Reviewerly/exHarmony huggingface dataset:
The relationship between nursing professionalism and nursing intention for patients with emerging infectious diseases of nursing students who had experienced COVID-19 pandemic: the mediating effect of e-Health literacy

Purpose: This study aimed to identify the relationship between nursing professionalism and nursing intention for patients with emerging infectious diseases of nursing students who had experienced coronavirus disease 2019 (COVID-19), with a focus on the mediating effect of e-Health literacy.Methods: The study surveyed 177 nursing students who had experienced COVID-19. The data were collected using self-reported questionnaires. The collected data were analyzed using IBM SPSS statistics 25.0, and the mediating effect was analyzed through the SPSS Process macro model 4.Results: Nursing professionalism (β=.26, p=.002) and e-Health literacy (β=.18, p=.021) were found to be significant predictors of nursing intention for patients with emerging infectious diseases. In addition, e-Health literacy partially mediated the relationship between nursing professionalism and nursing intention for patients with emerging infectious diseases.Conclusion: e-Health literacy was a mediating factor in the relationship between the nursing professionalism and nursing intention of nursing students for patients with emerging infectious diseases. In order to improve nursing intention of nursing students for patients with emerging infectious diseases, it is important to develop an education program that can enhance their e-Health literacy as well as nursing professionalism.
A Case Study on the Educational Effectiveness of Online English Content Using the Storytelling Learning Method: Focusing on Students’ Perceptions and Opinions

This is a case study designed to determine the educational effect of online English content using the Storytelling Learning Method (SLM). The study focused on the course Learning English through Film offered by a cyber university in Seoul. A survey was conducted among 1,024 students from 86 universities who participated in the course. The course was based on the film &lt;i&gt;A Dog’s Way Home&lt;/i&gt; (Smith, 2019) and followed the story of the film for 15 weeks over a semester. At the end of the semester, a survey was carried out to assess the following: 1) satisfaction with the online English learning content and improvement of English skills, 2) the effectiveness of SLM, and 3) students’ perceptions of their English skill improvement. The survey results revealed that 76% of the students found the SLM to be effective, and 92% expressed their interest and active participation in the course. In addition, 80% of the students reported that the online classes were more helpful in learning English, with listening and understanding context identified as the most improved language skills. These findings support the effectiveness of strategically structured course content utilizing SLM in terms of enhancing students’ motivation to learn and their academic achievements.
Implementasi Smart Home pada Platform Apple Homekit dan Google Home dengan Raspberry Pi 4B

This research examines the significant impact of technological advances, especially in the Internet of Things (IoT) paradigm, on various aspects of human life strongly manifested during the In-dustrial Revolution Era 4.0. The main focus of this research is on the application of advanced and innovative IoT concepts in the context of smart homes, integrating popular platforms such as Apple HomeKit and Google Home. The temperature sensor (DHT11) and light sensor (LDR) play a key role as important input elements, enabling the optimization of smart home automation functions. Raspberry Pi 4B was chosen as the main platform, the "brain" of the system, providing reliable computing capabilities. Using four-channel relays, this research specifically aims to increase ef-ficiency and integration in controlling devices in the smart home ecosystem. By emphasizing the concept of optimization, this research proposes a smart solution that is expected to not only provide an integrated and efficient experience for smart home users but also unlock the potential for further development of IoT technology. As a result, the implementation of the solutions proposed in this research is expected to create a smart home that is not only technologically smart but also responsive to the needs and preferences of its occupants, paving the way for further in-novation in the development and application of the Internet of Things in various contexts of human life.
Efficiency analysis of fixed and axis tracking options of photovoltaic systems to be installed in a marina

Electricity consumption is an important cost in businesses operating in the service sector such as marinas. Although the use of solar power for electricity has become widespread in various fields in Türkiye, marinas have yet to fully utilize this technology. The aim of this study is to examine the feasibility of supplying the electricity needs of a marina with a photovoltaic (PV) system. For this purpose, a marina in Muğla (Bodrum) was selected, and monthly/yearly electricity needs were determined. In this study, the PV installed capacity needed to meet the marina's electricity demand was selected. Simulations were performed for three different options using the Photovoltaic Geographical Information System (PVGIS). According to the calculations, a 2012 kW single-axis tracking PV system generated 4,469,618 kWh/year of electricity, which is sufficient to meet the annual electricity demand. It has been determined that the installation cost payback period is 3.91 years for the single-axis tracking PV system. In addition, it was observed that both the dual-axis tracking and single-axis tracking PV systems were more efficient than the fixed options.
HABERTAN: Game Petualangan 3D Dengan Tema Pemilahan Sampah Sebagai Upaya Pendekatan Inovatif Untuk Pengenalan Lingkungan

