A Traffic-Aware Approach for Enabling Unmanned Aerial Vehicles (UAVs) in Smart City Scenarios

In smart cities, vehicular applications require high computation capabilities and low-latency communication. Edge computing offers promising solutions for addressing these requirements because of several features, such as geo-distribution, mobility, low latency, heterogeneity, and support for real-time interactions. To employ network edges, existing fixed roadside units can be equipped with edge computing servers. Nevertheless, there are situations where additional infrastructure units are required to handle temporary high traffic loads during public events, unexpected weather conditions, or extreme traffic congestion. In such cases, the use of flying roadside units are carried by unmanned aerial vehicles (UAVs), which provide the required infrastructure for supporting traffic applications and improving the quality of service. UAVs can be dynamically deployed to act as mobile edges in accordance with traffic events and congestion conditions. The key benefits of this dynamic approach include: 1) the potential for characterizing the environmental requirements online and performing the deployment accordingly, and 2) the ability to move to another location when necessary. We propose a traffic-aware method for enabling the deployment of UAVs in vehicular environments. Simulation results show that our proposed method can achieve full network coverage under different scenarios without extra communication overhead or delay

Inhibitive action of Cystine on the corrosion of low alloy steel ASTM A213 grade T22 in sulfamic acid solutions

AbstractThe effect of Cystine on the corrosion behavior of low alloy steel ASTM A213 grade T22 in 0.5M sulfamic acid solutions have been investigated by various electrochemical techniques. The study was performed using electrochemical impedance spectroscopy (EIS) and the recent technique electrochemical frequency modulation (EFM). The results of the investigation show that the inhibition efficiency increased with increasing inhibitor concentration, but decreased with increasing the solution temperature and stirring velocity. All the collected results from the two techniques are in good agreements, which confirm the ability of EFM technique for monitoring the corrosion inhibition under the studied conditions

Benchmarking of Recommendation Trust Computation for Trust/Trustworthiness Estimation in HDNs

In the recent years, Heterogeneous Distributed Networks (HDNs) is a predominant technology implemented to enable various application in different fields like transportation, medicine, war zone, etc. Due to its arbitrary self-organizing nature and temporary topologies in the spatial-temporal region, distributed systems are vulnerable with a few security issues and demands high security countermeasures. Unlike other static networks, the unique characteristics of HDNs demands cutting edge security policies. Numerous cryptographic techniques have been proposed by different researchers to address the security issues in HDNs. These techniques utilize too many resources, resulting in higher network overheads. This being classified under light weight security scheme, the Trust Management System (TMS) tends to be one of the most promising technology, featured with more efficiency in terms of availability, scalability and simplicity. It advocates both the node level validation and data level verification enhancing trust between the attributes. Further, it thwarts a wide range of security attacks by incorporating various statistical techniques and integrated security services. In this paper, we present a literature survey on different TMS that highlights reliable techniques adapted across the entire HDNs. We then comprehensively study the existing distributed trust computations and benchmark them in accordance to their effectiveness. Further, performance analysis is applied on the existing computation techniques and the benchmarked outcome delivered by Recommendation Trust Computations (RTC) is discussed. A Receiver Operating Characteristics (ROC) curve illustrates better accuracy for Recommendation Trust Computations (RTC), in comparison with Direct Trust Computations (DTC) and Hybrid Trust Computations (HTC). Finally, we propose the future directions for research and highlight reliable techniques to build an efficient TMS in HDNs

Calcified Bronchogenic Cyst

Herein, we reported the case of a 32-year-old male patient presented with intermittent attacks of mild right chest pain and dyspnea for 2 years. On contrast-enhanced computed tomography (CT) of the chest, a non-enhancing subcarinal cystic lesion about 6×6.5 cm was detected in the posterior mediastinum, consistent with the features of bronchogenic cyst. The lesion showed small calcific focus changing its position posteriorly when patient changes his position from supine to prone. The flecks of calcium within the fluid in a cystic lesion constitute the origin of the future cyst wall calcifications and may reflect the long-standing nature of the lesion. Surgical excision is preferred to avoid the expected complications, including fistula formation, ulceration, and infection

