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Introduction: Paper folding and punched hole tests are used to measure spatial abilities in humans. These abilities are relevant since they are associated with success in STEM (Science, Technology, Engineering, and Mathematics). This study addresses the challenge of teaching spatial reasoning skills using an educational videogame, the Paper Folding Reasoning Game. Methods: The Paper Folding Reasoning Game is an interactive game which presents activities intended to help users train and understand how to fold a paper to get a specific shape (Part I) and the consequence of punching a hole on a folded paper (Part II). This educational videogame can automatically generate paper-folding-and-punched-hole questions with varying degrees of difficulty depending on the number of folds and holes made, thus producing additional levels for training due to its embedded reasoning mechanisms (Part III). Results: This manuscript presents the results of analyzing the gameplay data gathered by the Paper Folding Reasoning Game in its three parts. For Parts I and II, the data provided by 225 anonymous unique players are analyzed. For Part III (Mastermode), the data obtained from 894 gameplays by 311 anonymous unique players are analyzed. In our analysis, we found out a significant difference in performance regarding the players who trained (i.e., played Parts I and II) before playing the Mastermode (Part III) vs. the group of players who did not train. We also found a significant difference in players' performance who used the visual help (i.e., re-watch the animated sequence of paper folds) vs. the group of players who did not use it, confirming the effectiveness of the Paper Folding Reasoning Game to train paper-folding-and-punched-hole reasoning skills. Statistically significant gender differences in performance were also found. [ABSTRACT FROM AUTHOR]

Scientometrics indicators are used to assess scientists, universities and research institutes for scientific policy-making. The aim of this research was to assess the status of top Iranian medical researchers using scientometric indicators. The study was carried out using scientometric methods. The statistical population included the top 500 Iranian researchers in the field of medicine who were ranked in the Iranian Scientometric Information Database (ISID) based on some scientometric indicators. The data were analyzed using SPSS 22 software and Pearson's correlation coefficient, stepwise regression analysis and Chi-square tests were applied for data analysis. Findings revealed that each researcher had an average h index of 24.04, g index of 40.15, and i10 index of 90.79. There was a positive significant relationship between the number of internationally-collaborated papers and the number of citations received (r = .606, p < .01). The stepwise multiple regression analysis showed that the three variables of paper number, citation counts and mean citation rate determined 72 % of the changes in the h-index. It can be concluded that researchers publishing more papers are more likely to be cited. However, their scientometric indexes are not always better than those of other scientists. [ABSTRACT FROM AUTHOR]

This document is an editorial celebrating the 50th anniversary of Seminars in Thrombosis and Hemostasis (STH), a medical journal that first published in 1974. The editorial discusses the various celebratory issues that have been published over the years, which contain historical content related to the fields of thrombosis and hemostasis. The document also mentions the republishing of highly cited and downloaded papers from STH, along with accompanying commentaries from experts in the respective fields. Additionally, the document provides a list of the 50 most highly downloaded papers from STH between 2014 and 2023. [Extracted from the article]

Objective: To comparatively evaluate performances of tablet-based versus paper-based Venous Insufficiency Epidemiologic and Economic Study-Quality of Life/Symptom (VEINES-QOL/Sym) questionnaire. Methods: We prospectively evaluated 78 consecutive patients who completed tablet-based and paper-based VEINES-QOL/Sym questionnaires and compared their scores, completion time, data entry time, and ease of use. We used Student's t-test and Wilcoxon test for quantitative variables, Bland–Altman test and kappa coefficient for agreement between questionnaires and patients, respectively. Spearman's correlation coefficient was used to assess correlations. Results: Most participants (83.3%) found it easier to use the tablet device. Less time was needed to complete the tablet-based (median, 4.75; IQR, 3–7 min) than the paper-based (median, 8.3; IQR, 6.3–11.3 min) questionnaire (p <.001). Better educated patients took less time to complete paper-based (p =.003) and tablet-based (p =.001) questionnaires and considered the latter easier to use (p =.010). Conclusions: The tablet-based VEINES-QOL/Sym proved to be an easy-to-use and time-saving tool. [ABSTRACT FROM AUTHOR]

The apps for drawing are present in our children's life. Nevertheless, little is known about the impact of mobile technology on the freehand drawing educational activity. There are few works which are contextualised within short periods of time, with teachers who are not theirs and, in some cases, outside the children's classroom. In this paper, we are focussed on the use of technology on freehand drawing activity. Thus, we have compared the graphics produced by 4- and 5-year-old children with paper&crayon in comparison with those with tablet-finger. Children made the drawings during a planned free-drawing activity, in their ordinary classrooms, with their teachers and during five sessions. Assessment of drawings has evidenced tablet feasibility for making graphics. Nevertheless, with the passing of time, quality of graphics (tablet-finger vs paper&crayons), are nearly matched, demonstrating the low impact level technology has on this activity. In addition, if drawings are analysed specifically according to ages, results have shown that both groups have to develop adaptation strategies of visual perceptual skills and fine motor skills for the touch screen in order to obtain the same quality in the drawings made on both support types. [ABSTRACT FROM AUTHOR]

This study traces the evolution of computer-assisted language learning (CALL) by investigating published research articles (RAs) in four major CALL journals: ReCALL, Computer Assisted Language Learning, Language Learning & Technology, and CALICO Journal. All 2,397 RAs published over four decades (1983-2019) were included in the pool of data, and the Google Scholar citation metric was adopted to assess the impact of the papers. By selecting the top 15% of widely cited papers from each individual year, we minimized the time bias between years, enabling a balanced narration of the history of CALL through a representative dataset of 426 high-impact RAs. To identify the evolution of research trends, the contexts, methodologies, theoretical underpinnings and research foci of all 426 RAs were investigated using NVivo 12 and AntConc. The analysis of the data yielded encouraging results such as the upward trend in the number of publications and the international reach of CALL in the last two decades, the physical or virtual presence of language learners with diverse language profiles, and the growing tendency to triangulate methodology for increased complexity. However, long-standing issues such as the heavy reliance on traditional research contexts, poor reporting practices of basic demographic information, the large number of atheoretical papers and the concentration on a limited number of research foci continue to pose challenges in CALL research. Based on the findings, the paper suggests solutions for the controversies and addresses key issues for future research in CALL. [ABSTRACT FROM AUTHOR]

