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This paper examines the impact of sharia-compliant debt financing on stock price crash risk. Unlike those previous studies that took Sukuk or sharia-compliant firms, this study tests the impact of the proportion reported sharia-compliant debt financing in the balance sheet on the risk of price crash of a firm.

Using the data from 2,752 firm-year observations of 344 Malaysian non-financial listed companies from 2012 to 2019, this article used a robust panel data estimation technique for statistical inferences. This study also employs panel GMM and quantile least squares as the robustness check.

This study established a negative relationship between sharia-compliant debt financing and stock price crash risk. The robustness checks with different estimation techniques confirm the results. It implies that firms with a more significant proportion of Sharia-compliant financing tend to have lower future stock price crash risk.

Consistent with the Islamic finance literature, the present study contributes to the existing literature on Islamic capital markets from the perspective of stock price crash risk because it is vital for risk management and investment decision-making as a measure of tail risk for stocks. The findings of this research will assist investors in developing portfolio strategies that incorporate firms with higher levels of sharia-compliant debt financing in their balance sheets. Additionally, the results of this study suggest that policymakers and regulatory bodies should consider revising their monitoring approaches for publicly listed firms.

This study is interesting and unique, as it is a pioneer in testing the impact of sharia-compliant debt financing on reducing stock price crash risk.

Bacterial vaginosis (BV) is quite common and linked with serious public health issues such as premature delivery and spread of sexually transmitted infections. The study aims to identify different genital mycoplasmas (GM) in high vaginal swabs (HVS) from adult females in Bahrain.

In total, 401 HVS were collected and cultured on MYCOFAST^® RevolutioN 2 test for identification and antibiotic susceptibility. Polymerase chain reaction (PCR) was performed for detection of Mycoplasma genitalium (Mg), Mycoplasma hominis (Mh) and Ureaplasma species. DNA-probe based detection for Gardnerella, Candida and Trichomonas was performed by BD Affirm Assay. Representative PCR amplicons were sequenced by Sanger sequencing.

In PCR, Ureaplasma sp. was the most common GM, followed by Mg and Mh; the prevalence being 21.2, 5.2 and 1.5%, respectively. On the contrary, 10.7% samples showed positivity for Ureaplasma urealyticum (Uu) and 1.7% for Mh in MYCOFAST^® RevolutioN 2. The concordance rates between MYCOFAST^® RevolutioN 2 and PCR for Mh and Ureaplasma sp. were 97.7 and 84%, respectively. Considering PCR as gold standard, sensitivity, specificity, positive predictive value, and negative predictive value of MYCOFAST^® RevolutioN 2 were 33.3, 98.8, 28.6, 98.9 and 37.7, 96.5, 74.4, 85.2% for Mh and Ureaplasma sp., respectively. The Uu and Mh isolates showed antibiotic-resistance ranging from 53%–58% and 71%–86%, respectively.

The prevalence of Ureaplasma sp. was high. Significant co-occurrence of GM was noticed with BV. MYCOFAST^® RevolutioN 2 had lower detection-rate than PCR, so a combination is suggested for wider diagnostic coverage.

The research reflects on status of prevalence of GM in adult females in Bahrain, and their co-occurrence with bacterial vaginosis. Diagnostic approach with combination of tests is suggested for wider coverage. The research has epidemiologic, diagnostic, and therapeutic implications.

This is the first report from the Kingdom of Bahrain reflecting on burden of GM from this geographic location. The diagnostic efficacy of MYCOFAST^® RevolutionN 2 test and polymerase chain reaction was evaluated for GM detection.

This study aims to investigate tourists’ attitudes and intentions regarding the usage of Chat Generative Pre-trained Transformer (ChatGPT) for accessing tourism information. Furthermore, by integrating the perceived risks associated with ChatGPT and the theory of planned behavior (TPB), this research examines the impact of three types of perceived risks, such as privacy risk, accuracy risk and overreliance risk, on tourists’ behavioral intention.

Data were gathered for this study by using two online survey platforms, thus resulting in a sample of 536 respondents. The online survey questionnaire assessed tourists’ perceived risks, attitude, subjective norm, perceived behavioral control, behavioral intention and demographic information related to their usage of ChatGPT.

