Industrial monitoring systems, especially when deployed in Industry 4.0 environments, are experiencing a shift in paradigm from traditional rule-based architectures to data-driven approaches leveraging machine learning and artificial intelligence. This study presents a comparison between these two methodologies, analyzing their respective strengths, limitations, and application scenarios, and proposes a basic framework to evaluate their key properties. Rule-based systems offer high interpretability, deterministic behavior, and ease of implementation in stable environments, making them ideal for regulated industries and safety-critical applications. However, they face challenges with scalability, adaptability, and performance in complex or evolving contexts. Conversely, data-driven systems excel in detecting hidden anomalies, enabling predictive maintenance and dynamic adaptation to new conditions. Despite their high accuracy, these models face challenges related to data availability, explainability, and integration complexity. The paper suggests hybrid solutions as a possible promising direction, combining the transparency of rule-based logic with the analytical power of machine learning. Our hypothesis is that the future of industrial monitoring lies in intelligent, synergic systems that leverage both expert knowledge and data-driven insights. This dual approach enhances resilience, operational efficiency, and trust, paving the way for smarter and more flexible industrial environments.
Eneko Osaba, Iñigo Perez Delgado, Alejandro Mata Ali
et al.
This article explores the current state and future prospects of quantum computing in industrial environments. Firstly, it describes three main paradigms in this field of knowledge: gate-based quantum computers, quantum annealers, and tensor networks. The article also examines specific industrial applications, such as bin packing, job shop scheduling, and route planning for robots and vehicles. These applications demonstrate the potential of quantum computing to solve complex problems in the industry. The article concludes by presenting a vision of the directions the field will take in the coming years, also discussing the current limitations of quantum technology. Despite these limitations, quantum computing is emerging as a powerful tool to address industrial challenges in the future.
Ali Raza, Muhammad Farhan Khan, Zeeshan Alam
et al.
This paper presents a joint framework that integrates reconfigurable intelligent surfaces (RISs) with Terahertz (THz) communications and non-orthogonal multiple access (NOMA) to enhance smart industrial communications. The proposed system leverages the advantages of RIS and THz bands to improve spectral efficiency, coverage, and reliability key requirements for industrial automation and real-time communications in future 6G networks and beyond. Within this framework, two power allocation strategies are investigated: the first optimally distributes power between near and far industrial nodes, and the second prioritizes network demands to enhance system performance further. A performance evaluation is conducted to compare the sum rate and outage probability against a fixed power allocation scheme. Our scheme achieves up to a 23% sum rate gain over fixed PA at 30 dBm. Simulation results validate the theoretical analysis, demonstrating the effectiveness and robustness of the RIS-assisted NOMA MIMO framework for THz enabled industrial communications.
Orientation: The coronavirus disease 2019 (COVID-19) pandemic disrupted workplaces worldwide, prompting a re-evaluation of the meaning and significance of work, particularly among women who were uniquely impacted by the crisis.
Research purpose: This study aimed to understand the meaning that South African women attributed to their work during the pandemic. Additionally, the research aligned with the Sustainable Development Goals (SDGs 3, 5 and 8), contributing to efforts to improve well-being, promote gender equality and ensure decent work.
Motivation for the study: Understanding how the pandemic altered women’s perceptions and experiences of work can provide valuable insights for human resource professionals, helping to create more inclusive and supportive work environments.
Research approach/design and method: A generic qualitative approach was employed, involving 10 semi-structured interviews with South African women who were formally employed both before and during the pandemic. Thematic analysis was used to interpret the data collected.
Main findings: The study revealed that women had individual motivations for their chosen work, with the meaning of work varying among participants. Factors such as organisational and personal challenges, as well as the support received, significantly shaped these meanings.
Practical/managerial implications: Organisations need to consider the unique challenges and support needs of women in the workplace, especially in the context of recovery from the pandemic.
Contribution/value-add: The study enriches the body of literature on the meaning of work, particularly focussing on South African women during the COVID-19 pandemic, and informs organisational practices that can better support employees during crises and beyond.