Papers including articles that are produced because of the activities of LifeWatch ERIC, in the context of its second implementation period (2022 - 2026) and through the implementation of its new Strategic Working Plan, are published in this special collection. The articles include data papers, papers describing the development and functioning of analytical services and papers describing any other research outcome, produced either by LifeWatch ERIC or by any collaboration with any other ERIC, Research Infrastructure, global aggregator or other legal entity. [ABSTRACT FROM AUTHOR]

Sensor data fusion analysis is a crucial process that integrates data from multiple sensors to provide more accurate and comprehensive information. This analysis has various applications in fields such as industry, medicine, robotics, transportation, and information systems. The article highlights sixteen high-quality papers that explore different aspects of sensor data fusion, including facial detection, object detection, odometry systems, geospatial data evaluation, and fault detection. The papers demonstrate the potential of sensor data fusion in improving decision-making, efficiency, and productivity in various industries. Future research in this area will focus on miniaturization, multi-sensor systems, and addressing challenges related to data quality in mobile sensors. [Extracted from the article]

The severity of plastic pollution is increasing, and delaying sustainable development is not an option. China is a large consumer of plastic, so it is essential to encourage the use of eco-friendly shopping bags there. The paper focuses on the recognition and use of eco-friendly shopping bags among young people in Guangdong Province, China, and determines what factors can lead to a rise in the use of these bags. A questionnaire was utilized to gather data from 392 young people in Guangdong Province using a quantitative research approach. According to the data from the questionnaire, they generally are supportive of eco-friendly shopping bags. Ultimately, the paper's data emphasize the positive effects of materials (paper material), function (internal compartment), and design (green label). For the purpose of advocating sustainable development, this paper provides helpful guidance for the design of eco-friendly shopping bags. [ABSTRACT FROM AUTHOR]

Issues 1 and 2 of 2024 are composed of papers selected for the special section in memory of Dr. Jean-Marie Proth. Some papers are extended versions of articles presented at the 10th IFAC MIM 2022 conference (hub.imt-atlantique.fr/mim2022/) in the invited sessions in memory of Dr. Proth. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to investigate associations between digital urine color and paper urine color with other urine indices to assess hydration status. Methods: Twelve male subjects (mean ± standard deviation; age, 26 ± 8 years; body mass, 57.8 ± 5.3 kg; height, 177.5 ± 8.9 cm; VO2max, 57.8 ± 5.8 ml·kg−1·min−1) performed four exercise trials in the heat. Before and following exercise trials, subjects provide urine samples. Urine samples were measured using a digital urine color chart on a portable device screen. Urine samples were also assessed with urine specific gravity (USG), urine osmolality (UOsmo), and a validated paper urine color chart. Results: There were extremely large associations found between digital urine color and paper urine color (r = 0.926, p < 0.001). Correlation coefficients showing associations with USG and UOsmo were similar between digital urine color (USG, r = 0.695, p < 0.001; UOsmo, r = 0.555, p < 0.001) and paper urine color (USG, r = 0.713, p < 0.001; UOsmo, r = 0.570, p < 0.001). Bland–Altman analysis indicated that no proportional bias was observed between digital and paper urine colors (bias, − 0.148; SD of bias, 0.492; 95% LOA, − 1.11, 0.817; p = 0.094). Conclusions: Strong associations were found between digital and paper urine colors with no proportional bias. Furthermore, the degree of associations with USG and UOsmo was similar between digital and paper urine color. These results indicate that digital urine color is a useful tool to assess hydration status and this method could be used as an alternative method to using paper urine color. [ABSTRACT FROM AUTHOR]

Simple Summary: Blood clots are formed when blood vessels are injured. They help stop bleeding and heal wounds, but can also cause serious problems if they block blood flow or break off and travel to other organs. This study investigates how blood clots differ in people with cancer compared to healthy or non-cancerous individuals. This study found that cancer patients have higher levels of histones in their blood, which make their clots stiffer and resistant to lysis. Further, clots formed in cancer patients have higher viscoelastic properties, and hence are harder to break down. These findings suggest that cancer patients have abnormal clotting properties that may increase their risk of developing thrombosis, and evaluating these properties can be helpful in detecting cancer. Background: Blood viscoelasticity and plasma protein levels can play an important role in the diagnosis and prognosis of cancer. However, the role of histones and DNA in modulating blood clot properties remains to be investigated. This study investigates the differences in blood viscoelasticity and plasma protein levels among cancer patients, individuals with other diseases, and healthy individuals. Methods: Blood samples were collected from 101 participants, including 45 cancer patients, 22 healthy individuals, and 34 individuals with other diseases. Rheological properties of clots formed in vitro by reconstituted elements of fibrinogen or plasma were analyzed with an Anton Paar Rheometer, USA. Plasma protein levels of D-dimer, TPA, EPCR, fibrinogen, and histone H3 were measured through ELISA. Blood clots were formed with or without DNA and histones (H3) by adding thrombin and calcium to plasma samples, and were evaluated for viscoelasticity, permeability, and degradation. Results: Cancer patients show higher blood viscoelasticity and plasma D-dimer levels compared to healthy individuals and individuals with other diseases. Our in vitro analysis showed that the addition of histone to the plasma results in a significant decrease in viscoelasticity and mean fiber thickness of the clot formed thereafter. In parallel studies, using plasma from patients, DNA and histones were detected in fibrin clots and were associated with less degradation by t-PA. Moreover, our results show that the presence of DNA and histones not only increases clots' permeability, but also makes them more prone to degradation. Conclusions: Plasma histones and DNA affect the structure of the clot formed and induce defective fibrinolysis. Moreover, the increased viscoelastic properties of plasma from cancer patients can be used as potential biomarkers in cancer prognosis. [ABSTRACT FROM AUTHOR]

