Performance evaluation of TiAlCrYN nanocomposite coatings deposited using four-cathode reactive unbalanced pulsed direct current magnetron sputtering system

Approximately 1.5-2.5 μm thick nanocomposite coatings of TiAlCrYN were deposited using a four-cathode reactive unbalanced pulsed direct current magnetron sputtering system from the sputtering of Ti, Al, Cr, and Y targets in Ar + N₂ plasma. The TiAlCrYN nanocomposite coatings were deposited on various substrates such as high speed steel (HSS) drill bits, mild steel and silicon. TiAlCrYN coatings with almost similar mechanical properties but with different Ti, Al, Cr and Y contents were prepared to study their thermal stability and machining performance. The structural and mechanical properties of the coatings were characterized using X-ray diffraction and nanoindentation technique, respectively. The elemental composition, bonding structure, surface morphology and cross-sectional data were studied using energy-dispersive X-ray analysis, X-ray photoelectron spectroscopy and field-emission scanning electron microscopy, respectively. Nanoscratch tests were performed to determine the adhesive strength of the coatings. The corrosion behavior of TiAlCrYN nanocomposite coatings on mild steel substrate was studied using potentiodynamic polarization in a 3.5% NaCl solution. Micro-Raman spectroscopy was used to characterize the structural changes as a result of heating of the nanocomposite coatings in air (600-1000 °C). TiAlCrYN coatings prepared at 17 at.% Ti, 13 at.% Al, 21 at.% Cr and 1 at.% Y exhibited thermal stability as high as 900 °C in air (denoted as Sample 3). For the performance evaluation, the TiAlCrYN coated HSS drill bits were tested under accelerated machining conditions. With a drill speed of 800 rpm and a feed rate of 0.08 mm/rev the TiAlCrYN coated HSS drill bits (Sample 3) averaged 657 holes, while drilling a 12 mm thick 304 stainless steel plate under dry conditions, before failure. Whereas, the uncoated drill bits failed after drilling 50 holes under the same machining conditions. Results indicated that for the HSS drill bits coated with TiAlCrYN, the tool life increased by a factor of more than 12.     

n-3 Fatty Acids Abrogate Dyslipidemia-Induced Changes in Bile Acid Uptake,Synthesis, and Transport in Young and Aged Dyslipidemic Rats

In this study, the effect of n-3 fatty acids (FA) [α-linolenic acid (ALA) and eicosapentaenoic acid (EPA) + docosahexaenoic acid (DHA)] on the intestinal bile acid (BA) uptake, hepatic BA synthesis, and enterohepatic bile acid transporters (BAT) was assessed in young and aged dyslipidemic rats. Dyslipidemia was induced in young and aged rats by feeding a high-fat (HF) diet. Experimental groups received diets containing canola oil (HF + CNO) and fish oil (HF + FO) as a source of ALA and EPA + DHA, respectively. After 60 days of feeding, intestinal BA uptake and expression of apical sodium-dependent bile acid transporter (Asbt), organic solute transporter-alpha/beta (Osta/b) messenger RNA (mRNA), and hepatic expression of Na⁺ taurocholate cotransporting polypeptide (Ntcp), bile salt export pump (Bsep), cholesterol 7-α hydroxylase A1 (Cyp7a1), Farnesoid X receptor (Fxr), small heterodimer partner-1 (Shp), liver receptor homolog-1 (Lrh-1), and hepatic nuclear factor-4 alpha (Hnf4a) mRNA were measured. Hepatic 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase activity and total BA in serum, liver, and feces were assessed. The dyslipidemic HF group had: (1) increased intestinal BA uptake and Asbt and Osta/b mRNA expression, (2) increased BA in serum, (3) decreased hepatic expression of Ntcp, Bsep, and Cyp7a1 mRNA, (4) increased activity of HMG-CoA reductase, (5) increased hepatic expression of Fxr and Shp mRNA, (6) decreased hepatic expression of Lrh-1 and Hnf4a mRNA, and (7) decreased BA in feces, when compared to control, HF + CNO, and HF + FO groups. Immunostaining revealed increased expression of intestinal Asbt and hepatic Ntcp protein in the HF group when compared to control, HF + CNO, and HF + FO groups. n-3 FA abrogated dyslipidemia-induced changes in the intestinal uptake, hepatic synthesis, and enterohepatic transporters of BA in both young and aged rats. EPA + DHA was more effective than ALA in modulating dyslipidemia-induced changes.     

Entropies for detection of epilepsy in EEG

The electroencephalogram (EEG) is a representative signal containing information about the condition of the brain. The shape of the wave may contain useful information about the state of the brain. However, the human observer cannot directly monitor these subtle details. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the EEG signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. The aim of this work is to compare the different entropy estimators when applied to EEG data from normal and epileptic subjects. The results obtained indicate that entropy estimators can distinguish normal and epileptic EEG data with more than 95% confidence (using t-test). The classification ability of the entropy measures is tested using ANFIS classifier. The results are promising and a classification accuracy of about 90% is achieved.     

