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Historical newspaper collections provide a wealth of information about the past. Although the digitization of these collections significantly improves their accessibility, a large portion of digitized historical newspaper collections, such as those of KBR, the Royal Library of Belgium, are not yet searchable at article-level. However, recent developments in AI-based research methods, such as document layout analysis, have the potential for further enriching the metadata to improve the searchability of these historical newspaper collections. This paper aims to discuss the aforementioned issue.

In this paper, the authors explore how existing computer vision and machine learning approaches can be used to improve access to digitized historical newspapers. To do this, the authors propose a workflow, using computer vision and machine learning approaches to (1) provide article-level access to digitized historical newspaper collections using document layout analysis, (2) extract specific types of articles (e.g. feuilletons – literary supplements from Le Peuple from 1938), (3) conduct image similarity analysis using (un)supervised classification methods and (4) perform named entity recognition (NER) to link the extracted information to open data.

The results show that the proposed workflow improves the accessibility and searchability of digitized historical newspapers, and also contributes to the building of corpora for digital humanities research. The AI-based methods enable automatic extraction of feuilletons, clustering of similar images and dynamic linking of related articles.

The proposed workflow enables automatic extraction of articles, including detection of a specific type of article, such as a feuilleton or literary supplement. This is particularly valuable for humanities researchers as it improves the searchability of these collections and enables corpora to be built around specific themes. Article-level access to, and improved searchability of, KBR's digitized newspapers are demonstrated through the online tool (https://tw06v072.ugent.be/kbr/).

Using the lens of conservation of resources (COR) theory, the purpose of this paper is to explore the effect of humble leadership on project success by integrating the mediating role of goal clarity. The authors also argue that organizational culture moderates these direct and indirect relationships through goal clarity.

Time-lagged data were collected from 329 employees in the civil construction sector of Pakistan.

The results indicate that humble leadership enhances project success through mediating and moderating mechanisms.

The present research ends with an argument, managerial consequences, limits and guidance for future research.

The results influence a project-based organization on the selection and promotion of humility among project managers.

This research answers the following research question, which has been ignored in the literature: What are the suggested mechanisms for humble leadership in promoting project success?

The purpose of this study was to use bridge curvature method (BCM) to quantify stress, while multiscale modeling with adaptive coarsening predicted distortions based on experimentally validated models. Taguchi method and response surface method were used to optimize process parameters (energy density, hatch spacing, scanning speed and beam diameter).

Laser powder bed fusion (LPBF) offers significant design freedom but suffers from residual stresses due to rapid melting and solidification. This study presents a novel approach combining multiscale modeling and statistical optimization to minimize residual stress in SS316L.

Optimal parameters were identified through simulations and validated with experiments, achieving an 8% deviation. This approach significantly reduced printing costs compared to traditional trial-and-error methods. The analysis revealed a non-monotonic relationship between residual stress and energy density, with an initial increase followed by a decrease with increasing hatch spacing and scanning speed (both contributing to lower energy density). Additionally, beam diameter had a minimal impact compared to other energy density parameters.

This work offers a unique framework for optimizing LPBF processes by combining multiscale modeling with statistical techniques. The identified optimal parameters and insights into the individual and combined effects of energy density parameters provide valuable guidance for mitigating residual stress in SS316L, leading to improved part quality and performance.

The fear of COVID-19 has been identified as a significant predictor of adverse work-related outcomes. Grounded on conservation of resource theory, this study examines the impact of fear of COVID-19 on faculty members' job turnover intention (TI) and job insecurity, as well as the relationship between job insecurity and TI. Additionally, the authors investigate job insecurity as a potential mediating variable between the fear of COVID-19 and TI.

Data were collected from faculty members (n = 226) working in Pakistan's public sector universities and analysed through PLS-SEM using SmartPLS software.

The results indicated that fear of COVID-19 was positively and significantly associated with both TI and job insecurity. Furthermore, the results demonstrate that job insecurity has a positive correlation with TI. In addition, the study's findings endorsed the mediating role of job insecurity between fear of COVID-19 and TI.

The study highlights the importance of addressing the fear of COVID-19 and job insecurity among faculty members, as they are significant predictors of TI. The findings suggest employers should prioritise providing a safe work environment and reducing uncertainty to retain their workforce during the pandemic.

This study adds to the literature as it conceptualises the indirect mechanism that links fear of COVID-19 to TI and job insecurity and provides practical implications that may reduce faculty members' TI.

This exploratory study aims to explore the Pakhtun pregnant women’s experiences/issues during the COVID-19 pandemic.

This research is based on interviews.

This research found that plummeting medical services pose not only serious health risks to the Pakhtun women in Khyber Pakhtunkhwa (KP) but expose them to social and cultural challenges resulting in severe mental health issues. This study also found that the policies adopted by the Government of Pakistan for tackling COVID-19 completely threw off track basic health services that both men and women require in times of health emergencies.

This paper is 100% original research based on an exploratory study.

This paper analyzed a complex system consisting n-identical units under a k-out-of-n: G; configuration via a new method which has not been studied by previous researchers. The computed results are more supportable for repairable system performability analysis.

In this paper, the authors have analyzed a complex system consisting n-identical units under a k-out-of-n: G; configuration via a new method which has not been studied by previous researchers. The supplementary variable technique has employed for analyzing the performance of the system.

Reliability measures have been computed for different types of configuration. It generalized the results for purely series and purely parallel configurations.

This research may be beneficial for industrial system performances whereas a k-out-of-n-type configuration exists.

Not sure as it is a theoretical assessment.

This research may not have social implications.

This work is the sole work of authors that have not been communicated to any other journal before.

In the present era, digital technology can be used responsibly to provide developed and developing countries with high-quality health-care services to nations. This study aims to explore Saudi Arabia’s intentions to adopt digital health-care practices.

To be consistent with previous studies, this study used a quantitative methodology to collect the data from health-care professionals working in Saudi Arabia’s public and private health institutes. Consequently, this study’s findings are based on 306 valid samples.

On the one hand, the path analysis reveals that health-care professionals believe in perceptions relating to the use of e-health and technology (PEHT) and experiences regarding internet use (ERIU) and that these have positive and significant effects on attitudes toward the use of e-health and technology (ATEHT) and intentions to use e-health services (ITUES). On the other hand, barriers to using e-health (BUEH) negatively impact ATEHT and ITUES. Finally, ATEHT also has a positive and significant effect on ITUES.

This study’s findings will help Saudi Arabia’s policymakers and the country’s health ministry to develop policies to provide e-services that health-care professionals can use to improve the quality of the country’s health care, patients’ human rights and social care. Furthermore, this study’s findings are helpful in developing attitudes and intentions toward either e-health or digital health to provide better health facilities to serve Saudi Arabia’s citizens.

This study empirically confirms among Saudi Arabia’s health-care professionals the PEHT, ERIU and BUEH toward ATEHT and ITUES.

The present study aims to construct ensemble machine learning (EML) algorithms for groundwater potentiality mapping (GPM) in the Teesta River basin of Bangladesh, including random forest (RF) and random subspace (RSS).

The RF and RSS models have been implemented for integrating 14 selected groundwater condition parametres with groundwater inventories for generating GPMs. The GPM were then validated using the empirical and bionormal receiver operating characteristics (ROC) curve.

The very high (831–1200 km²) and high groundwater potential areas (521–680 km²) were predicted using EML algorithms. The RSS (AUC-0.892) model outperformed RF model based on ROC's area under curve (AUC).

Two new EML models have been constructed for GPM. These findings will aid in proposing sustainable water resource management plans.