Can potassium fertilization, soil amendments and land leveling ameliorate rice production under salt affected soils conditions?

The significance of nutrient and water and its sustainability was and still one of the most emerging issues in agriculture. Therefore, it should be considered the maintenance, improvement and efficiently utilization of nutrient and water resources. In present work, the effect of land leveling, soil amendments including gypsum and/or compost application and K- fertilizer on rice production under salt affected soils conditions have been studied. The results showed that the highest yield of grain and straw of rice was obtained with using K-fertilization, land levelling rate 0.05 % of surface slope in the presence of gypsum plus compost application. Furthermore, this study suggests that, the efficiency of irrigation application increased from about 60 (for control) to 65 and 78 % for land leveling with 0.0 and 0.05 % slope, respectively. That means, the water loss rate from irrigation were 43, 36 and 32 %, respectively using the previous land leveling treatments. Thus, about 17 % from the applied water for irrigation could be saved under 0.05 % slope. On the other hand, the highest decrease rate in soil salinity (EC, dS m-1) and alkalinity (sodium absorption ratio, SAR) was 26 and 20 %, respectively for the traditional land leveling or the farmers’ practices. Therefore, sustainable rice crop production should be managed to overcome the soil salinity and alkalinity under low land rice cultivation, improving soil quality and its fertility

Contamination of Plant Foods with Nicotine: An Overview

It is well known that, the explorer "Christopher Columbus" encountered tobacco in the 1400s during his earliest journey to the New World. Tobacco plant is native to North America and other parts of the Western Hemisphere. Furthermore, plant of tobacco contains nicotine and its use has a history that dates back to the earliest records of settlers arriving in America. Moreover, American Indians introduced these settlers to the tobacco plant. In various recent publications elevated nicotine concentrations have been reported to occur in many different foods and plant derived commodities (such as fungi, tea, fruit teas, spices and medicinal plants). Whereas, it is recorded that, high nicotine contaminations are also present in many plant derived products. Up till now, the causes of these contaminations are unknown and they are found in both conventional and in organic products. Thus, field and in vitro experiments are required to elucidate the origin for these nicotine contaminations. Therefore, this work aims to highlight on the nicotine contamination in some different food plants

An Anomaly-based Intrusion Detection System in Presence of Benign Outliers with Visualization Capabilities

Abnormal network traffic analysis through Intrusion Detection Systems (IDSs) and visualization techniques has considerably become an important research topic to protect computer networks from intruders. It has been still challenging to design an accurate and a robust IDS with visualization capabilities to discover security threats due to the high volume of network traffic. This research work introduces and describes a novel anomaly-based intrusion detection system in presence of long-range independence data called benign outliers, using a neural projection architecture by a modified Self-Organizing Map (SOM) to not only detect attacks and anomalies accurately, but also provide visualized information and insights to end users. The proposed approach enables better analysis by merging the large amount of network traffic into an easy-to-understand 2D format and a simple user interaction. To show the performance and validate the proposed visualization-based IDS, it has been trained and tested over synthetic and real benchmarking datasets (NSL-KDD, UNSW-NB15, AAGM and VPN-nonVPN) that are widely applied in this domain. The results of the conducted experimental study confirm the advantages and effectiveness of the proposed approach

Preparation, Antimicrobial Activity and Docking Study of Vanadium Mixed Ligand Complexes Containing 4-Amino-5-hydrazinyl-4H-1,2,4-triazole-3-thiol and Aminophenol Derivatives

The synthesis of mixed-ligand complexes is considered an important strategy for developing new metal complexes of enhanced biological activity. This paper presents the synthesis, characterization, in vitro antimicrobial assessment, and theoretical molecular docking evaluation for synthesized oxidovanadium (V) complexes. The proposed structures of the synthesized compounds were proved using elemental and different spectroscopic analysis. The antimicrobial tests showed moderate activity of the compounds against the Gram-positive bacterial strains and the fungal yeast, whereas no activity was observed against the Gram-negative bacterial strains. The performance of density functional theory (DFT) was conducted to study the interaction mode of the targeted compounds with the biological system. Calculating the quantitative structure-activity relationship (QSPR) was performed depending on optimization geometries, frontier molecular orbitals (FMOs), and chemical reactivities for synthesized compounds. The molecular electrostatic potentials (MEPs) that were plotted link the interaction manner of synthesized compounds with the receptor. The molecular docking evaluation revealed that the examined compounds may possess potential antibacterial activity

An intersection game-theory-based traffic control algorithm in a connected vehicle environment

