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The notable increase in retraction papers has attracted considerable attention from diverse stakeholders. Various sources are now offering information related to research integrity, including concerns voiced on social media, disclosed lists of paper mills, and retraction notices accessible through journal websites. However, despite the availability of such resources, there remains a lack of a unified platform to consolidate this information, thereby hindering efficient searching and cross-referencing. Thus, it is imperative to develop a comprehensive platform for retracted papers and related concerns. This article aims to introduce “Amend,” a platform designed to integrate information on research integrity from diverse sources.

In this paper, through the collection and analysis of data, the art of Guangling paper-cutting is theoretically researched, and the general features and shapes of Guangling paper-cutting are summarized. In order to overcome the limitations of traditional algorithms in the extraction of features of Guangling paper-cutting, the combination of spatial pyramid matching and context-dependent histogram methods are used to extract the shape features of paper-cutting images with stronger differentiation. The support vector machine is used to solve the problem of recognizing and classifying the image patterns in the digitized display. The design of the digital promotion of the Shanxi Guangling paper-cutting brand is carried out. Research variables are designed to analyze the effect of digital transformation and promotion of paper-cutting brands. The results show that the discrepancy of Guangling paper-cutting features extracted by the algorithm in this paper is very low, the e1 difference is maintained within 0.1, and the total recognition rate of SVM on Guangling paper-cutting features can reach 88.06%, and the overall effect is more satisfactory, and the regression equation of the influence of paper-cutting = −0.807+0.111*history+0.122* style+0.234*paper-cutting+0.216*display+0.136 * linkage, and propose strategies to enhance the influence of paper-cutting brand. The technical methods used in this study guarantee the quality of the digital transformation of Guangdong paper-cutting from the source.

To deeply analyze the performance of paper-cutting elements in interior space design, this paper explores the artistic expression of paper-cutting elements. The BIM model is constructed based on the TVL algorithm, and a noise-reducing style migration method with an additional total variable loss function is used to fuse the texture features of a specific paper-cutting style so that the paper-cutting texture is generated in the target object area more intensively. The algorithm is supplemented with a U-shaped network structure to obtain the mask map of the target object, modify and expand the ScanNet training data set, and input a content map and a style map to generate the stylized paper cutout image automatically. The results show that compared with other elements, the stability of paper-cut elements reaches 96.31%, the image smoothness reaches 89.34%, and the retention of significant regions reaches 93.26%. In modern design, the peak signal-noise of paper-cut elements improved by 13.418d on average, the structural similarity also improved by 0.34807, and the recognition rate of paper-cut elements in the furnishing category reached 95%. Applying paper-cut art in interior space design can give interior furnishing design better visual effects, provide inspiration and ideas for interior space design innovation, and contribute to improving aesthetics.

The goal of this study is a comparative analysis of the relation between funding (a main driver for scientific research) and citations in papers of Nobel Laureates in physics, chemistry and medicine over 2019-2020 and the same relation in these research fields as a whole.

In the realm of Chinese traditional arts, paper-cutting symbols embody deep-seated aesthetic and cultural values. Within the framework of artificial intelligence, the fusion of these conventional symbols with contemporary pattern design through intelligent reconstruction processes promotes innovation in modern design. This paper introduces a novel pattern feature extraction algorithm specifically designed for identifying and extracting the essence of traditional paper-cutting art. Utilizing Deep Convolutional Generative Adversarial Networks (DCGAN), an automated method for generating woven patterns is developed, integrating conventional motifs with modern design elements. Additionally, a segmentation model based on DeepLabV3+ semantics is constructed to facilitate this integration. The study focuses on the fusion of traditional paper-cutting symbols with fabric patterns, providing a new direction for textile design research. The empirical evaluation involved seven experimenters who predominantly favored patterns that blended abstract and traditional styles, with the average style rating exceeding 3.2. Moreover, the color performance analysis of the reconstructed fabric patterns across five regions showed color difference values greater than 4, indicating superior color fidelity. These findings underscore the potential of combining AI-driven techniques with traditional art forms to enhance and revolutionize modern design practices.

The study of metadiscourse word resources is an important way to reveal academic knowledge constructs and genre features in English papers. This paper selects intra- and interdisciplinary English academic papers as data samples, and the text representation is based on the vector space model. The text similarity is calculated using the word movement distance model to complete the clustering based on the density peak, and then the semantic annotation of metadiscourse verb patterns is performed using the conditional random field. Then, the intra- and interdisciplinary metadiscourse annotations are compared to analyze the variation of verb patterns. The intra-disciplinary variation of metadiscourse verb patterns was mainly found using attitude markers, where the log-likelihood ratios of 48.56, 30.25, and 35.64 were obtained for affirmative, critical, and critical declarative attitudes, respectively. In interdisciplinary studies, basic disciplines preferred to use verb patterns as transitions, while applied disciplines preferred to express the author’s point of view. The study of metadiscourse verb patterns effectively enriches the linguistic resources in academic English teaching and deepens the understanding of the characteristics of disciplinary essay genres.

