Electrochemical characteristics of titanium based biomaterials in artificial saliva

In the last decade, new titanium alloys have been developed in different areas of dentistry, such as Ti6Al7Nb, Ti6Al2Nb1Ta1Nb, and Ti5Al2.5Fe. The aim of this study was to compare the Ti6Al7Nb, Ti6Al2Nb1Ta1Nb, Ti5Al2.5Fe, and Ti6Al4V alloys with the commercial titanium, regarding the corrosion resistance in artificial saliva. In the electrochemical estimations the polarization data are converted into instantaneous corrosion rate values (I_corr). The passivation properties were comparable for the four alloys. The EIS spectra are best fitted using an equivalent circuit (EC), which corresponds to the model of a two‐layer structure for the passive film. High impedance values (in the order of 10⁶ Ω cm²) were obtained from medium to low frequencies for all materials suggesting high corrosion resistance in artificial saliva. The electrochemical and corrosion behavior of Ti6Al4V is not affected on substituting vanadium with niobium, iron, molybdenum, and tantalum.     

The effect of stress triaxiality and strain-rate on the fracture characteristics of ductile metals

Notched tensile tests have been carried out on three common metals (pure iron, mild steel and aluminium alloy BS1474) over a wide range of strain-rates (10^–3 to 10⁴ s^–1) and the strain-to-failure measured. The ductility of all three materials was found to be strongly dependent on the level of stress triaxiality in the specimen, this dependency being greatest for the ferrous materials and least for the aluminium alloy. No significant effect of strain-rate could be ascertained from the experimental results provided fracture remained fully ductile. However, for mild steel, a transition to a brittle fracture mode was observed for a given level of stress triaxiality as the strain-rate was increased. Numerical simulations of the experiments have been used to derive constants of a semi-empirical fracture model from the measured results. This model was found to give reasonable predictions of fracture over the range of conditions investigated.     

Wastewater from a sugar refining industry

The wastewater discharged from a sugar industry in Mosul was characterized and the variations in the wastewater quality parameters were noted. As compared to the characteristics of sugar factory wastewater in industrialized countries the sugar factory wastewater in Mosul is less concentrated because of the high intake of fresh water. Batch reactor studies were conducted because the estimates obtained from batch experiments are inexpensive and are generally in the design range. The study revealed that the wastewater is amenable to aerobic biodegradation. The kinetic coefficients were determined by fitting the data to the mathematical models reported in the literature. The COD reduction can be predicted for a given set of conditions with the help of performance relationship suggested by Tucek et al. (Water Res. 5, 647–680, 1971).     

Simulation of reactivity transients in current MTRs

This work aims at simulation of reactivity induced transients in High Enriched Uranium (HEU) and Low Enriched Uranium (LEU) cores of a typical Material Test research Reactor (MTR) using PARET code. The transient problem was forced through specification of externally inserted reactivity as a function of time. Reactivity insertions are idealized by ramps and steps. Superdelayed-critical transients, superprompt-critical transients and quasistatic transients are selected for the analysis. Ramp and step reactivity functions were employed to simulate these perturbations. The effect of initial power on transient behavior has also been investigated. The low enriched uranium core is analyzed for transients without scram. The magnitudes of maximum reactivity insertions are chosen to be in the range of $0.05 to 2.0 for different reactivity insertion times. Transient simulation with scram reveals that response of both HEU and LEU-cores is similar for selected ‘ramps’ and ‘steps’. The difference is observed in the peak values of power and coolant, clad and fuel temperatures. Trip level is achieved earlier in case of LEU-core. The peak clad temperatures in both LEU and HEU-cores remain below the melting point of aluminum-clad for the selected reactivity insertions. Simulation show that the LEU-core is more sensitive to perturbations at low power as compared to the transients at full power. For reactivity transients at low power level, power rises sharply to a higher peak value. In transients at full power, the peak power barely exceeds the trip level. The power oscillations after the first peak are observed for transients without scram.     

Structural similarity between TAFs and the heterotetrameric core of the histone octamer

A complex of two TFIID TATA box-binding protein-associated factors (TA FIIs) is described at 2.0A resolution. The amino-terminal portions of dTAFII42 and dTAFII62 from Drosophila adopt the canonical histone fold, consisting of two short alpha-helices flanking a long central alpha-helix. Like histones H3 and H4, dTAFII42 and dTAFII62 form an intimate heterodimer by extensive hydrophobic contacts between the paired molecules. In solution and in the crystalline state, the dTAFII42/dTAFII62 complex exists as a heterotetramer, resembling the (H3/H4)2 heterotetrameric core of the histone octamer, suggesting that TFIID contains a histone octamer-like substructure.     

An algorithm for characteristic input-output modes of discrete convolution systems

A new algorithm is presented for the determination of characteristic patterns (CPA) and characteristic vectors (CVE) of discrete multivariable convolution systems. It is based on the geometrical interpretation of characteristic vectors and, hence, leads to simpler computation and provides a useful measure for the analysis and design of discrete multivarlable systems.     

