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The need of developing systems that address traffic matters such as traffic control and accidents has led to the development of a number of techniques, methods and tools to address road usability issues. Many automated models have been proposed and applied in different scenarios such as road oddities. Despite of the advantages of these models the major problem of road accidents continue to pose problem globally. This has created the need to come up with more user-effective approaches to address road accidents. Main objective of this research therefore is to identify and address the gap in Location Based Services (LBS). A model that combines RFID and GPS technology to provide Location Based Services via audio alerts to drivers as they approach black spots is presented. The model provides location based services to drivers as they approach black spots causing them to adjust their driving accordingly (i.e. speeding, overtaking). Since LBS technologies have different limitations, most researchers have focused on addressing accuracy limitation by proposing hybrid technologies. Accuracy requirement varies depending on application area. The analysis of the different technologies revealed that in vehicle transportation medium accuracy is effective. This research focused on availability aspect which is a key requirement in LBS. To achieve this a model made up of RFID & GPS is formulated. Higher availability of significant alerts at black spots is registered through simulation as compared to alerts when the technologies are applied separately. Black spot accidents are therefore managed due to safer driving around black spots. This can lead to reduction in exposure to accidents, likelihood of occurrence and impact in the event of an incident. Usability metrics is used to determine effectiveness of the model. [ABSTRACT FROM AUTHOR]

Background: Coronavirus disease 2019 (COVID-19) is a rapidly escalating pandemic that has spread to many parts of the world. As such, there is urgent need to identify predictors of clinical severity in COVID-19 patients. This may be useful for early identification of patients who may require life-saving interventions. In this meta-analysis, we evaluated whether malignancies are associated with a significantly enhanced odds of COVID-19 severity and mortality.Method: A systematic search of literature was conducted between November 1, 2019, to May 26th, 2020 on PubMed and China National Knowledge Infrastructure (CNKI) to identify studies reporting data on cancers in patients with or without severe COVID-19 were included. The primary outcome of interest was the association between malignancies and COVID-19 severity, while the secondary outcome was the association between malignancies and COVID-19 mortality. Data were pooled into a meta-analysis to estimate pooled odds ratio (OR) with 95% confidence interval (95% CI) for either outcome.Results: A total of 20 studies (n = 4549 patients) were included. Overall, malignancies were found to be associated with significantly increased odds of COVID-19 severity (OR = 2.17; 95% CI 1.47-3.196; p < 0.001) and mortality (OR = 2.39; 95% CI 1.18-4.85; p = 0.016). No heterogeneity was observed for both outcomes (Cochran's Q = 6.558, p = 0.922, I2 = 0% and Cochran's Q = 2.91, p = 0.71, I2 = 0% respectively).Conclusion: Malignancies were significantly associated with a 2-fold increase in the odds of developing severe COVID-19 disease, as well as mortality. Larger studies are needed to corroborate these findings. These patients should be closely monitored for any signs of unfavorable disease progression. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine the prevalence and anatomic features of major tracheobronchial anomalies. Major electronic databases were systematically searched to identify eligible studies. Data were extracted and pooled into a meta-analysis. The primary outcome was the prevalence of major tracheobronchial anomalies, specifically tracheal bronchus (TB) and accessory cardiac bronchus (ACB). Secondary outcomes included the origin and types of TB and ACB. A total of 27 studies (n = 119,695 patients) were included. A TB was present in 0.99% (95% confidence interval, 0.67 to 1.37) of patients, and an ACB was present in 0.14% (95% confidence interval, 0.09 to 0.20). The overall prevalence of TB was higher in imaging than in operative studies (1.81% vs 0.82%). It was also higher in pediatric (2.55%) than in adult studies (0.50%). Patients with other congenital anomalies were 15 times more likely to have a TB (odds ratio 14.89; 95% confidence interval, 7.09 to 31.22). The most common origin of TBs was from the trachea (81.42%), primarily from the right side (96.43%). The most common origin of ACBs was from the intermediate bronchus (74.32%). The ACBs terminated as blind-ending diverticulum in two thirds of cases. Major tracheobronchial anomalies are present in approximately 1% of the population, although the prevalence is higher among pediatric patients and patients with accompanying congenital anomalies. Although rare, major tracheobronchial anomalies can be associated with significant respiratory morbidities and present challenges during airway management in surgical and critical care patients. Establishing a preoperative diagnosis of these variations is essential for planning and implementing an appropriate airway management strategy to minimize attendant complications. [Display omitted] [ABSTRACT FROM AUTHOR]