This investigation delves into the evolving patterns and regional variances in industry-academia collaboration (IAC) within Functional Nucleic Acids (FNAs) research. Analyzing publications and patents from 1990 to 2021, we dissected IAC at individual and collective levels, documenting the count and share of IAC endeavors, key partners, and regional differences. Results indicate a rising trend in IAC publications and collaborating institutions, while patent trends display a mix of increases, decreases, and steady states. The United States leads in IAC activities, correlating with its prowess in scientific research and technological innovation. Notably, regional discrepancies in IAC are mainly due to intra-regional variations, with Asia and Europe experiencing the most pronounced disparities.

Lignocellulose material is the main natural resource for the pulp and paper industry, and for its application the material should have a degree of whiteness as high as possible. For this reason, different bleaching treatments were applied during time. In this paper, the photobleaching induced by solar light of a lignocellulosic biomass using NaClO was studied. The colorimetric measurements, UV spectra absorption, and FTIR spectra changes are evaluated and discussed in this paper. The changes of L*a*b parameters can be considered a proof of the reactions generated by hypochlorite radicals during solar light exposure, leading to a biomass whitening. [ABSTRACT FROM AUTHOR]

A text generation based multidisciplinary problem identification method is proposed, which does not rely on a large amount of data annotation. The proposed method first identifies the research objective types and disciplinary labels of papers using a text classification technique; second, it generates abstractive titles for each paper based on abstract and research objective types using a generative pre-trained language model; third, it extracts problem phrases from generated titles according to regular expression rules; fourth, it creates problem relation networks and identifies the same problems by exploiting a weighted community detection algorithm; finally, it identifies multidisciplinary problems based on the disciplinary labels of papers. Experiments in the "Carbon Peaking and Carbon Neutrality" field show that the proposed method can effectively identify multidisciplinary research problems. The disciplinary distribution of the identified problems is consistent with our understanding of multidisciplinary collaboration in the field. It is necessary to use the proposed method in other multidisciplinary fields to validate its effectiveness. Multidisciplinary problem identification helps to gather multidisciplinary forces to solve complex real-world problems for the governments, fund valuable multidisciplinary problems for research management authorities, and borrow ideas from other disciplines for researchers. This approach proposes a novel multidisciplinary problem identification method based on text generation, which identifies multidisciplinary problems based on generative abstractive titles of papers without data annotation required by standard sequence labeling techniques. [ABSTRACT FROM AUTHOR]

This article has two main parts. In the first part we show that some of the basic theory of generalized polynomials on commutative semi-groups can be extended to all semigroups. In the second part we show that if a sub-semigroup S of a group G generates G in the sense that G = S · S−1, then a generalized polynomial on S with values in an Abelian group H can be extended to a generalized polynomial on G into H. Finally there is a short discussion of the extendability of exponential functions and generalized exponential polynomials. [ABSTRACT FROM AUTHOR]

The paper shows how the agri-sector is influenced by the emergence and development of the digitisation process. This is presented using a bibliometric analysis. The importance of studying and understanding the current challenges facing the agricultural sector including the emergence and development of the digitisation process of the sector is the main aim of this paper. All these challenges are felt by both the agricultural sector and the economy as a whole. This paper contributes to the literature. This is due to the bibliometric analysis through which the most important aspects of the challenges facing the entire agricultural sector today are observed. Among the current challenges facing the agricultural sector, climate change is among the most important. The results of the bibliometric analysis show that the keywords searched and their clustering confirm that the emergence and rapid development of digitisation brings both positive and negative effects to the whole agricultural sector. Following the search of Web of Science and Scopus databases, 203 papers were identified in Web of Science and Scopus using the phrase "the impact of digitization on agriculture". The bilbiometric analysis comprises several steps, including the analysis of the years of emergence of studies on the emergence of the digitisation process in agriculture. Thus, within this stage, the analysis of the years, it is signalled the transition from some aspects that concern the technological side to other economic and even human aspects. On the whole, there is a shift in research topics towards studying how the emergence and development of the digitisation process brings both positive and negative influences between the agricultural sector and society. [ABSTRACT FROM AUTHOR]

Copyright of Internal Medicine / Medicină Internă is the property of Sciendo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Leveraging artificial intelligence (AI), this study revolutionizes examination management and education in universities by developing an intelligent system encompassing comprehensive management, pre-examination activities, scheduling, and preparation. The system also features a quality management component for educational outcomes. An enhanced genetic algorithm introduces an adaptation function to optimize intelligent grouping, facilitating effective exam paper distribution. Applied at Y University, our innovative approach significantly refines exam paper difficulty (ranging between 0.5016 and 0.5581) and differentiation (0.3845 to 0.4596), showcasing the intelligent algorithm’s effectiveness in exam management and contributing valuable insights to educational research.