The increasing awareness of the importance of maintaining forest cleanliness as a primary ecosystem is becoming more urgent, especially in remote areas with limited deep socialization. This research aims to develop an innovative game titled "HABERTAN" focusing on waste sorting in forest areas to raise public awareness of the waste present in the forest. By utilizing a 3D model for visual assets with stages of 2D sketch, 3D modeling, UV Mapping, and Texture Baking. The development of this game is conducted using the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) method. The ADDIE method is used to ensure a systematic game development process, starting from needs analysis to performance evaluation. The goal of this game is to provide players with an interactive experience that not only entertains but also provides a deep understanding of the impact of waste on forest sustainability. The game "HABERTAN (Let's Clean the Forest)" is designed to provide players with a fun and educational learning experience. The results of the development of this game show that "HABERTAN" provides a unique experience for players, with the ability to learn while playing. It is hoped that this game can be an effective tool in raising public awareness of the importance of maintaining forest cleanliness, especially in the context of waste sorting. Through this innovative approach, it is hoped to encourage active participation from the community in preserving forests as extremely valuable natural resources.
Implementasi Chatbot Kesehatan Kucing Melalui Dialogflow dan Telegram untuk Pemberian Informasi Penyakit dan Perawatan

Cats are an integral part of human life, but their health needs are often complicated for their owners. This research proposes and implements a Chatbot system using Natural Language Processing (NLP) through the Dialogflow framework to provide advice on cat care and treatment. This method is intended to help cat owners understand basic care needs and identify symptoms of illness their cat may be exhibiting. Using Dialogflow as the main framework enables intuitive and responsive interactions between chat owners and Chatbots. This system has gone through comprehensive stages of analysis, development and testing to ensure reliability and accuracy in providing cat health care information. This test also includes several real-life cases to validate the Chatbot's ability to provide appropriate treatment advice and solutions for cat health problems. The results of this research show that the application of Chatbots via Dialogflow has great potential in helping cat owners in caring for and dealing with diseases in cats. With the ability to understand natural language and provide accurate information, this Chatbot can be a useful tool to increase cat owners' understanding of proper care and early treatment of possible illnesses in their pets.
Automated Systems and Artificial Intelligence

There are two human rights properties overshadowing academic discourse and policy documents in relation to automated systems and artificial intelligence which are operating in the digital realm. These properties are about the trust in artificial intelligence and automated systems, and secondly, of robustness. The latter appears in two aspects related to law governing the AI solutions and the AI itself. The degree of our trust in physical judges is related to our expectation that they are capable of distrusting the law. And our trust in automated systems and artificial intelligence is weaker because we assume that they completely trust the law. It could be said that we cannot find a better positivist than artificial intelligence. The moment artificial intelligence can independently exercise disavowal and intolerability formulas, that is, articulate a reasoned understanding that a specific legal norm or rule is profoundly unfair, then the non-coherence disappears. However, then we would no longer be dealing with artificial intelligence; perhaps we could term such a decision-maker an artificial brain.
The E-state and Fundamental Rights

There are two fundamentally related perceptions, which are of a religious nature, about the e-state from the perspective of fundamental rights. The first hails e-state positivity by suggesting that public power draws closer to the people because this framework is providing more efficient, transparent and neutral procedures and outcomes. Here fundamental rights would therefore appear to be more safeguarded since e-solutions minimise arbitrariness. The opposite perception suggests there is obscurity and distrust despite the apparent efficiency and neutrality. Four caveats appear in relation to the image of e-state through the non-coherence theory. These are: the dominance of human rights rhetoric, questionability of the success of the e-state, the expectation of horizontality and the potential road to a police state.
Focus Realization in Heritage Spanish

We shed light on the question of how narrow information (F) and contrastive focus (CF) are intonationally and syntactically realized by heritage speakers (HSs) of Peninsular Spanish (PS) who have German as their second L1, and compare their data to those of monolingual speakers (MSs) of PS. Results from a production experiment show clear differences between the groups with respect to preferred syntactic strategies and, consequently, the intonational realization of focal pitch accents. The preferred strategy of HSs is stress shift, followed by p-movement and simple clefts, for both focus types. Conversely, MSs mostly use different strategies for each focus type; that is, pseudo-clefts and p-movement for F, and simple clefts and focus fronting for CF. Interestingly, stress shift is not a relevant option. The attested differences support the view that the interface between discourse on one hand, and syntax and phonology on the other, is challenging for bilingual speakers (Sorace, 2011).
Exploring the Security Vulnerability in Frequency-Hiding Order-Preserving Encryption