Lixia Wang,1,* Yilai Pei,2,* Yuanfei Zhu,1 Haiying Long,3 Weiguo Pang4 1Shanghai Teacher Institute, Shanghai, People’s Republic of China; 2China Institute of Education and Social Development, Beijing Normal University, Beijing, People’s Republic of China; 3Department of Educational Psychology, University of Kansas, Lawrence, KS, USA; 4School of Psychology and Cognitive Science, East China Normal University, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Haiying Long; Weiguo Pang, Email hlong@ku.edu; wgpang@psy.ecnu.edu.cnIntroduction: The schizotypy-creativity link has been studied from different perspectives over the past few decades, yet the results of this relationship are inconsistent in the literature. Previous studies have suggested that two basic motivational systems—Behavioral Inhibition System (BIS, avoidance motivation) and Behavioral Activation System (BAS, approach motivation)—underlie the relationship between schizotypy and creativity. Few empirical studies, however, have examined how the relationship interacts with other variables. This study fills these gaps and explores the role of the approach and avoidance motivation assessed by trait behavioral activation and inhibition in the link between schizotypy as a dimensional personality trait and creative ideational behavior as a measure of creativity.Method: Undergraduate students (N = 388) completed questionnaires including the Schizotypal Personality Questionnaire (SPQ) measuring 3 dimensions of schizotypy, Runco Ideational Behavior Scale (RIBS) measuring creative ideational behavior, and BIS/BAS Scales measuring trait behavioral motivation. Bivariate Pearson correlation was computed, and hierarchical linear regression was performed to explore the effects of schizotypy, BIS/BAS, and their interaction on creative ideational behavior. The conditional effect of schizotypy based on different levels of the moderator was further tested.Results: The total score, positive dimension and disorganized dimension of SPQ were all positively correlated with RIBS, BAS, and BIS. Negative dimension of SPQ was not significantly correlated with the RIBS score but was positively correlated with BIS. Additionally, after controlling gender and age, BAS significantly moderated the relationship between the positive and disorganized dimensions of schizotypy and creative ideational behavior measured by RIBS. However, BIS was not a significant moderator.Discussion: The findings of this study regarding the relationships between different dimensions of schizotypy, two motivational systems, and creative ideational behavior were mostly consistent with previous findings. The significant moderated effect of BAS on the relationship between two dimensions of schizotypy and creative ideational behavior made significant contributions to the understanding of the relationship between schizotypy and creativity.Keywords: schizotypy, creativity, creative ideational behavior, motivation
The growing connectivity of industrial devices as a result of the Internet of Things is increasing the risks to Industrial Control Systems. Since attacks on such devices can also cause damage to people and machines, they must be properly secured. Therefore, a threat analysis is required in order to identify weaknesses and thus mitigate the risk. In this paper, we present a systematic and holistic procedure for analyzing the attack surface and threats of Industrial Internet of Things devices. Our approach is to consider all components including hardware, software and data, assets, threats and attacks throughout the entire product life cycle.
This review aims to contribute to the quest for artificial general intelligence by examining neuroscience and cognitive psychology methods for potential inspiration. Despite the impressive advancements achieved by deep learning models in various domains, they still have shortcomings in abstract reasoning and causal understanding. Such capabilities should be ultimately integrated into artificial intelligence systems in order to surpass data-driven limitations and support decision making in a way more similar to human intelligence. This work is a vertical review that attempts a wide-ranging exploration of brain function, spanning from lower-level biological neurons, spiking neural networks, and neuronal ensembles to higher-level concepts such as brain anatomy, vector symbolic architectures, cognitive and categorization models, and cognitive architectures. The hope is that these concepts may offer insights for solutions in artificial general intelligence.