Journals, regardless of their quality, may facilitate the publication of studies of affiliated authors or those of researchers in their close networks, this exhibiting biased behaviors in favor of insider researchers during peer review. The aim of this research was to determine insider authors' motivations for obtaining high and fast rates of acceptance of studies published by their affiliated institutions. A total of 11 Turkish dentistry journals with regular publishing schedules between 2017 and 2021 were examined. The publication language of the papers was either English or Turkish, and the papers were of four groups: original articles, reviews, case reports, and short communications. The submission date, acceptance date, and time from submission to acceptance of each paper were examined. The number of authors and the corresponding authors' countries of origin were noted, and the papers were analyzed to determine whether the researchers were insiders. The findings show that insider authors both publish in large numbers in their affiliated universities' journals (15.6% - 65.0%) and have significantly faster speeds (up to 82 days). The average time from submission to acceptance significantly differed for insider and outsider researchers in all journals except four. As in most areas of the health sciences, dentistry also lacks research on bias and the literature contains no study examining this issue in the field of dentistry both in Turkey and in the world. This study invokes a new discussion in this area by focusing on national dentistry journals and the bias inherent in editorial attitudes. In the future studies, it would be better to compare data on insiders and outsiders by incorporating both national and international dentistry papers in the future studies. [ABSTRACT FROM AUTHOR]

In this paper, a stylistic approach has been used to investigate the linguistic features of President Joe Biden's inauguration political speech. Special importance is given to its linguistic characteristics that affect the structure of the selected political speech. This paper is an attempt to highlight the political language of Biden's political speech. The aim is to seek out how political speeches are packaged to persuade citizens and readers and how stylistic analytical tools assist readers in interpreting the language of Biden in the selected speech. The data has been collected from Time Magazine. The data selection is restricted to Biden's inauguration political speech and has been chosen based on certain foregrounding features that indicate a powerful stylistic effect on readers. The qualitative method has been used to analyze the selected data. In the analysis, some linguistic features, such as graphological, syntactic, grammatical deviations, transitivity, and modality have been used to investigate the style of the selected speech to reveal persuasion. The findings show that Biden's inauguration political speech achieves power, and persuasion through the use of certain stylistic features including lexical and grammatical categories such as abstract nouns, personal pronouns, mental processes, and certain modal auxiliaries. It is concluded that the lexical items that Biden uses are crucial in passing his message to his nation. However, the tendency to use distinctive foregrounding features in the consistent repetition of lexical items and sentence structures are stylistic technique used by Biden for the sake of persuasion. [ABSTRACT FROM AUTHOR]

In today's dynamic digital landscape, the prevalence of multimedia content across various platforms underscores the importance of advanced techniques for analyzing data across diverse modalities. This paper explores the integration of text data with other modalities such as images, videos, and audio to enable comprehensive analysis and understanding. Specifically, the focus is on investigating methods for sentiment analysis in multimedia content and facilitating cross-modal retrieval. The paper addresses the challenges and opportunities in multimodal analysis, reviews existing techniques, and proposes novel methods for enhancing sentiment analysis and cross-modal retrieval through multimodal fusion and deep learning architectures. The challenges inherent in multimodal analysis include data heterogeneity, semantic gap, modality imbalance, and scalability. These challenges necessitate the development of robust techniques for multimodal fusion, feature representation, and cross-modal mapping. Existing methods, including early fusion, late fusion, and hybrid fusion techniques, are reviewed, alongside recent advancements in deep learning-based multimodal fusion architectures. Proposed methodologies aim to augment sentiment analysis and cross-modal retrieval through innovative multimodal fusion techniques and deep learning architectures. Experimental evaluations validate the effectiveness of the proposed methods in improving sentiment analysis accuracy and cross-modal retrieval performance. This research contributes to advancing techniques for analyzing and understanding multimedia content in the increasingly complex digital landscape, facilitating enhanced data-driven insights and decision-making processes across various domains. [ABSTRACT FROM AUTHOR]

An existential clause is a clause that shows a proposition about the existence or an event. This paper aims to describe the structure of existential clauses, the types of existential clauses, and the constraints of noun phrases that fill the existence elements in Balinese. This study used the descriptive qualitative method. The data used are primary data taken from five Balinese language teachers. The Balinese language teachers elicited the data made by the first teacher. Written data from Balinese stories are also used to assist the oral data. The data analysis technique chosen is comparison, omission, and replacement. Some research results are found in this paper. The core structure of Balinese existential clauses is verb ada + existence, and the extended structure of Balinese existential clauses is verb ada + existence + extension. There are two types of existential clauses in Balinese: bare and extended existential clauses. The definiteness of a noun phrase filling the existence element determines the choice of existential or non-existential clauses. This paper is helpful as a reference for Balinese grammar, which concerns the existential clauses of Balinese. [ABSTRACT FROM AUTHOR]

The escalating consumption of LPG in Indonesia has prompted the country's National Oil & Gas Company to embark on constructing a new LPG Facility. This paper addresses the imperative to streamline the Front-End Loading (FEL) stage to prevent cost and schedule overruns due to scope creep. The primary objective is to formulate a comprehensive Work Breakdown Structure (WBS) and Cost Breakdown Structure (CBS) for the LPG Facility Construction project, aimed at facilitating accurate cost estimation and scheduling processes for diverse stakeholders. Using the unfolded tesseract theory to analyze stakeholder needs and elucidate the object-oriented WBS, a Multi-Attribute Decision Making (MADM) analysis was conducted. The study concludes that a multidimensional WBS, particularly employing OmniClass, is the optimal choice for addressing the complexities of the LPG Facility Project and meeting stakeholder needs within BIM software. [ABSTRACT FROM AUTHOR]