This paper aims to examine the changes in global value chains (GVCs) in the years 2020–2022 (times of the COVID-19 pandemic) compared to 2019 (last year before the pandemic). GVCs are illustrated by diagrams based on the statistics on international trade measured by value-added exports and imports. In this paper, the final demand approach is applied to measure international trade by value-added exports and imports and they were computed based on inter-country input-output tables delivered by the Asian Development Bank (ADB). The catchphrase "Made in the World" makes an impression, but in reality, value chains are rarely global. They are rather regional with three centers. "Factory Europe", "Factory Asia", and "Factory America" can easily be identified in the years 2019–2022 as there were three large regional supply hubs in GVCs: Germany, China, and the United States. When the years 2020–2022 were compared to 2019, "Factory Asia" with center in China elevated their position in GVCs at the expense of "Factory Europe" with center in Germany and "Factory America with center in the USA." [ABSTRACT FROM AUTHOR]

Accurately assigning the document type of review articles in citation index databases like Web of Science(WoS) and Scopus is important. This study aims to investigate the document type assignation of review articles in Web of Science, Scopus and Publisher's websites on a large scale. 27,616 papers from 160 journals from 10 review journal series indexed in SCI are analyzed. The document types of these papers labeled on journals' websites, and assigned by WoS and Scopus are retrieved and compared to determine the assigning accuracy and identify the possible reasons for wrongly assigning. For the document type labeled on the website, we further differentiate them into explicit review and implicit review based on whether the website directly indicates it is a review or not. Overall, WoS and Scopus performed similarly, with an average precision of about 99% and recall of about 80%. However, there were some differences between WoS and Scopus across different journal series and within the same journal series. The assigning accuracy of WoS and Scopus for implicit reviews dropped significantly, especially for Scopus. The document types we used as the gold standard were based on the journal websites' labeling which were not manually validated one by one. We only studied the labeling performance for review articles published during 2017-2018 in review journals. Whether this conclusion can be extended to review articles published in non-review journals and most current situation is not very clear. This study provides a reference for the accuracy of document type assigning of review articles in WoS and Scopus, and the identified pattern for assigning implicit reviews may be helpful to better labeling on websites, WoS and Scopus. This study investigated the assigning accuracy of document type of reviews and identified the some patterns of wrong assignments. [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]

Potentially toxic elements (PTEs) in ecosystems and construction materials pose a significant environmental concern. Various qualitative and quantitative techniques are employed to analyse PTEs in a sample. This study explores an innovative approach that incorporates PTE (Cd, Zn, Cu, Pb) adsorbent ash, specifically adsorbed paper ash (APA) and adsorbed mulch ash (AMA), into mortar composites. This approach offers several advantages, including reduced reliance on waste landfills, energy recovery during the ashing process, and immobilisation of PTEs within a cement matrix. This study evaluated the elemental and microstructural characteristics of mortar composites incorporated with adsorbed ash by using a scanning electron microscope (SEM) equipped with energy-dispersive X-ray spectroscopy (EDS), followed by analysing the elemental maps with ImageJ software version 1.8.0. Parallel experiments were conducted to measure the leaching of mortar composites. The total elemental content of PTEs in the leachate solutions was quantified using an inductively coupled plasma-optical emission spectrometer (ICP-OES). The differences in adsorption capacity and leaching of PTEs observed between paper and mulch can be ascribed to their distinct affinities, which are influenced by the recorded pH levels. The examined elemental mapping revealed a consistent distribution across the APA and AMA mortar matrix structures, with greater intensity than the blank mortar sample. Furthermore, there is a reverse correlation between the order of percentage area coverage of the immobilised elements and the order of leaching, indicating that the PTEs were successfully immobilised. The percentage of PTE area coverage within AMA mortar composites followed the subsequent order: Pb > Cd > Zn > Cu, constituting 32.1 %, 28.6 %, 13.8 %, and 12.4 %, respectively. This order was also observed in the blank mortar composite, with percentages of 12.5 %, 8.6 %, 4.5 %, and 4.2 %, respectively. In the case of the APA mortar composite, the percentage of area coverage followed a different sequence: Cd > Pb > Zn > Cu, representing 27.7 %, 26.6 %, 14.5 %, and 14.1 %, respectively. The results also demonstrated notable improvements in the microstructure of the mortar when AMA and APA are incorporated, which is attributed to the ash additives' micro-filling capacity. The findings contribute to advancing environmentally sound construction practices, with implications for sustainable waste management and pollution mitigation. [ABSTRACT FROM AUTHOR]

