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Volatile flavor plays a main role in defining the fruit quality by consumers. Bruising leads often to dark spots on fruits and its amount could highly affect product quality. This paper aims to study the effect of bruising on the volatilome released by pears by using proton transfer reaction – mass spectrometry (PTR-MS).

Fingerprints of non-bruised and bruised pear samples were collected through PTR-MS for 28 days, and discriminant analysis was used to discriminate the fruit products. The CIELAB color changes were also measured during the entire ripening period.

Bruised pears released a higher intensity of volatile organic compounds (VOCs) compared to non-bruised pears (p_16days = 0.049, p_22days = 0.012, p_28days = 0.006). In particular, the release of m/z 45 and m/z 47 were significantly (p_m/z 45 = 0.076, p_m/z 47 = 0.095.) higher in bruised samples, suggesting that the bruising event accelerated the natural ripening process. CIELAB color coordinates were also recorded. The coordinate a* showed a linear increase during the whole 28 days because of the loss of the green component. The CIELAB ΔE* was higher in the bruised pears than the non-bruised pears (p = 0.022).

Bruising can affect food quality and taste. Bruise susceptibility has been largely studied on apples, tomatoes and peaches, but rarely on pears. Very little is known about the effect of bruising on the volatilome of pears. Moreover, bruising research usually involved the study of physical properties; on the contrary, PTR-MS, applied to bruising research, has never been used before. Besides the analysis of volatilome, the changes in color were also recorded for the whole 28 days of analysis. The proposed method could be applied for the monitoring of pears quality in the food industry.

Fingerprints and blood samples are important for the identification of individuals and criminals. The present study aims to identify the predominant fingerprint patterns and the association between the fingerprint patterns and ABO–Rh blood groups in Omani population.

A cross-sectional study was conducted on 200 Omani individuals aged 18 years (104 males and 96 females). The imprints of all right and left-hand fingers were taken, and the types of the fingerprints were determined using a standard protocol. The blood group of all the subjects was recorded. Chi-square test was performed to identify the association between the fingerprint patterns and the ABO and Rh blood groups.

The loop fingerprint pattern was the most common in Omani subjects (49.4%), followed by whorl (44.9%) and arch (5.7%) pattern. A significant association (p < 0.001) was found between gender and fingerprint pattern. The loop was the highest occurring pattern in the females (54.6%), while the whorl was more in males (50.0%). The whorl pattern was the most common in the AB+ and O− groups. The loop was a predominant pattern in the A+, A−, B+, B− and O+ groups. The Chi-square test also revealed a significant correlation between different fingerprint patterns and blood groups of the subjects (p < 0.001).

The present study is an outcome of undergraduate student's research project thesis for the Doctor of Medicine (MD) program. The results of the present study may help in creating a data bank for biometrics, which can be useful for diagnosing associated diseases and also help in identification of individuals.

This paper aims to propose a solution for detecting and grading diabetic retinopathy (DR) in retinal images using a convolutional neural network (CNN)-based approach. It could classify input retinal images into a normal class or an abnormal class, which would be further split into four stages of abnormalities automatically.

The proposed solution is developed based on a newly proposed CNN architecture, namely, DeepRoot. It consists of one main branch, which is connected by two side branches. The main branch is responsible for the primary feature extractor of both high-level and low-level features of retinal images. Then, the side branches further extract more complex and detailed features from the features outputted from the main branch. They are designed to capture details of small traces of DR in retinal images, using modified zoom-in/zoom-out and attention layers.

The proposed method is trained, validated and tested on the Kaggle dataset. The regularization of the trained model is evaluated using unseen data samples, which were self-collected from a real scenario from a hospital. It achieves a promising performance with a sensitivity of 98.18% under the two classes scenario.

The new CNN-based architecture (i.e. DeepRoot) is introduced with the concept of a multi-branch network. It could assist in solving a problem of an unbalanced dataset, especially when there are common characteristics across different classes (i.e. four stages of DR). Different classes could be outputted at different depths of the network.

Maintaining food safety techniques in the supply chain management require special food safety labelling techniques during distribution in the retail food industry. The food products have to be of good quality and labelling inbound, manufacturing, and outbound in the supply chain contributes to this aim. The purpose of this study is to evaluate how food safety labelling is managed in Vietnam’s retail food industry with a special focus on food in Ho Chi Minh City, Vietnam. Photography was used in an observational study conducted among five separate retail market chains all located in this city. In which ways are the applications of the developed food safety labelling techniques among three separate retail food markets similar and dissimilar being accounted for? The results show that the packaging and labelling in Big C, Aeon Citimart, and Giant using the symbols of food safety build trust for their customers. The Big C indicates guidelines for VietGAP and green labelling. Aeon Citimart indicates the name of the good, expiration date and instructions for use as well as guidelines for the government factor (VietGAP) to the food safety practices in the Vietnamese food retail sector.

Studies on the coronavirus disease 2019 (COVID-19) tracing apps have mostly focused on how to optimize adoption and continuous use, but did not consider potential long-term effects of their introduction. This study aims to analyse whether the characteristics of the recent introduction of tracing apps may negatively impact individuals' attitudes and intentions to adopt future tracking technology.

In an online experiment across three countries (Australia, Germany, UK), the authors measured how perceived benefits of COVID-19 tracing apps as well as specific government and campaign-related factors affect privacy concerns, attitude towards future tracking apps and intention to adopt. The authors manipulated the type of provider (governmental vs private) and the type of beneficiaries of the future tracking technology app (the individual alone or also the public) as determinants of adoption.