To enhance employee collaboration and streamline operations, businesses are spending more money on digital solutions in the current environment of rapid technological advancement. Employees can operate efficiently remotely by utilizing online platforms for communication and cooperation, which improves job satisfaction and organizational performance. This paper proposes to present a retrospective analysis of publications on digital technology used in the context of performance improvement and satisfaction within organizations. In this sense, a bibliometric study is carried out based on the analysis of scientific works published in the Web of Science database. The searches were carried out using the keywords "digital technology", "performance", and "satisfaction". Querying the database revealed the existence of 1005 papers, collected data being analyzed with the help of Microsoft Excel and VOSviewer software. The collected and analyzed data highlighted the existence of several clusters of publications, authors or organizations that addressed the analyzed topic. This research also indicates clusters of keywords that suggest potential directions for future research and clearly identify the impact of digital technology on organizational performance and employee or customer satisfaction. Through this bibliometric study, the authors provide valuable information from which to start those who want to investigate the digital domains, organizational performance, or satisfaction in organizations. [ABSTRACT FROM AUTHOR]

The development of efficient and reliable online assessments has become increasingly important in the digital era. We developed a 10-min online word reading assessment of global English based on the existing paper-and-pencil version of our English silent word reading test. The test includes two parts, namely, random word recognition and contextual word reading. A total of 889 participants (437 children and 392 adults; 62.7% female) took part in the study. They were from various regions including mainland China, Hong Kong SAR, Macau SAR, Poland, the United States, and the Philippines. Reliability and validity analyses on various demographics samples (by age and country/region of origin) demonstrated that the WordSword Test is highly reliable and valid (e.g., the correlation of this test with other English reading measures were above.80). Education level was positively correlated with test performance, while the correlations between age and test performance were not consistent. Ninety-seven children participants also took the paper-and-pencil version of the WordSword Test. The correlation between performances on the online and paper-and-pencil versions of the test was.879, one year apart. With more children and adults taking the WordSword Test, we ultimately hope to establish norms by area, grade level, and age. [ABSTRACT FROM AUTHOR]

This paper provides empirical evidence using two studies to explain the primary factors facilitating electronic health record (EHR) systems adoption through the lens of the resource advantage theory. We aim to address the following research questions: What are the main organizational antecedents of EHR implementation? What is the role of monitoring in EHR system implementation? What are the current themes and people's attitudes toward EHR systems? This paper includes two empirical studies. Study 1 presents a research model based on data collected from four different archival datasets. Drawing upon the resource advantage theory, this paper uses archival data from 200 Texas hospitals, thus mitigating potential response bias and enhancing the validity of the findings. Study 2 includes a text analysis of 5154 textual data, sentiment analysis, and topic modeling. Study 1's findings reveal that joint ventures and ownership are the two main enablers of adopting EHR systems in 200 Texas hospitals. Moreover, the results offer a moderating role of monitoring in strengthening the relationship between joint-venture capability and the implementation of EHR systems. Study 2's results indicate a positive attitude toward EHR systems. The U.S. was unique in the sample due to its slower adoption of EHR systems than other developed countries. Physician burnout also emerged as a significant concern in the context of EHR adoption. Topic modeling identified three themes: training, healthcare interoperability, and organizational barriers. In a multimethod design, this paper contributes to prior work by offering two new EHR antecedents: hospital ownership and joint-venture capability. Moreover, this paper suggests that the monitoring mechanism moderates the adoption of EHR systems in Texas hospitals. Moreover, this paper contributes to prior EHR works by performing text analysis of textual data to carry out sentiment analysis and topic modeling. [ABSTRACT FROM AUTHOR]

As an important way to expand financing channels, the listing can significantly improve the enterprises' comprehensive competitiveness. However, few studies pay attention to the continuous impact of listing years on enterprise innovation. Based on the sample data of Chinese enterprises before and after listing from 2004 to 2017, this paper discusses the relationship between the listing years and dual innovation. And analyzes the moderating effect of slack. The research shows that the listing years are related to the quantity and quality of innovation in the inverted U-shaped, but the inflection point of the innovation quantity is later than the innovation quality. Before listing, the innovation quantity and quality increased; after listing, the innovation quantity first increased and then decreased, while the innovation quality declined. High slack makes the inverted U-shaped relationship between the listing years and innovation quality steeper. [ABSTRACT FROM AUTHOR]

This paper considers theoretical foundations and mathematical methods of data analysis under the conditions of the Rice statistical distribution. The problem involves joint estimation of the signal and noise parameters. It is shown that this estimation requires the solution of a complex system of essentially nonlinear equations with two unknown variables, which implies significant computational costs. This study is aimed at mathematical optimization of computer algebra methods for numerical solution of the problem of Rician data analysis. As a result of the optimization, the solution of the system of two nonlinear equations is reduced to the solution of one equation with one unknown variable, which significantly simplifies algorithms for the numerical solution of the problem, reduces the amount of necessary computational resources, and enables the use of advanced methods for parameter estimation in information systems with priority of real-time operation. Results of numerical experiments carried out using Wolfram Mathematica confirm the effectiveness of the developed methods for two-parameter analysis of Rician data. The data analysis methods considered in this paper are useful for solving many scientific and applied problems that involve analysis of data described by the Rice statistical model. [ABSTRACT FROM AUTHOR]

This paper studied the spatial pattern of supergentrification in the core area of Shanghai. The area is divided into 23 subdistricts based on the standard pattern of subdistrict division provided by CREIS (China Real Estate Index System) and then the 23 subdistricts are taken as objects for analysis. By establishing the evaluation index system of supergentrification level, the integrated analysis method entropy weight method and exploratory spatial data analysis is used to explore the general characteristics of the spatial pattern, spatial agglomeration characteristics, and spatial agglomeration hotspots of supergentrification in the core area of Shanghai. The research results of the spatial pattern reveal that the level of supergentrification in the core area of Shanghai is high in Puxi and low in Pudong. The Puxi district, represented by the People's Square subdistrict, West Nanjing Road subdistrict, and Hengshan Road subdistrict, has a higher level of supergentrification, while the Pudong district, represented by the Tangqiao subdistrict, Yangjing subdistrict, and Huamu subdistrict, has a lower level of supergentrification. The results of spatial autocorrelation analysis reveal that supergentrification in the core area of Shanghai presents obvious spatial agglomeration characteristics on the subdistrict scale and that the significantly high-high subdistricts are mainly distributed in the core area of Puxi. [ABSTRACT FROM AUTHOR]