Recent years have witnessed the rapid development of large language models (LLMs) in various domains. To better serve the large number of Chinese users, many commercial vendors in China have adopted localization strategies, training and providing local LLMs specifically customized for Chinese users. Furthermore, looking ahead, one of the key future applications of LLMs will be practical deployment in industrial production by enterprises and users in those sectors. However, the accuracy and robustness of LLMs in industrial scenarios have not been well studied. In this paper, we present a comprehensive empirical study on the accuracy and robustness of LLMs in the context of the Chinese industrial production area. We manually collected 1,200 domain-specific problems from 8 different industrial sectors to evaluate LLM accuracy. Furthermore, we designed a metamorphic testing framework containing four industrial-specific stability categories with eight abilities, totaling 13,631 questions with variants to evaluate LLM robustness. In total, we evaluated 9 different LLMs developed by Chinese vendors, as well as four different LLMs developed by global vendors. Our major findings include: (1) Current LLMs exhibit low accuracy in Chinese industrial contexts, with all LLMs scoring less than 0.6. (2) The robustness scores vary across industrial sectors, and local LLMs overall perform worse than global ones. (3) LLM robustness differs significantly across abilities. Global LLMs are more robust under logical-related variants, while advanced local LLMs perform better on problems related to understanding Chinese industrial terminology. Our study results provide valuable guidance for understanding and promoting the industrial domain capabilities of LLMs from both development and industrial enterprise perspectives. The results further motivate possible research directions and tooling support.
Davide Frizzo, Francesco Borsatti, Alessio Arcudi
et al.
Anomaly Detection (AD) is crucial in industrial settings to streamline operations by detecting underlying issues. Conventional methods merely label observations as normal or anomalous, lacking crucial insights. In Industry 5.0, interpretable outcomes become desirable to enable users to understand the rational under model decisions. This paper presents the first industrial application of ExIFFI, a recent approach for fast, efficient explanations for the Extended Isolation Forest (EIF) AD method. ExIFFI is tested on four industrial datasets, demonstrating superior explanation effectiveness, computational efficiency and improved raw anomaly detection performances. ExIFFI reaches over then 90\% of average precision on all the benchmarks considered in the study and overperforms state-of-the-art Explainable Artificial Intelligence (XAI) approaches in terms of the feature selection proxy task metric which was specifically introduced to quantitatively evaluate model explanations.
Katie J. Shillington, Carmen T. Labadie, Andrew M. Johnson
et al.
The purpose of this longitudinal, mixed-methods study was two-fold: (1) to investigate the impact of a motivational coaching credit-bearing course on the resilience, mental health, health-related quality of life, compassion, and social support of graduate students in Ontario, Canada; and (2) to qualitatively explore students’ overall experience participating in the course, how the course influenced the lives of students, and recommendations for course improvement. Thirty-two students completed five previously validated scales at four time-points, as well as open-ended questions and end-of-term course reflections. Friedman’s test suggested that the motivational coaching course had a statistically significant effect on anxiety and giving emotional support over time. Inductive content analysis was conducted on the open-ended questions and course reflections. Qualitative themes included increased self-reflection, skill development, relationship building, positive course experience, acknowledgement of self-improvement, the impact and transferability of motivational coaching, and course improvements.
Special aspects of education, Industrial psychology
The purpose of this study is to evaluate themes on ‘user experiences’ among college students (N = 265) enrolled in an upper-division Psychopathology course who were assigned a project in which they were instructed to identify a self-care goal, choose from a list of six mental health-focused mobile applications (apps) provided by the instructor, and use the app over the course of three weeks to support progress towards their goal. Prior literature on user experiences typically evaluates user reviews, or asks participants to reflect on past app use or anticipate future use. Students reported their experiences using the app during key decision points: app selection, while using the app, and at the conclusion of the assignment. Using thematic analysis, results identified seven central themes and eight subthemes pertaining to the content of the app (e.g., app features) and the context of using the app (e.g., classroom assignment). Content-wise students liked: 1) features with a strong evidence base, namely, thought diaries and guided meditations; 2) progress tracking, because it increased awareness of mood/stressors, motivated students to see improvement, and helped them stay on track. Students appreciated having 3) crisis support resources; 4) app interfaces that allowed for customization (poor app interfaces were sometimes cited as the reason for disengagement); and 5) apps that included varied, comprehensive resources such that it felt like a one-stop shop. In addition to the content of features and design interface, the context in which mental health apps are introduced and used is important. The remaining themes related to the context in which the app was used, including 6) preparation for app usage, such as reviewing scholarly/credible sources, and 7) social support from fellow students completing the same assignment. Future research should evaluate the ‘who, what, when, why, where, and how’ of app utilization during key decision points, such as initial app selection or subscription renewal, to better understand the impact of user experience on engagement.