Neural networks for classification aim at identifying the class label of new observation based training data containing instances whose category memberships are known. Therefore the data fed into neural networks has to be preprocessed to enhance its quality resulting in promoting the extraction of meaningful insights of data. However, the fact of processing data until you have the required high quality is challenging and time-consuming to manually search for the best method in a sequence of preprocessing independent methods. For feature scaling methods, they consist of scaling the dataset into the same range of data without monitoring data outliers that should eventually occur in the data source. Zscore for outlier's detection suffers from the issue of predefining the parameters. This paper discussed various approaches that are applied to scale features and detect outliers during data pre-processing. Thereafter, the paper proposed the algorithm that combines Zscore as an outlier's detection method with every classical feature scaling method in high-dimensional data. The proposed algorithm has benefits in selecting the optimal subset of methods from a sequence of chained methods, detecting outliers, and removing zero variance predictors. The study findings from five sample sizes revealed that the proposed method significantly excels the classical method in terms of accuracy. The outstanding from them was performed at the rate of 99.67% and had a significant difference of 0.20% over classical feature scaling. • Chaining Zscore and feature scaling methods impacts positively classification accuracy. • Chaining Zscore and feature scaling methods selects the optimal sequence of methods. • No feature scaling method outperforms in all machine learning algorithms. • Data Outliers removal from dataset may or may not improve the model accuracy. [ABSTRACT FROM AUTHOR]

Mycoremediation of unsterilized PCDD/F-contaminated field soil was successfully demonstrated by solid-state fermentation coupled with Pleurotus pulmonarius utilizing a patented incubation approach. The experiments were carried out in four setups with two as controls. The contaminated soil was homogenously mixed with solid inocula, 1:0.5 dry w/w, resulting in an initial concentration of 4432 ± 623 ng WHO-TEQ kg−1. After a 30-day incubation under controlled conditions, the overall removal (approx. 60%) was non-specific. The removal was attributed to degradation by extracellular ligninolytic enzymes and uptake into the fruiting tissue (~110 ng WHO-TEQ kg−1 of mushroom). Furthermore, less recalcitrant chlorinated metabolites were found, implying ether bond cleavage and dechlorination happened during the mycoremediation. These metabolites resulted from the complex interaction between P. pulmonarius and the indigenous microbes from the unsterilized soil. This study provides a new step toward scaling up this mycoremediation technique to treat unsterilized PCDD/F-contaminated field soil. [Display omitted] • A patented technique was developed to treat unsterilized PCDD/F-contaminated soil. • The overall PCDD/F degradation was non-specific, with 60% removal after 30 days. • PCDD/F translocation in Pleurotus pulmonarius ' fruiting body was confirmed. • Less recalcitrant metabolites, and enzymatic mediators and biosurfactants occurred. • The systematic technique can be easily upscaled for field-scale application. [ABSTRACT FROM AUTHOR]

The human health risks caused by heavy metal contamination (As, Cd, Cr, Cu, Hg, Pb, Ni, and Zn) in the surface water of the Houjing River, the most contaminated river in southern Taiwan, were assessed in this study. Firstly, heavy metal contamination was evaluated by the contamination factors (CF) and the metal indexes (MI). Secondly, the human health risks due to heavy metal contamination were simulated using the Adaptive Risk Assessments Modeling System (ARAMS) through three scenarios; fish ingestion, dermal water contact, and incidental water ingestion during swimming. The hazard quotient (HQ) and the hazard index (HI) were used to evaluate non-carcinogenic risks, while carcinogenic risks were estimated by the lifetime cancer incidence risk index (CR) and the cumulative cancer risk (CCR). The results showed that the synergistic contamination of heavy metals in the surface water was severe (MI = 12.4), with the highest contribution from Cu, Ni, and Pb. Copper had the highest non-carcinogenic risk at the "adverse effect" level, while Ni and Cr had the highest carcinogenic risk at an "unacceptable" level. In addition, the cumulative risks of fish ingestion (HI FI = 6.75 and CCR FI = 1.25E-03) were significantly higher than those of the swimming scenarios (HI (DC + WI) = 1.94E-03 and CCR (DC + WI) = 9.32E-08). The results from this study will be beneficial for immediate and future contamination control measures and human health management plans for this study area. This study has also demonstrated the effectiveness of using ARAMS in human health risk assessment. [Display omitted] • High heavy metal contamination in the Houjing River's surface water was reported. • Adaptive Risk Assessments Modeling System was effective in health risk assessment. • Copper and Nickel had the highest noncarcinogenic and carcinogenic risk, respectively. • Cumulative noncarcinogenic risk was classified as "adverse effect". • Cumulative carcinogenic risk was classified as "unacceptable". [ABSTRACT FROM AUTHOR]

