Robust Link Research Articles

The effect of political alignment on street‐level bureaucrat job satisfaction and motivation

AbstractThis paper examines how political alignment influences the job satisfaction and motivation of street‐level bureaucrats (SLBs)—low‐level frontline workers implementing policies while interacting directly with the public. I argue that political alignment affects SLBs' job satisfaction and motivation to work harder through three theoretical channels: (1) policy‐driven effects, particularly demoralization from implementing disagreeable policies; (2) spill‐over effects from other policy areas; and (3) political person‐organization fit effects, which result in decreased pride in their employer. Using the International Social Survey Program data from 34 countries, and panel data from the German Socio‐Economic Panel, tracking 880 respondents over 30 years, I find a robust link between political alignment and job satisfaction and motivation, and evidence for all three links. These findings underscore the importance of considering political alignment as a key factor in understanding and improving street‐level bureaucrat performance beyond policy‐specific and client‐specific contexts.

Does emotional intelligence contribute to career success? Evidence from a systematic literature review

AbstractThe relationship between career success and emotional intelligence has garnered substantial academic attention, prompting this systematic literature review to critically assess its impact. Spanning from 1995 to 2022, this review adopts the PRISMA and TCCM frameworks to examine 36 studies, focusing on the role of emotional intelligence as a predictor, mediator, moderator, and criterion in career success. The evidences predominantly indicate that emotional intelligence is a critical antecedent for various career‐related outcomes including objective and subjective career success. Further, emotional intelligence serves as a pivotal mediator in linking personality traits, career planning, and self‐efficacy to career outcomes, as elucidated in few studies. Moreover, some studies reveal its moderating role between career commitment and both objective and subjective career success. Additionally, emotional intelligence emerges as an outcome influencing emotional exhaustion and balance. The review synthesizes findings from nine theoretical frameworks, establishing a robust link between emotional intelligence and career success. This review not only affirms emotional intelligence as a substantial contributor to career advancement but also opens avenues for future research and practical applications in organizational contexts.

Robust Temporal Link Prediction in Dynamic Complex Networks via Stable Gated Models With Reinforcement Learning.

Temporal link prediction is one of the most important tasks for predicting time-varying links by capturing dynamics within complex networks. However, it suffers from difficulties such as vulnerability to adversarial attacks and inadaptation to distinct evolutionary patterns. In this article, we propose a robust temporal link prediction architecture via stable gated models with reinforcement learning (SAGE-RL) consisting of a state encoding network (SEN) and a self-adaptive policy network (SPN). The former is utilized to capture network dynamics, while the latter helps the former adapt to distinct evolutionary patterns across various time periods. Within the SEN, a novel stable gate is introduced to ensure multiple spatiotemporal dependency paths and defend against adversarial attacks. An SPN is proposed to select different SEN instances by approximating the optimal action function, thereby adapting to various evolutionary patterns to learn the robust temporal and structural features from dynamic complex networks. It is proven that SAGE-LR with integral Lipschitz graph convolution is stable to relative perturbations in dynamic complex networks. With the aid of extensive experiments on five real-world graph benchmarks, SAGE-LR is shown to substantially outperform current state-of-the-art approaches in terms of precision and stability of temporal link prediction and ability to successfully defend against various attacks. We also implement the temporal link prediction in shipping transaction networks, which forecast effectively its potential transaction risks.

