Dipper Throated Algorithm for Feature Selection and Classification in Electrocardiogram

Arrhythmia has been classified using a variety of methods. Because of the dynamic nature of electrocardiogram (ECG) data, traditional handcrafted approaches are difficult to execute, making the machine learning (ML) solutions more appealing. Patients with cardiac arrhythmias can benefit from competent monitoring to save their lives. Cardiac arrhythmia classification and prediction have greatly improved in recent years. Arrhythmias are a category of conditions in which the heart's electrical activity is abnormally rapid or sluggish. Every year, it is one of the main reasons of mortality for both men and women, worldwide. For the classification of arrhythmias, this work proposes a novel technique based on optimized feature selection and optimized K-nearest neighbors (KNN) classifier. The proposed method makes advantage of the UCI repository, which has a 279-attribute high-dimensional cardiac arrhythmia dataset. The proposed approach is based on dividing cardiac arrhythmia patients into 16 groups based on the electrocardiography dataset’s features. The purpose is to design an efficient intelligent system employing the dipper throated optimization method to categorize cardiac arrhythmia patients. This method of comprehensive arrhythmia classification outperforms earlier methods presented in the literature. The achieved classification accuracy using the proposed approach is 99.8%.     

Modelling of the Boronizing Kinetics of Vanadis 6 Steel by the Integral Diffusion Model

Protection of Metals and Physical Chemistry of Surfaces - In this work, the Vanadis 6 steel was subjected to the solid boronizing treatment in the range of 950–1050°C, and for the...     

Lysosomes Targeting pH Activable Imaging-Guided Photodynamic Agents

Photodynamic therapy (PDT) is a photochemistry-based medical treatment combining light at a specific wavelength and a photosensitizer (PS) in the presence of oxygen. Application of PDT as a conventional treatment is limited and clearly the approval in clinics of new PS is challenging. The selective accumulation of the PS in the targeted malignant cells is of paramount importance to reduce the side effects that are typical of the current worldwide approved PS. Here we report a new series of aniline- and iodine-substituted BODIPY derivatives ( 1 – 3 ) as promising lysosome-targeting and pH-responsive theranostic PS, which displayed a significant in vitro light-induced cytotoxicity, efficient imaging properties and low dark toxicity (for 2 and 3 ). These compounds were obtained in few reproducible synthetic steps and good yields. Spectroscopic and electrochemical measurements along with computational calculations confirmed the quenching of the emissive properties of the PS, while both fluorescence and ¹O₂ emission were obtained only under acidic conditions inducing amine protonation. The pK_a values and pH-dependent emissive properties of 1 – 3 being established, their cellular uptake and activation in the lysosomal vesicles (pH≈4-5) were confirmed by their co-localization with the commercial LysoTracker deep red and light-induced cytotoxicity (IC₅₀ between 0.16 and 0.06 μM) against HeLa cancer cells.     

Second-harmonic generation and structural rearrangements in multicomponent antimonite glasses by electrothermal poling

Electrothermal poling is shown here to effectively induce second-order nonlinear effects in heavy-metal oxide antimonite glasses. In M₂O–PbO–WO₃–Sb₂O₃ (M = Li, Na, K) glasses, the poling-induced second-harmonic generation intensity is five times larger than in silica (Infrasil) for M = Na, twice as large as in silica for M = Li, and smaller than in silica for M = K. X-ray photoelectron spectroscopy suggests that antimony ions exist predominantly in the trivalent oxidation state in the studied glass samples. Raman and infrared spectroscopy confirm that the glass network is comprised of SbO₃, WO₄, WO₆, and PbO₄ units—with some SiO₄ moieties due to leaching from the silica crucible. The WO₄ units appear to exist in two distinct sites, as evidenced by comparison of the vibrational spectra of alkali–tungsten–antimonite glasses with those of previously reported crystalline tungstate phases. The alkali type influences the equilibrium between tetrahedral tungstate anions, [WO₄]²⁻, and the isomeric partially polymerized octahedral tungstate units, [WØ₄O₂]²⁻ (Ø denotes a bridging oxygen). Raman spectroscopy line scans were used to track near-surface structural changes on the anode side of poled glasses. They reveal that the tungstate equilibrium is also affected by poling. At the anode side, the population of partially polymerized [WØ₄O₂]²⁻ species increases at the expense of anionic [WO₄]²⁻ species. This yields a net increase in the average bond length of the network forming constituents, which is commensurate with poling-induced structural changes observed in other systems experimentally and computationally.     

Erosion Regimes Characterization of Soda-Lime Glass

Silicon - In this work, a semi-empirical relationship between sandblasting times and the surface roughness is presented. The derived relation is valid for the case where the erosion process does...     

Robust stabilization for affine control systems in Banach spaces

This paper is devoted to the investigation of feedback stabilization of affine control systems on real Banach spaces. Under an appropriate decomposition of the state space, we provide sufficient conditions for exponential stabilization of the system at hand. Furthermore, we show that the proposed feedback law remains a stabilizing control under some types of perturbations on the dynamic and the control operator. Finally, two illustrative examples are provided.     

Intelligent Aquila Optimization Algorithm-Based Node Localization Scheme for Wireless Sensor Networks

In recent times, wireless sensor network (WSN) finds their suitability in several application areas, ranging from military to commercial ones. Since nodes in WSN are placed arbitrarily in the target field, node localization (NL) becomes essential where the positioning of the nodes can be determined by the aid of anchor nodes. The goal of any NL scheme is to improve the localization accuracy and reduce the localization error rate. With this motivation, this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme (IAOAB-NLS) for WSN. The presented IAOAB-NLS model makes use of anchor nodes to determine proper positioning of the nodes. In addition, the IAOAB-NLS model is stimulated by the behaviour of Aquila. The IAOAB-NLS model has the ability to accomplish proper coordinate points of the nodes in the network. For guaranteeing the proficient NL process of the IAOAB-NLS model, widespread experimentation takes place to assure the betterment of the IAOAB-NLS model. The resultant values reported the effectual outcome of the IAOAB-NLS model irrespective of changing parameters in the network.