Vinay S Chauhan, Markanday Sharma, Kaushik Chatterjee
et al.
Bipolar affective disorder (BPAD) is a major psychiatric illness impairing the quality of life. The etiology of BPAD is influenced by different factors possibly related to gene-environment interactions. Approximately 30% to 50% of individuals with BPAD have experienced some traumatic event in childhood. Serious adverse experiences that children may suffer early in life are often described as childhood trauma (CT). It includes physical, emotional, and sexual abuse and physical and emotional neglect. CT is linked with an elevated risk of developing BPAD. Childhood adversities play a role in modulating the early onset of illness, increased number of depressive episodes, increased suicide attempts, and other clinical severity of BPAD. Hospital-based studies comprising heterogeneous populations had researched the specific role of each trauma subtype as a predisposing factor for BPAD. Identifying and addressing CT through early intervention methods may prevent the future development of chronic disorders like BPAD. This review article is an attempt to explore and highlight the existing literature regarding the association of different subtypes of CT with BPAD.
Xiaogang Zhou,1 Yimeng Wang,1 Xinlin Zhang,1 Liqing Li2 1School of Economics and Management, East China Jiaotong University, Nanchang, Jiangxi, People’s Republic of China; 2School of Economics and Management, Jiangxi Science and Technology Normal University, Nanchang, Jiangxi, People’s Republic of ChinaCorrespondence: Xiaogang Zhou, School of Economics and Management, East China Jiaotong University, 808 Shuanggang East Street, Economic and Technological Development Zone, Nanchang, Jiangxi, 330013, People’s Republic of China, Tel +8618970876258, Email sunnyzhxg@163.comPurpose: The derivation of employees’ innovative behaviour is a complex multi-stage process influenced by decision logic. However, previous research on the relationship between the two has not been comprehensive without considering the individual level of employees, and the mechanism of action between the two is still unclear. Based on the behavioral decision theory, the broaden-and-build theory of positive emotions and triadic reciprocal determinism. This study investigates the mediating effects of positive error orientation between decision-making logic and employees’ innovative behavior, and the moderating effects of environmental dynamics between decision-making logic and employees’ innovative behavior, focusing on the individual level.Methods: The questionnaire data was obtained from 403 employees randomly selected from 100 companies in Nanchang, China, in various industries such as manufacturing, transportation, storage and postal services, trade, and wholesale and retail trade. Hypotheses were tested using structural equation modeling.Results: Effectual logic had a significantly positive impact on employees’ innovative behavior. The direct effect of causal logic on employees’ innovative behavior was not significant, but the total effect was significantly positive. Positive error orientation played a mediating role between both types of decision-making logic and employees’ innovative behavior. Moreover, environmental dynamics played a negative moderating role between effectual logic and employees’ innovative behavior.Originality/Value: This study expands the application of behavioral decision theory, the broaden-and-build theory of positive emotions and triadic reciprocal determinism in employees’ innovative behaviour, enriches the research on the mediating and moderating mechanism between employees’ decision-making logic and innovative behaviour, and provides a new research perspective and empirical support for subsequent related research.Practical Implications: The results of this study provide practical suggestions for promoting employees’ innovative behaviour. For example, employees need to cultivate logical thinking, train their decision-making ability, form a positive error orientation, and objectively assess the external environment.Keywords: causal logic, effectual logic, error orientation, innovative behavior, environmental dynamics
The prevalence of psychosocial distress is increasing in the United States. At the same time, the American default lifestyle has steadily displaced household food production with industrial food production, despite increased cultural interest in cooking. An important focus of cooking research to date has been on cooking’s association with nutrition and dietary quality. Less focus has been placed on how cooking might foster the qualities that allow for mitigation of psychosocial distress and promote well-being. Rooted in its evolutionary role in the human experience, cooking requires skills and knowledge that have the capacity to encourage aspects of well-being as described by Seligman as flourishing. Evidence for a beneficial role of cooking in psychosocial health exists, but the exploration is limited, potentially due to lack of a theoretical context to explain these benefits. From this perspective, we review the current literature showing the application of Seligman’s prominent well-being model, Positive emotion, Engagement, Relationships, Meaning, and Accomplishment (PERMA), to cooking, defined as the activity related to the preparation of food or a meal. We propose that the PERMA model as applied to cooking may function as a theoretical framework to explore psychosocial outcomes associated with cooking. Broader application of this approach may also help to further the application of positive psychology in the developing literature around psychosocial health and nutrition-related chronic diseases.