Frequency-hiding order-preserving encryption (FH-OPE) has emerged as an important tool in data security, particularly in cloud computing, because of its unique ability to preserve the order of plaintexts in their corresponding ciphertexts and enable efficient range queries on encrypted data. Despite its strong security model, indistinguishability under frequency analyzing ordered chosen plaintext attack (IND-FA-OCPA), our research identifies a vulnerability in its design, particularly the impact of range queries. In our research, we quantify the frequency of data exposure resulting from these range queries and present potential inference attacks on the FH-OPE scheme. Our findings are substantiated through experiments on real-world datasets, with the goal of measuring the frequency of data exposure resulting from range queries on FH-OPE encrypted databases. These results quantify the level of risk in practical applications of FH-OPE and reveal the potential for additional inference attacks and the urgency of addressing these threats. Consequently, our research highlights the need for a more comprehensive security model that considers the potential risks associated with range queries and underscores the importance of developing new range-query methods that prevent exposing these vulnerabilities.
Prediksi Harga Minyak Dunia Dengan Fuzzy Time Series

The government uses economic growth as a metric to measure prosperity and the effectiveness of economic development. However, oil price fluctuations can increase inflation through increasing fuel prices and have an impact on the world economy, including Indonesia. This research will apply a fuzzy time series using the Cheng method to predict world oil prices. The results of this research show that the MAPE value for forecasting world oil prices using the Fuzzy Time Series Cheng method is 2%, which means the forecasting model has very good value.
How are texts analyzed in blockchain research? A systematic literature review

Abstract This paper provides a systematic literature review of text analysis methodologies used in blockchain-related research to comprehend and synthesize existing studies across disciplines and define future research directions. We summarize the research scope, text data, and methodologies of 124 papers and identify the two most common combinations of these dimensions: (1) papers that focus on specific cryptocurrencies tend to apply sentiment analysis to instant user-generated content or news articles to discover the correlations between public opinion and market behavior, and (2) studies that examine the broad concept of blockchain with text data from documents published by companies tend to apply topic modeling techniques to explore classifications and trends in blockchain development. We discover five major research topics in the academic literature: relationship discovery, cryptocurrency performance prediction, classification and trend, crime and regulation, and perception of blockchain. Based on these findings, we highlight three potential research directions for researchers to select topics and implement suitable methodologies for text analysis.
Exploring Bitcoin dynamics against the backdrop of COVID-19: an investigation of major global events

Abstract COVID-19 has significantly influenced global financial markets, including Bitcoin. Recent studies have focused on investigating the first wave of the COVID-19 outbreak and accounting for market changes, which were mostly due to the pandemic. This research not only analyzes the contagion effects of COVID-19 but also considers aftermath events beyond the first pandemic wave to examine spillovers of Bitcoin. The study employs Diebold and Yilmaz’s method to explore the static and dynamic spillovers of the selected variables and identifies several major global events, including crypto-specific affairs, macroeconomic policies, and geopolitical conflicts, to explain the new market dynamics of Bitcoin using network analysis. The findings identify a few high-contagion periods related to Bitcoin. The paper also found that Bitcoin is more likely to produce extreme returns and is more connected to other markets. Contagion effects “from” and “to” other markets are asymmetrical in terms of arrival time and market response. Bitcoin is more likely to be affected by other markets in extreme situations and receives spillovers from them sooner than it transmits spillovers to others. In the context of various global events, impacts arising from developed countries are stronger. China still has some impact on cryptocurrency markets, but they are waning. Bitcoin is thus not a safe haven from the shocks of global events, but can sometimes work as a hedge or diversifier. The results offer alternative explanations for Bitcoin’s different market dynamics and enrich our understanding of Bitcoin’s safe haven, hedge, and diversifier properties within a diversified portfolio.
The Implementation of Technique Used by Teacher to Develop Students’ Speaking Skill: A Case Study at Muhammadiyah University of Surakarta in 2023/2024

Techniques are a way to assist students to explore and increase their ability. This study aimed to describe (1) the classroom techniques used by teacher and their purposes, (2) the teacher’s role in implementing the techniques, and (3) the elements of speaking improved in implementing the techniques. This research used a case study qualitative method. The subjects are English teachers instructing third-semester speaking classes in the English Education Department at Muhammadiyah University of Surakarta in 2023/2024. The researcher used observation, interview, and documentation to collect the data. The result of the research showed that teachers used some techniques in teaching speaking, such as conversation drill, debate, role play, and presentation. Debate and conversation drill is mostly used by the English teachers in teaching and learning speaking. Teachers’ role in implementing technique in teaching speaking are as controller and tutor. Elements that need to be improved in implementing techniques in teaching speaking, namely fluency and accuracy, then grammar, vocabulary, and pronunciation. The implementation of conversation drill and debate technique as a teaching technique developed the students’ speaking performance in terms of accuracy dealing with acceptable pronunciation, correct grammar, and appropriate word choice as well as making possible chance to students to work cooperatively, brainstorm ideas, develop vocabulary, and read to support an opinion. The researcher suggests that teachers use various techniques as it encourages students in speaking
MFLion‐DMN: Mayfly Lion‐optimized deep maxout network for prediction of software development effort

