bluuebunny/crossref_metadata_2025_split huggingface dataset:
Damage detection and localization of structural cracks based on dynamic attention based transformer
Authors: Honarjoo Ahmad , Darvishan Ehsan , Rezazadeh Hassan , Kosarieh Amir Homayoon 
Published: December 2024

PurposeThis article addresses the need for a comprehensive model for structural crack detection in the context of structural health monitoring. The main innovation of this research is the introduction of a dynamic attention-based transformer model that significantly enhances the accuracy and efficiency of detecting and localizing cracks in structures. This study seeks to overcome previous limitations and contribute to advancements in structural health monitoring practices.Design/methodology/approachThe research focuses on three primary computer vision tasks: classification, object detection and semantic segmentation applied to crack detection in concrete, brick and asphalt structures. The proposed approach employs transformer encoders with dynamic attention mechanisms to assess the severity and extent of damage accurately.FindingsIn this study, we propose a dynamic attention-based transformer model for structural crack detection, achieving a remarkable accuracy of 99.38% and an impressive F1 score. Our method demonstrates superior performance compared to existing techniques, such as the fusion features-based broad learning system and deep convolutional neural networks, while also significantly reducing execution time, highlighting its efficiency and potential for practical applications in structural health monitoring.Originality/valueThis research introduces a novel framework for crack detection, leveraging recent advancements in deep learning technology, with significant implications for the field of civil engineering and maintenance.
The predictive power of technology leadership and green HRM toward green innovation, work engagement and environmental performance
Authors: Abdelwahed Nadia A. Abdelmegeed 
Published: December 2024

PurposeDeveloping and maintaining green innovation (GI) and environmental performance (EP) has become a significant challenge for every organization. The present paper attempts to confirm the contributions of technology leadership (TL) and green HRM (GHRM) to green work engagement (GWE), GI and EP. The study also recognizes GWE’s contribution to connecting TL, GHRM, GI and EP.Design/methodology/approachThe study applies a deductive approach where data are gathered through questionnaires from employees of manufacturing firms in Egypt. Consequently, the study utilizes 312 cases to draw its conclusions.FindingsWith regard to analysis, the researcher used path analysis through AMOS and established a positive effect of TL on GI and EP but a negative on GWE. GHRM has been confirmed to predict GWE, GI and EP positively. Furthermore, GWE positively influences GI and EP among the employees of manufacturing firms in Egypt. The indirect paths establish a significant contribution of GWE in developing the links between TL and EP, GHRM, GI and EP. On the other hand, it negatively affects the link between TL and GI.Practical implicationsThe study assists employers in setting green goals for their employees by offering the required knowledge, skills and training for green environmental management. The study also benefits employees’ workplace green behaviors in performance appraisals and promotions.Originality/valueThe study’s originality assists in overcoming the remaining gaps in the literature by enriching the penetration of the literature from a developing context.
Impacts of supply chain finance on supply chain resilience: empirical evidence from a dynamic capability perspective
Authors: Lu Qiang , Lu Wanfei , Jiang Yu , Zhang Qian 
Published: December 2024

PurposeIn a volatile and highly dynamic business environment, supply chain operations face various challenges. This study, grounded in dynamic capability theory (DCT), investigates how supply chain collaboration (SCC) and supply chain transparency (SCT) influence the relationship between supply chain finance (SCF) and supply chain resilience (SCR) in manufacturing firms. This demonstrates the intrinsic mechanism between SCF and SCR, which provides insights for relative research.Design/methodology/approachThe quantitative research approach was utilized. Employing data collected from 289 Chinese manufacturing firms, structural equation modeling is conducted to test the theoretical hypotheses.FindingsThe research findings have revealed that SCF has a positive impact on SCC and SCT and SCC has a positive impact on SCT. Moreover, both SCC and SCT can improve SCR, and SCT plays a positive mediating role between SCC and SCR.Practical implicationsThis study provides insightful ideas for managers in enhancing SCR by considering SCF. Moreover, this study highlights the concrete responses firms should do to improve SCC and SCT, thus managers can develop more effective strategies to optimize SCR.Originality/valueThis study contributes to the extant literature on improving SCR through SCF, considering the two dimensions of dynamic capability (i.e. SCC and SCT), which explains the intrinsic mechanisms by which SCF affects SCR. This study also broadens the scope of application of DCT.
The generation and influence of colleague-oriented deviant behavior
Authors: Wang Xianghui , Chu Shuai 
Published: December 2024