CARLA+: An Evolution of the CARLA Simulator for Complex Environment Using a Probabilistic Graphical Model

In an urban and uncontrolled environment, the presence of mixed traffic of autonomous vehicles, classical vehicles, vulnerable road users, e.g., pedestrians, and unprecedented dynamic events makes it challenging for the classical autonomous vehicle to navigate the traffic safely. Therefore, the realization of collaborative autonomous driving has the potential to improve road safety and traffic efficiency. However, an obvious challenge in this regard is how to define, model, and simulate the environment that captures the dynamics of a complex and urban environment. Therefore, in this research, we first define the dynamics of the envisioned environment, where we capture the dynamics relevant to the complex urban environment, specifically, highlighting the challenges that are unaddressed and are within the scope of collaborative autonomous driving. To this end, we model the dynamic urban environment leveraging a probabilistic graphical model (PGM). To develop the proposed solution, a realistic simulation environment is required. There are a number of simulators—CARLA (Car Learning to Act), one of the prominent ones, provides rich features and environment; however, it still fails on a few fronts, for example, it cannot fully capture the complexity of an urban environment. Moreover, the classical CARLA mainly relies on manual code and multiple conditional statements, and it provides no pre-defined way to do things automatically based on the dynamic simulation environment. Hence, there is an urgent need to extend the off-the-shelf CARLA with more sophisticated settings that can model the required dynamics. In this regard, we comprehensively design, develop, and implement an extension of a classical CARLA referred to as CARLA+ for the complex environment by integrating the PGM framework. It provides a unified framework to automate the behavior of different actors leveraging PGMs. Instead of manually catering to each condition, CARLA+ enables the user to automate the modeling of different dynamics of the environment. Therefore, to validate the proposed CARLA+, experiments with different settings are designed and conducted. The experimental results demonstrate that CARLA+ is flexible enough to allow users to model various scenarios, ranging from simple controlled models to complex models learned directly from real-world data. In the future, we plan to extend CARLA+ by allowing for more configurable parameters and more flexibility on the type of probabilistic networks and models one can choose. The open-source code of CARLA+ is made publicly available for researchers

An Assessment of the Filling Process of the Grand Ethiopian Renaissance Dam and Its Impact on the Downstream Countries

The Grand Ethiopian Renaissance Dam (GERD), formerly known as the Millennium Dam, has been filling at a fast rate. This project has created issues for the Nile Basin countries of Egypt, Sudan, and Ethiopia. The filling of GERD has an impact on the Nile Basin hydrology and specifically the water storages (lakes/reservoirs) and flow downstream. In this study, through the analysis of multi-source satellite imagery, we study the filling of the GERD reservoir. The time-series generated using Sentinel-1 SAR imagery displays the number of classified water pixels in the dam from early June 2017 to September 2020, indicating a contrasting trend in August and September 2020 for the upstream/downstream water bodies: upstream of the dam rises steeply, while downstream decreases. Our time-series analysis also shows the average monthly precipitation (derived using IMERG) in the Blue Nile Basin in Ethiopia has received an abnormally high amount of rainfall as well as a high amount of runoff (analyzed using GLDAS output). Simultaneously, the study also demonstrates the drying trend downstream at Lake Nasser in Southern Egypt before December 2020. From our results, we estimate that the volume of water at GERD has already increased by 3.584 billion cubic meters, which accounts for about 5.3% of its planned capacity (67.37 billion cubic meters) from 9 July–30 November 2020. Finally, we observed an increasing trend in GRACE anomalies for GERD, whereas, for the Lake Nasser, we observed a decreasing trend. In addition, our study discusses potential interactions between GERD and the rainfall and resulting flood in Sudan. Our study suggests that attention should be drawn to the connection between the GERD filling and potential drought in the downstream countries during the upcoming dry spells in the Blue Nile River Basin. This study provides an open-source technique using Google Earth Engine (GEE) to monitor the changes in water level during the filling of the GERD reservoir. GEE proves to be a powerful as well as an efficient way of analyzing computationally intensive SAR images