Abstract The precise evaluation of predicting software development effort is a serious process in software engineering. The underestimates require more time, which seems to be the negotiation of complete efficient design and complete software testing. Thus, this paper devises a novel model for inspecting the effort taken for the design of software. The Mayfly Lion Optimization (MFLion) algorithm is devised, which ensembles the Mayfly Algorithm (MA) with the Lion Optimization Algorithm (LOA) for precise estimation. The deep maxout network (DMN) is adapted wherein the different weights are produced out of which the most suitable is infused considering the MFLion during model training. The optimal features are selected using recursive feature elimination (RFE) wherein the best features are selected and the remaining irrelevant features are eliminated from the list. The proposed MFLion obtained better performance with the smallest mean magnitude of relative error (MMRE) of 5.909 and the smallest root mean square error (RMSE) of 75.505, respectively. Each technique is produced using a separate database generated using the Promise software engineering repository. The outcomes produced from the assessment of the accuracies of models suggested that the MFLion‐DMN is a substitute to forecast software effort, which is extensively devised in engineering platforms.
Advanced systems and technologies for the enhancement of user experience in cultural spaces: an overview

Abstract Human–computer interaction, Artificial Intelligence, and the multilingualism of digital culture open up unexpected scenarios in the contemporary design of cultural spaces with the creation of artifacts in which the analogic and digital dimensions come together to enhance the experience. Sensors and devices track user movement in the real world and translate the inputs into commands through hand gestures, speech recognition, head movements, tangible interfaces, or a combination of these elements. Through theorical models, concepts and tools, the paper reports the evolution of “User Experience” applied to personalized enjoyment and use of cultural places. The functional-performance survey of tools and technologies for perception, narrative and augmented interaction revealed models that highlight the diversity and richness of tangible and intangible cultural heritage through new forms of interaction and knowledge transfer. In this direction, new technological tools make it possible to detect, track and evaluate the personalized user experience by processing or producing large amounts of data. Therefore, on one hand the paper explores the limitations dictated by data management and user privacy in using such systems and, on the other, it prefigures new scenarios for amplifying and personalizing the user experience.
Quantifying coherence via the generalized Wigner–Yanase–Dyson skew information

Quantum coherence is an important feature that distinguishes quantum mechanics from classical physics. In this paper, we study the coherence of a quantum state with respect to a quantum channel, and introduce a coherence measure in terms of the generalized Wigner–Yanase–Dyson skew information. The basic properties and operational significance of the measure are expounded in detail, which shows that it is indeed a veritable quantity and satisfies many desirable conditions intuitively required for the coherence measures. We illustrate the significance of characterizing channels from the coherence perspective through some examples. Finally, we consider the average coherence of a state based on the generalized Wigner–Yanase–Dyson skew information with respect to any complete mutually unbiased bases in prime power dimensional systems, as well as with respect to all orthonormal bases, and show that these two averages are equivalent since they both can be seen as the coherence of the quantum state with respect to the depolarizing quantum channel.
<scp>WD‐XRF</scp> technique for speciation of iron and quantification of its oxidation states in geological samples using L‐series of iron X‐ray spectrum

Abstract Wavelength dispersive X‐ray fluorescence (WD‐XRF) spectrometry is a fast and widely used technique for elemental analysis of geological samples from Na to U. However, it has seldom been applied for quantitative determination of oxidation states of elements in complex matrices. In this study, we present a method to determine the oxidation states of iron in geological samples by WD‐XRF. We used the FeLα 1,2 fluorescence line as a tool for iron speciation and Fe(II)/Fe total ratio determination. We found that the normalized intensity (peak height) of FeLα 1,2 fluorescence line was linearly correlated with the spin multiplicity (2S + 1) of ferrous and ferric content in the samples. To account for the matrix effects of chemical environment (matrix and chemical bonding) on FeLα 1,2 fluorescence line, we introduced a chemical index factor (μ) that enabled accurate determination of Fe(II)/Fe total ratio in different types of geological samples. The method was validated using international certified reference materials and their mixtures and obtained promising results, with only 6 out of 55 determinations showing relative error more than 5% of the certified values.