The Internet of Multimedia Things (IoMT) refers to a network of interconnected multimedia devices that communicate with each other over the Internet. Recently, smart healthcare has emerged as a significant application of the IoMT, particularly in the context of knowledge‐based learning systems. Smart healthcare systems leverage knowledge‐based learning to become more context‐aware, adaptable, and auditable while maintaining the ability to learn from historical data. In smart healthcare systems, devices capture images, such as X‐rays, Magnetic Resonance Imaging. The security and integrity of these images are crucial for the databases used in knowledge‐based learning systems to foster structured decision‐making and enhance the learning abilities of AI. Moreover, in knowledge‐driven systems, the storage and transmission of HD medical images exert a burden on the limited bandwidth of the communication channel, leading to data transmission delays. To address the security and latency concerns, this paper presents a lightweight medical image encryption scheme utilising bit‐plane decomposition and chaos theory. The results of the experiment yield entropy, energy, and correlation values of 7.999, 0.0156, and 0.0001, respectively. This validates the effectiveness of the encryption system proposed in this paper, which offers high‐quality encryption, a large key space, key sensitivity, and resistance to statistical attacks. [ABSTRACT FROM AUTHOR]

We live in the era of large data analysis, where processing vast datasets has become essential for uncovering valuable insights across various domains of our lives. Machine learning (ML) algorithms offer powerful tools for processing and analyzing this abundance of information. However, the considerable time and computational resources needed for training ML models pose significant challenges, especially within cascade schemes, due to the iterative nature of training algorithms, the complexity of feature extraction and transformation processes, and the large sizes of the datasets involved. This paper proposes a modification to the existing ML-based cascade scheme for analyzing large biomedical datasets by incorporating principal component analysis (PCA) at each level of the cascade. We selected the number of principal components to replace the initial inputs so that it ensured 95% variance retention. Furthermore, we enhanced the training and application algorithms and demonstrated the effectiveness of the modified cascade scheme through comparative analysis, which showcased a significant reduction in training time while improving the generalization properties of the method and the accuracy of the large data analysis. The improved enhanced generalization properties of the scheme stemmed from the reduction in nonsignificant independent attributes in the dataset, which further enhanced its performance in intelligent large data analysis. [ABSTRACT FROM AUTHOR]

Aim: This study aims to adapt the "Nursing Practice Readiness Scale" to Turkish culture, and evaluate its psychometric properties. Background: New graduates' nursing practice readiness can impact their work adaptation and performance. Design: The research employed a methodological design. Methods: Data were collected between May and July 2022. The sample consisted of 436 newly graduated nurses. Content validity, construct validity and criterion validity were evaluated. Reliability was examined with adjusted item‐total correlation, Cronbach's a coefficient, composite‐reliability and split‐half reliability. Results: The Turkish version of Nursing Practice Readiness Scale was found to have good content and criterion validity. As a result of confirmatory factor analysis, the original five‐factor structure of the scale was also confirmed for the Turkish version. The scale's overall Cronbach's α coefficient was determined to be 0.96, with subscale coefficients ranging from 0.73 to 0.94. The composite reliability values of the subscales were found between 0.75 and 0.94. In split‐half reliability, the correlation coefficient between half was 0.952, with a Spearman–Brown Coefficient (Unequal Length) of 0.976. Conclusions: The Turkish version of Nursing Practice Readiness Scale is a valid and reliable measurement tool for evaluating the nursing practice readiness of newly graduated nurses. Summary statement: What is already known about this topic? The nursing practice readiness of newly graduated nurses may impact their work adaptation and performance.Work adaptation is an important predictor of intention to leave the profession and productivity. What this paper adds? This study adapted the Nursing Practice Readiness Scale to Turkish culture, and evaluated its psychometric properties.The Turkish version of Nursing Practice Readiness Scale was shown to be a valid and reliable tool that can be used to evaluate newly graduated nurses' nursing practice readiness. The implications of this paper Nurse educators will be able to assess the readiness of graduating students for nursing practice by using the scale.Nurse managers will be able to evaluate the readiness of new graduate nurses for nursing practice using the scale.Nurse managers and educators will be able to identify areas that need to be prioritized to increase the readiness of newly graduated nurses for nursing practice by using the scale. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study is to describe and evaluate how nurses caring for COVID and non‐COVID patients assess changes in their work and in nursing activities during the two waves of the COVID‐19 pandemic. Methods: Two cross‐sectional surveys were conducted for Estonian nurses working during the first and second waves of the COVID‐19 pandemic, using The impact of COVID‐19 emergency on nursing care questionnaire. Based on convenience sampling, the data were collected among the members of professional organizations, unions and associations. Responses from the first (n = 162) and second wave (n = 284) were analysed using descriptive statistics, Fisher's exact test and McNemar's test. Results: The COVID‐19 pandemic changed the working context during both waves for nurses caring for COVID and non‐COVID patients. Changes were considered to a greater extent during the second wave, when Estonia was severely affected, and by nurses caring for COVID patients. During the second wave, the number and complexity of patients increased, and nurses caring for COVID patients performed fundamental care, nursing techniques and symptom control significantly more frequently compared to nurses caring for non‐COVID patients. Conclusion: Taking care of COVID patients is demanding, requiring nurses to perform more direct patient care. However, the pandemic also increased the frequency of activities not related with direct patient care. Summary statement: What is already known about this topic? The COVID‐19 pandemic has influenced the context of care and all dimensions of nurses' work.Despite increasing research on the impact of the COVID‐19 pandemic on nursing care, little attention has been given to differences between caring for COVID and non‐COVID patients during the different waves of the COVID‐19 pandemic. What this paper adds? Nursing care for COVID patients requires from nurses more direct patient care through fundamental care activities, nursing techniques and symptom control compared to non‐COVID patients.The impact of the COVID‐19 pandemic on nurses' work reflects the severity and progress of different waves of the pandemic, which needs to be considered in preparing for future pandemics.Nursing care during a pandemic may also lead to an extensive workload due to tasks not related to direct patient care as nurses contribute to the management of the pandemic on all levels of health care. The implications of this paper: The COVID‐19 pandemic has had a significant impact on nursing, where the mitigation of long‐term effects of the pandemic is still ongoing, and thus, knowledge about the details of the resulting changes is required.Study findings enable us to mitigate the impact of the pandemic on nurses and to highlight aspects that need to be taken into account when preparing for future pandemics. [ABSTRACT FROM AUTHOR]