Impact of AI Adoption on Business Process Automation and Competitiveness in Manufacturing Industry in Nigeria

This study analyzed the impact of AI adoption on business process automation and competitiveness in the Nigerian manufacturing industry, utilizing Dangote Cement Plc and Nigerian Breweries Plc as case studies. The study employed structured questionnaires and regression analysis on a sample of 301 to investigate the impact of AI technology on operational efficiency, productivity, and competitive advantage in manufacturing enterprises. The results indicate a robust positive link between AI adoption and enhanced operational efficiency, with AI markedly diminishing human mistakes and optimizing production processes. Moreover, the implementation of AI enhances market competitiveness, allowing companies to innovate, reduce manufacturing costs, and respond to market fluctuations more efficiently. Nonetheless, challenges such as high implementation costs, insufficient qualified workforce, and technological intricacies persist as impediments to widespread adoption. The study corroborated worldwide findings while also emphasizing context-specific obstacles in Nigeria, including infrastructure deficiencies and data privacy issues. The report advocated for legislative interventions, infrastructural enhancements, and worker training initiatives to address these difficulties and optimize the advantages of AI.

Mapping collaboration networks in community health nursing research: A bibliometric analysis

Objective: To conduct a bibliometric analysis of community health nursing research from 2019-2023 to identify publication trends, influential entities, research themes, and collaboration patterns. Methodology: Data on 870 community health nursing publications from 2019-2023 was retrieved from Web of Science database. Quantitative and network analysis were conducted using VOSviewer and R programing softwares to examine trends and collaboration patterns. Results: The study included 870 community health nursing publications from 2019-2023. Annual output peaked in 2021, then declined. Average citations per article decreased over time. Public Health Nursing published the most articles, with output increasing annually. Yoshioka-maeda was the most productive author. The University of California System led affiliations. The United States dominated production and international collaborations. Keyword analysis revealed clusters around vulnerable groups, interventions, mental health, risks, and populations. Country collaboration network mapping showed robust North America-Europe links. The United States exhibited the most co-authorships. Conclusion: This bibliometric analysis of community health nursing research from 2019-2023 provides insights into publication trends, influential authors, sources, countries, research themes, and collaboration patterns. Tracking changes over time and expanding diversity could further advance the field.

A Convolutional Neural Network for Beam Prediction in 5G and Beyond Massive MIMO Systems

This paper presents an innovative Convolutional Neural Network (CNN) architecture designed for the prediction of beamforming vectors in Massive Multiple-Input Multiple-Output (MIMO) systems, a cornerstone technology in 5G and emerging wireless communication networks. As mmWave frequencies become central to modern MIMO systems, ensuring precise beam alignment amid susceptibility to blockages is imperative for maintaining robust communication links. Traditional beamforming algorithms, challenged by high complexity and sluggish adaptation to dynamic environmental conditions, are outperformed by the proposed CNN, which effectively captures complex channel patterns for accurate beam prediction. Leveraging a rich dataset from the DeepSense 6G scenarios, the study meticulously preprocesses the data through normalization and scaling before dividing it into training and testing subsets. The CNN, evaluated against real-world signal propagation behaviors, demonstrates a high prediction accuracy in beam indices, particularly in clear line-of-sight scenarios. The paper concludes with an assessment of the model's predictive performance, using Mean Absolute Error as a key metric, and proposes future enhancements to the model's architecture and training process. The implications of this work are significant, heralding a new era of intelligent, self-optimizing wireless networks that can adapt autonomously to environmental changes and user mobility

Biophilic Design as Participative Design (Restaurant Case Study)

I have been developing the concept for a new “Biophilic Organization” to bridge the gap between organizations and the natural world, despite their claims of sustainability. By drawing from fields such as evolutionary psychology and architecture, this research aims to establish a robust link between nature and culture within organizations, demonstrating how this connection can significantly contribute to sustainability. Furthermore, the paper takes a comprehensive approach to sustainability, recognizing and addressing the various challenges. Regarding the restaurant concept, it is commercial in nature, and I am planning a comprehensive revamp. After conducting a thorough assessment of the restaurant, I have identified key areas for improvement with a unique style in mind. Upon researching the structural aspects that require enhancement, I have concluded that expanding the restaurant’s space and seating capacity is paramount. Furthermore, I have diligently studied three comparable eateries and drawn inspiration from their concepts to infuse into my own establishment. Despite the upcoming competition from restaurants near the Amman Mall construction, I am confident that my restaurant will differentiate itself with a unique interior design that captivates visitors with an abundance of gorgeous indoor plants, exuding life, innocence, and beauty.

