Artificial intelligence in cyber security: research advances,challenges, and opportunities

Artificial Intelligence Review - In recent times, there have been attempts to leverage artificial intelligence (AI) techniques in a broad range of cyber security applications. Therefore, this paper...     

Evaluation of a robust, diimide-based, porous organic polymer (POP) as a high-capacity sorbent for representative chemical threats

A previously described porous organic polymer (NU-POP-1) was evaluated against four representative chemical threats: ammonia, cyanogen chloride, sulfur dioxide, and octane. Ammonia, cyanogen chloride, and sulfur dioxide are examples of toxic industrial chemicals (TICs) spanning the range from highly basic to strong-acid forming substances, while octane is used to assess physical adsorption capacity. Experiments were carried out using a microbreakthrough test apparatus, which measures the adsorption capacity at saturation and gives an indication of the strength of adsorption. The NU-POP-1 material exhibited substantial removal capabilities against the majority of the toxic chemicals, with capacities as high as or better than an activated, impregnated carbon. The ability to remove the highly volatile toxic chemicals ammonia and cyanogen chloride was intriguing, as these chemicals typically require reactive moieities for removal. The present work presents a benchmark for toxic chemical removal, and future work will focus on incorporating functional groups targeting the toxic chemicals of interest.     

Review: Heart Diseases Detection by Machine Learning Classification Algorithms

Most human deaths are caused by heart diseases. Such diseases cannot be efficiently detected for the lack of specialized knowledge and experience. Data science is important in healthcare sector for the role it plays in bulk data processing. Machine learning (ML) also plays a significant part in disease prediction and decision-making in medical care industry. This study reviews and evaluates the ML approaches applied in heart disease detection. The primary goal is to find mathematically effective ML algorithm to predict heart diseases more accurately. Various ML approaches including Logistic Regression, Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), t-Distributed Stochastic Neighbor Embedding (t-SNE), Nave Bayes, and Random Forest were utilized to process heart disease dataset and extract the unknown patterns of heart disease detection. An analysis was conducted on their performance to examine the effecacy and efficiency. The results show that Random Forest out-performed other ML algorithms with an accuracy of 97%.     

The voltage mirror–current mirror pair as a universal element

The voltage mirror–current mirror (VM–CM) pair is shown to be a universal active element. It provides two alternative realizations for the nullor. The VM–CM pair is also capable of realizing the op amp and all the four types of the current conveyors namely CCII?, CCII+, ICCII? and ICCII+ as special cases. Copyright © 2009 John Wiley & Sons, Ltd.     

Smooth and conductive DNA-templated Cu₂O nanowires: growth morphology, spectroscopic and electrical characterization

DNA strands have been used as templates for the self-assembly of smooth and conductive cuprous oxide (Cu?O) nanowires of diameter 12-23 nm and whose length is determined by the template (16 μm for λ-DNA). A combination of spectroscopic, diffraction and probe microscopy techniques showed that these nanowires comprise single crystallites of Cu?O bound to the DNA molecules which fused together over time in a process analogous to Ostwald ripening, but driven by the free energy of interaction with the template as well as the surface tension. Electrical characterization of the nanowires by a non-contact method, scanned conductance microscopy and by contact mode conductive AFM showed the wires are electrically conductive. The conductivity estimated from the AFM cross section and the zero-bias conductance in conductive AFM experiments was 2.2-3.3 S cm?1. These Cu?O nanowires are amongst the thinnest reported and show evidence of strong quantum confinement in electronic spectra.     

Real‐Time Activity Bioassay of Single Osteoclasts Using a Silicon Nanocrystal‐Impregnated Artificial Matrix

The lack of an in vitro real‐time osteoclast (OC) activity assay has hampered mechanistic studies of bone resorption. Such an assay is developed, employing a hydroxyapatite matrix impregnated with alkyl‐capped silicon nanocrystals, which is capable of monitoring the time‐course of resorption by single osteoclasts. Resorption of the matrix by OC releases the nanocrystals, which are internalized by the cell and detected as an increase in OC luminescence. This particular choice of nanocrystals is motivated by their bright pH‐independent luminescence, proportional to concentration, and by their rapid uptake without cytotoxicity. In this in vitro assay, OCs are inhibited by calcitonin (CT) and methyl‐β‐cyclodextrin (MCD), and stimulated by receptor activator of nuclear factor kappa‐B ligand (RANKL) in the expected manner. The kinetics of the assay exhibit a lag phase representing cell attachment and commencement of resorption processes, followed by a growth of cell luminescence intensity, and the whole time‐course is satisfactorily described by the logistic equation.