Aims: To investigate the relationship between the psychological resilience and burnout of nurses caring for COVID‐19 patients and to determine the factors that affect their psychological resilience and burnout. Background: In pandemic diseases such as COVID‐19, nurses experience burnout due to long working hours, decreased quality of life and anxiety/fear about their own/families' health. Psychological resilience helps to control burnout in nurses and prevent the development of a global nurse shortage. Design: This was a descriptive, correlational study. Methods: The sample of this study included 201 nurses in a Training and Research Hospital. The study used the Brief Resilience Scale and the Burnout Measure Short Version. Data were collected between 4 May and 1 June 2020. Statistical analysis was made with Pearson/Spearman, independent sample t test, one‐way analysis of variance (ANOVA) test. Results: Nurses reported moderate burnout and psychological resilience, with a negative and highly significant correlation between psychological resilience and burnout levels. Conclusions: In order to increase the quality of patient care/treatment, nurse managers need to reduce nurses' burnout and increase their psychological resilience. Nurses are recommended to adopt a healthy lifestyle, organize training programmes and implement psychological resilience interventions to prevent sleep disorders. Giving nurses the tools to understand what they need to manage within their locus of control will allow them to find a new sense of resilience, preventing potential burnout. Summary statement: What is already known about this topic? Epidemics and pandemics cause many negative effects on the individual/society in terms of physical, psychological, social and economic aspects.During epidemic and pandemic, nurses experience burnout caused by the accumulation of professional stress.Nurses with high levels of psychological resilience experience less psychological distress such as anxiety, fear, burnout, sensory and psychosocial problems. What this paper adds? Nurses experienced moderate burnout and resilience during the early stages of the COVID‐19 pandemic.A negative correlation was found between nurses' burnout and psychological resilience.The burnout levels of nurses who were not college graduates, who were dissatisfied with their jobs and who intended to leave their jobs were found to be high. The implications of this paper: Nurses were vulnerable to burnout due to increased workloads in the COVID‐19 crisis, increased shifts and the fear of infecting themselves and their families.It is necessary to increase the psychological resilience of nurses in order to provide the highest level of care to patients with COVID‐19.Nurse manager should focus on reducing burnout in their nursing teams by supporting the postgraduate education of nurses and reducing their workload. [ABSTRACT FROM AUTHOR]

The relative advantages and disadvantages of sum scores and estimated factor scores are issues of concern for substantive research in psychology. Recently, while championing estimated factor scores over sum scores, McNeish offered a trenchant rejoinder to an article by Widaman and Revelle, which had critiqued an earlier paper by McNeish and Wolf. In the recent contribution, McNeish misrepresented a number of claims by Widaman and Revelle, rendering moot his criticisms of Widaman and Revelle. Notably, McNeish chose to avoid confronting a key strength of sum scores stressed by Widaman and Revelle—the greater comparability of results across studies if sum scores are used. Instead, McNeish pivoted to present a host of simulation studies to identify relative strengths of estimated factor scores. Here, we review our prior claims and, in the process, deflect purported criticisms by McNeish. We discuss briefly issues related to simulated data and empirical data that provide evidence of strengths of each type of score. In doing so, we identified a second strength of sum scores: superior cross-validation of results across independent samples of empirical data, at least for samples of moderate size. We close with consideration of four general issues concerning sum scores and estimated factor scores that highlight the contrasts between positions offered by McNeish and by us, issues of importance when pursuing applied research in our field. [ABSTRACT FROM AUTHOR]

The meta-learning method proposed in this paper addresses the issue of small-sample regression in the application of engineering data analysis, which is a highly promising direction for research. By integrating traditional regression models with optimization-based data augmentation from meta-learning, the proposed deep neural network demonstrates excellent performance in optimizing glass fiber reinforced plastic (GFRP) for wrapping concrete short columns. When compared with traditional regression models, such as Support Vector Regression (SVR), Gaussian Process Regression (GPR), and Radial Basis Function Neural Networks (RBFNN), the meta-learning method proposed here performs better in modeling small data samples. The success of this approach illustrates the potential of deep learning in dealing with limited amounts of data, offering new opportunities in the field of material data analysis. [ABSTRACT FROM AUTHOR]

Theoretical background: Sustainable marketing is an increasingly popular topic in the field of scientific work. In the literature, a clear popularity of given approaches and perspectives can be seen, but only meta-analysis is able to define clear trends occurring in the literature. Purpose of the article: This paper aimed to analyze the state-of-the-art research on sustainable marketing through a bibliometric study using the Biblioshiny tool. Based on the articles published from 2019 to 2023 the results from the perspective of growing trends in the field were achieved. Research methods: The analysis was initiated by the appropriate selection of keywords and subsequent narrowing of the database of scientific articles in accordance with the adopted criteria. The results in graphic form have been discussed and interpreted in detail. The comparison of this article’s output with the literature review allowed for the confrontation of the obtained research with the conclusions of the foregoing studies. Main findings: In the results, existing trends, such as a consumer-oriented approach, can be found. The multicultural approach seems to be an aspect not visible in the manual literature overview. The analysis also shows a clear increase and potential of publications on sustainable marketing and a multipronged perspective of the topic in the context of different aspects of business. [ABSTRACT FROM AUTHOR]

