality features of the video. Finally, the cross-modal representation of the query and video features is obtained through a bidirectional attention module, and an adversarial contrastive learning objective is introduced to enhance more precise moment localization. Our model is evaluated on two representative video corpus moment retrieval benchmarks: TVR and DiDeMo. Extensive experiments have been conducted to demonstrate that our method outperforms existing work.
An approach to face Detection and Recognition using Viola Jones

The face of human may be a muddled visual dimension model and is therefore extremely difficult to create a computing model for the cognitive basic process. The paper displays a system for perceiving the human face smitten by image-based highlights. The technique proposed is available in 2 phases. In an image using Viola-Jones calculation, the main preparation distinguishes the human face. Using a combination of Principle Component Analysis and Artificial Neural Network, the distinguished face within the image is perceived at the next stage contrasting the execution of the proposed strategy with existing ways. The proposed strategy recognizes greater accuracy in the acknowledgement.
Image Steganography Technique based on Canny Edge Detection and Hamming Code for Medical Data

Image steganography has major role in enhancing the confidentiality of sensitive information related to business information, research data, and health record data and so on. Here the sensitive data considered is Medical data. When the medical image is transmitted through in secure public network, there are chances for medical images to be tampered. To avoid intruders in viewing the sensitive data i.e. Medical information the need of hiding it becomes the foremost criteria. This project mainly aims at enhancing medical integrity. To achieve medical integrity, it is required to hide the medical information within a cover image which is the medical image here. The proposed system aims at providing high security of data integrity by using cryptography along with steganography. The method of digital steganography is involved in the transfer of high imperceptible method that enhances the hiding of Electronic patients record (EPR) into medical images without major modification in the data transfer. It is predominantly required to protect and enhance the security methods ensures that the eavesdroppers will not have any suspicion that medical image or sensitive medical data is hidden in that image
The Impact of Business Strategy on Competitive Advantage and Performance of Small &amp; Medium Enterprises in Jordan

Purpose: This study also examines the impact of business strategies on achieving competitive advantage and improved organizational performance in Jordan-based SMEs. Theoretical framework: Competitions keep an enterprise active and alive. Especially today, when business arenas are comparatively more challenging, demand for organizational excellence. As a result, business strategies are required to be effective and efficient enough to cope with these challenges. Design/methodology/approach: For an empirical investigation, we randomly selected a sample of n= 300 employees currently working in Small and Medium Enterprises in Jordan. We also executed the Structural Equation Modelling technique to examine the extent to which, the data validates proposed relationships between study variables. Findings: Results indicated a strong significant relationship between business strategy and vision &amp; objectives (p≥ .000), core values (p≥ .000), SWOT analysis, and resource allocation plan (p≥ .000). Besides these factors, findings also showed a positive correlation with sustained competitive advantage (p≥ .000), and improved performance (p≥ .000). Research, Practical &amp; Social implications: By keeping in view the importance of business strategy, we suggest that an organization can achieve dynamic competitive advantages, only by effective business strategies that can help an organization to achieve its desired goals. Originality/value: The findings suggest several consequences forth fields of business and Performance of Small &amp; Medium Enterprises. Additionally, the Middle East nations, including the Jordanian business environment, have had numerous challenge that this study aids in resolving. through achieve competitive advantage and improved organizational performance.
Protected Simultaneous Quantum Remote State Preparation Scheme By Weak and Reversal Measurement in Noisy Environments

Abstract In this paper, we discuss a quantum remote state preparation protocol by which two parties, Alice and Candy, prepare a single-qubit and a two-qubit state, respectively, at the site of the receiver Bob. The single-qubit state is known to Alice while the two-qubit state which is a non-maximally entangled Bell state is known to Candy. The three parties are connected through a single entangled state which acts as a quantum channel. We first describe the protocol in the ideal case when the entangled channel under use is in a pure state. After that, we consider the effect of amplitude damping (AD) noise on the quantum channel and describe the protocol executed through the noisy channel. The decrement of the fidelity is shown to occur with the increment in the noise parameter. This is shown by numerical computation in specific examples of the states to be created. Finally, we show that it is possible to maintain the label of fidelity to some extent and hence to decrease the effect of noise by the application of weak and reversal measurements. We also present a scheme for the generation of the five-qubit entangled resource which we require as a quantum channel. The generation scheme is run on the IBMQ platform.
Problems of interpersonal interaction in a students’ group

The article explores the concept of interpersonal interaction as a necessary condition for the development of human life activity. The key problems of interaction of student groups in collaborative work are considered. The study suggests that in collaborative work on a project, each learner gains experience, learns and creates new things, and establishes contacts within the group. The conducted diagnostics indicate a high level of communicative ability of the students, and a high degree of favorable microclimate within a small group. On the basis of the studied material, the authors come to the conclusion that the students will be the most productive in working on a project in collaboration in small groups due to harmonious relations and mutual solidarity.
“DOSPEMKU” CHAT APPLICATION PROTOTYPE WITH THREADING FEATURE USING CORDOVA FRAMEWORK FOR ANDROID-BASED COMPETENCY CONSULTATION

Abstract—In this days, human communication that is efficient and easy is through a system of social media chat application devices. By relying on internet signals, users can carry out meeting activities between one party using social media without the need to use face-to-face meetings, one of which is in communicating consultations on competency issues in the world of education. The reference for this final project is based on the author's thoughts to form a web-based media Halodoc, which is the formulation of the core problem of this final project. With DOSPEMKU, the author can hope to solve some case examples. As for examples of cases such as difficulties coming because there is no time to go (in busyness), determining a time schedule that is not suitable, being inflexible, and so on. DOSPEMKU is a chat application based on the Android operating system, implementing Usecase Diagrams and Activity Diagrams as a designer for functionality requirements that are implemented into DOSPEMKU. The Cordova network is used as an Integrated Development Environment (IDE) platform with html, javascript programming languages ​​and uses the phpMyAdmin database as the database base. Design Implementation uses several methods, ranging from interface design, database, to functionality design in determining what features are contained in DOSPEMKU. The implementation process is tested both in terms of functionality and non-functionality to test whether the application is in accordance with the design stage. So that the process of designing, implementing and testing it was found that the application was made according to and accommodated the conversation according to the discussion.&#x0D; &#x0D;