Non-linear analysis of EEG signals at various sleep stages

Application of non-linear dynamics methods to the physiological sciences demonstrated that non-linear models are useful for understanding complex physiological phenomena such as abrupt transitions and chaotic behavior. Sleep stages and sustained fluctuations of autonomic functions such as temperature, blood pressure, electroencephalogram (EEG), etc., can be described as a chaotic process. The EEG signals are highly subjective and the information about the various states may appear at random in the time scale. Therefore, EEG signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. The sleep data analysis is carried out using non-linear parameters: correlation dimension, fractal dimension, largest Lyapunov entropy, approximate entropy, Hurst exponent, phase space plot and recurrence plots. These non-linear parameters quantify the cortical function at different sleep stages and the results are tabulated.     

Multiperson interaction recognition in images: A body keypoint based feature image analysis

Most interaction recognition approaches have been limited to single‐person action classification in videos. However, for still images where motion information is not available, the task becomes more complex. Aiming to this point, we propose an approach for multiperson human interaction recognition in images with keypoint‐based feature image analysis. Proposed method is a three‐stage framework. In the first stage, we propose feature‐based neural network (FCNN) for action recognition trained with feature images. Feature images are body features, that is, effective distances between a set of body part pairs and angular relation between body part triplets, rearranged in 2D gray‐scale image to learn effective representation of complex actions. In the later stage, we propose a voting‐based method for direction encoding to anticipate probable motion in steady images. Finally, our multiperson interaction recognition algorithm identifies which human pairs are interacting with each other using an interaction parameter. We evaluate our approach on two real‐world data sets, that is, UT‐interaction and SBU kinect interaction. The empirical experiments show that results are better than the state‐of‐the‐art methods with recognition accuracy of 95.83% on UT‐I set 1, 92.5% on UT‐I set 2, and 94.28% on SBU clean data set.     

Promoting Software Reuse Using Self Organizing Maps

Reusability of software, regardless of its utilizing technique, is widely believed to be a promising means for improving software productivity and reliability. However it is not practiced adequately due to the lack of techniques that facilitate the locating of reusable components that are functionally close. In this paper we apply Kohonen's Self-Organizing Maps to develop an approach for promoting Software Reuse. We look at the details of how Self-Organization can arrange and regularize data from the original pattern space into a topology preserving map. We describe a practical implementation of the SOM methodology for Software Reuse using a database of UNIX commands. And finally we briefly present our proposed Software Reuse Methodology.     

Direct Numerical Simulation of pulsed jets-in-crossflow

Direct Numerical Simulations of a jet with a passive scalar injected vertically into a crossflow (velocity ratio = 6) is performed at a jet Reynolds number of 5000. The role of sinusoidal forcing of the jet on the dynamics of the flow structures, and on the jet trajectory and jet spreading is examined. Sinusoidal excitations selected are at non-dimensional frequencies of 0.2, 0.4, and 0.6. For the unforced jet, shear-layer vortices on the leading edge of the jet have a preferred mode frequency of around 0.35. With forcing, the dominant frequency in the near field of the jet is the forcing frequency, but further downstream, vortex interactions/mergings lead to the growth of the subharmonic modes. For a forcing frequency of 0.2, the jet bifurcates in the vertical plane; at a forcing frequency of 0.4, the jet trifurcates into three jet-streams in the vertical plane; and, at a forcing frequency of 0.6, the jet bifurcates in the horizontal plane. The largest vertical penetration is at a forcing frequency of 0.4, while the largest horizontal spreading occurs at a non-dimensional forcing frequency of 0.6. Wake vortices, with a U-loop structure, are seen for all cases except at a forcing frequency of 0.6, where they are completely suppressed. The U-loop structure is asymmetric for the unforced and 0.2 forcing frequency case, and is consistent with the earlier experimental observations for unpulsed jets-in-crossflow. Through particle visualizations, a mechanism for the development of the wake vortices is presented in the paper. Mean statistics on isosurface contours are also presented, and asymmetry in the mean counter-rotating kidney pair vortex structures are also seen for the unforced and 0.2 forcing cases. The results of this study indicate the potential of using external forcing as a potential control strategy for controlling the jet penetration and mixing with the crossflow in either the vertical plane or the horizontal plane.     

A Case‐Based Reasoning system for complex medical diagnosis

A Case‐Based Reasoning (CBR) system for medical diagnosis mimics the way doctors make a diagnosis. Given a new case, its accuracy in practice depends on successful retrieval of similar cases. CBR systems have had some success in dealing with simple diseases because of the robustness of their case base. However, their diagnostic accuracy suffers when dealing with complex diseases particularly those that involve multiple domains in medicine. An example of such a condition is Premenstrual syndrome (PMS) as it falls under both gynaecology and psychiatry. To address this issue, the paper proposes a CBR‐based expert system that uses the K‐nearest neighbour (KNN) algorithm to search k similar cases based on the Euclidean distance measure. The novelty of the system is in the design of a flexible auto‐set tolerance (T), which serves as a threshold to extract cases for which similarities are greater than the assigned value of T. A prototype software tool with a menu‐driven Graphical User Interface (GUI) has been developed for case input, analysis of results, and case adaptation within the system. Finally, the performance of the tool has been checked on a set of real‐world PMS cases.