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Intelligent and safe overtaking maneuvering is always a challenging task for autonomous vehicles. This paper proposes and experimentally implements a novel approach of overtaking maneuvering using modified form of Rendezvous Guidance (RG) algorithm for trajectory planning and obstacle avoidance, considering driver safety and comfort during autonomous overtaking. The simulations for all possible scenarios are conducted to ensure the effectiveness of proposed modified RG algorithm. These scenarios involved presence and absence of obstacle vehicle in overtaking lane alongside leading vehicle in driving lane. In addition, the enhanced performance of modified RG algorithm is established over conventional RG algorithm by comparative analysis. The results indicate that overtaking maneuvering period could be decreased by 10% using a modified RG algorithm and vehicle will cover less distance to complete overtaking. The efficacy of proposed method is justified by performing experiments using mobile robots. The experimental results and simulation results of modified RG algorithm are compared, and their plots are almost identical.

Navigating an autonomous vehicle through a circular ramp to join a multilane highway having high-density traffic is a very challenging task. Occupant and vehicle safety are the major considerations while establishing merging scenarios. This article proposes and experimentally implements safe and tactical navigational procedures for merging and leaving the highway scenario using the rendezvous guidance (RG) technique and its modified form. Test scenarios have been established for navigating AVs to merge and leave the highway on a multilane highway with or without the presence of any other vehicle in the zone. In addition, the navigation with enhanced performance of the modified RG algorithm is also established and compared to the conventional RG algorithm. The results indicate that time is reduced considerably by using the modified RG technique. The experimental and simulation results are compared, and their results are the same.

Introduction Karachi, Pakistan was affected by a heat wave in June 2015 during the Muslim holy month of Ramadan. Many media reports attributed the excess deaths in part to the practice of daylight fasting during Ramadan. As much of the published research reports on heat-related mortality in Europe and the United States, an exploration of the effects of extreme heat on residents of a South Asian mega-city address a gap in current disaster research. Hypothesis/Problem This report investigated potential risk factors for excess mortality associated with the June 2015 heat wave in Karachi, Pakistan. Data were obtained through manual review of death certificates at public hospitals and private clinics in Karachi, Pakistan, conducted from July 1 through July 31, 2015 by a trained physician. Demographic data for any deaths with a primary cause of death of heat-related illness were recorded in Microsoft Excel (Microsoft Corp.; Redmond, Washington USA). EpiSheet (2012; Rothman. Modern Epidemiology. Lippincott Williams & Wilkins; Philadelphia, Pennsylvania USA) was used to calculate risk differences (RD), rate ratios (RR), and 95% confidence intervals (95% CI). Overall, residents of Karachi were approximately 17 times as likely to die of a heat-related cause of death during June 2015 (RR=17.68; 95% CI, 13.87-22.53) when compared with the reference period of June 2014. Residents with a monthly income lower than 20,000 Pakistani Rupees (US $196; RD=0.03; 95% CI, 0.01-0.05) and those with less than a fifth grade education (RD=0.03; 95% CI, 0.00-0.05) were at significantly higher risk of death during the 2015 heat wave compared to the reference period. Fasting during Ramadan was not a significant risk factor for mortality from heat-related causes during the Karachi heat wave of June 2015. A large number of excess deaths were reported across all demographic groups, which due to the burden of record keeping in an under-resourced health system during a public health emergency, are almost certainly an underestimate. Ghumman U , Horney J . Characterizing the impact of extreme heat on mortality, Karachi, Pakistan, June 2015. Prehosp Disaster Med. 2016;31(3):263-266.