Healthcare is a vital part of a healthcare system, which is governed by a set of responsibilities and responsibilities. This paper explores the evolution of healthcare systems through the use of the Internet of Things (IoT) and telemedicine. The paper aims to identify areas for improvement and explore strategies to leverage network technologies to enhance healthcare offerings and outcomes. The data analysis technique used was thematic analysis. Thematic analysis identified and categorized key themes related to challenges and innovations in the collected studies. Telemedicine, supported by cloud computing, offers significant potential for improving healthcare delivery but faces challenges related to high assurance, interoperability, and storage adaptability. The development and use of telecommunications technology in healthcare require careful policy considerations to address the significant challenges in healthcare delivery. The research also explores how technology influences the development of healthcare delivery systems known for its efficiency, accessibility, and improved patient welfare. [ABSTRACT FROM AUTHOR]

Simple Summary: The paper describes the statistical analysis of the response of gastric cancer cells and normal cells to broadband terahertz radiation up to 4 THz, both with and without the use of nanostructured contrast agents. A statistical analysis was conducted towards multiple pairwise comparisons in order to identify the narrow THz frequency ranges where the contrast is enhanced and allows a clear identification of tumor cells in the presence of contrast agents. The paper describes the statistical analysis of the response of gastric cancer cells and normal cells to broadband terahertz radiation up to 4 THz, both with and without the use of nanostructured contrast agents. The THz spectroscopy analysis was comparatively performed under the ATR procedure and transmission measurement procedure. The statistical analysis was conducted towards multiple pairwise comparisons, including a support medium (without cells) versus a support medium with nanoparticles, normal cells versus normal cells with nanoparticles, and, respectively, tumor cells versus tumor cells with nanoparticles. When generally comparing the ATR procedure and transmission measurement procedure for a broader frequency domain, the differentiation between normal and tumor cells in the presence of contrast agents is superior when using the ATR procedure. THz contrast enhancement by using contrast agents derived from MRI-related contrast agents leads to only limited benefits and only for narrow THz frequency ranges, a disadvantage for THz medical imaging. [ABSTRACT FROM AUTHOR]

In the rapidly evolving domain of cryptocurrency trading, accurate market data analysis is crucial for informed decision making. Candlestick patterns, a cornerstone of technical analysis, serve as visual representations of market sentiment and potential price movements. However, the sheer volume and complexity of cryptocurrency price time-series data presents a significant challenge to traders and analysts alike. This paper introduces an innovative rule-based methodology for recognizing candlestick patterns in cryptocurrency markets using Python. By focusing on Ethereum, Bitcoin, and Litecoin, this study demonstrates the effectiveness of the proposed methodology in identifying key candlestick patterns associated with significant market movements. The structured approach simplifies the recognition process while enhancing the precision and reliability of market analysis. Through rigorous testing, this study shows that the automated recognition of these patterns provides actionable insights for traders. This paper concludes with a discussion on the implications, limitations, and potential future research directions that contribute to the field of computational finance by offering a novel tool for automated analysis in the highly volatile cryptocurrency market. [ABSTRACT FROM AUTHOR]

While education is often seen as a main strategy for enabling sustainable futures, youth question the ability of modern schooling to provide them with the necessary tools to mitigate our current planetary crises. In this paper, we argue for the need for more critical insight into how youth understand and envision sustainability. The paper is based on a pedagogical intervention study, with a design inspired by decolonial pedagogy (Pashby & Sund, 2019, p. 38). Data was collected in two interconnected workshops at three Norwegian upper secondary schools. We share reflections communicated by students in conversations during the workshops. The material shows that although the students display criticality and an acknowledgement of the need for alternative ways of thinking, they also express a frustration over not being provided with the necessary tools to express this critique through their current education. We argue that if sustainability is to provide an educational avenue of hope and change, it requires tools that can help students challenge the limitations of modern-colonial habits of being and knowing. As the students suggest themselves, there is also a need for making space for more creative and imaginative pedagogical practices in education. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate how to identify and address production levelling problems in assembly lines utilising an intensive manual workforce when higher productivity levels are urgently requested to meet market demands. Design/methodology/approach: A mixed-methods approach was used in the research design, integrating case study analysis, interviews and qualitative/quantitative data collection and analysis. The methodology implemented also introduces to the literature on operational performance a novel combination of data analysis methods by introducing the use of the Natural Language Understanding (NLU) methods. Findings: First, the findings unveil the impacts on operational performance that transportation, limited documentation and waiting times play in assembly lines composed of an intensive workforce. Second, the paper unveils the understanding of the role that a limited understanding of how the assembly line functions play in productivity. Finally, the authors provide actionable insights into the levelling problems in manual assembly lines. Practical implications: This research supports industries operating assembly lines with intensive utilisation of manual workforce to improve operational performance. The paper also proposed a novel conceptual model prescriptively guiding quick and long-term improvements in intensive manual workforce assembly lines. The article assists industrial decision-makers with subsequent turnaround strategies to ensure higher efficiency levels requested by the market. Originality/value: The paper offers actionable findings relevant to other manual assembly lines utilising an intensive workforce looking to improve operational performance. Some of the methods and strategies examined in this study to improve productivity require minimal capital investments. Lastly, the study contributes to the empirical literature by identifying production levelling problems in a real context. [ABSTRACT FROM AUTHOR]

Background: Coronavirus disease 2019 (COVID-19) has had a significant impact on dermatology, but to date no bibliometric analysis of this field has been identified. Therefore, the aim of this study was to perform a bibliometric indicator analysis of the worldwide scientific production of COVID-19 in dermatology. Materials and Methods: An advanced bibliographic search was performed in the Scopus database to identify articles on COVID-19 and dermatology from 2020 to 2021. The collected information was analysed with SciVal software. Bibliometric data were described through figures and summary tables. Results: A total of 1448 documents were collected and analysed. Torello Lotti was the author with the greatest scientific production; however, Esther Freeman had the greatest impact. Harvard University was the institution with the highest number of published articles. Most papers were published in the first quartiles. The United States and Italy were the leading countries in terms of production. Articles with international collaboration had the highest impact. Conclusion: Articles related to dermatology and COVID-19 are mostly published with American and Italian affiliations. In addition, there has been an increase in the distribution of articles published in the first quartile, which would reflect a growing interest in the community. Publications with international collaboration reported the highest impact, so future authors should take this into account. [ABSTRACT FROM AUTHOR]