Urban traffic congestion is a growing problem that we experience every day. Intersections are one of the major bottlenecks that contribute to urban traffic congestion. Traditional traffic control methods, such as traffic signal and stop sign control are not optimal for all demand levels as demonstrated in the literature. Recently, numerous research efforts proposed Intelligent Transportation System (ITS) applications to enhance intersection capacity and hence reduce congestion. In this paper we propose a game-theory-based algorithm for controlling autonomous vehicle movements equipped with Cooperative Adaptive Cruise Control (CACC) systems at uncontrolled intersections. The goal of this research effort is to develop an algorithm capable of using the future autonomous/automated vehicle capabilities to replace the usual state-of-the-practice control systems at intersections (e.g. stop signs, traffic signals, etc.). The proposed algorithm is chicken-game inspired and is efficient for application in real-time. It assumes vehicles can communicate with a central agent at the intersection to provide their instantaneous speeds and locations. The proposed algorithm assumes that vehicles obey the Nash equilibrium solution of the game. The simulation results demonstrated reductions in vehicle travel time and delay relative to an all-way stop sign control in the range of 49 and 89 percent on average respectively.</p

Role of BAL cellularity in assessment of severity of idiopathic pulmonary fibrosis

Background/aim: Study the role of BAL cellularity in assessment of the degree of severity of IPF. Methods: Forty IPF patients underwent, history taking, clinical examination, HRCT chest, ABGs, 6MWT, spirometry, echocardiography, FOB and BAL. Results: Neutrophils were present in 28 patients, mean value 57.25 and SD ± 31.27. The second predominant cell was Alveolar Macrophages with mean value 24.25 and SD ± 27.828.HRCT pattern and BAL cellularity, showed the most predominant cell neutrophils in the ground glass and Honey combing on HRCT. There was no statistical significance between the sex and the BAL cellularity, the most predominant cell was neutrophils in both sexes. Corticosteroids did not have an effect on BAL cellularity and the predominant cell was neutrophils in IPF patients using steroids and those not. BAL cellularity in relation to treatment by azathioprine and/or acetlycysteine showed no statistical significance between patients using those drugs and those not, the most predominant cell was neutrophils in both groups.Correlation between BAL cellularity and age, showed no statistical significance but there was a negative correlation between age to neutrophils and lymphocytes. There was a negative correlation between neutrophils and PaCO2, PaO2, SO2, FVC%, FEV1 and 6MWT with no statistical significance but with significance to FEF25–75%.Macrophages showed a positive correlation with age, PaO2, 6MWT, FVC%, FEV1% with no statistical significance but with significance to SO2 and FEF25–75% and a negative correlation with PaCO2 and PASP. Conclusion: There was a positive correlation between neutrophils and severity of the disease and a negative correlation between Macrophages and severity of the disease. Most commonly used drugs did not show any effect on BAL cellularity

TEXTUAL EMOTION DETECTION APPROACHES: A SURVEY

Over the past decades, social media attracted individuals to express their feelings on any topic or item, resulting in an incremental growth in the size of created data. These feelings and unstructured data paved the path for business organizations to gather information and build statistical analysis. Various machine learning and natural language processing-based approaches are used for sentiment and emotion analysis. Moreover, deep learning-based approaches recently gained popularity due to their remarkable performance in text analysis. This paper provides a comprehensive overview of the prominent machine learning models applied in emotion analysis. It explores various emotion analysis taxonomies, in addition to the constraints of prevalent deep learning architectures. The paper also reviews some of the previously presented contributions in emotion analysis with a focus on deep learning methodologies as well as the most common datasets. It presents a comprehensive comparison between several emotion analysis models. This paper demonstrates the effectiveness of learning-based techniques in tackling emotion analysis challenges

Smart bike-sharing systems for smart cities

In the next few decades, many traditional cities will be turned into smart cities, which are greener, safer, and faster. This transformation is supported by recent advances in information and communication technology (ICT) in addition to the expected fast spread of the Internet of Things and big data analytics. Smart cities will mitigate some of the negative impacts of traditional cities, which consume 75% of the world’s resources and energy and produce 80% of the greenhouse gases (Mohanty et al. 2006). Smart cities have many components, including smart transportation. Smart transportation will integrate different transportation networks and allow them to work together so travelers and commuters can enjoy seamless multi-mode trips based on their preferences. Consequently, more commuters will be inspired to use public transportation systems and many traffic-related problems such as congestion will be relaxed. The last mile problem is a pressing problem that needs to be solved in order for different transportation networks to work together efficiently. This problem is defined as “the short distance between home and public transit or transit stations and the workplace, which may be too far to walk.” One solution to this<br/