Hepatitis disease diagnosis using a new hybrid system based on feature selection (FS) and artificial immune recognition system with fuzzy resource allocation

This paper presents a novel method for diagnosis of hepatitis disease. The proposed method is based on a hybrid method that uses feature selection (FS) and artificial immune recognition system (AIRS) with fuzzy resource allocation mechanism. AIRS has showed an effective performance on several problems such as machine learning benchmark problems and medical classification problems like breast cancer, diabets, liver disorders classification. By hybridizing FS and AIRS with fuzzy resource allocation mechanism, a method is obtained to solve this diagnosis problem via classifying. The robustness of this method with regard to sampling variations is examined using a cross-validation method. We used hepatitis disease dataset which is taken from UCI machine learning repository. We obtained a classification accuracy of 92.59%, which is the highest one reached so far. The classification accuracy was obtained via 10-fold cross validation. The obtained classification accuracy of our system was 92.59% and it was very promising with regard to the other classification applications in literature for this problem. Also, sensitivity, and specificity values for hepatitis disease dataset were obtained as 100 and 85%.     

A novel hybrid method based on artificial immune recognition system (AIRS) with fuzzy weighted pre-processing for thyroid disease diagnosis

Proper interpretation of the thyroid gland functional data is an important issue in the diagnosis of thyroid disease. The primary role of the thyroid gland is to help regulation of the body’s metabolism. Thyroid hormone produced by the thyroid gland provides this. Production of too little thyroid hormone (hypothyroidism) or production of too much thyroid hormone (hyperthyroidism) defines the type of thyroid disease. Artificial immune systems (AISs) is a new but effective branch of artificial intelligence. Among the systems proposed in this field so far, artificial immune recognition system (AIRS), which was proposed by A. Watkins, has shown an effective and intriguing performance on the problems it was applied. This study aims at diagnosing thyroid disease with a new hybrid machine learning method including this classification system. By hybridizing AIRS with a developed Fuzzy weighted pre-processing, a method is obtained to solve this diagnosis problem via classifying. The robustness of this method with regard to sampling variations is examined using a cross-validation method. We used thyroid disease dataset which is taken from UCI machine learning respiratory. We obtained a classification accuracy of 85%, which is the highest one reached so far. The classification accuracy was obtained via a 10-fold cross-validation.     

Evaluation of the antibacterial influence of silver nanoparticles against fish pathogenic bacterial isolates and their toxicity against common carp fish

At present, nanotechnology and nanomaterials are being emerged very quickly and gained the attention of researchers due to their frequent application history, especially their antibacterial effects against certain bacterial isolates. Therefore, the present study was aimed to check the antibacterial influence and toxic effects of the market available (Chemical Fabricated) silver nanoparticles (AgNPs). For this purpose, the AgNPs were obtained from the local market and used against fish pathogenic bacterial species. The highest zone of inhibition was observed against Aeromonas hydrophila (27.53 ± 0.69). Moreover, the AgNPs were exposed to the common carp fish for toxicity and toxic effects. The highest mortality was seen at the highest concentration (0.09 mg/L) of AgNPs. Finally, the AgNPs mainly were accumulated in the liver, followed by the intestine, gills, and muscles. The intestine absorbed the nanomaterials; therefore, it is critical to check the influence of these AgNPs on the fish intestinal bacterial community via MiSeq Illumina Sequencing.     

Mine Wastewater Treatment with Upflow Anaerobic Fixed Film Reactors

Mine Water and the Environment - Microbial bioremediation of metals in wastewater by sulfate-reducing bacteria (SRB) has received much attention due to its high efficiency, eco-friendly techniques,...     

Integrating the LSSVM and RBFNN models with three optimization algorithms to predict the soil liquefaction potential

Engineering with Computers - Liquefaction has caused many catastrophes during earthquakes in the past. When an earthquake is occurring, saturated granular soils may be subjected to the liquefaction...     

Effects of freeze-thawing cycles on the physical and mechanical properties of basaltic and dolomitic rocks evaluated with a decay function model

Bulletin of Engineering Geology and the Environment - Basalts from Çorlu Karatepe and dolomite from Kırklareli subjected to freeze-thawing (F-T) cycles were studied, and the resulting...     

Food safety governance in Saudi Arabia: Challenges in control of imported food

The operating environment for food safety interventions in nations such as Saudi Arabia, with limited local agricultural productivity, high reliance on foreign food imports and observance of Islamic laws, is remarkably challenging for the national control and regulatory institutions, since compliance to the mandatory food safety regulations and the local religious Halal standards must be ensured. This review offers a comprehensive analysis of the recently restructured food safety governance in Saudi Arabia from the perspective of its food imports control. Specifically, the nature of the food imports, the organization of the food safety governance and the current control practices of imported food, in consideration of food safety and Halal requirements, are analyzed through a triangulation of data and information from secondary sources (academic literature review and gray literature search) and primary sources (direct consultation of field experts). Statistical trade data on imported food were also performed. Results revealed that the process of centralizing all the control and regulatory activities under a single agency, which the government started to strengthen the national food safety governance, has not been completed yet. The resulting overlap of legislative and monitoring tasks by multiple entities augments the challenge of ensuring the safety, quality, and authenticity of imported food and their compliance to Halal standards. The vulnerabilities and challenges still to be addressed by the local food industry and the public sector are discussed, with implications for national and international field practitioners and policymakers of countries facing similar challenges.