Investigating the Correlation Between Emotional Intelligence and Academic Achievement: A Multifaceted Analysis in UK Secondary Schools

This comprehensive review explores the correlation between emotional intelligence (EI) and academic achievement in the context of UK secondary schools. Grounded in a thorough examination of emotional intelligence, its theoretical foundations, and influencing factors during adolescence, the analysis synthesizes existing studies to establish a robust link between EI and academic success. The impact of school culture, teacher-student relationships, and familial influences on emotional intelligence is explored, emphasizing the pivotal role of the school environment in shaping socio-emotional growth. Empirical evidence highlights the mediating role of EI in the complex interplay of socio-emotional factors and academic achievement. Practical implications include targeted educational strategies to enhance emotional intelligence, recognizing its potential to positively influence various academic outcomes. The exploration concludes by emphasizing the significance of recognizing and prioritizing emotional intelligence in fostering holistic educational approaches for secondary school students in the UK.

Urinary tract infections and risk of preterm birth: a systematic review and meta-analysis.

This systematic review and meta-analysis assessed the association between urinary tract infections (UTIs) during pregnancy and the risk of preterm birth (PTB). We searched multiple databases for relevant observational studies, categorizing them as UTI-based (comparing PTB incidence in women with and without UTIs) or PTB-based (comparing UTI prevalence in women with and without PTB). Using a random-effects model in Stata software version 17.0, we estimated pooled and adjusted odds ratios (ORs) with 95% confidence intervals (CIs), and performed subgroup, sensitivity, and cumulative analyses to explore heterogeneity. In total, 30 studies comprising 32 datasets were included, involving a total of 249,810 cases and 2,626,985 healthy controls. The meta-analysis revealed a significant positive association between UTIs during pregnancy and PTB occurrence (OR, 1.92; 95% CI, 1.62-2.27). A sub-group analysis based on studies, the participants showed significant association in both PTB-based (OR, 2.01; 95% CI, 1.58-2.56) and UTI-based studies (OR, 1.79; 95% CI, 1.42-2.26). However, Egger's test indicated the presence of publication bias (p=0.020), and substantial heterogeneity was observed across the included studies (I2=96.6; p< 0.001). These findings emphasize the critical importance of early detection and effective management of UTIs in pregnant women to reduce the risk of PTB and its associated adverse outcomes. While the results highlight a robust link between UTIs during pregnancy and PTB risk, the potential influence of publication bias and substantial heterogeneity should be considered to interpret these findings. Further research is needed to better understand the underlying mechanisms and to develop targeted interventions for high-risk pregnant women.

Prevalence and predictors of social anxiety disorders among Malaysian secondary school students during the COVID-19 pandemic: Exploring the influence of internet gaming disorder and impulsivity.

This study aimed to investigate the prevalence of social anxiety disorder (SAD) among Malaysian secondary school students during the COVID-19 pandemic and to explore its correlations with demographic variables, impulsivity behavior, and internet gaming disorder (IGD). A total of 1574 participants from 12 government secondary schools across five Malaysian states, comprising 569 males and 1005 females, completed an online questionnaire containing validated Malay versions of the Social Interaction Anxiety Scale, Barratt Impulsiveness Scale, and Internet Gaming Disorder Scale - Short Form. The findings revealed a notable SAD prevalence rate of 40.53% among Malaysian adolescents. Logistic regression analysis unveiled significant associations between SAD and factors such as attention impulsiveness (OR = 2.58, p < .001), motor impulsiveness (OR = 1.47, p = .03), female gender (OR = 2, p < .001), Malay ethnicity, and IGD (OR = 1.08, p < .001). In conclusion, this study provides valuable insights into the extent of social anxiety experienced by Malaysian secondary school students during the pandemic, shedding light on the demographic and psychosocial factors linked to its emergence. Furthermore, the research underscores a robust link between IGD and SAD, emphasizing the need for comprehensive interventions addressing both issues concurrently. By recognizing the multifaceted nature of these associations, future interventions can be tailored to provide holistic support for adolescents' mental well-being.