Nowadays, space debris is one of the main subjects of discussion regarding satellites in Earth's orbit. Right now, there are about 26,000 orbiting satellites and only few of these satellites are operational. Recently, the Polish space sector has been strongly growing and delivering instruments working in space. The first part of this paper describes the several space instruments designed in the Space Research Centre Polish Academy of Science (SRC PAS). Instruments such as SWI, RPPWI, LPPWI, Ebox or Pre-boxes have been created for a mission to Jupiter named "JUICE". After fulfilling their scientific mission, these instruments can increase the amount of debris in space. This is one of the reasons for taking up the topic of space debris reduction and the use of technical solutions used in this mission for the proposed solution presented later. The second part of this paper describes the new methods related to space debris. The activities can be related to the space debris removal programmes. The paper describes two methods developed by Polish scientists used for removal of space debris. One of them is the new capture method and mechanism designed for it. The special mechanism is based on tubular boom application for opening the net, to capture the space debris. The main parts of the mechanism are mechanisms which have been used in the JUICE space mission. The paper describes the main idea for these new methods, and for the design part prepared the strength confirmation by structural analysis. The main function of the mechanism has been verified by simulations and tests performed in laboratories. [ABSTRACT FROM AUTHOR]

This paper aims to investigate literature on digital maturity modelling in order to build a better understanding of this field of research which is gaining increased attention from both public as well as private institutions. The objective of the study is to outline a clear vision of what the main areas of research related to digital maturity models are and ultimately map out particular research directions that could benefit from further academic attention in the future. For this purpose, a bibliometric analysis was employed, relying on academic publishing data obtained from the Scopus scientific database. After selection and filtering, 468 pieces of literature were deemed relevant and were subsequently mapped for analysis using co-occurrence and bibliographic coupling. Results show that there is an exponential increase in academic attention for digital maturity modelling in the last 3 years, with recent interest being focused towards the manufacturing sector and small and medium sized enterprises, while other expected sectors such as e-government have fallen behind. It has also been found that digital maturity modelling is in a divergent stage, producing a large amount of different models and only in the last year there are signs of attempts at converging existing knowledge into fewer models with a more rigorous, quantitative development. Consequently, this paper proposes that a key direction of research for digital maturity modelling should be the addition of quantitative based evaluation of digital maturity components and their effectiveness as part of a digital maturity model. [ABSTRACT FROM AUTHOR]

Urban digital twin is a key step to build a smart city, digital twin is an important application scenario for smart city platform, and the relationship between the two are both current research hotspots. In this paper, we will start from the demand of digital twin on smart city platform, study the architecture method and key technology of smart city platform, in this paper's platform construction method compared to the traditional construction method, reduces the difficulty of digital twin smart city construction, and also reduces the coupling degree between smart city platform modules, and use a smart city platform for engineering verification. Finally compared with the traditional smart platform construction techniques, the techniques in this paper are better than the traditional ones in terms of coupling, difficulty and cost. Through engineering verification and experimental results show that this paper on the digital twin-oriented smart city construction technology, the coupling degree of each module is the lowest, and in the development efficiency experiments, this paper by comparing with the traditional technology, the experimental development cycle compared to the traditional technology can be shortened by 61.7% of the development cycle, greatly reducing the development cost and improving the construction efficiency. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamics of market synchronicity and International Financial Reporting Standards (IFRS) adoption in Africa. It seeks to determine whether or not IFRS is an augmentor or inhibitor of market synchronicity in Africa. This study is not only a foundational study that unfolds the dynamics of market synchronicity and IFRS adoption in Africa but also extends the scope of synchronicity from firm-level assessment to country-level market synchronicity. It is one of the few studies which have shifted the literature on synchronicity from one largely limited to firm-level synchronicity to country-level synchronicity through analyses of cross-border market synchronisation. It employs Dynamic Ordinary Least Square (DOLS) and Generalised Method of Moments (GMM) to investigate the market synchronicity-IFRS nexus. The study uses monthly data from March 2005 to November 2021 in five African markets: Botswana, Ghana, Namibia, Nigeria, and South Africa generating 1005 observations in an 18-year data span. The paper reveals a significant negative consequence of IFRS on market synchronicity. Thus, IFRS exhibits an inhibition role in market synchronicity (reduces synchronicity) and improves price informativeness. A decreasing pattern was also observed immediately after IFRS was adopted by the stock markets and persisted for about five years. It implies that the price informativeness of stock markets through IFRS makes them good candidates for intra-Africa portfolio diversification due to reduced investors' risk exposure to market synchronicity. [ABSTRACT FROM AUTHOR]

