Design Models for Trusted Communications in Vehicle-to-Everything (V2X) Networks

Intelligent transportation system is one of the main systems which has been developed to achieve safe traffic and efficient transportation. It enables the road entities to establish connections with other road entities and infrastructure units using Vehicle-to-Everything (V2X) communications. To improve the driving experience, various applications are implemented to allow for road entities to share the information among each other. Then, based on the received information, the road entity can make its own decision regarding road safety and guide the driver. However, when these packets are dropped for any reason, it could lead to inaccurate decisions due to lack of enough information. Therefore, the packets should be sent through a trusted communication. The trusted communication includes a trusted link and trusted road entity. Before sending packets, the road entity should assess the link quality and choose the trusted link to ensure the packet delivery. Also, evaluating the neighboring node behavior is essential to obtain trusted communications because some misbehavior nodes may drop the received packets. As a consequence, two main models are designed to achieve trusted V2X communications. First, a multi-metric Quality of Service (QoS)-balancing relay selection algorithm is proposed to elect the trusted link. Analytic Hierarchy Process (AHP) is applied to evaluate the link based on three metrics, which are channel capacity, link stability and end-to-end delay. Second, a recommendation-based trust model is designed for V2X communication to exclude misbehavior nodes. Based on a comparison between trust-based methods, weighted-sum is chosen in the proposed model. The proposed methods ensure trusted communications by reducing the Packet Dropping Rate (PDR) and increasing the end-to-end delivery packet ratio. In addition, the proposed trust model achieves a very low False Negative Rate (FNR) in comparison with an existing model

The impact of e-service quality on atitude toward online shopping

The research was designed to fill the gap in the existing body of knowledge regarding attitudes toward online shopping and differences in electronic service quality perception between two different geographical and cultural countries. In addition, this research extended previous effort done in an online shopping context by providing evidence that high service quality increase consumers’ trust perception, which in turn results in favorable attitude toward online shopping, with risk perception moderating the impact on consumer’s trust. Cluster random sampling was used to select respondents with previous online shopping experience. Correlation and hierarchical regression was used to analyze the direct and indirect relationship between service quality, risk, trust and attitude, while t-test was used to compare the two cultures in e-service quality perception. The present study demonstrates that e-service quality is affected by consumer’s culture. This research also provides evidence that trust in Internet shopping is built on high service quality. Notably, risk moderates the effect of e-service quality on trust toward online retailer. Finally, the research highlights the significant effect of trust on the attitude towards online shopping

Could the SARS-CoV-2 infection be acquired from Smartphones?

Based on the provided information, smartphone devices can be a mediator in the transmission of infectious diseases, including SARS-CoV-2 in healthcare centers and the community. It is known that smartphones are no longer only for phone calls, but their use is necessary for communication, health information, e-learning, and medical consultations. Strategies should go beyond the imposition of behavioral controls for individuals with a commitment to regularly disinfect smartphones, portable electronic medical record devices, etc. Besides, finding alternative ways to use these devices in a clinical setting is paramount importance

Graphene Nanoflake Uptake Mediated by Scavenger Receptors

The biological interactions of graphene have been extensively investigated over the last 10 years. However, very little is known about graphene interactions with the cell surface and how the graphene internalization process is driven and mediated by specific recognition sites at the interface with the cell. In this work, we propose a methodology to investigate direct molecular correlations between the biomolecular corona of graphene and specific cell receptors, showing that key protein recognition motifs, presented on the nanomaterial surface, can engage selectively with specific cell receptors. We consider the case of apolipoprotein A-I, found to be very abundant in the graphene protein corona, and observe that the uptake of graphene nanoflakes is somewhat increased in cells with greatly elevated expression of scavenger receptors B1, suggesting a possible mechanism of endogenous interaction. The uptake results, obtained by flow cytometry, have been confirmed using Raman microspectroscopic mapping, exploiting the strong Raman signature of graphene

Advancements in cardiac structures segmentation: a comprehensive systematic review of deep learning in CT imaging