The structural equation modeling analysis revealed that tourists express concerns about the associated risks of using ChatGPT to search for tourism information, specifically privacy risk, accuracy risk and overreliance risk. It was found that perceived risks significantly influence tourists’ attitude and intention toward the usage of ChatGPT, which is consistent with the hypotheses proposed in previous literature regarding tourists’ perceived risks of ChatGPT.

This work is a preliminary empirical study that assesses tourists’ behavioral intention toward the use of ChatGPT in the field of tourism. Previous research has remained at the hypothetical level, speculating about the impact of ChatGPT on the tourism industry. This study investigates the behavioral intention of tourists who have used ChatGPT to search for travel information. Furthermore, this study provides evidence based on the outcome of this research and offers theoretical foundations for the sustainable development of generative AI in the tourism domain. This study has limitations in that it primarily focused on exploring the risks associated with ChatGPT and did not extensively investigate its range of benefits.

First, to address privacy concerns that pose significant challenges for chatbots various measures, such as data encryption, secure storage and obtaining user consent, are crucial. Second, despite concerns and uncertainties, the introduction of ChatGPT holds promising prospects for the tourism industry. By offering personalized recommendations and enhancing operational efficiency, ChatGPT has the potential to revolutionize travel experiences. Finally, recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises.

Recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises. As their interest in adopting ChatGPT grows, increased investments and resources will be dedicated to developing and implementing ChatGPT solutions. This enhancement may involve creating customized ChatGPT solutions and actively engaging in training and development programs to empower employees in effectively using ChatGPT’s capabilities. Such initiatives can contribute to improved customer service and overall operations within the tourism industry.

This study integrates TPB with perceived risks in ChatGPT, thus providing empirical evidence. It highlights the importance of considering perceived risks in tourists’ intentions and contributes to the sustainable development of generative AI in tourism. As such, it provides valuable insights for practitioners and policymakers.

本研究旨在调查游客对使用ChatGPT获取旅游信息的态度和意向。此外, 通过将与ChatGPT相关的感知风险与计划行为理论（TPB）相结合, 本研究探讨了三种感知风险（隐私风险、准确性风险和过度依赖风险）对游客行为意向的影响。

本研究通过两个在线调查平台收集了536名受访者的数据。在线调查问卷评估了游客对ChatGPT使用的感知风险、态度、主观规范、感知行为控制、行为意向以及与其使用ChatGPT相关的人口统计信息。

结构方程建模分析显示, 游客对使用ChatGPT搜索旅游信息的相关风险表示关切, 特别是隐私风险、准确性风险和过度依赖风险。发现感知风险显著影响游客对使用ChatGPT的态度和意向, 与先前有关游客对ChatGPT感知风险的文献中提出的假设一致。

本研究将TPB与ChatGPT中的感知风险相结合, 提供了实证证据。它强调了在考虑游客意向时考虑感知风险的重要性, 并为旅游中生成AI的可持续发展提供了贡献。因此, 它为从业者和政策制定者提供了宝贵的见解。

ß-thalassemia is a hereditary disorder due to mutation in the ß-globin gene on chromosome 11. Out of 200 known ß-globin gene chain mutations recognized, it is better to identify the most common mutation in specific regions and ethnicity for cost-effective molecular diagnosis of this disorder. Therefore, this study aims to practice multiplex-amplification refractory mutation system (ARMS) PCR on patients with thalassemia in Khyber Pakhtunkhwa (KP) to investigate the most common mutations in the ß-globin chain gene.

Twenty-two individuals (patients, their parents and non-affected siblings) with signed consent were studied from six consanguineous families of ß-thalassemia. Blood samples were collected for DNA isolation. For the detection of mutations in the ß-globin gene, ARMS-PCR was used. The amplicon was visualized through 2% Agarose Gel.

The most common mutations among different ethnic groups in the study area residents were Fr 8-9 (+G) and IVS 1-5 (G> C). The prominent enhancing factors for ß-thalassemia are inter-family marriages and lack of awareness.

Multiplex ARMS_PCR is the most valuable technique for assessing multiple mutations in a single reaction tube.

Due to extensively found ethnic and regional variations and a high rate of consanguinity, the Pashtun population has a great risk of mutations in their genome. Therefore, ARMS-PCR is a cost-effective mutational diagnostic strategy that can help to control disease burden.

Limited studies using ARMS-PCR for mutational analysis in the ß-globin gene are conducted. This study is unique as it targeted consanguineous families of KP Pakistan.