Augmenting CCAM Infrastructure for Creating Smart Roads and Enabling Autonomous Driving

Autonomous vehicles and smart roads are not new concepts and the undergoing development to empower the vehicles for higher levels of automation has achieved initial milestones. However, the transportation industry and relevant research communities still require making considerable efforts to create smart and intelligent roads for autonomous driving. To achieve the results of such efforts, the CCAM infrastructure is a game changer and plays a key role in achieving higher levels of autonomous driving. In this paper, we present a smart infrastructure and autonomous driving capabilities enhanced by CCAM infrastructure. Meaning thereby, we lay down the technical requirements of the CCAM infrastructure: identify the right set of the sensory infrastructure, their interfacing, integration platform, and necessary communication interfaces to be interconnected with upstream and downstream solution components. Then, we parameterize the road and network infrastructures (and automated vehicles) to be advanced and evaluated during the research work, under the very distinct scenarios and conditions. For validation, we demonstrate the machine learning algorithms in mobility applications such as traffic flow and mobile communication demands. Consequently, we train multiple linear regression models and achieve accuracy of over 94% for predicting aforementioned demands on a daily basis. This research therefore equips the readers with relevant technical information required for enhancing CCAM infrastructure. It also encourages and guides the relevant research communities to implement the CCAM infrastructure towards creating smart and intelligent roads for autonomous driving

Effect of hemodiafiltration on sclerostin level and bone specific alkaline phosphatase in comparison with high flux dialysis

 Background: Sclerostin (sScl), an osteocyte-derived glycoprotein acts as a soluble inhibitor of the Wnt signaling pathway and bone formation. Its serum levels increase with the progression of CKD. The present study investigated the effect of hemodiafiltration (HDF) on sScl and bone specific alkaline phosphatase (BS-AP) in comparison with high flux hemodialysis (HF-HD). Methods: a prospective study was conducted upon 32 ESRD patients; 16 on regular HF-HD and 16 shifted to 3 months of HDF. Results: There was a significant reduction of predialysis sScl and BS-AP with a significant increase in sScl reduction ratio in the HDF group after 3months. SScl had a significant positive correlation with total but not BS-AP. Conclusion: sScl and BS-AP significantly decrease but are poorly correlated with each other in HDF. So either sScl reduction does not translate into better bone turnover or the BS-AP is not a suitable biomarker to assess bone turnover in HDF.

Four-country surveillance of intestinal intussusception and diarrhoea in children

Aim: Establishment of baseline epidemiology of intussusception in developing countries has become a necessity with the possibility of reintroduction of rotavirus vaccine. The current study assessed the seasonal trend in cases admitted with intussusceptions and dehydrating acute watery diarrhoea in children aged 2 months to 10 years. Methods: In a prospective surveillance study, teaching and research hospital sites in India (Lucknow and Nagpur), Brazil (Fortazela), Egypt (Ismailia) and Kenya (Nairobi) established a surveillance where a network of hospitals with surgical facilities catered to a reference population of about 1-2 million for reporting of intussusception. One large hospital per site also recruited admitted cases of acute watery diarrhoea. Results: From April 2004 to March 2006, 173 and 2346 cases of intussusception and diarrhoea, respectively, were recruited. Cases of intussusception had no apparent seasonality. Most cases of intussusception (61.3%) (107/173) were in the ≤1 year age group, with males comprising 68.8% (119/173) of all cases. Hospital mortality of intussusception was 4.2% (4/96). Cases of diarrhoea peaked in March, with 56.6% (1328/2346) of admitted cases being males. Majority (83.1%) of cases of diarrhoea had received antibiotics, and the hospital mortality was 0.8% (18/2280). Conclusion: Intussusception in the four participating countries exhibited no seasonal trend. We found that it is feasible to establish a surveillance network for intussusception in developing countries. Future efforts must define population base before the introduction of rotavirus vaccine and continue for some years thereafter. © 2009 Paediatrics and Child Health Division (Royal Australasian College of Physicians)