The authors find that privacy concerns towards the COVID-19 tracing apps negatively impact attitude and intention to adopt future tracking apps. Future adoption is more likely if the app is provided by the government, whereas additional benefits to the public do not positively stimulate adoption. Second, the study analyzed different factors, including perceptions on governments and the app introduction, as well as perceived benefits.

Taking the introduction of COVID-19 apps in different countries as a basis, the authors link both perceived benefits and contextual factors to privacy concerns, attitudes towards and intention to adopt the related technology in the future. The authors hereby clarify the responsibility of governmental actors who conduct large-scale technology introductions for the future diffusion of related technologies.

This paper aims to examine the moderated mediation effect of the lack of students’ socialization (as one of the COVID-19 consequences) and the university reputation on the relationship between the service innovation and students satisfaction. The relationship between students satisfaction and their loyalty is also examined.

This study adopts a quantitative research approach, whereas the study population consists of all universities’ students in Lebanon. Data were collected from 201 students, elected depending on snowballing sample technique. A questionnaire was used to gather data, whereby partial least squares structural equation modeling was used to check the proposed scales validity and the relationships between the study variables.

The findings reveal a significant direct effect for university’s service innovation on students satisfaction and an indirect effect through the mediation role for university reputation. Moreover, an evidence for weak negative significant effect for lack of socialization on students satisfaction exists. Whereby, lack of socialization does not moderate the relationship between university service innovation and students satisfaction. Finally, students satisfaction has a significant positive effect on their loyalty.

This paper advances the service innovation literature in the higher education sector. In addition, the paper might be the first paper to address the influence of lack of socialization as one of the COVID-19 consequences on students satisfaction. Furthermore, areas for future research are suggested.

Gaining independence from fossil fuels and combating climate change are the main factors to increase the generation of electricity from renewable fuels. Amongst the renewable technologies, solar photovoltaic (PV) is believed to have the largest potential. However, the number of people adopting solar PV technologies is still relatively low. Therefore, the purpose of this paper is to examine the household consumers’ acceptance of solar PV technology being installed on their premises.

To examine the solar PV technology acceptance, this study uses technology acceptance model (TAM) as a reference framework. A survey was conducted to gather data and to validate the research model. Out of 780 questionnaires distributed across Malaysia, 663 were returned and validated.

The analysis revealed that perceived ease of use, perceived usefulness and attitude to use significantly influenced behavioural intention to use solar PV technology.

This study contributes by extending the understanding of public inclination towards the adoption of solar PV technology. Also, this study contributes in identifying the areas which need to be examined further. However, collecting data from urban peninsular Malaysian respondents only limits the generalization of the results.

On the policy front, this study reveals that governmental support is needed to trigger PV acceptance.

This paper uses TAM to analyse the uptake of solar PV technology in Malaysian context.

This study aims to explore the risk and protective factors of abuse on older adults by family caregivers, with a special focus on the protective role of caregiver resilience in elder abuse.

This cross-sectional survey was conducted on a purposive sample of 600 family caregivers of community-dwelling older adults in Hong Kong (mean age = 71.04 and female = 67.2%). Caregivers reported in a guided interview about elder abuse behaviours, caregiver burden, care recipients’ agitated behaviours, caregiver resilience, self-efficacy, social support and basic demographic characteristics. Hierarchical linear regression analyses were conducted to examine the predictors of different forms of elder abuse.

Caregiver resilience was predictive of lower levels of verbal abuse, physical abuse, injury and financial exploitation but not potentially harmful behaviour (PHB). Social support was independent with all forms of elder abuse, while self-efficacy predicted greater physical abuse after the adjustment of confounding variables. Caregiver burden and agitated behaviours by care recipients remained as significant risk factors in the final models when protective factors were considered.

This study extends current knowledge on the protecting role of resilience in elder abuse in family caregiving. Mixed findings revealed on social support and self-efficacy also highlight the complexity of the prediction of caregiver abuse. Further research should address this area.

The findings of this study warrant the inclusion of caregiver resilience as a key component in developing interventions to prevent elder abuse. Addressing caregiver burden and agitated behaviours have the potential in preventing elder abuse.

The findings raise awareness of the importance of supporting caregivers in the community to prevent elder abuse.

Research concerning the protective factors of elder abuse is in a preliminary stage. To the best of the authors’ knowledge, this study is among the first which successfully demonstrates the protective role of resilience in caregiver abuse on older adults. The findings shed invaluable light on the design of effective interventions.

The purpose of this paper is to describe the mental health issues among teachers globally and to investigate the significant factors that specifically impact the mental health of school teachers in Okinawa, Japan.

This cross-sectional study examined depression, anxiety, stress, self-esteem and resiliency among 174 teachers from seven schools in Okinawa, Japan. The study questionnaire consisted of four parts, including demographic data, Depression, Anxiety, and Stress scale (DASS-42), Rosenberg Self-Esteem Scale (RSE), and Connor-Davidson Resiliency Scale (CD-RISC). Multiple regression analyses were performed to identify predictors of mental health variables.

Of the 174 teachers, 111 were females (64%) and 60 were males (35%). Average age of participants was 41.65 (SD = 10.07). Average number of years being a teacher was 15.50 (SD = 9.88). There was a significant gender difference in the level of self-esteem. Significant differences in anxiety were found among varying grade levels taught. Regression analyses indicated that resiliency and self-esteem significantly predicted depression, anxiety and stress among school teachers in Okinawa.

This is the first study among school teachers in Okinawa that examined the impact of resiliency and self-esteem on their mental health. To reduce psychological distress common within the teaching profession, social and environmental support should be provided within the school to better foster the successful promotion of teacher resiliency and self-esteem.