Research Paths Research Articles

Innovative Cultural Transmission Paths Analysis for Local Opera Based on Data Mining

With the rapid development of society and cultural diversity, local opera, as a representative of traditional art, faces dual challenges of inheritance and innovation. The inheritance of traditional Chinese opera often relies on oral instruction, but in modern society, this method is no longer suitable for the rapidly changing cultural environment. The purpose of this study is to explore in depth the innovative cultural dissemination path of local opera through data mining techniques. This paper uses data mining techniques to explore and analyze the inheritance of innovative culture in local opera, and to study the inheritance paths. This paper proposes a data mining-based method for analyzing and identifying the paths of inheritance of innovative culture in local opera. This paper focuses on two aspects of technology clustering and technology theme association, and the research paths are divided into flexible clustering based on data enhancement and technology evolution path identification based on theme extraction. Firstly, the heritage changes of dating tunes are discussed. Secondly, the unique artistic esthetics of the dating tune is compared with the artistic characteristics of Henan opera and the three-stringed book. Through the research and learning experience of the Dai Yongqu, it is easier to thoroughly understand the artistic essence and cultural connotation of the Dai Yongqu, and that exposure to the Dai Yongqu is a process of touching traditional culture. In the text clustering section, the data co-occurrence frequency matrix is constructed based on the results of multiple clustering, transforming the problem of determining the number of clusters into a co-occurrence frequency problem with semantic information of the text, thus achieving the purpose of flexible clustering on demand. In a comparison with existing methods, the text representation method using data-enhanced coding achieves better semantic coding results. The flexible clustering method can differentiate the data better than the clustering method with a defined number of clusters and obtains clustering results with high intra-class similarity and high inter-class differentiation.

Inaction inertia in online shopping: impact of promotional formats and sequence

PurposeInaction inertia occurs when people are less likely to act on a similar but inferior option after missing a superior opportunity, compared to if they had not missed out. This study aims to explore how promotional formats and their sequence affect the inaction inertia effect in online shopping, under the assumption of economic equivalence.Design/methodology/approachThe authors performed two online experiments and analyzed the data by analysis of variance.FindingsThe findings indicate that, under the premise of economic equivalence: Monetary promotions exhibit a higher inaction inertia effect on consumers than nonmonetary promotions. When consumers miss a more favorable promotion and subsequently encounter a relatively less attractive one presented in a different promotional format, the inaction inertia effect is lower than when reencountering the same promotion format. When consumers miss a better monetary promotion and presently encounter a relatively less attractive nonmonetary promotion, the inaction inertia effect is lower than when they miss a superior nonmonetary promotion and currently encounter a relatively less attractive monetary promotion.Originality/valueThis study reveals the sequence effects of promotional formats, indicating that nonmonetary promotions following monetary ones effectively reduce inaction inertia. A strategically sequenced set of formats enhances consumer recommendations, mitigating inaction inertia. These findings open new research paths, providing insights into the impact of promotional format sequences on the inaction inertia effect. Consequently, this knowledge helps e-retailers in implementing effective promotional strategies and driving online purchases.

Enhancing Efficiency and Security in MTC Environments: A Novel Strategy for Dynamic Grouping and Streamlined Management

This study presents a new strategy to improve security and efficiency in Machine-Type Communication (MTC) networks, addressing the drawbacks of the existing Adaptive Hierarchical Group-based Mutual Authentication and Key Agreement (AHGMAKA) protocol. The AHGMAKA protocol, crucial for securing communication within groups of devices with limited resources, has been found to cause significant operational delays and inefficiencies. Our proposed solution integrates advanced cryptographic methods, including an optimized Authenticated Message Authentication Code (AMAC) and lightweight encryption, sophisticated optimization algorithms for dynamic grouping, and an efficient, lightweight group management protocol. It also introduces adaptive network management strategies to customize performance according to the needs of MTC networks. The effectiveness of this approach has been validated through empirical analysis, showing considerable improvements in operational performance and energy efficiency. These improvements mark a significant step toward achieving an optimal balance between efficiency and security for MTC networks. However, the research acknowledges ongoing challenges, including the trade-off between security and efficiency and the issue of compatibility with older devices, suggesting these as areas for future study. The paper outlines potential research paths, including using machine learning for better group management, adopting post-quantum cryptographic methods, applying hardware acceleration, and pushing to standardize these technologies. This work significantly advances the field of secure and efficient communication in MTC, a critical component of the growing Internet of Things (IoT) landscape, setting the stage for future breakthroughs.

