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Uncrewed Aerial Vehicles (UAV) constitute a rapidly evolving technology field that is becoming more accessible and capable of supplementing, expanding, and even replacing some traditionally manual bridge inspections. Given the classification of the bridge inspection types as initial, routine, in-depth, damage, special, and fracture critical members, specific UAV mission requirements can be developed, and their suitability for UAV application examined. Results of a review of 23 applications of UAVs in bridge inspections indicate that mission sensor and payload needs dictate the UAV configuration and size, resulting in quadcopter configurations being most suitable for visual camera inspections (43% of visual inspections use quadcopters), and hexa- and octocopter configurations being more suitable for higher payload hyperspectral, multispectral, and Light Detection and Ranging (LiDAR) inspections (13%). In addition, the number of motors and size of the aircraft are the primary drivers in the cost of the vehicle. 75% of vehicles rely on GPS for navigation, and none of them are capable of contact inspections. Factors that limit the use of UAVs in bridge inspections include the UAV endurance, the capability of navigation in GPS deprived environments, the stability in confined spaces in close proximity to structural elements, and the cost. Current research trends in UAV technologies address some of these limitations, such as obstacle detection and avoidance methods, autonomous flight path planning and optimization, and UAV hardware optimization for specific mission requirements.

Objective: The negative impacts of the Coronavirus Disease 2019 (COVID-19)outbreak on public mental health are enhancing the number of individuals requiring psychotherapy. Besides, anxiety is becoming more frequent than any other mental health issue among individuals. Similar to other anxiety types, coronavirus anxiety is associated with elevated attentional bias. The present study aimed to examine the effects of Attentional Bias Modification (ABM) on attentional bias towards coronavirus-related stimuli, and coronavirus anxiety. Methods: This was a quasi-experimental study with pretest-posttest-follow-up and a control group design. The research participants were 37 adults (aged 18 to 38 y), who were randomly assigned to the experimental (n=18) and control (n=19) groups. The experimental group received ABM, while no intervention was delivered to the controls. Attentional bias and coronavirus disease anxiety were assessed at pretest, posttest, and 2 months follow-up stages using the Dot-Probe Task (DPT) and the Corona Disease Anxiety Scale (CDAS). The collected data were analyzed using two-way repeated-measures Analysis of Variance (ANOVA) and Fisher’s least significant difference in SPSS v. 26. Results: After receiving online ABM, the study participant’s coronavirus-related attentional bias decreased, leading to a significant reduction in coronavirus anxiety (P<0.05). These significant changes were evident at the posttest and maintained until the follow-up step. However, no significant changes occurred in the control group (P>0.05). Conclusion: The presented ABM could decrease coronavirus anxiety; thus, its online implementation is a suitable approach to treat individuals with this anxiety while observing social distancing.

Objective: Numerous children with Obsessive-Compulsive Disorder (OCD) either have no access to its main treatment, i.e. Cognitive Behavioral Therapy (CBT), or fail to respond to it. Cognitive Bias Modification of Interpretation (CBMI) is a novel and promising intervention that targets the incorrect interpretation of intrusive thoughts and impulses, i.e. the characteristics of OCD. The present study aimed to determine the effects of CBMI in children with OCD for the first time. Besides, we evaluated the possibility of online implementation of this intervention. Methods: A sample of 35 children with OCD (aged 7-12 years) were randomly assigned to two study groups. The experimental group (n=18) received CBMI and the controls (n=17) received placebo treatment. Interpretation bias and OCD severity were assessed at pre-test, post-test, and 2-month follow-up stages, using the Obsessive Compulsive Inventory-Child Version (OCICV), Obsessive Beliefs Questionnaire-Child Version (OBQCV), and Ambiguous Scenarios Task (AST). The present study results were analyzed using two-way repeated-measures Analysis of Variance (ANOVA) and Paired Samples t-test. Results: The collected findings demonstrated that after receiving CBMI, children’s propensity to positively interpret ambiguous situations was increased, their tendency towards negative interpretation and OCD severity was also decreased. There was no such significant change in the control group. Furthermore, the effects of CBMI was sustained at the 2-month follow-up step. Conclusion: This study provided preliminary evidence that suggests CBMI is capable of modifying interpretation bias in children with OCD, can reduce the severity of their disorder, and works as an online intervention. This brief and inexpensive intervention could be considered as an auxiliary or standalone treatment for OCD in children.

COVID-19 is a highly infectious disease. Studies suggest that its severity is amplified in patients diagnosed with Diabetes Mellitus. In this study, the correlation between the prevalence of COVID-19 and Diabetes was analyzed at the regional and global scale using data extracted from WHO and IDF Diabetes Atlas. For the regional investigation data was assorted into ten regions including Central Asia, Middle east and western Asia, Africa, North America and the Caribbean, South east Asia, East Asia, Europe, South and Central America, South Asia and Oceania. The results show a positive correlation coefficient of 0.47 in Middle east and western Asia. While at the global scale analysis all the selected countries were considered together and a correlation coefficient of 0.32 was observed. This number was increased to 0.69 when the top most affected countries by COVID-19 were considered for the analysis. In order to investigate the time dependent relationship of the two diseases, the data was analysed in five windows of 45 days each since the beginning of pandemic. The results show an increasing pattern of the correlation coefficient in the last three windows. Overall, based on this study by increasing the prevalence of Diabetes Mellitus, the prevalence of COVID-19 cases may also increase.