PurposeThe colleague-oriented deviant behavior greatly affects the sustainable development of enterprises. Research on how colleague-oriented deviant behavior occurs and its consequences is limited. This empirical study will explore what factors lead to colleague-directed deviant behavior and what consequences will occur when colleague-directed deviant behavior occurs from three aspects: organizational management model, workplace deviant behavior and employee psychology.Design/methodology/approachThe paired data of 283 employees and supervisors were collected using a seven-point scale to assess important concepts such as abusive supervision, negative colleague-directed behaviors, emotional exhaustion and negative affective traits. Structural relationships among these factors were analyzed using principal component analysis and exploratory factor analysis, employing a simultaneous equation model.FindingsThe findings suggest that abusive supervision (external factor) and negative emotional traits (internal factor) produce negative colleague-oriented deviant behavior, and when negative colleague-oriented behavior is produced, employees experience emotional exhaustion. In addition, there was a significant negative correlation between employees’ emotional exhaustion and employees’ working years, with the more the employees’ working years, the less likely they were to be emotionally exhausted by negative colleague-oriented deviant behavior.Originality/valueThis study is the first to show that the colleague-oriented deviant behavior can lead to emotional exhaustion among employees, especially those with fewer years of experience. Organizations should improve business ethics by reducing abusive supervision, increasing the proportion of employees with longer working experience and opening professional psychological counseling services to mitigate the generation and influence of colleague-oriented deviant behavior.
Exploring the impact of a four-day workweek on sustainable people management: a systematic review of the literature
Authors: Araújo Ana , Rodrigues Ana Cláudia , Ferreira Marisa R. 
Published: December 2024

PurposeSustainability, based on the principles of sustainable development, is supported through human resource management practices that enable the attraction, development and efficient management of organizations' employees. These sustainable practices bring various benefits to organizations, the environment and their employees, so should consider how employees are treated and how their well-being is promoted through actions that value their health, development, work–life balance and the provision of adequate working conditions.Design/methodology/approachWe conducted a bibliometric analysis and a systematic literature review. We identified 644 records from the past 52 years related to the four-day workweek and performed a two-step analysis. From these records, we selected 104 organizational-focused papers and analyzed them using VOSViewer. We categorized this initial sample into 10 clusters across five dimensions: societal, environmental, organizational, family and individual. In the second step, we thoroughly examined eight papers to understand the impact of this work arrangement on people management. Our analysis revealed that the primary effects of a four-day workweek are improved satisfaction, productivity and work–life balance.FindingsFindings show that four-day workweek is mainly studied at a macro-level, and it still lacking research at the organizational level, namely on the people management topic. However, it was possible to identify elements that are considered fundamental to take into account for the success of organizations that intend to adopt this working method, namely employee satisfaction, production levels and the balance between their personal and professional life.Practical implicationsThe study’s development is crucial for academia and entrepreneurship, serving as a foundation for future research on the impact of the four-day workweek on people management. The detailed characterization of scientific documents and identification of the most relevant aspects in pertinent areas provides a foundation for understanding and exploring this work model. It underscores the importance of considering factors such as satisfaction, productivity and work–life balance, exposing different results obtained in various scientific productions and offering a detailed view of the existing literature on this topic.Originality/valueFindings show that four-day workweek is mainly studied at a macro-level, and it is still lacking research at the organizational level, namely on the people management topic. However, it was possible to identify elements that are considered fundamental to take into account for the success of organizations that intend to adopt this working method, namely employee satisfaction, production levels, and the balance between their personal and professional life.
Measuring service-dominant orientation (SDO): a firm-based approach
Authors: Nguyen Tuan Van , Le Nguyen-Hau 
Published: December 2024

Purpose
For developing and testing service-dominant logic (SDL)-based midrange theories of marketing, the operationalization of SDL into the managerial concept of service-dominant orientation (SDO) and its measures is imperative. However, existing scales found in the literature are insufficient and incomplete. This study aims to develop and validate an alternative firm-based scale for measuring SDO.

Design/methodology/approach
The established procedure for scale development was adopted which comprised three phases. First, a mix of qualitative study and literature deduction was applied to conceptualize and define SDO. Second, based on quantitative data (Study 1, N = 228 cases), scale development and refinement were undertaken. Finally, another data set (Study 2, N = 379 cases) was used to validate the scale.

Findings
SDO is defined as a set of managerial principles that govern all marketing processes and activities of a firm at strategic and operational levels so that they conform to SDL tenets. It is a second-order construct comprising four dimensions: customer solution, customer interaction, customer co-creation and system-based orientation. The suggested scale consists of 15 reflective items in total.