Current literature dealing with the theory of sampling process flows is limited in scope, a situation addressed by papers presented at conferences by the author. This paper provides a summary of methods to quantify process sampling variance in a sound statistical manner. Two methods of calculation of the process sampling variance are presented here with models for robust estimation of the process covariance/variogram. The strategies for process sampling to acquire the data for process characterisation are described. The method for process characterisation can be based on special sampling campaigns, on the analysis of on-line measurement data, or on the analysis of historical data, which may be based on composite samples, such as shift samples. These scenarios are all dealt with as well as methods based on analysis of process dynamics. The latter analysis demonstrates that use of covariance functions drawn from geostatistical practice can be inappropriate for process analysis. The work is supported with plant data examples and quantitative analyses of process conditions. [ABSTRACT FROM AUTHOR]

Although various academic disciplines use data papers to support effective research practices, data papers are still uncommon in the educational sciences. Main goals of data papers are enhancing transparency regarding research processes and supporting data sharing among researchers and thus, open science. As many educational research projects include personal data often of minors, publishing raw data can be challenging due to privacy regulations and laws (GDPR). The present article aims at exploring how a data paper can contribute to open science and enhancing transparency regarding research and publication processes for educational research projects, often containing personal data that cannot be made openly available in its raw form. To this end, we describe a dataset of a research project on teachers' noticing as basis for their classroom management. As this project includes rich process-tracing recording methods, the dataset is diverse and serves as basis for multiple analyses and publications while containing personal data of teachers and minors. By elaborating on the characteristics of the dataset, its gathering, analysis approaches and sharing preprocessed and anonymized data files, this data paper explores how to contribute to transparency and open science in educational sciences while acting within the boundaries set by privacy regulations and laws. [ABSTRACT FROM AUTHOR]

For a finite set of balls of radius r, the k-fold cover is the space covered by at least k balls. Fixing the ball centers and varying the radius, we obtain a nested sequence of spaces that is called the k-fold filtration of the centers. For k=1, the construction is the union-of-balls filtration that is popular in topological data analysis. For larger k, it yields a cleaner shape reconstruction in the presence of outliers. We contribute a sparsification algorithm to approximate the topology of the k-fold filtration. Our method is a combination and adaptation of several techniques from the well-studied case k=1, resulting in a sparsification of linear size that can be computed in expected near-linear time with respect to the number of input points. Our method also extends to the multicover bifiltration, composed of the k-fold filtrations for several values of k, with the same size and complexity bounds. [ABSTRACT FROM AUTHOR]

The main aim of this work is to provide insight into a bibliometric analysis of Data Journals and Data Papers in terms of research areas, disciplines, publication year and country. In particular, we calculated many bibliometric indicators, especially: the number of publications and citations. Furthermore, this work also investigated the top 20 journals in which scientists published the largest number of Data Papers. It was found that the first Data Paper in Medical and Health Science was published in 2006. Our results indicate that about 64% of Data Papers are cited and about 30% of Data Papers are articles that have international co-authors. We also found that a significant number of Data Papers were published in top quartile (Q1) Open Access journals. Furthermore, most Data Papers were published in Multidisciplinary Sciences, followed by Biological Sciences, Earth and related Environmental Sciences as well as Computer and Information Sciences. Our analyses show that the largest number of Data Papers were published in journals with an Impact Factor ranging from 5 to 6. Additionally, the largest number of Data Papers were published in the USA, China, the United Kingdom, Italy and France. From the point of view of scientists, this work is needed because scientists can check information about journals in which they may publish research data. Moreover, they can find Data Journals with a high Impact Factor and MEiN points. This analysis is also interesting because scientists/publishers can compare the disciplines and countries in which researchers have published the greatest number of Data Papers. Finally, it is worth noting that this work gives insights into the various bibliometric indicators related to citations and the number of publications. This information can be useful for people associated with bibliometric analyses. [ABSTRACT FROM AUTHOR]

This study aims to explore the SCImago Institutional Ranking (SIR) 2022 to gain insight into the profile of Sri Lankan universities. Additionally, the study aims to investigate whether there was consistency between Scopus profiles and SIR. Furthermore, the research delves into various factors that impact the research ranking of an academic institution as defined by SCImago, which goes beyond just the number of publications. The data for the study were retrieved from SIR (2022) and Scopus database (2022) and were systematically analyzed. The author chose the following options to extract the data for overall ranking, Universities as a sector, Sri Lanka as the country and 2022 as the year based on all subject areas. The study found that the number of Sri Lankan universities eligible for the SCImago ranking has gradually increased from 2013 to 2022. According to SIR, the University of Colombo is the top-ranked academic institution in Sri Lanka, followed by Rajarata University of Sri Lanka and the University of Jaffna. Out of the fourteen universities in Sri Lanka, eight were ranked by SIR, with six being in the Q1 (first cluster) and two in the Q2 (second cluster). Interestingly, the Rajarata University of Sri Lanka was ranked 1st in SIR 2022 for its research performance among Sri Lankan universities with their 105 publications indexed in Scopus. Analysis of data shows that there is no relationship between the Scopus profile and the SIR. It is also suggesting that having a high number of articles in the Scopus database does not necessarily guarantee a high rank in SIR. The SIR not only depends on the number of publications but also on other factors related to the quality of the publications. Therefore, universities cannot assume their SIR position by considering only the quantity of Scopus indexed publications. SIR mainly considers the quality of the publications to measure the institutional research performance. The SCImago ranking evaluates the institutional whole performance through three of its indicators, and research performance is measured only through Scopus indexed publication. Sri Lankan publications in local and international journals which are not indexed in Scopus and conference papers were not counted for research performance. The findings of this study will facilitate the institutions to compare their position with other institutions, standardize their research practices, improve the international collaboration to uphold the academic benchmark, regulate their research publications and promote their visibility and finally support government bodies and policymakers regarding fund allocations and strategic planning. [ABSTRACT FROM AUTHOR]