Challenges of Biochar Usages in Arid Soils: A Case Study in the Kingdom of Saudi Arabia

Biochar is a carbon-rich material produced from the pyrolysis of organic biomasses in the absence of oxygen or under low-oxygen conditions. Biochar has received a great interest during the last few decades due to its beneficial roles for carbon dioxide capturing and soil fertility improvement. However, applications of biochar in arid soils are very limited, and there is a lack of knowledge on practical aspects of adding biochar to arid soils. In this chapter, we will focus on biochar applications in the Kingdom of Saudi Arabia soils as an example of arid soils. These soils are characterized by several marks, i.e., high soil pH, sand structures, high CaCO3 contents, and low soil fertility. In addition, the unsuccessful recycling practices of agricultural and food wastes in the Kingdom of Saudi Arabia are also discussed. This chapter provides an overview of current biochar knowledge pertinent to its application to arid soils, summarizes what is known so far about biochar and its applications in arid regions, and demonstrates the possible strategies that can be used for enhancing the practices of biochar addition to these soils

The transmission dynamics of Campylobacter jejuni among broilers in semi-commercial farms in Jordan

Campylobacter is the leading cause of foodborne bacterial gastroenteritis in humans worldwide, often associated with the consumption of undercooked poultry. In Jordan, the majority of broiler chicken production occurs in semi-commercial farms, where poor housing conditions and low bio-security are likely to promote campylobacter colonisation. While several studies provided estimates of the key parameters describing the within-flock transmission dynamics of campylobacter in typical high-income countries settings, these data are not available for Jordan and Middle-East in general. A Bayesian model framework was applied to a longitudinal dataset on Campylobacter jejuni infection in a Jordan flock to quantify the transmission rate of C. jejuni in broilers within the farm, the day when the flock first became infected, and the within-flock prevalence (WFP) at clearance. Infection with C. jejuni is most likely to have occurred during the first 8 days of the production cycle, followed by a transmission rate value of 0.13 new infections caused by one infected bird/day (95% CI 0.11–0.17), and a WFP at clearance of 34% (95% CI 0.24–0.47). Our results differ from published studies conducted in intensive poultry production systems in high-income countries but are well aligned with the expectations obtained by means of structured questionnaires submitted to academics with expertise on campylobacter in Jordan. This study provides for the first time the most likely estimates and credible intervals of key epidemiological parameters driving the dynamics of C. jejuni infection in broiler production systems commonly found in Jordan and the Middle-East and could be used to inform Quantitative Microbial Risk Assessment models aimed to assess the risk of human exposure/infection to campylobacter through consumption of poultry meat

Prevalence, antibiotic resistance and genotypes of Campylobacter jejuni and Campylobacter coli isolated from chickens in Irbid governorate, Jordan

Campylobacter is the world's leading cause of bacterial gastroenteritis, causing nearly 9 million cases of food poisoning in Europe every year. Poultry is considered the main source of Campylobacter infection to humans. The objectives of the study were to determine occurrence of C. jejuni and C. coli in chickens, the antimicrobial resistance, genotypes, and relatedness of the isolates. A total of 177 chicken samples obtained from informal butcher shops (fresh), formal poultry slaughterhouses (refrigerated) and retail market (frozen) were analyzed. Isolation of Campylobacter spp. was conducted according to the ISO 10272-2006 method. Multiplex PCR was used for confirmation and identification of the isolates. The disk diffusion method was used to determine the antimicrobial resistance of the isolates and multilocus sequence typing was used for genotyping. The proportion of samples with Campylobacter spp. was 31.6% among all chicken samples (fresh and refrigerated 47.5%, frozen 0%) C. coli was isolated from 42.4% of chicken samples obtained from butcher shops and from 18.6% of samples obtained in formal slaughterhouses. C. jejuni was isolated from 17.0% of samples obtained in butcher shops and formal slaughterhouses. Campylobacter spp. was not isolated in frozen chicken samples. All tested isolates showed resistance toward ciprofloxacin and susceptibility toward imipenem and all of the isolates were multidrug resistant toward 5 or more antimicrobials. Three sequence types were identified among 10 C. coli isolates and seven sequence types were identified among 10 C. jejuni isolates. Among sequence types, chicken isolates shared similarities of both phenotypic and genetic levels