Cultivating commitment: how cultural ecosystem services affect visitor loyalty attitudes and intention-to-return in parks and protected areas

ABSTRACT Parks and protected areas (PPAs) are crucial for providing society with essential ecosystem services, encompassing both tangible and intangible benefits derived from healthy ecosystems. While previous research has predominantly focused on material-based ecosystem services, limited attention has been devoted to the impact of non-material cultural ecosystem services (CES), such as recreation and cultural-historic aspects, on visitor loyalty. Visitor loyalty refers to an individual’s commitment and willingness to repeatedly visit a PPA. CES can significantly shape these attitudes, as many visitors are drawn to specific PPAs due to their cultural significance or scenic beauty. This study investigated how CES influences visitor loyalty attitudes and intention-to-return at the Great Bay National Estuarine Research Reserve (GBE). In the summer of 2022, data were collected from 645 GBE visitors using a population sampling approach. Structural equation modeling analyses revealed a robust link between various CES factors, visitor loyalty attitudes, and intention-to-return. For instance, findings suggest that education and the sense of place exert a strong and consistent influence on visitor attitudes regarding referrals, financial support, volunteerism, and advocacy. Additionally, positive visitor attitudes toward referrals strongly and independently predicted their overall intent to revisit the GBE. This research contributes to the advancement of both CES and visitor loyalty frameworks, offering empirical insights for natural resource managers. By acknowledging the significance and trade-offs associated with CES elements, like education and the sense of place, resource managers can enhance visitor loyalty and secure the long-term sustainability of natural resources worldwide.

The Potential of Grapevine Leaf Extract in Treating Hyperpigmentation

Hyperpigmentation, characterized by the excessive accumulation of melanin in the skin, is a common dermatological concern triggered by various factors, including UV radiation exposure. This study investigates the potential of grapevine leaf extracts in treating hyperpigmentation induced by UV radiation, focusing on 11 European and 12 Israeli grapevine varieties. Our research explores the correlations between total polyphenol content (TPC), tyrosinase inhibition, sun protection factor (SPF), and half-maximal inhibitory concentration (IC50) of these extracts. Our findings reveal substantial variation in TPC among grapevine varieties’ leaves, with the Israeli varieties showing higher TPC levels than the European ones. Correlation analysis demonstrates a robust link between TPC and SPF, indicating that increased TPC contributes to enhanced sun protection properties. However, TPC alone does not strongly correlate with tyrosinase inhibition, suggesting the importance of specific polyphenols in tyrosinase inhibition. Furthermore, the study identifies specific peaks in the HPLC analysis that correlate with desired activities. In summary, our research highlights the potential of grapevine leaf extracts, especially those from Israeli indigenous varieties, in addressing hyperpigmentation. It emphasizes the importance of specific polyphenols rather than TPC alone in achieving the desired effects. These findings open doors for further investigation into identifying and isolating active compounds from grapevine leaves for skincare applications.

California's Comprehensive Perinatal Services Program and birth outcomes.