Amerindian poetics: a reading of anthroposemiotic enunciation

By proposing the ability to deal with the widest possible range of texts, semiotic theory seeks above all to shed light on the processes of constructing meaning. For this work, we intend to make use of developments in the theory, such as the notion of anthroposemiotic enunciation (Fontanille, 2019) and the tensive arc of the work (Mancini, 2020), with the aim of analyzing Amerindian poetic productions. The shamanic translations of the Marubo peoples, undertaken by anthropologist Pedro Cesarino (2011), constitute the corpus chosen for analysis. The issues addressed are listed in the following order: the transposition of oral literature into writing; the presence of mnemonic language; and the multipositionality of voices present in the songs. Although semiotic theory has gaps that make it impossible to encompass all the complexity of productions that escape the Western model, we believe we have presented the necessary foundations to engender new research paths that allow us to think about an epistemology of diversity (or diversity of epistemologies?).

Optimized wireless communication for 6G signal processing using memory‐augmented deep unfolding network

SummaryIn this manuscript, optimized wireless communication for 6G signals processing using memory‐augmented deep unfolding network (WC‐6G‐SP‐MADUN) is proposed. The aim of this work is to give a memory‐augmented deep unfolding network approach with a focus on belief propagation decoding of error correction codes and multiple‐input multiple‐output (MIMO) wireless systems. In contrast, compares and tabulates the performance of memory‐augmented deep unfolding methodologies with classic principled procedures, which could potentially enable 6G. Here, the wireless communication for 6G signal processing methods was used for a variety of receiver functions, including self‐interference cancelation, signal estimation and detection using memory‐augmented deep unfolding Network (MADUN), and advanced error correction by clouded leopard optimization algorithm (CLOA). Furthermore, outline the general framework of memory‐augmented deep unfolding method for any kind of signal processing application and talk about cutting edge research paths that will make it possible to build communication networks in the future. The proposed approach is implemented in MATLAB; the performance is analyzed with performance metrics such as reliability, complexity, SNR gain, convergence rate, hardware efficiency, and quantization bit width. The proposed approach attains higher SNR gain 17.96%, 24.75%, and 30.09%; lower complexity 17.92%, 23.41%, and 30.13%; and higher convergence 18.01%, 25.41%, and 31.39% when analyzed with existing techniques such as redefined wireless communication for 6G: signal processing meets deep learning and deep unfolding (RWC‐6G‐SP‐DU), lower complication deep unfolded neural network receiver for MIMO under probability data association detector (LC‐DUNN‐MIMO‐PDAD), and deep learning in physical layer communications: evolution with prospects on 5G and 6G networks (DL‐PLC‐6G), respectively.

Evolving Attitudes of Science Graduate Students Toward Science Policy and Communication

Widespread changes in the exchange and politicization of science have made it imperative for scientists to be prepared to engage in science communication and science policy. Separately, science graduate students express interest in a more diverse array of career trajectories beyond the traditional academic research path. These forces together inspire changes to graduate education to develop critical science communication and policy skills. However, universities remain focused on training students in primarily academic research skills. This case study measured changes to beliefs about and participation in science communication and policy among science graduate students over three years to better understand the evolution of interest in these practices. Importantly, not only did students report a significantly increased interest in and belief in the importance of science communication and policy, but also these increases were observed regardless of their initial beliefs. Graduate students also provided qualitative feedback about the reasons behind these changes and perceived barriers to participating in science communication and policy. These data help to both motivate universal changes to graduate education to include science communication and policy and to inform stakeholders on how these changes can be optimally designed to address barriers and interests. Finally, corresponding policy changes are recommended to departments, universities, scientific societies, and other stakeholders to enact effective change to graduate training.