This paper critically examines the claim that Utah is "the most sexist state" in the United States, as suggested by a WalletHub report ranking it lowest in "Women's Equality." Utilizing an economic analysis from the Austrian School perspective, this study scrutinizes the data, metrics, and conclusions of reports by the Utah Women & Leadership Project (UWLP). The analysis focuses on distinguishing statistical disparities from sexism, proposing that observed gender inequalities in Utah are largely influenced by cultural and economic factors, particularly the state's high marriage rate and traditional gender roles. Contrary to the notion that sexism predominantly drives gender disparities, the paper argues that personal choices and subjective value theory play significant roles in shaping these outcomes. The study highlights the importance of considering cultural context, individual preferences, and the marital asymmetry hypothesis when interpreting gender-related data, challenging the assertion that Utah's gender disparities are primarily due to sexist attitudes. The findings suggest that Utah's gender gaps in areas such as income and workforce participation are more accurately attributed to the state's unique cultural and economic landscape rather than pervasive sexism. [ABSTRACT FROM AUTHOR]

The Multi-skilled Resource Constrained Project Scheduling Problem (MS-RCPSP) is a complex and multi-faceted problem that involves scheduling activities whilst considering various resource constraints. These constraints include limited availability of workers, equipment, and materials, with each activity requiring a minimal set of skills to be executed. Furthermore, for a better resemblance to reality, workers/machines are assumed to be multi-skilled/multi-purpose posing another dimension of complexity to the problem. The objective is to minimize project duration, cost, or other relevant criteria while accounting for the inherent resources flexibility. This paper provides a systematic review of the literature pertaining to MS-RCPSP, and an in-depth analysis of 171 papers published between 2000 and 2021 inclusive. The conducted bibliometric analysis identifies the top contributing authors, most influential papers, existing research tendencies, and thematic research topics within the field. In addition, this review highlights different aspects of the MS-RCPSP, spanning the significance of performance measures, solution approaches, application areas, and the incorporation of time constraints. While project completion time, cost, and tardiness are common performance indicators, other measures such as multi-skilled staff assignment and schedule robustness are also deemed important. Although various methods have been employed to solve the MS-RCPSP including exact and approximate approaches, the selection of the most-suited approach depends on the problem's scale, complexity, and constraints, necessitating careful consideration of each method's strengths and weaknesses. Interestingly, several studies have jointly addressed resource and time constraints in the context of MS-RCPSP, often considering tardiness, and have proposed different algorithms, models, and metaheuristics to tackle these challenges. This paper clearly highlights research gaps and promising avenues for future research. This work provides valuable insights for project managers to effectively schedule tasks in the presence of multiple flexible resources. [ABSTRACT FROM AUTHOR]

This paper aims to address the limitations in existing research on the evolution of knowledge flow networks by proposing a meso-level institutional field knowledge flow network evolution model (IKM). The purpose is to simulate the construction process of a knowledge flow network using knowledge organizations as units and to investigate its effectiveness in replicating institutional field knowledge flow networks. The IKM model enhances the preferential attachment and growth observed in scale-free BA networks, while incorporating three adjustment parameters to simulate the selection of connection targets and the types of nodes involved in the network evolution process Using the PageRank algorithm to calculate the significance of nodes within the knowledge flow network. To compare its performance, the BA and DMS models are also employed for simulating the network. Pearson coefficient analysis is conducted on the simulated networks generated by the IKM, BA and DMS models, as well as on the actual network. The research findings demonstrate that the IKM model outperforms the BA and DMS models in replicating the institutional field knowledge flow network. It provides comprehensive insights into the evolution mechanism of knowledge flow networks in the scientific research realm. The model also exhibits potential applicability to other knowledge networks that involve knowledge organizations as node units. This study has some limitations. Firstly, it primarily focuses on the evolution of knowledge flow networks within the field of physics, neglecting other fields. Additionally, the analysis is based on a specific set of data, which may limit the generalizability of the findings. Future research could address these limitations by exploring knowledge flow networks in diverse fields and utilizing broader datasets. The proposed IKM model offers practical implications for the construction and analysis of knowledge flow networks within institutions. It provides a valuable tool for understanding and managing knowledge exchange between knowledge organizations. The model can aid in optimizing knowledge flow and enhancing collaboration within organizations. This research highlights the significance of meso-level studies in understanding knowledge organization and its impact on knowledge flow networks. The IKM model demonstrates its effectiveness in replicating institutional field knowledge flow networks and offers practical implications for knowledge management in institutions. Moreover, the model has the potential to be applied to other knowledge networks, which are formed by knowledge organizations as node units. [ABSTRACT FROM AUTHOR]

The integration of data analytics into forensic accounting has revolutionized the detection and prevention of financial fraud. This paper conducts a comprehensive analysis of recent advancements in this field, highlighting the application of machine learning, data mining, and big data techniques in identifying fraudulent activities. By reviewing the latest research and examining case studies, we demonstrate the enhanced accuracy and efficiency these technologies offer over traditional methods. The findings suggest that financial institutions should adopt these advanced tools to mitigate fraud risks and improve overall financial security. The paper also explores future research directions, emphasizing the need for developing hybrid models and real-time detection systems to further enhance fraud detection capabilities. [ABSTRACT FROM AUTHOR]