Originality/value
This SDO scale is viewed from and assessed by a firm’s strategic managers which covers all internal and external marketing aspects of the firm’s operation. It is different from a customer perspective or cultural perspective as used in the scales existing in the literature.
A systematic review of current trends in artificial intelligence in foreign language learning
Authors: Alhusaiyan Eman 
Published: December 2024

PurposeThis study aims to examine the trends and advancements in AI-supported language learning over the past decade. By analyzing 15 empirical research articles, the study seeks to fill the gap in understanding the effectiveness and challenges of AI-assisted language learning for both first- and second-language learners.Design/methodology/approachThe research utilizes activity theory, which includes seven components: tool, subject, object, rules, community, division of labor and outcome. This theoretical framework helps to reveal the dynamic interactions and contradictions among these elements. The selection and screening process for relevant articles followed the PRISMA method, ensuring a systematic and comprehensive review.FindingsThe study found that AI-supported technology shows promise in enhancing language learning, particularly in areas such as writing quality, scoring accuracy and learner engagement. However, challenges remain in terms of dialogic competence and the necessity of teacher intervention in pedagogical design. While AI-supported systems can effectively aid in language acquisition, improvements are needed to foster language use for communication and collaborative design.Research limitations/implicationsThe review highlights the need for more empirical studies on the pedagogical impacts of AI-supported language learning and the engagement levels of both learners and teachers. It also underscores the importance of investigating the application of AI-assisted language learning in actual classroom environments.Practical implicationsThe implications of this study offer significant insights for both educational practice and future research in AI-supported language learning. As AI technologies continue to evolve, their potential to enhance learning outcomes and support teachers’ efforts becomes increasingly apparent. However, effective implementation requires not only the availability of technological tools but also proper pedagogical integration and teacher intervention. Furthermore, AI presents unique opportunities to personalize learning and foster collaboration among learners, aligning with the growing trend of hybrid learning environments.Originality/valueThis paper addresses the need for a comprehensive review of AI’s role in language education, providing insights into emerging trends and identifying areas for future research. It emphasizes the importance of integrating AI tools with educational theories and the necessity of teacher configuration in enhancing AI-supported language learning.
Research on velocity measurement and location method based on improved Kalman filter algorithm
Authors: Zhang Zhao , Yang Jie , Jiang Jusong 
Published: December 2024

Purpose
This paper aims to propose a novel adaptive Kalman filter (APRKF) designed to accommodate the operational environment of maglev pipeline trains, enhancing positioning accuracy by mitigating the impact of noise and sensor errors.

Design/methodology/approach
This approach is built upon the Kalman filtering algorithm, using a limited-memory weighted method to derive adaptive factors, while establishing judgment thresholds to constrain the range of their variation.

Findings
A comparative analysis with the traditional Kalman filter and the Sage-Husa adaptive filter reveals that APRKF offers superior speed estimation performance while effectively mitigating error accumulation caused by speed integration. The results indicate that APRKF excels in both speed and position estimation, demonstrating its effectiveness in improving estimation accuracy.

Originality/value
This study proposes an innovative method for the velocity and position estimation system of maglev tube-track trains.
Persistent Epstein–Barr Virus Infection of Epithelial Cells Leads to APOBEC3C Expression and Induces Mitochondrial DNA Mutations
Authors: Wai Aung Phyo , Richardo Timmy , Wakae Kousho , Okada Shunpei , Muramatsu Masamichi , Yoshiyama Hironori , Iizasa Hisashi 
Published: December 2024

ABSTRACTUpon infection with the virus, cells increase the expression of cytidine deaminase APOBEC3 family genes. This leads to the accumulation of C‐to‐T mutations in the replicating viral genome and suppresses viral propagation. In contrast, herpesviruses, including Epstein–Barr virus (EBV), express genes that counteract APOBEC3 during lytic infection. However, because viral resistance factors are not expressed during EBV latent infection, it is unknown how APOBEC3 functions during latent infection. We observed that in gastric epithelial cells persistently infected with EBV, the expression of APOBEC3 family genes increased, C‐to‐T mutations in the D‐loop genome of mitochondrial DNA (mtDNA) increased, and mtDNA copy number decreased. By introducing and expressing individual APOBEC3 family genes, APOBEC3C was particularly expressed in the cytoplasm, increasing C‐to‐T mutations in mtDNA and decreasing mtDNA copy number. Furthermore, we confirmed that APOBEC3C co‐localized with mitochondria in EBV‐infected cells. Expression of the EBV latent gene LMP2A increased APOBEC3C expression. Conversely, APOBEC3C expression was reduced in LMP2A‐deficient EBV‐infected cells compared to wild‐type EBV‐infected cells. These results indicate that persistent infection of EBV in gastric epithelial cells reduces the number of mitochondria through mtDNA mutations induced by APOBEC3C expression.
Physiological profiling of the soil microbe community using the EcoPlate and assessment of soil properties at 74 planted forest sites across Japan
Authors: Nakamura Masahiro , Terada Chisato , Ito Kinya , Hiura Tsutom , Shibata Hideaki , Miki Takeshi , Saitoh Taku M. , Takagi Masahiro , Hougen Toshiyuki , Matsuzaki Shin‐ichiro S. , Watanabe Mirai , Tado Hiroyuki , Hotta Norifumi , Kosugi Yoshiko , Aiko Nobuyuki , Kojima Nagahiro , Katagiri Nana , Kishimoto Koju , Yoshida Tomohiro , Tsunoda Yuuki , Takamiya Tatsumi , Ito Kosuke , Utsumi Yasuhiro , Yoshikawa Tetsuro , Kenta Tanaka , Oda Miho , Agetsuma Naoki , Kawai Masataka , Fujita Toru , Hishi Takuo , Shimada Hiromasa , Ichie Tomoaki , Hoshizaki Kazuhiko , Kobayashi Hajime , Seino Tatsuyuki , Noguchi Mahoko , Nagamatsu Dai , Saito Haruo , Tateno Ryunosuke , Ishihara Masae Iwamoto , Kitagawa Yoichiro , Hisamoto Yoko , Homma Kosuke , Hirao Toshihide , Otani Tatsuya , Toda Motomu , Terada Jinshi , Kume Tomonori , Fukuzawa Karibu , Takashima Atsushi , Kurose Koki , Fujii Sakae , Itoh Shunsuke , Ohta Tamihisa , Otsuki Kazuhiko , Nagaike Takuo , Hasegawa Kyohei , Makoto Kobayashi , Shirahata Manabu , Matsuki Sawako , Hatanaka Masayuki , Suzuki Satoshi , Muro Noriyuki , Yamoto Tomoyuki , Adachi Naoyuki , Kaneko Nobuhiro , Yamashita Tamon 
Published: December 2024