Performance comparison of deep CNN models for detecting driver’s distraction

According to various worldwide statistics, most car accidents occur solely due to human error. The person driving a car needs to be alert, especially when travelling through high traffic volumes that permit high-speed transit since a slight distraction can cause a fatal accident. Even though semiautomated checks, such as speed detecting cameras and speed barriers, are deployed, controlling human errors is an arduous task. The key causes of driver’s distraction include drunken driving, conversing with co-passengers, fatigue, and operating gadgets while driving. If these distractions are accurately predicted, the drivers can be alerted through an alarm system. Further, this research develops a deep convolutional neural network (deep CNN) models for predicting the reason behind the driver’s distraction. The deep CNN models are trained using numerous images of distracted drivers. The performance of deep CNN models, namely the VGG16,ResNet, and Xception network, is assessed based on the evaluation metrics, such as the precision score, the recall/sensitivity score, the F1 score, and the specificity score. The ResNet model outperformed all other models as the best detection model for predicting and accurately determining the drivers’ activities.peer-reviewe

Remediation technologies of heavy metal contaminated soils

© 2018 Dr. Khalid A. AlaboudiEnvironmental contamination with heavy metals has become a serious problem, worldwide. Several remediation technologies are available for treating heavy metal contaminated soils. However, each technology has some advantages and disadvantages. The main objective of the current study was to compare different remediation technologies of soil, which was artificially contaminated by Pb, Cd, Cr and Hg. To achieve these goals, several experiments were performed as follows: (1) phytoremediation by using sunflower plant for treating Pb and Cd contaminated soils, (2) soil washing of Pb, Cd and Cr contaminated soils by using FeCl3 and EDTA extracts, (3) stabilization of Pb, Cd and Cr metal ions by using biochar and (4) thermal treatment of Hg and Cd contaminated soils at 1000 °C. All experiments were performed at different concentrations of studied metals (200, 400 and 600 mg kg-1), and finally, concentrations and speciation of heavy metals were measured by using different extraction methods. In addition, the possible changes that might be occurring in the treated soils were also a matter of concern. The obtained results showed that the Helianthus annuus plant can accumulate Pb and Cd in its tissues. However, the uptake of Cd was more favourable for the plant compared to Pb. It could be recommended the use of plant growth promoters and/or biochar in combination, along with phytoremediation technology. The use of biochar enhanced the growth of maize plants, and stabilized Pb and Cd in soil. In addition, biochar positively improved soil fertility in terms of, nutrients contents and organic matter. Attention should be paid regarding the use of biochar in soil co-contaminated with Cr due to the release of Cr into the soil due to biochar addition. Therefore, biochar can be used effectively in combination with phytoremediation technology for enhancing the removal efficiency of heavy metals from contaminated soils. Soil washing technology has proven to be a suitable tool for removing heavy metals from contaminated soils. FeCl3 was more efficient and cheaper for washing Pb, Cd and Cr compared to EDTA salt. Considerable attention should be paid during soil washing technology to overcome the soil salinization and nutrients leaching problems. Thermal treatment application for 60 min. was not sufficient to remove Cd from contaminated soil, and the maximum removal capacity was 66.87%. However, more than 98% of Hg was removed by using thermal treatment. Thermal treatment has some disadvantages in terms of, increasing soil pH and decreasing nutrients availability. These findings contribute with helpful tools in environmental management of contaminated soil with heavy metals and the future of reclaiming contaminated soils for agricultural and other use is important factor for selecting the appropriate remediation technology with varying costs of the different technologies applied

Phytoremediation of Pb and Cd contaminated soils by using sunflower (Helianthus annuus) plant