This paper documents the resilience of fenye (分野, lit., "field allocation") and its applications through the nineteenth century in China. Despite literati (and eventually imperial) criticisms that the fenye system of correlative cosmography was outdated and unworthy of belief, fenye retained a sizeable audience through the close of the Qing period. At the top, the Qing imperial state continued to reference fenye correlations in its official communications late into the dynasty. In local society, literati looked to newly issued dynastic sources of astrological knowledge to update local gazetteers; in the nineteenth century, these trends were pronounced along frontier areas lacking longstanding gazetteer records. Finally, people engaged in the practice of fengshui looked to fenye knowledge to update the values and layout of the compass, the historical origins of which related to geomantic practices. In the Qing period, the compass was both theoretically and physically altered under the influence of Jesuit-introduced "Western Learning" (Xixue 西學). The paper contends that the status of fenye in pre-twentieth century China was seldom an allor-nothing proposition between a celebrated component of imperial orthodoxy and an outdated relic in inexorable decline: people critiqued fenye, used fenye, and updated fenye. [ABSTRACT FROM AUTHOR]

This study investigated the publication behaviour of 573 chief editors managing 432 Social Sciences journals in Turkey. Direct inquiries into editorial qualifications are rare, and this research aims to shed light on editors' scientific leadership capabilities. This study contrasts insider publication behaviour in national journals with international articles in journals indexed by the Web of Science (WOS) and Scopus. It argues that editors demonstrating a consistent ability to publish in competitive WOS and Scopus indexed journals signal high qualifications, while editors with persistent insider behaviour and strong local orientation signal low qualification. Scientific leadership capability is measured by first-authored publications. Correlation and various regression tests are conducted to identify significant determinants of publication behaviour. International publications are rare and concentrated on a few individuals, while insider publications are endemic and constitute nearly 40% of all national articles. Editors publish 3.2 insider papers and 8.1 national papers for every SSCI article. 62% (58%) of the editors have no SSCI (Scopus) article, 53% (63%) do not have a single lead-authored WOS (Scopus) article, and 89% publish at least one insider paper. Only a minority consistently publish in international journals; a fifth of the editors have three or more SSCI publications, and a quarter have three or more Scopus articles. Editors with foreign Ph.D. degrees are the most qualified and internationally oriented, whereas non-mobile editors are the most underqualified and underperform other editors by every measure. Illustrating the overall lack of qualification, nearly half of the professor editors and the majority of the WOS and Scopus indexed journal editors have no record of SSCI or Scopus publications. This research relies on local settings that encourage national publications at the expense of international journals. Findings should be evaluated in light of this setting and bearing in mind that narrow localities are more prone to peer favouritism. Incompetent and nepotistic editors pose an imminent threat to Turkish national literature. A lasting solution would likely include the dismissal and replacement of unqualified editors, as well as delisting and closure of dozens of journals that operate in questionable ways and serve little scientific purpose. To my knowledge, this is the first study to document the publication behaviour of national journal chief editors. [ABSTRACT FROM AUTHOR]

This article presents an in-depth analysis of global research trends in Geosciences from 2014 to 2023. By integrating bibliometric analysis with expert insights from the Deeptime Digital Earth (DDE) initiative, this article identifies key emerging themes shaping the landscape of Earth Sciences. The identification process involved a meticulous analysis of over 400,000 papers from 466 Geosciences journals and approximately 5,800 papers from 93 interdisciplinary journals sourced from the Web of Science and Dimensions database. To map relationships between articles, citation networks were constructed, and spectral clustering algorithms were then employed to identify groups of related research, resulting in 407 clusters. Relevant research terms were extracted using the Log-Likelihood Ratio (LLR) algorithm, followed by statistical analyses on the volume of papers, average publication year, and average citation count within each cluster. Additionally, expert knowledge from DDE Scientific Committee was utilized to select top 30 trends based on their representation, relevance, and impact within Geosciences, and finalize naming of these top trends with consideration of the content and implications of the associated research. This comprehensive approach in systematically delineating and characterizing the trends in a way which is understandable to geoscientists. Thirty significant trends were identified in the field of Geosciences, spanning five domains: deep space, deep time, deep Earth, habitable Earth, and big data. These topics reflect the latest trends and advancements in Geosciences and have the potential to address real-world problems that are closely related to society, science, and technology. The analyzed data of this study only contain those were included in the Web of Science. This study will strongly support the organizations and individual scientists to understand the modern frontier of earth science, especially on solid earth. The organizations such as the surveys or natural science fund could map out areas for future exploration and analyze the hot topics reference to this study. This paper integrates bibliometric analysis with expert insights to highlight the most significant trends on earth science and reach the individual scientist and public by global voting. [ABSTRACT FROM AUTHOR]