COVID-19 has catastrophically affected the world’s panoramic view of human well-being in terms of healthcare and management. With the increase in the number of cases worldwide, neurological symptoms and psychological illnesses from COVID-19 have increasingly upsurged. Mental health illness and affective disorders, including depression, obsessive-compulsive disorder, anxiety, phobia, and panic disorders, are highly impacted due to social distress. The COVID-19 pandemic not only affected people with pre-existing mental and affective illnesses, but also healthy individuals with anxiety, worrying, and panic symptoms, and fear conditioning. In addditon, the novel coronavirus is known to impact the central nervous system in the brain, resulting in severe and certain long-lasting neurological issues. Owing to the significance of neurological and psychological events, the present perspective has been an attempt to disseminate the impact of COVID-19 on neural injury through inflammation, and its interrelation with psychological symptoms. In this current review, we synthesize the literature to highlight the critical associations between SARS-CoV-2 infection and the nervous system, and mental health illness, and discuss potential mechanisms of neural injury through psycho-neuroimmunity.

War is a disaster that has both acute and long-term effects, which often results in refugee migration, as has been the case in the Syrian war. Most agencies and organizations concentrate on providing necessities such as food, clothing, and shelter. However, mental health must not be forgotten among other important needs of the refugees. This review explores the mental health needs of refugees, with a focus on posttraumatic stress disorder (PTSD), finding that refugees appear especially susceptible to PTSD and PTSD symptoms, especially women and children. Although PTSD can lead to other negative consequences such as physical health complications, many are unlikely to seek help and treatment remains widely unavailable to refugees. Viable treatment options for PTSD and presented and telehealth is proposed as a way to overcome barriers to service delivery for this population. La guerre est une situation désastreuse qui a des répercussions à la fois graves et de longue durée, et qui souvent donne lieu à la migration de réfugiés, comme c'est le cas du conflit en Syrie. La plupart des agences et des organisations d'aide cherchent à fournir les nécessités de base, comme la nourriture, les vêtements et un logement. Toutefois, il ne faut pas oublier les soins en santé mentale comme l'un des besoins des réfugiés. La présente revue examine les besoins des réfugiés sur le plan de la santé mentale, en particulier en ce qui a trait au trouble de stress post-traumatique (TSPT). Ainsi, on constate que les réfugiés sont particulièrement sujets au TSPT ou à présenter de ses symptômes, en particulier les femmes et les enfants. Bien que le TSPT puisse avoir d'autres conséquences nuisibles, comme des problèmes de santé physique, très peu de réfugiés cherchent à obtenir de l'aide, et les traitements demeurent rarement disponibles. Des options viables pour le traitement du TSPT sont présentées, et la télésanté est proposée en tant que moyen de surmonter les obstacles à la prestation de services à cette population.

Intelligent and safe overtaking maneuvering is always a challenging task for autonomous vehicles. This paper proposes and experimentally implements a novel approach of overtaking maneuvering using modified form of Rendezvous Guidance (RG) algorithm for trajectory planning and obstacle avoidance, considering driver safety and comfort during autonomous overtaking. The simulations for all possible scenarios are conducted to ensure the effectiveness of proposed modified RG algorithm. These scenarios involved presence and absence of obstacle vehicle in overtaking lane alongside leading vehicle in driving lane. In addition, the enhanced performance of modified RG algorithm is established over conventional RG algorithm by comparative analysis. The results indicate that overtaking maneuvering period could be decreased by 10% using a modified RG algorithm and vehicle will cover less distance to complete overtaking. The efficacy of proposed method is justified by performing experiments using mobile robots. The experimental results and simulation results of modified RG algorithm are compared, and their plots are almost identical.

In the context of intelligent transportation, this paper presents a novel on-line trajectorygeneration method for autonomous lane changing. The proposed scheme is guidance based, realtime applicable, and ensures safety and passenger ride comfort. Based on the principles of , the passing vehicle is guided in real-time to match the position and velocity of a target (i.e., rendezvous with) during the overtaking manoeuvre. The shadow target’s position and velocity are generated based on real-time sensory information gathered about the slower vehicle ahead of the passing vehicle as well as other vehicles which may be travelling in the passing lane. Namely, the guidance principle is also used to prevent any potential collision with these vehicles. The proposed method can be used as a fully autonomous system or simply as a driver-assistance tool. Extensive simulations and experiments, some of which are presented herein, clearly demonstrate the tangible efficiency of the proposed method.