Prescribing Change: Unpacking Privatization's Impact on Government Teaching Hospitals in Punjab, Pakistan

Lack of financial support is one of the main causes of low-quality services in Government teaching hospitals of developing countries. Recent recommendations for privatization of government teaching hospitals were aimed at improving the services to that of private teaching hospitals. The strategy is expected to increase the efficiency & performance of government teaching hospitals and generate revenues for their continued improvements. The measuring dimensions of hospital performance not only predict the financial performance of a hospital, but also provide assessment on steps required for betterment of the Government teaching hospital. The non-financial performance of a hospital setting is based on non-financial variables such as Reliability, waiting time, sanitary facility, hygiene and information unique to particular treatment. Good human resource practices are one of the key components that may predict the monetary & non-monetary performances of a hospital. This study demonstrated these variables along with their dimensions across the whole public teaching hospitals settings in Lahore Punjab with a sample size of 300 respondents. Respondents were highly qualified Doctors, Nurses and administration staff of public teaching hospitals Lahore, Punjab. Smart PLS-4 was used as a statistical tool and ran reliability, mediation analysis and linear correlation for research findings. The results have been found significant that hospital performance can be increased through privatization. Although there are some limitations such as it was limited to public teaching hospitals only. Public DHQs (District Head-quarters), THQs (Tehsil Head-quarters) & RHC (Rural Health Centers) were not part of study. The opted variables to assess the hospital performance were not total markers, so for future research there is a path for researchers to opt the rest variables to explore the further significance.

Gas-driven triboelectric nanogenerator for mechanical energy harvesting and displacement monitoring

Gas as an energy carrier has been widely studied, ranging from small bubble motions to steam strike turbines. Despite the remarkable results, fewer studies have investigated the gas-driven liquid column movement commonly used in hydraulic systems, oil extraction, and other fields. Herein, we proposed a gas-driven triboelectric nanogenerator (GD-TENG) with liquid column motion for mechanical energy harvesting and displacement monitoring. When the gas drives a single liquid column to move inside a polytetrafluoroethylene (PTFE) tube, the solid-liquid interface of the GD-TENG can achieve efficient sliding friction and generate an open-circuit voltage of 15.9 V. Meanwhile, the influence of some critical parameters such as liquid column length, PTFE tube wall thickness and liquid column motion speed on the output performance of the GD-TENG were systematically investigated. Furthermore, the GD-TENG can successfully harvest mechanical energy to power microelectronic devices. A sensing system was designed based on the GD-TENG device for displacement monitoring of moving objects. This work provides a new research path in the field of mechanical energy harvesting and self-powered displacement monitoring.

Validation Evidence for the Oviedo Grit Scale (EGO) in a Non-Western Context

Grit is a positive non-cognitive characteristic related to perseverance and passion for long-term goals. It positively impacts various aspects of life, but limited tools are available for measuring it, particularly in Turkish. Thus, this research aimed to establish the psychometric values for the Turkish version of the Oviedo Grit (EGO) scale by Postigo et al. (2021). The sample consisted of 500 Turkish university students. The analyses for single items, structural validation, measurement invariance, and the scale’s relationship with personality traits (i.e., big five personality dimensions) and external variables (i.e., grade point average) supported the claim that the EGO scale, originally developed in Spanish by Postigo et al. (2021), is a reliable, unidimensional tool to measure grit Turkish language. Some limitations and potential paths for future research were also discussed.

Research Map on Marketing Law Studies Based on Scopus Database

This study aims to see the development of research on the topic of "Marketing Law" and research plans that can be carried out based on journals published on the theme. This research uses a qualitative method with a bibliometric analysis approach. The data used is secondary data with the theme "Marketing Law" which comes from the Scopus database with a total of 192 journal articles. Then, the data is processed and analyzed using the VosViewer application with the aim of knowing the bibliometric map of "Marketing Law" research development in the world. The results of the study found that in bibliometric author mapping, the authors who published the most research with the theme "Marketing Law" were Petty R. D; Yahelson Y; Pressey A. D; Renke S.; Steennot R; and Shimpock-Vieweg K. Furthermore, based on bibliometric keyword mapping, there are 3 clusters with the most used words are legislation, product, ambush marketing, strategy, change, and implementation. Then, the research path topics related to marketing law are Future trends in marketing law, Legal implications of brand advertising and EU law and ambush marketing.