This paper presents a detailed model of low-frequency oscillations and their damping within the Electric Power System (EPS) of Bosnia and Herzegovina (B&H). The system is modeled using MATLAB software, analysing the steady state and dynamic responses. This research highlights the challenges and impacts of integrating renewable energy sources, such as wind farms, on grid stability and oscillation damping. The paper utilizes eigenvalue analysis to investigate the dynamic characteristics of the system, emphasizing the need for efficient damping strategies to maintain system stability. The methodology includes a comprehensive review of existing literature, the creation of a detailed EPS model of B&H, and the application of eigenvalue and oscillation amplitude analysis to determine damping ratios. The dynamic responses of hydro power plants, HPP Mostar and HPP Jablanica, to transient disturbances are analysed to validate the model and refine damping strategies. The results indicate that the B&H EPS is well-damped, with all eigenvalues possessing negative real parts, and demonstrate the system's resilience to small disturbances. The results are compared with the technical report on the integration of the wind power plant WPP Podveležje. This comparative analysis shows consistent patterns between the modeled calculations and empirical data, confirming the robustness of the EPS model. This alignment underscores the effectiveness of current damping mechanisms and provides a foundational strategy for enhancing system stability with increasing renewable energy penetration. The findings highlight the importance of developing advanced control strategies to sustain system stability as the integration of variable renewable energy sources continues to grow. [ABSTRACT FROM AUTHOR]

The aim of this paper is to verify the applicability and accuracy of the Altman model in the case of Slovenian companies. The use of the Altman model is hugely popular and widespread among financiers, analysts and other stakeholders who want to determine the creditworthiness of a company's operations and the likelihood of it running into financial difficulties in the coming years. The study was conducted on a sample of 66 Slovenian companies, which were divided into two equal groups: bankruptcy and non-bankruptcy companies. Based on accounting data for the last five years, the authors of this paper calculated the Z-Score, which is based on the Multiple Discriminant Analysis (MDA). By calculating the statistical error of the estimate (type I and II), the authors verified the extent (in percentage terms) to which the companies had been correctly classified by the model. The Mann-Whitney U test was used to check whether there was a difference in the average Z-Score between the two groups of companies. The authors determined that the reliability of the Altman model was 71.21% when tested at the upper bound (the threshold value of the Z-Score was 2.6) and 80.30% when tested at the lower bound (the threshold value of the Z-Score was 1.1). This is similar to other countries, where the reliability was found to be over 70% in most cases. Despite the lower reliability of the model, the Z-Score proved to be an important factor in differentiating between the two groups of companies, as bankruptcy companies had a lower value of this indicator than non-bankruptcy companies. Based on the results of this study, as well as those of other studies, it can be summarized that the Altman model is a fairly good way for companies to determine the success of their business in a relatively simple and quick way and also to predict the potential risk of their operations in the future. However, since the reliability of the model is not 100%, it is important to be careful when making business predictions and carry out additional in-depth analyses or use other methods. [ABSTRACT FROM AUTHOR]

The International Journal of Management and Economics has released its second issue of 2024, featuring six papers written by authors from various Polish universities and institutions. The papers cover a range of topics, including a comparative analysis of regional labor market differentiation, the negative impacts of social relationships on business activity in the video game industry, key criteria for project evaluation, diverse conceptualizations of the "common good" in the context of European integration during the COVID-19 pandemic, the number and structure of gig workers in Poland, and changes in global value chains during the COVID-19 pandemic. The journal hopes that these papers will provide valuable insights and inspiration to readers. [Extracted from the article]

An editorial is presented which expresses the views on various research papers featured in the International Journal of Management and Economics in 2024. Topics include examining the resilience of organizational startups post-COVID-19, assessing technological changes for energy security, evaluating trends in the leasing sector, and analyzing the impact of Russia's invasion of Ukraine on the EUR/PLN exchange rate.

When loading liquefied natural gas (LNG) onto a dual-fuel LNG container ship fuelled by LNG, there is a considerable temperature difference between LNG and the fuel tank at room temperature. The current solution is to pre-cool the tank with LNG through a spray line but the cooling process, if not correctly handled, can result in excessive cooling rates and Boil-Off Gas (BOG), which can expose the tank to increased temperature stress and gas pressure. Therefore, this paper takes the Mark III fuel tank of a specific type of LNG container ship as the object and realises a real-time predictive control system by writing a UDF (User Defined Function) to simulate and analyse the influence of LNG spray rate on the change of cooling effect, cooling time and cooling cost under the unidirectional LNG spray cooling mode. Compared with the results of the fuel tank gas experiment, the deviation of numerical model simulation results is less than 5%. Under the same cooling rate, the real-time control scheme can achieve a more uniform cooling rate and reduce the total LNG consumption by 25%. With the increase in LNG cooling rate, the cooling time, LNG usage, and the total BOG exhaust volume all decrease; however, the decreased range gradually decreases as well. The results of this paper provide parameters and suggestions for optimising and improving the LNG fuel tank cooling monitoring and control system. [ABSTRACT FROM AUTHOR]