In the context of intelligent transportation, this Thesis presents a novel on-line trajectory-generation method for autonomous highway overtaking. The focus of this Thesis has been on two autonomy aspects of overtaking manoeuvre: (i) time optimal overtaking in the possible presence of obstacle vehicles in the passing lane, while ensuring passenger comfort, and (ii) ensuring that a safety distance is always maintained between vehicles in order to avoid any collision. The proposed scheme is guidance based, real-time applicable, and ensures safety and passenger ride comfort. The propose methodology is based on the principles of Rendezvous Guidance, the passing vehicle is guided in real-time to match the position and velocity of a shadow target (i.e., rendezvous with) during the overtaking manoeuvre. The shadow target's position and velocity are generated based on real-time sensory information gathered about the slower vehicle ahead of the passing vehicle as well as other vehicles which may be travelling in the passing lane. The guidance principle is also used to prevent any potential collision with these obstacle vehicles. The proposed method can be used as a fully autonomous system or simply as a driver-assistance tool. The proposed method was implemented in both computer simulations and experiments. The results clearly demonstrate the tangible efficiency of the proposed method.

Objective Identifying the time of SARS-CoV-2 viral infection relative to specific gestational weeks is critical for delineating the role of viral infection timing in adverse pregnancy outcomes. However, this task is difficult when it comes to Electronic Health Records (EHR). In combating the COVID-19 pandemic for maternal health, we sought to develop and validate a clinical information extraction algorithm to detect the time of clinical events relative to gestational weeks. Materials and methods We used EHR from the National COVID Cohort Collaborative (N3C), in which the EHR are normalized by the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). We performed EHR phenotyping, resulting in 270,897 pregnant women (June 1.sup.st, 2018 to May 31.sup.st, 2021). We developed a rule-based algorithm and performed a multi-level evaluation to test content validity and clinical validity, and extreme length of gestation (300). Results The algorithm identified 296,194 pregnancies (16,659 COVID-19, 174,744 without COVID-19) in 270,897 pregnant women. For inferring gestational age, 95% cases (n = 40) have moderate-high accuracy (Cohen's Kappa = 0.62); 100% cases (n = 40) have moderate-high granularity of temporal information (Cohen's Kappa = 1). For inferring delivery dates, the accuracy is 100% (Cohen's Kappa = 1). The accuracy of gestational age detection for the extreme length of gestation is 93.3% (Cohen's Kappa = 1). Mothers with COVID-19 showed higher prevalence in obesity or overweight (35.1% vs. 29.5%), diabetes (17.8% vs. 17.0%), chronic obstructive pulmonary disease (0.2% vs. 0.1%), respiratory distress syndrome or acute respiratory failure (1.8% vs. 0.2%). Discussion We explored the characteristics of pregnant women by different gestational weeks of SARS-CoV-2 infection with our algorithm. TED-PC is the first to infer the exact gestational week linked with every clinical event from EHR and detect the timing of SARS-CoV-2 infection in pregnant women. Conclusion The algorithm shows excellent clinical validity in inferring gestational age and delivery dates, which supports multiple EHR cohorts on N3C studying the impact of COVID-19 on pregnancy.

Glaciers are also known as solid reservoirs, and in this regard, Pakistan is a blessed country to have enriched glaciers. The change in glacial extent becomes very crucial for rivers whose discharges are associated with glacier melt. Even a little change in the glacial extent may bring a significant change in the resulting river flows. Considering climate change scenarios, many researchers have predicted future flows in such catchments. But in almost all such studies, the reduction in the glaciers is not normally based on any rational. Therefore, research is needed in order to estimate how glaciers are actually behaving under the change of temperature and precipitations to better estimate the future flows. For this purpose, Chitral watershed was considered as the study area. The seasonal change in the snow extent was estimated by using MODIS data for various years that helped to identify the month with minimum glacial extent. With the help of remote sensing, unsupervised classification was performed to estimate the glacier area in Chitral watershed. The results show a definite receding trend with respect to time in the glaciers of the region for the past decade.