California's Medicaid (Medi-Cal) sponsors Comprehensive Perinatal Services Program (CPSP), a program with enhanced perinatal care for women (more education, nutritional supplements, and psychosocial counseling/support). Past evaluations of CPSP's effectiveness in birth outcomes were limited to pilot programs and yielded mixed results. We used 2012-2016 California's statewide data about singleton live births with any receipt of prenatal care (N = 2,385,811) to examine whether Medi-Cal with CPSP enrollment was associated with lower odds of preterm birth (PTB), spontaneous PTB, and low birthweight (LBW) than non-CPSP births. With three binary variables of PTB, spontaneous PTB, and LBW as the response variables, three multilevel logistic models were used to compare the outcomes of participants enrolled in Medi-Cal with CPSP against those with private insurance, adjusting for maternal factors and county-level covariates. Logistic models showed that participants enrolled to Medi-Cal with CPSP [n (%) = 89,009 (3.7)] had lower odds of PTB, spontaneous PTB and LBW, respectively, as compared with those with private insurance [n (%) = 1,133,140 (47.2)]. Within the Medi-Cal sub-population, the CPSP enrollment was associated with lower odds of PTB, SPTB and LBW than Medicaid beneficiaries without CPSP [n (%) = 967,094 (40.3)]. With statewide data, these findings revealed a robust link between CPSP enrollment and better birth outcomes. Expanding access to comprehensive prenatal services could be an important strategy to improve birth outcomes.

How much schizophrenia do famines cause?

Since the 1970s, famines have been widely invoked as natural experiments in research into the long-term impact of foetal exposure to nutritional shocks. That research has produced compelling evidence for a robust link between foetal exposure and the odds of developing schizophrenia. However, the implications of that research for the human cost of famines in the longer run have not been investigated. We address the connection between foetal origins and schizophrenia with that question in mind. The impact turns out to be very modest—much less than one per cent of the associated famine death tolls—across a selection of case studies.

Testing the Predictions of Surprisal Theory in 11 Languages

Abstract Surprisal theory posits that less-predictable words should take more time to process, with word predictability quantified as surprisal, i.e., negative log probability in context. While evidence supporting the predictions of surprisal theory has been replicated widely, much of it has focused on a very narrow slice of data: native English speakers reading English texts. Indeed, no comprehensive multilingual analysis exists. We address this gap in the current literature by investigating the relationship between surprisal and reading times in eleven different languages, distributed across five language families. Deriving estimates from language models trained on monolingual and multilingual corpora, we test three predictions associated with surprisal theory: (i) whether surprisal is predictive of reading times, (ii) whether expected surprisal, i.e., contextual entropy, is predictive of reading times, and (iii) whether the linking function between surprisal and reading times is linear. We find that all three predictions are borne out crosslinguistically. By focusing on a more diverse set of languages, we argue that these results offer the most robust link to date between information theory and incremental language processing across languages.

Double jeopardy: Exploring the moderating effect of educational mismatch in the relationship between work-family conflict and depressive symptoms among Korean working women

RationaleDespite a growing body of empirical evidence on the detrimental effects of work-family conflict (WFC) on psychological health, little attention has been given to whether educational mismatch in the workplace, which refers to the perceived level of match between one's attained education and the required educational level for a position, may exacerbate these effects. ObjectiveThe purpose of this study was to examine the relationship between WFC, educational mismatch, and depressive symptoms in Korean working women, with a particular focus on the potential moderating effects of educational mismatch on the association between WFC and depressive symptoms. MethodsThe data utilized for this study were collected from 5174 married working women over five waves (16,610 person-observations) of the Korean Longitudinal Survey of Women and Families spanning 8 years between 2012 and 2020. Fixed effects (FE) models were estimated to account for unobserved individual-level heterogeneity. ResultsFE estimates indicated that WFC is associated with an increase in depressive symptoms, even after accounting for unobserved confounding factors and time-varying covariates. The interaction model provides evidence for the moderating role of educational mismatch in the association between WFC and depressive symptoms. The positive association between WFC and depressive symptoms was more pronounced among those who perceive themselves as “overeducated.” The estimated coefficient for the association was about 45% larger for those who perceive themselves as “overeducated” than their “well-matched” counterparts. ConclusionThe study's findings suggest a robust link between WFC and depressive symptoms and further elaborate on how this association varies depending on educational mismatch. In Korea, where conservative gender role norms of female-caregiver ideology are still prevalent, WFC and educational mismatch can act as double jeopardy, exacerbating the mental health of working women.