Enhanced X-wave recognition in ECG signal using max–min thresholds and detection of QRS complex

Due to the advantages of Electrocardiogram (ECG) signals, which are challenging to replicate yet easy to get, ECG-based identification has become a new path in biometric recognition research. These classic feature extraction techniques require Hand-crafted or feature-specific implications. The methods used for selection and integration of features, are time-consuming. The main objective of this study is develop deep learning approach to study the features of ECG data digital characteristics, thus saving a lot of signal pre-processing steps. This research proposed novel technique in X-wave recognition of ECG signal using max-min threshold technique and classification of ECG signal. This signal has been processed for noise removal and normalization. Then this processed signal has been used to recognize X-wave from ECG signal. From recognized X-wave, the ECG signal has been classified using Improved Support Vector Machine (ISVM). The QRS complex has been detected using Stacked Auto-Encoder with Neural Networks (SAENN). The study took raw ECG signals and entropy-based features evaluated from extracted QRS complexes. Exams are based on classifying heart disorders into two, five, and twenty classes. The experimental findings showed that our suggested model attained a high classification accuracy of 97%, precision of 89%, recall of 90%, F-1 score of 88%.

Analysing the Cyanobacterial PipX Interaction Network Using NanoBiT Complementation in Synechococcus elongatus PCC7942.

The conserved cyanobacterial protein PipX is part of a complex interaction network with regulators involved in essential processes that include metabolic homeostasis and ribosome assembly. Because PipX interactions depend on the relative levels of their different partners and of the effector molecules binding to them, in vivo studies are required to understand the physiological significance and contribution of environmental factors to the regulation of PipX complexes. Here, we have used the NanoBiT complementation system to analyse the regulation of complex formation in Synechococcus elongatus PCC 7942 between PipX and each of its two best-characterized partners, PII and NtcA. Our results confirm previous in vitro analyses on the regulation of PipX-PII and PipX-NtcA complexes by 2-oxoglutarate and on the regulation of PipX-PII by the ATP/ADP ratio, showing the disruption of PipX-NtcA complexes due to increased levels of ADP-bound PII in Synechococcus elongatus. The demonstration of a positive role of PII on PipX-NtcA complexes during their initial response to nitrogen starvation or the impact of a PipX point mutation on the activity of PipX-PII and PipX-NtcA reporters are further indications of the sensitivity of the system. This study reveals additional regulatory complexities in the PipX interaction network, opening a path for future research on cyanobacteria.

Quantitative Proteomics of COVID-19 Recovered Patients Identifies Long-Term Changes in Sperm Proteins Leading to Cellular Stress in Spermatozoa.

Following an initial recovery, COVID-19 survivors struggle with a spectrum of persistent medical complications, including fatigue, breathlessness, weight loss, hair loss, and attention deficits. Additionally, there is growing evidence of adverse effects of COVID-19 on the male reproductive system. This investigation seeks to understand the long-term ramifications on male fertility by examining hormonal profiles, semen parameters, and sperm proteome of recovered COVID-19 patients compared to controls. The serum hormone profiles between the two groups showed minimal variations except for prolactin, cortisol, and testosterone levels. Testosterone levels were slightly lower, while prolactin and cortisol were elevated in COVID-19 cases compared to controls. Though semen parameters exhibited no significant disparities between the COVID-19 and control groups, quantitative proteomics analysis revealed changes in sperm proteins. It identified 190 differentially expressed proteins, of which 161 were upregulated and 29 downregulated in COVID-19 cases. Western blotting analysis validated the differential expression of serpin B4 and calpain 2. Bioinformatics analysis signifies cellular stress in the spermatozoa of COVID-19 recovered patients and thus, SOD and MDA levels in semen were measured. MDA levels were found to be significantly elevated, indicating lipid peroxidation in COVID-19 samples. While the effects of COVID-19 on semen parameters may exhibit a potential for reversal within a short duration, the alterations it inflicts on sperm proteome are persisting consequences on male fertility. This study paves the path for further research and emphasizes the significance of comprehending the complex molecular processes underlying the long-term consequences of COVID-19 on male reproductive health.