Background Segmentation of cardiac structures is an important step in evaluation of the heart on imaging. There has been growing interest in how artificial intelligence (AI) methods—particularly deep learning (DL)—can be used to automate this process. Existing AI approaches to cardiac segmentation have mostly focused on cardiac MRI. This systematic review aimed to appraise the performance and quality of supervised DL tools for the segmentation of cardiac structures on CT. Methods Embase and Medline databases were searched to identify related studies from January 1, 2013 to December 4, 2023. Original research studies published in peer-reviewed journals after January 1, 2013 were eligible for inclusion if they presented supervised DL-based tools for the segmentation of cardiac structures and non-coronary great vessels on CT. The data extracted from eligible studies included information about cardiac structure(s) being segmented, study location, DL architectures and reported performance metrics such as the Dice similarity coefficient (DSC). The quality of the included studies was assessed using the Checklist for Artificial Intelligence in Medical Imaging (CLAIM). Results 18 studies published after 2020 were included. The DSC scores median achieved for the most commonly segmented structures were left atrium (0.88, IQR 0.83–0.91), left ventricle (0.91, IQR 0.89–0.94), left ventricle myocardium (0.83, IQR 0.82–0.92), right atrium (0.88, IQR 0.83–0.90), right ventricle (0.91, IQR 0.85–0.92), and pulmonary artery (0.92, IQR 0.87–0.93). Compliance of studies with CLAIM was variable. In particular, only 58% of studies showed compliance with dataset description criteria and most of the studies did not test or validate their models on external data (81%). Conclusion Supervised DL has been applied to the segmentation of various cardiac structures on CT. Most showed similar performance as measured by DSC values. Existing studies have been limited by the size and nature of the training datasets, inconsistent descriptions of ground truth annotations and lack of testing in external data or clinical settings. Systematic Review Registration: [www.crd.york.ac.uk/prospero/], PROSPERO [CRD42023431113]

Public knowledge, attitude and practice towards antibiotics use and antimicrobial resistance in Saudi Arabia: A web-based cross-sectional survey

Background: Antimicrobial resistance is a global issue that causes significant morbidity and mortality. Therefore, this study aims to assess knowledge, attitudes, and practices (KAP) of the general Saudi populations toward antibiotics use. Design and methods: A cross-sectional, anonymous online survey was conducted from January 1 to May 11, 2020, across five major regions of Saudi Arabia. Participants (aged ≥18 years) were invited through social media to complete an online self-structured questionnaire. All data were analyzed by Statistical Package (SPSS v.25). Descriptive statistics, Pearson's Chi-squared, t-tests, one-way analysis of variance (ANOVA), and Pearson correlation analyses were conducted. Results: Out of 443 participants, the majority (n=309, 69.8%) were females, 294 (64.4%) were married, 176 (39.7%) were 25-34 years of age, 338 (76.3%) were living in the Eastern Province, 313 (70.7%) had college or higher education, 139 (31.4%) were not working, and 163 (36.8%) had a monthly income of USD 800-1330. Overall, most participants demonstrated good knowledge and practice (88% and 85.6%, respectively).  However, 76.8%had inadequate attitude score levels towards antibiotics use. Of all the respondents, 74.9% knew that not completing a full course of antibiotics may cause antibiotics resistance, 91.33% did not agree that antibiotics should be accessed without a prescription, and 94.04% will not hand over leftover antibiotics to family members. Factors associated with adequate knowledge were female, medical jobs, and higher income (p<0.05). Conclusions: Our findings revealed that while most participants were aware of antibiotics use and demonstrated good knowledge, good practices, they had negative attitudes towards antibiotics use

Perceived responsibility for mechanical ventilation and weaning decisions in intensive care units in the Kingdom of Saudi Arabia

Background: Optimizing patient outcomes and reducing complications require constant monitoring and effective collaboration among critical care professionals. The aim of the present study was to describe the perceptions of physician directors, respiratory therapist managers and nurse managers regarding the key roles, responsibilities and clinical decision-making related to mechanical ventilation and weaning in adult Intensive Care Units (ICUs) in the Kingdom of Saudi Arabia (KSA). Methods: A multi-centre, cross-sectional self-administered survey was sent to physician directors, respiratory therapist managers and nurse managers of 39 adult ICUs at governmental tertiary referral hospitals in 13 administrative regions of the KSA. The participants were advised to discuss the survey with the frontline bedside staff to gather feedback from the physicians, respiratory therapists and nurses themselves on key mechanical ventilation and weaning decisions in their units. We performed T-test and non-parametric Mann-Whitney U tests to test the physicians, respiratory therapists, and nurses’ autonomy and influence scores, collaborative or single decisions among the professionals. Moreover, logistic regressions were performed to examine organizational variables associated with collaborative decision-making. Results: The response rate was 67% (14/21) from physician directors, 84% (22/26) from respiratory therapist managers and 37% (11/30) from nurse managers. Physician directors and respiratory therapist managers agreed to collaborate significantly in most of the key decisions with limited nurses’ involvement (P<0.01). We also found that physician directors were perceived to have greater autonomy and influence in ventilation and waning decision-making with a mean of 8.29 (SD±1.49), and 8.50 (SD±1.40), respectively. Conclusion: The key decision-making was implemented mainly by physicians and respiratory therapists in collaboration. Nurses had limited involvement. Physician directors perceived higher autonomy and influence in ventilatory and weaning decision-making than respiratory therapist managers and nurse managers. A critical care unit’s capacity to deliver effective and safe patient care may be improved by increasing nurses’ participation and acknowledging the role of respiratory therapists in clinical decision-making regarding mechanical ventilation and weaning