Synergistic boost of catalytic activity in ZrTe topological catalyst via multiple topologically-electronic states

Topological materials feature highly-active topological surface states and high carrier mobility, making them promising catalysts. While ongoing research centers on topological catalysis, most topological semimetal catalysts tend to showcase either a singular topological electronic state or a lone highly catalytic surface, imposing limitations on overall efficiency. Our study highlights ZrTe as a standout catalyst for hydrogen evolution, boasting multiple topological states that excel across various surfaces. ZrTe exhibits a Weyl nodal ring and a triple degenerate nodal point near the Fermi energy, resulting in topological surface states on multiple surfaces. Notably, the (010) and (001) surfaces exhibit remarkable catalytic performance, with Gibbs free energy (ΔGH*) values surpassing that of the Pt metal. Our work establishes a robust and unequivocal link between catalysis and topological properties on the catalytic surfaces, revealing a linear correlation between ΔGH* and topological surface state density. ZrTe emerges as an exceptional topological catalyst, with both of its topological states significantly contributing to the catalytic performance on distinct surfaces. This pioneering discovery offers a valuable platform for advancing catalyst research in the concept of topological catalysts.

Decoding Demographics on Generation Z's Post-Pandemic Shopping Trends: E-Commerce Evolution 4.0, the Digital Shopper's Dilemma, and Tailoring Strategies

This quantitative study investigates the impact of demographic factors on customer satisfaction and subsequent online purchase intentions among Generation Z university students in Dhaka, Bangladesh, during the post-COVID-19 era. Employing a cross-sectional research design, the study uses a stratified random sampling technique to collect data from 433 respondents. The questionnaire, based on a five-point Likert scale, explores variables such as gender, internet literacy, product price perception, income, education, customer satisfaction, and intention to purchase. IBM SPSS Version 25 (Licensed) is used for data analysis, incorporating descriptive statistics, correlation analysis, and regression analysis. The study unveils positive and significant relationships between gender, internet literacy, product price, income, and education with customer satisfaction. Moreover, a robust link between customer satisfaction and the intention to purchase online is identified. Theoretical frameworks such as Social Identity Theory and Consumer Satisfaction Models guide the research, highlighting the importance of a nuanced understanding for tailored marketing strategies. The findings contribute valuable insights for businesses and policymakers navigating the post-COVID-19 digital landscape. Future research avenues include exploring emerging technologies and cross-cultural variations within Generation Z.

Reconfigurable Intelligent Surfaces and Capacity Optimization: A Large System Analysis

Reconfigurable Intelligent Surfaces (RISs) have been recently proposed as an enabling technology for programmable wireless environments. In this paper, we present asymptotic closed-form expressions for the mean and variance of the mutual information for a multi-antenna transmitter-receiver pair in the presence of RISs, using statistical physics methods. While nominally valid in the large-system limit, we show that the derived Gaussian approximation for the mutual information can be quite accurate, even for modest-sized antenna arrays and metasurfaces. The above results are particularly useful when fast-fading conditions are present, which renders channel estimation challenging. We find that, when the channel close to an RIS is correlated, for instance due to small angle spread, which is reasonable for wireless systems with increasing carrier frequencies, the communication link benefits significantly from statistical RIS optimization, resulting in gains that are surprisingly higher than the nearly uncorrelated case. Using our novel asymptotic properties of the correlation matrices of the impinging and outgoing signals at the RISs, we can optimize the metasurfaces without brute-force numerical optimization. When the desired reflection from any of the RISs departs significantly from geometrical optics, the metasurfaces can be optimized to provide robust communication links, without significant need for their optimal placement.

Robust Dual-Wavelength DRoF Link by Quasi-2-bit 256-QAM OFDM With Delta-Sigma Modulation

Robust Dual-Wavelength DRoF Link by Quasi-2-bit 256-QAM OFDM With Delta-Sigma Modulation