This study aims to demonstrate the possibility of showing the functionality of complex microbial groups, within ancient structures within a process of refurbishment on a heritage building information modelling (BIM) platform.

Both a qualitative and qualitative research method will be used throughout, as observational and scientific results will be obtained and collated. This path being; phenomena – acquisition tools – storage – analysis tools – literature. Using this methodology, one pilot study within the scope of demolition and refurbishment, using suitable methods of collecting and managing data (structural or otherwise), will be used and generated by various software and applications. The principle methods used for the identification of such micro-organisms will incorporate a polymerase chain reaction method (PCR), to amplify DNA and to identify any or all spores present. The BIM/historical BIM (HBIM) process will be used to create a remotely-based survey to obtain and collate data using a laser scanner to produce a three-dimensional point cloud model to evaluate and deduce the condition, make-up and stature of the monument. A documentation management system will be devised to enable the development of plain language questions and an exchange information requirement, to identify such documentation required to enable safe refurbishment and to give health and safety guidance. Four data sampling extractions will be conducted, two for each site, within the research, for each of the periods being assessed, that being the Norman and Tudor areas of the monument.

From laboratory PCR analysis, results show a conclusive presence of micro-organism groups and will be represented within a hierarchical classification, from kingdom to species.

The BIM/HBIM process will highlight results in a graphical form to show data collected, particularly within the PCR application. It will also create standardisation and availability for such data from ancient monuments to make available all data stored, as such analysis becomes substantially important to enable the production of data sets for comparison, from within the framework of this research.

The purpose of this study was to determine the influence of environmental pH on production of biofilms and virulence genes expression in Pseudomonas aeruginosa.

Among 303 clinical and environmental samples 109 (61 + 48) isolates were identified as clinical and environmental P. aeruginosa isolates, respectively. Clinical samples were obtained from patients in the Al-Yarmouk hospital in Baghdad city, Iraq. Waste water from Al-Yarmouk hospital was used from site before treatment unit to collect environmental samples. The ability of producing biofilm at various pH levels was examined by microtiter plate and the prevalence of Alg D, Psl A and Pel A was determined by quantitative real time-polymerase chain reaction (qRT-PCR).

This study showed that the ability of clinical and environmental isolates to biofilm development was observed in 86.9% and 85.42% of clinical and environmental isolates, respectively. As well as, the environmental P. aeruginosa isolates showed the highest biofilm production at pH 7. Clinical isolates showed the highest genes expression of Alg D, Psl A and Pel A as compared to environmental isolates with pH change. In general, both clinical and environmental isolates formed biofilm and carried AlgD, PslA and PelA genes. Also, alkaline pH was favored for biofilm production.

There are very few studies done to find out the influence of environmental pH on production of biofilms and virulence genes expression in Pseudomonas aeruginosa. This study is unique as it has highlighted the influence of environmental pH on the ability of clinical and environmental isolates to biofilm development and genes expression.

Nature and occurrence of food-borne pathogens in raw and processed food products evolved greatly in the past few years due to new modes of transmission and resistance build-up against sundry micro-/macro-environmental conditions. Assurance of food health and safety thus gained immense importance, for which bio-sensing technology proved very promising in the detection and quantification of food-borne pathogens. Considering the importance, different studies have been performed, and different biosensors have been developed. This study aims to summarize the different biosensors used for the deduction of food-borne pathogens.

The present review highlights different biosensors developed apropos to food matrices, factors governing their selection, their potential and applicability. The paper discusses some related key challenges and constraints and also focuses on the needs and future research prospects in this field.

The shift in consumers’ and industries’ perceptions directed the further approach to achieve portable, user and environmental friendly biosensing techniques. Despite of these developments, it was still observed that the comparison among the different biosensors and their categories proved tedious on a single platform; since the food matrices tested, pathogen detected or diagnosed, time of detection, etc., varied greatly and very few products have been commercially launched. Conclusively, a challenge lies in front of food scientists and researchers to maintain pace and develop techniques for efficiently catering to the needs of the food industry.

Biosensors deduction limit varied with the food matrix, type of organism, material of biosensors’ surface, etc. The food matrix itself consists of complex substances, and various types of food are available in nature. Considering the diversity of food there is a need to develop a universal biosensor that can be used for all the food matrices for a pathogen. Further research is needed to develop a pathogen-specific biosensor that can be used for all the food products that may have accuracy to eliminate the traditional method of deduction.