A systematic literature review of crisis management in online public opinion: evolutionary path and implications for China

PurposeThis study aims to explore the dissemination and evolutionary path of online public opinion from a crisis management perspective. By clarifying the influencing factors and dynamic mechanisms of online public opinion dissemination, this study provides insights into attenuating the negative impact of online public opinion and creating a favorable ecological space for online public opinion.Design/methodology/approachThis research employs bibliometric analysis and CiteSpace software to analyze 302 Chinese articles published from 2006 to 2023 in the China National Knowledge Infrastructure (CNKI) database and 276 English articles published from 1994 to 2023 in the Web of Science core set database. Through literature keyword clustering, co-citation analysis and burst terms analysis, this paper summarizes the core scientific research institutions, scholars, hot topics and evolutionary paths of online public opinion crisis management research from both Chinese and international academic communities.FindingsThe results show that the study of online public opinion crisis management in China and internationally is centered on the life cycle theory, which integrates knowledge from information, computer and system sciences. Although there are differences in political interaction and stage evolution, the overall evolutionary path is similar, and it develops dynamically in the “benign conflict” between the expansion of the research perspective and the gradual refinement of research granularity.Originality/valueThis study summarizes the research results of online public opinion crisis management from China and the international academic community and identifies current research hotspots and theoretical evolution paths. Future research can focus on deepening the basic theories of public opinion crisis management under the influence of frontier technologies, exploring the subjectivity and emotionality of web users using fine algorithms and promoting the international development of network public opinion crisis management theory through transnational comparison and international cooperation.

Of power, knowledge and method: The influence of Michel Foucault in accounting history

Michel Foucault's work had a strong influence not only in philosophy but also in a wide range of humanistic and social disciplines, including accounting. Notably, the first studies which brought Foucault's thought to the attention of interdisciplinary accounting scholars were historical. This article documents how Foucault's ideas have directly inspired accounting history scholars, how the latter have interpreted and brought Foucault's work into their field as well as what future research paths may lie ahead. The article offers a systematisation of how the complex ideas of Foucault have been translated into eight key themes that have provided a crucial interpretive prism to many studies in accounting history. In doing so, it assists scholars wishing to familiarise themselves with Foucault's work and employ it in their research.

The prominent and heterogeneous gender disparities in scientific novelty: Evidence from biomedical doctoral theses

Scientific novelty is the essential driving force for research breakthroughs and innovation. However, little is known about how early-career scientists pursue novel research paths, and the gender disparities in this process. To address this research gap, this study investigates a comprehensive dataset of 277,288 doctoral theses in the biomedical sciences authored by US Ph.D. graduates. Spanning from 1980 to 2016, the data originates from the ProQuest Dissertations & Theses Database. This study aims to shed light on Ph.D. students’ pursuit of scientific novelty in their doctoral theses and assess gender-related differences in this process. Using a combinatorial approach and a pre-trained Bio-BERT model, we quantify the scientific novelty of doctoral theses based on bio-entities. Applying fractional logistic and quantile regression models, this study reveals a decreasing trend in scientific novelty over time and heterogeneous gender disparities in doctoral theses. Specifically, female students consistently exhibit lower scientific novelty levels than their male peers. Under the supervision of female advisors, students tend to produce doctoral theses that exhibit lower levels of novelty compared to those supervised by male advisors. The significant interaction effect of female students and female advisors suggests that female advisors may amplify gender disparities in scientific novelty. Moreover, heterogeneous gender disparities in scientific novelty are identified, with non-top-tier universities displaying more pronounced disparities, while the gender differences at higher percentile ranges of scientific novelty scores were comparatively more minor. These findings indicate a potential underrepresentation of early-career female scientists pursuing novel research. Notably, the outcomes of this study hold significant policy implications for advancing the careers of female scientists.

Magnetism and electronic properties of ConMoP (n = 1 ~ 5) cluster: a DFT study.

