A Review on Machine Learning Approaches for Network Malicious Behavior Detection in Emerging Technologies

Network anomaly detection systems (NADSs) play a significant role in every network defense system as they detect and prevent malicious activities. Therefore, this paper offers an exhaustive overview of different aspects of anomaly-based network intrusion detection systems (NIDSs). Additionally, contemporary malicious activities in network systems and the important properties of intrusion detection systems are discussed as well. The present survey explains important phases of NADSs, such as pre-processing, feature extraction and malicious behavior detection and recognition. In addition, with regard to the detection and recognition phase, recent machine learning approaches including supervised, unsupervised, new deep and ensemble learning techniques have been comprehensively discussed; moreover, some details about currently available benchmark datasets for training and evaluating machine learning techniques are provided by the researchers. In the end, potential challenges together with some future directions for machine learning-based NADSs are specified.     

Application of Sol–Gel Based Poly(ethylene glycol)/Multiwalled Carbon Nanotubes Coated Fiber for SPME of Methyl tert-Butyl Ether in Environmental Water Samples

In this research, the sol–gel technology was applied for the preparation of solid-phase microextraction fibers for extracting of methyl tert-butyl ether (MTBE) from environmental water samples. For this purpose, two different polymers such as poly(ethylene glycol) (PEG) and combination of PEG and multiwall carbon nanotubes (MWCNTs) were prepared using sol–gel technology as coating procedure for the fibers. The pre-concentration process followed by GC–FID determination was used and the results evidenced that pre-concentration factor for PEG/CNTs fiber was approximately five times higher than PEG. Parameters affecting the extraction efficiency such as temperature, extraction time, stirring speed and salt effect for each fiber were investigated and optimized. On the optimal conditions, the linear range for MTBE with PEG and PEG/CNT fibers were 10–3,000 and 1–1,000 ng mL^?1 and the detection limits (S/N = 3) were 1.0 and 0.3 ng mL^?1, respectively. The sol–gel PEG/CNTs fiber has good performance and therefore relatively better figures of merit and experimental results such as thermal stability (up to 320 °C), average of life time (over 150 times) and repeatability (RSD < 4) in comparison to conventional PDMS/Carboxen fiber, which was already reported for determination of MTBE.     

Enhancement of Kerr nonlinearity at long wavelength in a quantum dot nanostructure

The giant Kerr nonlinearity with reduced linear and nonlinear absorption in a four-level quantum dot by employing the tunnel coupling is investigated. It is shown that by enhancement of tunnel coupling value the Kerr nonlinearity increases and at the same time linear and nonlinear absorption reduces at the long wavelength which is very important for communicational applications. Enhanced of Kerr nonlinearity in a double quantum dots is investigated. It is found that the electron tunneling has an essential role to reducing the linear absorption and increasing the Kerr nonlinearity at long wavelength.     

Solid phase extraction of nitrate and nitrite anions using naturally and available sorbent

Radioactive waste contains nitrate and nitrite as well as radioactive fission products. Nitrate and nitrite anions are two of the major components of nuclear waste streams and contribute to environmental release hazards. The removal of nitrate and nitrite is a necessary step for the further treatment low-level radioactive wastes. The focus of the research is to evaluate the adsorption potential of solid phase derived from rice straw for nitrate and nitrite anions in single- and binary-component systems due to the fact that the rice straw is a very abundant and by-product material. The removal was accomplished under the optimize conditions of temperature, concentration, pH, contact time and quantity of adsorbent as these parameters are some of the main factors influencing the uptake of two solutes at the solid–solution interface. Batch-mode kinetic and equilibrium studies have been carried out. The experimental data was analyzed using equilibrium isotherm and kinetic models. The thermodynamic parameters (?G°, ?H°, and ?S°) were also determined using the equilibrium constant value obtained at different temperatures. Results show that this adsorbent is effective and much better or even superior than many sorbents for removal of nitrate and nitrite. The prepared sorbent as solid-phase extractant was successfully applied for the extraction of nitrate from actual water samples.     

Flow-injection potentiometric determination of clobutinol hydrochloride in pure state and pharmaceutical preparations

Clobutinol (Cb) ion-selective plastic-membrane electrodes based on ion associates of clobutinolium phosphotungstate (Cb-PTA), clobutinolium phosphomolybdate (Cb-PMA), or a mixture of both Cb-PTA and PMA were prepared. The electrodes were fully characterized in terms of membrane composition, life span, pH, and temperature. The electrodes were applied to the potentiometric determination of clobutinol in pure form and pharmaceutical preparations under batch and flow-injection conditions. Also, conductimetric titrations were applied to the assay of clobutinol in its pure form and pharmaceutical preparations. The selectivity of the electrodes towards a large number of inorganic cations, amino acids, and sugars was tested. The solubility product of ion-associates and the formation constant of the precipitation reactions leading to the ion-associate formation were determined conductimetrically. The text was submitted by the authors in English.     

Contact between the β1 and β2 Segments of α‐Synuclein that Inhibits Amyloid Formation

Conversion of the intrinsically disordered protein α‐synuclein (α‐syn) into amyloid aggregates is a key process in Parkinson’s disease. The sequence region 35–59 contains β‐strand segments β1 and β2 of α‐syn amyloid fibril models and most disease‐related mutations. β1 and β2 frequently engage in transient interactions in monomeric α‐syn. The consequences of β1–β2 contacts are evaluated by disulfide engineering, biophysical techniques, and cell viability assays. The double‐cysteine mutant α‐synCC, with a disulfide linking β1 and β2, is aggregation‐incompetent and inhibits aggregation and toxicity of wild‐type α‐syn. We show that α‐syn delays the aggregation of amyloid‐β peptide and islet amyloid polypeptide involved in Alzheimer’s disease and type 2 diabetes, an effect enhanced in the α‐synCC mutant. Tertiary interactions in the β1–β2 region of α‐syn interfere with the nucleation of amyloid formation, suggesting promotion of such interactions as a potential therapeutic approach.