Investigation of metal/V2O5 nanorod Ohmic contacts

In this work, V₂O₅ nanorods was prepared by thermal evaporation method followed by annealing at 550 °C in dry oxygen atmosphere for 60 min. X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM) were used to investigate the structure and surface characteristics of V₂O₅ nanorods. To comparatively analyze and find the best Ohmic contact with optimum electrical properties, different metals (Al, Ag, Cu, Au, Ni, and Pt) with thickness of 200 nm each were deposited on V₂O₅ nanorods under a high vacuum using a sputtering system. To improve the Ohmicity of the metal/V₂O₅ contacts, annealing process was carried out at 300 °C in air atmosphere for 60 min. The Ohmic contact resistance of (metal/V₂O₅) interfaces can undervalue the actual contact resistance under standard operating conditions. Hence, the contact resistance, specific contact resistance, and the current transfer length were determined at room temperature, before and after annealing, by characterizing the current–voltage (I–V) relation using Transmission Line Method (TLM). Al metal was found to be the best for V₂O₅ Ohmic contact, because it produced the smallest resistivity, the lowest specific contact resistance, and the lowest current transfer length as compared to the other metals.

     

NTRU_ SSS: Anew Method Signcryption Post Quantum Cryptography Based on Shamir’s Secret Sharing

With the advent of quantum computing, numerous efforts have been made to standardize post-quantum cryptosystems with the intention of (eventually) replacing Elliptic Curve Cryptography (ECC) and Rivets-Shamir-Adelman (RSA). A modified version of the traditional N-Th Degree Truncated Polynomial Ring (NTRU) cryptosystem called NTRU Prime has been developed to reduce the attack surface. In this paper, the Signcryption scheme was proposed, and it is most efficient than others since it reduces the complexity and runs the time of the code execution, and at the same time, provides a better security degree since it ensures the integrity of the sent message, confidentiality of the data, forward secrecy when using refreshed parameters for each session. Unforgeability to prevent the man-in-the-middle attack from being active or passive, and non-repudiation when the sender can’t deny the recently sent message. This study aims to create a novel NTRU cryptography algorithm system that takes advantage of the security features of curve fitting operations and the valuable characteristics of chaotic systems. The proposed algorithm combines the (NTRU Prime) and Shamir's Secret Sharing (SSS) features to improve the security of the NTRU encryption and key generation stages that rely on robust polynomial generation. Based on experimental results and a comparison of the time required for crucial exchange between NTRU-SSS and the original NTRU, this study shows a rise in complexity with a decrease in execution time in the case when compared to the original NTRU. It’s encouraging to see signs that the suggested changes to the NTRU work to increase accuracy and efficiency.     

Handling Class Imbalance in Online Transaction Fraud Detection

With the rise of internet facilities, a greater number of people have started doing online transactions at an exponential rate in recent years as the online transaction system has eliminated the need of going to the bank physically for every transaction. However, the fraud cases have also increased causing the loss of money to the consumers. Hence, an effective fraud detection system is the need of the hour which can detect fraudulent transactions automatically in real-time. Generally, the genuine transactions are large in number than the fraudulent transactions which leads to the class imbalance problem. In this research work, an online transaction fraud detection system using deep learning has been proposed which can handle class imbalance problem by applying algorithm-level methods which modify the learning of the model to focus more on the minority class i.e., fraud transactions. A novel loss function named Weighted Hard- Reduced Focal Loss (WH-RFL) has been proposed which has achieved maximum fraud detection rate i.e., True Positive Rate (TPR) at the cost of misclassification of few genuine transactions as high TPR is preferred over a high True Negative Rate (TNR) in fraud detection system and same has been demonstrated using three publicly available imbalanced transactional datasets. Also, Thresholding has been applied to optimize the decision threshold using cross-validation to detect maximum number of frauds and it has been demonstrated by the experimental results that the selection of the right thresholding method with deep learning yields better results.     

Automatic Heart Disease Detection by Classification of Ventricular Arrhythmias on ECG Using Machine Learning

This paper focuses on detecting diseased signals and arrhythmias classification into two classes: ventricular tachycardia and premature ventricular contraction. The sole purpose of the signal detection is used to determine if a signal has been collected from a healthy or sick person. The proposed research approach presents a mathematical model for the signal detector based on calculating the instantaneous frequency (IF). Once a signal taken from a patient is detected, then the classifier takes that signal as input and classifies the target disease by predicting the class label. While applying the classifier, templates are designed separately for ventricular tachycardia and premature ventricular contraction. Similarities of a given signal with both the templates are computed in the spectral domain. The empirical analysis reveals precisions for the detector and the applied classifier are 100% and 77.27%, respectively. Moreover, instantaneous frequency analysis provides a benchmark that IF of a normal signal ranges from 0.8 to 1.1 Hz whereas IF range for ventricular tachycardia and premature ventricular contraction is 0.08–0.6 Hz. This indicates a serious loss of high-frequency contents in the spectrum, implying that the heart’s overall activity is slowed down. This study may help medical practitioners in detecting the heart disease type based on signal analysis.