The present paper summarized and categorized the different types of biosensors developed for food-borne pathogens.

The COVID-19 pandemic had a huge impact on people's lives, air travel and tourism. The authors explored travelers' perceptions of COVID rapid antigen tests before boarding aircraft, willingness to fly and the precautionary actions for safe air travel.

All the participants were asked to complete the survey while reflecting on their experiences of air travel during this COVID-19 pandemic. The questionnaire consisted of demographic information of the participants and air travel preferences during pandemic. The survey was conducted through Google Form in both English and Arabic language. The link was shared through emails and WhatsApp.

In this survey, majority had willingness to fly during pandemic. 45.2% preferred to undergo rapid test before boarding, while 41.9% refused owing to no added benefit (23.8%) and nasal discomfort (9.3%) among others. The best indicators to resume safe air travel were COVID-19 vaccination (80.4%), wearing face mask during flying hours (70.8%) and maintain social distancing with aircraft seating (49.6%).

The findings of the current survey could help the organizations and the biosecurity authorities to act and support accordingly and thus reduce passenger anxiety about resuming the flights, thereby increasing willingness to fly and preparing oneself and the aviation industry for future pandemics.

The findings of the current survey could help the organizations and the biosecurity authorities to act and support accordingly and thus reduce passenger anxiety about resuming the flights, thereby increasing willingness to fly, and preparing oneself and the aviation industry for future pandemics.

This study investigates the relationship between credit booms and bank risk in Association of Southeast Asian Nations (ASEAN) countries, with credit information sharing acting as a moderator.

The authors use a two-step System Generalized Method of Moments (SGMM) estimator on a sample of 79 listed banks in 5 developing ASEAN countries: Indonesia, Philippines, Malaysia, Thailand and Vietnam in the period 2006–2019. In addition, the authors perform robustness tests with different proxies for credit booms and bank risk. The data are collected on an annual basis.

Bank risk is positively related to credit booms and is negatively associated with credit information sharing. Further, credit information sharing reduces the detrimental effect of credit booms on bank stability. The authors find that both public credit registries and private credit bureaus are effective in enhancing bank stability in ASEAN countries. These results are robust to regression models with alternative proxies for credit booms and bank risk.

Banks in ASEAN countries tend to have strong lending growth to support the economy, but this could be detrimental to stability of the sector. Credit information sharing schemes should be encouraged because these schemes might enable growth of credit without compromising bank stability. Therefore, policymakers could promote private credit bureaus (PCB) and public credit registries (PCR) to realize their benefits. The authors' research focuses on developing ASEAN countries, but future research could provide more evidence by expanding this study to other emerging economies. In-depth interviews and surveys with bankers and regulatory bodies about these concerns could provide additional insights in the future.

The study is the first to examine the role of PCB and PCR in alleviating the negative impact of credit booms on bank risk. Furthermore, the authors use both accounting-based and market-based risk measures to provide a fuller view of the impact. Finally, there is little evidence on the link between credit booms, credit information sharing and bank risk in ASEAN, so the authors aim to fill this gap.

Since the beginning of 2020, economies faced many changes as a result of coronavirus disease 2019 (COVID-19) pandemic. The effect of COVID-19 on the Egyptian Exchange (EGX) is investigated in this research.

To explore the impact of COVID-19, three periods were considered: (1) 17 months before the spread of COVID-19 and the start of the lockdown, (2) 17 months after the spread of COVID-19 and the during the lockdown and (3) 34 months comprehending the whole period (before and during COVID-19). Due to the large number of variables that could be considered, dimensionality reduction method, such as the principal component analysis (PCA) is followed. This method helps in determining the most individual stocks contributing to the main EGX index (EGX 30). The PCA, also, addresses the multicollinearity between the variables under investigation. Additionally, a principal component regression (PCR) model is developed to predict the future behavior of the EGX 30.

The results demonstrate that the first three principal components (PCs) could be considered to explain 89%, 85%, and 88% of data variability at (1) before COVID-19, (2) during COVID-19 and (3) the whole period, respectively. Furthermore, sectors of food and beverage, basic resources and real estate have not been affected by the COVID-19. The resulted Principal Component Regression (PCR) model performs very well. This could be concluded by comparing the observed values of EGX 30 with the predicted ones (R-squared estimated as 0.99).

To the best of our knowledge, no research has been conducted to investigate the effect of the COVID-19 on the EGX following an unsupervised machine learning method.