Abstract Career adaptability as a resource and adaptation as a process are essential concepts in career research and counseling, inspired by and building on a long tradition in vocational psychology. Career proactivity, a sub-facet of proactive work behavior in general, comes from industrial- and organizational psychology and is grounded in the literature on self-regulation. The current paper aims to compare these literatures, highlighting communalities and differences in their conceptual backgrounds, implied assumptions, and behaviors studied. Given how these literatures complement rather than contradict one another, we then integrate both literatures into a common framework based on the Rubicon model, a self-regulatory model of action phases. With this, we strive to highlight differences and communalities, potential blind spots and areas where either literature may learn from the other as well as directions for future research that might be beneficial for both literatures and the study of career related action overall.
H. Washington, J. Piccolo, E. Gómez‐Baggethun
et al.
Anthropocentrism in Western (modern industrial) society is dominant, goes back hundreds of years, and can rightly be called ‘hubris’. It removes almost all moral standing from the nonhuman world, seeing it purely as a resource. Here, we discuss the troubling components of anthropocentrism: worldview and ethics; dualisms, valuation and values; a psychology of fear and denial; and the idea of philosophical ‘ownership’. We also question whether it is a truly practical (or ethical) approach. We then discuss three troubling examples of anthropocentrism in conservation: ‘new’ conservation; ecosystem services; and the IPBES values assessment. We conclude that anthropocentrism is fuelling the environmental crisis and accelerating extinction, and urge academia to speak out instead for ecocentrism.
Parvaneh Bahmani Makvandzadeh, Amin Koraei, Seyedeh Zahra Alavi
et al.
Background: Depression could negatively impact the mood, behavior, attitude, and efficiency of women and massively harm family performance. The present study aimed to investigate the mediating role of the self-esteem in the association of attachment behaviors with depression and marital quality in women in Ahvaz, Iran.Methods: The study was descriptive-correlational estimated through structural equation modeling. The statistical population was made up of married women with at least high school education in Ahvaz, Iran in 2021. Convenience sampling was used to choose 340 individuals. The instruments included the Quality Marriage Index (QMI), Beck Depression Inventory (BDI- 13), the Brief Accessibility, Responsiveness, and Engagement (BARE) Scale, and the Rosenberg Self-Esteem Scale (RSES). A path analysis approach was adopted to evaluate the proposed model and the indirect relationships were examined through bootstrapping in AMOS version 24.Results: The mean and standard deviation (SD) of depression, marital quality, and self-esteem were 5.78±2.86, 28.58±6.48, and 7.22±2.93, respectively. Depression was negatively correlated with marital quality (r=-0.78) and self-esteem (r=-0.72) in women. The direct paths from attachment behaviors to self-esteem (P<0.001) and from self-esteem to depression (β=-0.53, P<0.001) and marital quality (β=0.18, P<0.001) were significant. The indirect paths from attachment behaviors to depression and marital quality through self-esteem were also significant (P<0.05).Conclusion: The suggested model suited the data well. The relationship between attachment behaviors, depression, and marital quality in women was mediated by self-esteem. Workshops on boosting self-esteem and outlining its advantageous effects on women’s mental health are advised.