Hydrogen has emerged as a promising clean energy carrier, underscoring the imperative need to comprehend its adsorption mechanisms. This study delves into the magnetic and electronic properties of Co-Mo-P clusters, aiming to unveil their catalytic potential in hydrogen production. Employing density functional theory (DFT), we optimized cluster configurations and scrutinized their magnetic behaviors. Our investigation unveiled 16 stable configurations of the ConMoP (n = 1 ~ 5) cluster, predominantly in steric forms. The magnetic attributes were primarily ascribed to the d orbitals of Co metal atoms, with Co3MoP exhibiting exceptional magnetic characteristics. Analysis of density of state diagrams revealed the prevalence of spin-up α-electrons in d orbitals, while spin-down β-electrons attenuated overall magnetic properties. Localized orbital (LOL) analysis highlighted stable covalent bonds within the clusters, affirming their catalytic potential. Orbital delocalization index (ODI) analysis revealed diverse spatial distribution ranges for orbitals across different configurations, suggesting a progressive attenuation of off-domain properties with increasing cluster size. Furthermore, infrared spectroscopy unveiled distinct vibrational peaks in various configurations, indicative of unique infrared activities. These findings contribute to a nuanced theoretical understanding of Co-Mo-P clusters and pave the path for future research aimed at augmenting their catalytic efficiency in hydrogen production. This study underscores the viability of Co-Mo-P clusters as alternatives to conventional Pt catalysts, offering insights into the design of novel materials for sustainable energy applications. Further research is warranted to explore the behavior of the Co-Mo-P system under diverse reaction conditions, fostering advancements in materials and energy science. In this study, we harnessed the ConMoP (n = 1 ~ 5) cluster as a simulation platform for probing the local structure of the material. Our aim was to scrutinize the magnetism, electronic characteristics influenced by the varying metal atoms within these clusters. A systematic exploration involved incrementing the number of metal atoms and expanding the cluster size to elucidate the corresponding property variations. Density functional theory (DFT) calculations were pivotal to our methodology, employing the B3LYP hybrid functional implemented in the Gaussian16 software package. The ConMoP (n = 1 ~ 5) cluster underwent optimization calculations and vibrational analysis at the def2-tzvp quantization level, yielding optimized configurations with diverse spin multiplet degrees. To comprehensively characterize and visually represent the stability, electronic features, and catalytic attributes of these configurations, we employed a suite of computational tools. Specifically, quantum chemistry software GaussView and wave function analysis software Multiwfn played integral roles. Through the integrated use of these computational tools, we acquired valuable insights into the magnetism, electronic characteristics of the ConMoP (n = 1 ~ 5) cluster, shedding light on their dependency on distinct metal atoms.

A Review on Wire-Laser Directed Energy Deposition: Parameter Control, Process Stability, and Future Research Paths

Wire-laser directed energy deposition has emerged as a transformative technology in metal additive manufacturing, offering high material deposition efficiency and promoting a cleaner process environment compared to powder processes. This technique has gained attention across diverse industries due to its ability to expedite production and facilitate the repair or replication of valuable components. This work reviews the state-of-the-art in wire-laser directed energy deposition to gain a clear understanding of key process variables and identify challenges affecting process stability. Furthermore, this paper explores modeling and monitoring methods utilized in the literature to enhance the final quality of fabricated parts, thereby minimizing the need for repeated experiments, and reducing material waste. By reviewing existing literature, this paper contributes to advancing the current understanding of wire-laser directed energy deposition technology. It highlights the gaps in the literature while underscoring research needs in wire-laser directed energy deposition.

The Modernity in the Creation of Shen Congwen’s Western Hunan Novels

Shen Congwen’s novels of western Hunan provide inspiration and warning for reality. Using literature research from various angles, this paper explains the reasons for the modernity of Shen’s Western Hunan novels, which resonate with contemporary thoughts. The depiction of pure and noble human nature and the tranquil living environment in his works make up for the missing mental support of modern urban residents. This paper chooses Shen Congwen’s masterpieces, the text “Border Town,” “Xiao Xiao,” and “San San,” to discuss their characteristics about the context of their creation. Furthermore, it examines the relationship between social development and individual growth. Shen Congwen’s works convey the importance of maintaining individual freedom and consciousness, which continues to serve as a spiritual warning for modern urban residents. This conclusion opens up a path of research in which the development of human society cannot be separated from the internal support of literary works.

The present and future of QCD

This White Paper presents an overview of the current status and future perspective of QCD research, based on the community inputs and scientific conclusions from the 2022 Hot and Cold QCD Town Meeting. We present the progress made in the last decade toward a deep understanding of both the fundamental structure of the sub-atomic matter of nucleon and nucleus in cold QCD, and the hot QCD matter in heavy ion collisions. We identify key questions of QCD research and plausible paths to obtaining answers to those questions in the near future, hence defining priorities of our research over the coming decades.