Overall equipment effectiveness (OEE) is a key indicator to measure the effectiveness of production systems. This paper aims to evaluate and improve a plastic production line based on OEE evaluation. An integrated framework is proposed to enhance the production system efficiency. This paper presents the data for a Plastic production line in Jordan under real working conditions. The data covers three months. A framework process to improve the OEE of the Plastic production system was proposed. Six major stoppage losses were inspected with the help of Pareto analysis. Furthermore, the actual availability, efficiency, and quality rate measures, together with the whole OEE for each working day, week, and month of the production line were shown. The methodology is based on determining the OEE of a Plastic production line after determining the causes of failures. The fishbone diagram tool is used to determine the root causes of failures. To improve the OEE measure, several losses are identified. The results reveal that the company should improve its policy to improve the production line's performance and reduce losses. Top management should also pay attention to reducing the speed losses, which consist of 58.1%, and eliminate the planned and unscheduled disruptions covering 12.73% of all losses. This can be achieved by establishing a proper operation management procedure and strategy. This, in turn, optimized the equipment's effectiveness. The quality procedure should include the changeover program that may be executed every day. Similarly, all preventive maintenance procedures for the six machines should be properly executed in predetermined intervals. There are several limitations in the research. Firstly, the research case study is only the plastic production system. Secondly, the research is related to the downtime or stoppage by analyzing it using fishbone diagram. Further, supported by other techniques such as the Pareto chart, six big losses analyses and CED. This research conducted on a Plastic industry. However, similar studies can be carried out in future in other manufacturing industries like electronic, pharmaceutical, textile industries, etc., and service industry. However, as future research work the contributions of this paper with other lean manufacturing concept like six sigma, quality function deployment, TQM, and just-in-time manu-facturing, can also be conducting to assess the overall production line efficiency. On the other hand, several statistical tests can be implemented based on data collected of TPM performance indicators. The proposed method supports policymakers in their decision-making process on the operations management line. Further-more, it improves the production systems' productivity quality, and performance, reducing unplanned stop-pages and breakdowns, and reducing maintenance costs. [ABSTRACT FROM AUTHOR]

The enlargement of the European Union in 2004 marked a significant milestone in the history of European integration, bringing ten new member states into the Union. This paper provides a comprehensive analysis of the economic impact of this enlargement two decades later. Drawing from the economic literature and descriptive analysis, the paper examines both anticipated benefits and realised outcomes. Preceding the enlargement, ex ante analyses projected substantial gains in GDP, trade integration and welfare for both acceding and existing member countries. These expectations were largely met. At the macroeconomic level, the paper shows a significant reduction in trade costs, enhanced trade integration and deepening participation in cross-border value chains within the Single Market. Some challenges remain, however, in terms of social and territorial cohesion in these countries. The lessons learned from this enlargement underscore the continuous nature of integration, beginning with accession preparation and producing tangible effects throughout the process. [ABSTRACT FROM AUTHOR]

A resilient economy is a strong base for large volume of trade as it provides a perfect solution to poverty. Synthesis of Yoruba textiles and modern technology for resilient economy in this turbulent era is the concern of this paper. It highlights how Yoruba indigenous textiles are face lifted by modern technology to eradicate economic downturn. The paper gives insight to improvement on the production of Yoruba textiles therefore giving opportunity of job creation and self-reliance through the fusion. The huge tragedy of the Nigerian experience hinges on the downturn of economy which is at its peak of crashing. Most Nigerian are not believing that indigenous textile contents can increase drastically the income of the nation if facelifted or rebranded. The high rate at which naira is depreciating is very alarming at present ($1USD = ₦ 1440) being because of fluctuation now. The paper projects a way out of economic turbulence with the synthesis of Yoruba textiles and modern technology by building a resilient economy. The paper further discusses the new orientation and training involved; raw materials used, computer knowledge, recommendations, and conclusion. [ABSTRACT FROM AUTHOR]

In this paper we investigate disposal activities in a reverse logistics models with linear costs structure. The two models have different disposal strategy. The first model analyzes a continuous disposal strategy, i.e. disposal can happen in every time in the planning horizon. This type of models was investigated in earlier works. The second possible disposal strategy assumes that disposal is only at the end of the planning horizon. After characterization of the optimal strategies of the two models we compare the costs and the trajectories of the optimal paths. The result of the paper is that the relevant costs are higher in case of disposal at the end of the planning horizon. It is cost efficient to dispose off the not necessary products inside of the planning horizon. [ABSTRACT FROM AUTHOR]