A typical two-day start-up of municipal solid waste incinerators (MSWIs) can yield polychlorinated dibenzo- p -dioxin and dibenzofuran (PCDD/F) and polychlorinated biphenyl (PCB) emission quantities around 10 times higher than those from an entire year of normal operations, as measured in this study. Thus, we tested specific control strategies for inhibiting the formation of chlorinated persistent organic pollutants (Cl-POPs), namely, extensively cleaning the ash accumulated beneath the furnace bed of the combustion chamber and deposited on the walls of the superheater and economizer and shortening the residence time of the flue gas in the optimal temperature window for Cl-POP formation. Also, we advanced the injection times of the activated carbon and lime slurry to lower Cl-POP emissions during start-up. Our findings show that these strategies were highly effective and reduced the Cl-POP emissions by > 98%, most of which (96.4–98.2%) was attributable to inhibiting formation. In summary, the proposed control strategies require no modifications to existing air pollution control devices, have little influence on operational cost, and are effective and feasible for the majority of MSWIs. Image 1 • Start-up processes contribute 95% of the total annual PCDD/F emissions. • The proposed control strategies reduce PCDD/F emissions by 99%. • Inhibiting the formation of PCDD/Fs reduces their emission more effectively than enhancing the removal. • These strategies require no modifications to existing control devices. The proposed control strategies potentially reduce emissions of PCDD/Fs, PCBs, and PCDEs during the cold start-up of municipal solid waste incinerators (MSWIs) by > 98%. [ABSTRACT FROM AUTHOR]

Observational studies have reported an association between underlying cardiovascular diseases (CVD) and worse prognosis in COVID-19 patients, but this still remains unclear. We conducted a meta-analysis of recent studies that reported the association of CVD with worse prognosis and increased mortality in COVID-19 patients. Literature search through PubMed, the Cochrane Library, and Embase was completed by 2 reviewers from November 1, 2019 to April 20, 2020. Inclusion criteria were observational case-control or cohort studies on COVID-19 patients with a history of CVD included, which reported outcomes of COVID-19 infection severity, clearly outlined the definition of "severe disease" and with sample size >10. Data were abstracted independently by 2 authors. Studies were divided into 2 separate cohorts for analysis: severity (severe vs nonsevere) and mortality (nonsurvivors vs survivors). Data was pooled into a meta-analysis to estimate pooled odds ratio (OR) with 95% confidence interval (95% CI) for each outcome. A total of 18 studies (n = 4858 patients) were included. Sixteen studies were from China, while 2 were from the United States. Pre-existing CVD was associated with a significantly increased risk of a severe form of COVID-19 (OR = 3.14; 95% CI 2.32-4.24; I2 = 0%; Q = 8.68, P= 0.73) and overall risk of COVID-19 all-cause mortality (OR = 11.08; 95% CI: 2.59-47.32; I2 = 55%; P = 0.11). However, this study did not find a significant association between previous history of CVD and mortality in severe COVID-19 disease (OR = 1.72; 95% CI: 0.97-3.06, I2 = 0%, P = 0.46). Pre-existing CVD is associated with worse outcomes among patients with COVID-19. Clinicians and policymakers need to take account of these findings in implementing risk stratification models. [ABSTRACT FROM AUTHOR]