Phytoextraction is an emerging cost effective remediation technology that uses plants to remove metals from contaminated soils. Pot experiments were conducted to compare the biomass of Helianthus annuus L. plant grown on Pb and Cd contaminated soils, and to evaluate its efficacy for the removal of Pb and Cd. The obtained results showed that as the concentration of heavy metals increased in soil, the fresh and dry weights of the growing plants gradually decreased. The application of 200 mg kg−1 soil of Pb and Cd reduced the fresh weights of shoot and root (up to 76.6% and 64.3%; 88.5% and 80.80%, respectively), shoot and root length (up to 71.6% and 94.1%; 83.2% and 95.1%, respectively). The maximum concentration of Pb and Cd in shoot (40.1 and 65.7 mg kg−1 Dwt) and roots (107.7 and 71.3 mg kg−1, respectively) were recorded in the plant cultivated in soil amended with 200 mg kg−1 metal concentration. The highest bioaccumulation (BAF) was recorded for Cd in the root grown on soil amended with 20 mg kg−1 with an average value of 1.67. In addition, the value of the translocation factor (TF) of Cd increased by increasing the levels of Cd in soil; however, Pb translocation factor decreased by increasing the levels of Pb in soil. The study concludes that H. annuus plant was more favorable for Cd uptake compared to Pb, and we suggest its ability for the remediation of Pb and Cd contaminated soils. Keywords: Heavy metal, Soil, Helianthus annuus, Plant biomass, Translocation factor, Bioaccumulation facto

The role of E-Government in Increasing Transparency in Saudi Arabia

As many nations globally continue to embrace e-government technology, the Kingdom of Saudi Arabia has not been left behind, and it’s aiming to be in its pivotal spot. The deployment of e-government is expected to increase government transparency and accountability in its departments. In this era of instant information access, most government entities are under great pressure to be transparent and accountable in their activities and decision-making processes. E-government does not only involve the application of new technology, but it also involves an electronic administration that touches various key relationships between KSA and its citizens. The paper presents a discussion on the roles played by e-government to enhance transparency in Saudi Arabia

A Machine Learning Way to Classify Autism Spectrum Disorder

In recent times Autism Spectrum Disorder (ASD) is picking up its force quicker than at any other time. Distinguishing autism characteristics through screening tests is over the top expensive and tedious. Screening of the same is a challenging task, and classification must be conducted with great care. Machine Learning (ML) can perform great in the classification of this problem. Most researchers have utilized the ML strategy to characterize patients and typical controls, among which support vector machines (SVM) are broadly utilized. Even though several studies have been done utilizing various methods, these investigations didn't give any complete decision about anticipating autism qualities regarding distinctive age groups. Accordingly, this paper plans to locate the best technique for ASD classi-fication out of SVM, K-nearest neighbor (KNN), Random Forest (RF), Naïve Bayes (NB), Stochastic gradient descent (SGD), Adaptive boosting (AdaBoost), and CN2 Rule Induction using 4 ASD datasets taken from UCI ML repository. The classification accuracy (CA) we acquired after experimentation is as follows: in the case of the adult dataset SGD gives 99.7%, in the adolescent dataset RF gives 97.2%, in the child dataset SGD gives 99.6%, in the toddler dataset Ada-Boost gives 99.8%. Autism spectrum quotients (AQs) varied among several sce-narios for toddlers, adults, adolescents, and children that include positive predic-tive value for the scaling purpose. AQ questions referred to topics about attention to detail, attention switching, communication, imagination, and social skills

Case Report Neuropathy Dermatitis following Surgical Nerve Injury

Background. Cutting nerve during operations like saphenous vein grafting and knee joint surgery are common surgical procedures. Objective. To report cases of dermatitis at the site of neuropathy following skin incision for saphenous vein grafting and knee joint surgery. Patients and Methods. This case report work was done in the Department of Dermatology, Baghdad Teaching Hospital, during 2009-2010, seven cases were recorded, six following saphenous vein grafting and one case after knee surgery. Five males and two females, their ages ranged from 50 to 66 (58 ± 5.033223) years. Detailed history and full clinical examination were done for each patient regarding all points related to their conditions. Results. All cases presented around 2-3 months following the operation with dermatitis at the site of operational incision. The dermatitis appeared on one side of the operational scar and at area of neuropathy, and the rash did not cross to contralateral side. The dermatitis was well-defined plaque or patch erythematous slight scaly and nonitchy and subsided within few weeks with or without topical therapy. Conclusions. Neuropathy dermatitis is apparently a new variant of dermatitis that follows nerve cut during surgery