AbstractDue to policies supporting large‐scale expansion of plantation forestry, about 40% of the forests in Japan are planted forests, such as Japanese cedar (Cryptomeria japonica) and hinoki cypress (Chamaecyparis obtusa). We present the largest freely available EcoPlate dataset for planted forests in Japan, comprising data collected from a network of 74 planted forest sites (114 plots) in regions ranging from cool‐temperate to subtropical. The EcoPlate is a 96‐well microplate that contains three sets of 31 “response wells” with different carbon substrates. The utilization of each carbon substrate by the microbial community is quantified based on the color development of the well during incubation, providing a multifunctional index of the soil microbial community. Soil properties (water content, carbon, nitrogen, the carbon/nitrogen (C/N) ratio, and pH) essential for interpreting the EcoPlate results were also analyzed. Using a standardized protocol, soil was sampled between July and November 2021. A preliminary principal coordinate analysis (PCoA) was performed on the temporal integration of color density using the 31 substrates. PCo1 explained 36.5% of the variance of the overall absorbance of all substrates. A model of environmental factors, including elevation, and a model of soil properties, including pH, water content, and carbon, were the best‐fit models. EcoPlate data allow us to test hypotheses related to community ecology and the ecosystem functions of the soil microbial community in planted forests on a regional scale. The complete data set for this abstract published in the Data Article section of the journal is available in electronic format in MetaCat in JaLTER at https://jalter.diasjp.net/data/ERDP-2024-08.
Transporting difference‐in‐differences estimates to assess health equity impacts of payment and delivery models
Authors: Ianni Katherine , Chen Alyssa , Rodrigues Daniela , Hatfield Laura A. 
Published: December 2024

AbstractObjectiveTo demonstrate the use of transportability methods to extend findings from payment model evaluations to groups of historically underserved beneficiaries.Study Setting and DesignWe used a simulation study to transport the effects of the Comprehensive Primary Care Plus (CPC+) model to a target population of Black fee‐for‐service (FFS) Medicare beneficiaries living outside the original 18 CPC+ regions. Our main outcome variable was total Medicare spending per beneficiary per year (pbpy).Data Sources and Analytic SampleWe simulated practice‐level spending in 18 CPC+ regions and 32 non‐CPC+ regions (1200 practices per region). We calibrated the simulation parameters to values from the literature and then varied four key parameters to create 16 realistic simulation scenarios. These scenarios varied the representativeness of practices in CPC+ regions that joined CPC+ (i.e., the sample) relative to the target population by changing the distribution of Black beneficiaries across practices and the distribution of practices across regions. Practices were characterized by their experience with the Medicare Shared Savings Program (SSP) and system/hospital ownership because these are known to modify the effect of CPC+ on spending.Principal FindingsAcross the 16 simulation scenarios, transporting the treatment effect of CPC+ to Black FFS beneficiaries in non‐CPC+ regions yielded median treatment effects that ranged from $15.5 pbpy smaller to $10 pbpy larger than in the sample. These differences are roughly the same magnitude as the estimated overall effect of $13 pbpy.ConclusionsThe Center for Medicare and Medicaid Innovation has pledged to put equity at the center of its demonstration models. However, offering models in limited geographic areas with voluntary provider participation may result in unrepresentative samples. Naively generalizing CPC+ effects from geographically limited, voluntary samples to all Black FFS beneficiaries could be misleading. Under some circumstances, transportability methods can be used to estimate effects in this target population.