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This paper proposes a solution for recognizing human faces under mask-wearing. The lower part of human face is occluded and could not be used in the learning process of face recognition. So, the proposed solution is developed to recognize human faces on any available facial components which could be varied depending on wearing or not wearing a mask.

The proposed solution is developed based on the FaceNet framework, aiming to modify the existing facial recognition model to improve the performance of both scenarios of mask-wearing and without mask-wearing. Then, simulated masked-face images are computed on top of the original face images, to be used in the learning process of face recognition. In addition, feature heatmaps are also drawn out to visualize majority of parts of facial images that are significant in recognizing faces under mask-wearing.

The proposed method is validated using several scenarios of experiments. The result shows an outstanding accuracy of 99.2% on a scenario of mask-wearing faces. The feature heatmaps also show that non-occluded components including eyes and nose become more significant for recognizing human faces, when compared with the lower part of human faces which could be occluded under masks.

The convolutional neural network based solution is tuned up for recognizing human faces under a scenario of mask-wearing. The simulated masks on original face images are augmented for training the face recognition model. The heatmaps are then computed to prove that features generated from the top half of face images are correctly chosen for the face recognition.

This study examined the risk factors associated with hypertension in Bhutan.

The cross-sectional data of 30,889 adults from the National Health Survey of Bhutan was used in this study. Multivariable regression accounting for the complex survey design was performed to identify the risk factors. The backward elimination approach was applied in the multivariable analysis.

The prevalence of hypertension was 17%. Increasing age, being female, being previously married, higher wealth status, past alcohol use, having diabetes, loneliness, health service use and low vegetable intake was associated with increased hypertension risk, whereas, higher education level, being employed and residing in the eastern region was associated with reduced risk. Age, gender, education, wealth status, diabetes status, loneliness and health service use were common factors in all the regions. Marital status and vegetable intake were associated with hypertension in the western and central regions, and alcohol use in the eastern and central regions.

Affecting around one-sixth of the population, hypertension is a significant public health problem in Bhutan. Interventions to improve health education and access, motivate healthy lifestyles, and reduce harmful alcohol use, and strategies to create health-promoting social and built environments are needed to curb the hypertension epidemic and its consequences.

The study examined the personal information management (PIM) challenges encountered by faculty in six universities in Ghana, their information refinding experiences and the perceived role of memory. The study tested the hypothesis that faculty PIM performance will significantly differ when the differences in the influence of personal factors (age, gender and rank) on their memory are considered.

The study was guided by a sample survey design. A questionnaire designed based on themes extracted from earlier interviews was used to collect quantitative data from 235 faculty members from six universities in Ghana. Data analysis was undertaken with a discrete multivariate Generalized Linear Model to investigate how memory intermediates in the relationship between age, gender and rank, and, refinding of stored information.

The paper identified two subfunctions of refinding (Refinding 1 and Refinding 2) associated with self-confidence in information re-finding, and, memory (Memory 1 and Memory 2), associated with the use of complimentary frames to locate previously found and stored information. There were no significant multivariate effects for gender as a stand-alone variable. Males who were aged less than 39 could refind stored information irrespective of the memory class. Older faculty aged 40–49 who possess Memory 1 and senior lecturers who possess Memory 2 performed well in refinding information. There was a statistically significant effect of age and memory; and rank and memory.

This study was limited to faculty in Ghana, whereas the study itself has implications for demographic differences in PIM.

Identifying how memory mediates the role of personal factors in faculty refinding of stored information will be necessary for the efforts to understand and design systems and technologies for enhancing faculty capacity to find/refind stored information.

Understanding how human memory can be augmented by technology is a great PIM strategy, but understanding how human memory and personal factors interplay to affect PIM is more important.

PIM of faculty has been extensively examined in the literature, and limitations of memory has always been identified as a constraint. Human memory has been augmented with technology, although the outcome has been very minimal. This study shows that in addition to technology augmentation, personal factors interplay with human memory to affect PIM. Discrete multivariate Generalized Linear Model applied in this study is an innovative way of addressing the challenges of assimilating statistical methodologies in psychosocial disciplines.

Coronavirus disease 2019 (COVID-19) has had a tremendous negative effect on the economies around the world by infusing uncertainty into supply chains. In this paper, the authors address two important research questions (RQs): (1) did COVID-19 wage subsidies impact small and medium enterprises (SMEs) to become more flexible towards the SMEs' business customers and (2) can such flexibility be a source for greater resilience to the crisis? As a result, the authors investigate the relationship between governmental wage subsidies and SMEs' flexibility norms towards the SMEs' business customers (study 1). The authors further uncover when and how flexibility towards existing customers contributes to SME resilience (study 2).

The authors frame the inquiry under the resource dependence theory (RDT) and behavioural additionality principle. The authors use survey methodology and test the assumptions in study 1 (n = 225) and study 2 (n = 95) on a sample of SMEs from various business-to-business (B2B) industries in Croatia.

Overall, in study 1, the authors find that SMEs that receive governmental wage subsidies have greater flexibility norms. However, this relationship is significantly conditioned by SMEs' competitive profile. SMEs that strongly rely on innovation are more willing to behave flexibly when receiving subsidies, whereas SMEs driven by branding do not. Study 2 sheds light on when flexibility towards existing customers increases SME resilience. Findings show that flexibility norms are negatively related to resilience, but this relationship is becoming less negative amongst SMEs with lower financial dependence on the largest customer.

This study extends RDT in the area of firm–government relationships by showing that wage subsidies became a source of power for the Government and a source of dependency for SMEs. In such cases, the SMEs receiving those subsidies align with the governmental agenda and exhibit higher flexibility towards the SMEs' customers. Drawing arguments from behavioural additionality, the authors show that this effect varies due to SMEs' attention and organisational priorities resulting from different competitive profiles. Ultimately, the authors showcase that higher flexibility norms can contribute to resilience if the SME restructures its dependency by having a less-concentrated customer base.

The use of digital technologies in the financial service industry has brought new complexities to the corporate governance in banks. Relying on the agency perspective of the shareholder, debtholder and societal governance in banks, this research examines the impact of financial technology innovation (FinTech) on banks' performance by enlightening the monitoring role of female independent directors.

Relying on a sample of Italian banks observed during the period 2016–2020, the authors hand-collected data on the use of FinTech by considering (1) the in-house provisions of FinTech solutions, (2) the collaboration with external FinTech firms and (3) a combination of both measures. The authors run a panel data regression analysis with fixed effects, measuring bank performance through bank competitiveness and bank riskiness.

The authors find that FinTech increases bank competitiveness in gathering money from depositors and that independent women on board mitigate the negative relationship between FinTech and the riskiness of banks' assets, ameliorating the conflicting interests among shareholders, debtholder and societal governance.

This study emphasizes the complexities of bank governance when dealing with FinTech in the wider perspective of equity governance, debt governance and the societal governance spotlighting the importance of appointing female directors in independent positions to enhance the bright sides of financial innovation. The authors enrich the literature on FinTech with a finer understanding of the drivers and implications of in-house provisions of FinTech solutions versus the collaboration with external FinTech firms.