Effects of Mold Pressure on Mechanical, Microstructures, Oxidation Behavior, and Thermodynamic Properties of an Al-Based Alloy

In this study, the effects of mold pressure variation on the microstructure, mechanical, oxidation behavior, and thermodynamics properties of an AlSi12CuNi alloy have been investigated by means of optical microcopy, scanning electron microscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, differential thermal analysis, and thermo-gravimetric analysis techniques. It is observed that hardness and tensile strength of the alloys increase as die-casting mold pressure increases due to an improvement in the distribution pattern of secondary phases and reduction in porosity. Oxidation behavior parameters and thermodynamic parameters such as formation enthalpy, heat capacity, and entropy are determined from TGA and DTA. It is found that mold pressure also has a significant effect on the oxidation behavior and thermodynamic parameters.     

Group sequential testing of homogeneity in genetic linkage analysis

Human genetic linkage studies have the objective of testing whether disease genes are linked to genetic markers based on family genetic data. Sometimes, these studies require many years of recruiting informative families and large amount of funds. One way to reduce the required sample size for such studies is to use sequential testing procedures. In this paper, we investigate two group sequential tests for homogeneity in binomial mixture models that are commonly used in genetic linkage analysis. We conduct Monte Carlo simulations to examine the performance of the group sequential procedures. The results show that the proposed group sequential procedures can save, on average, substantial sample size and detect linkage with almost the same power as their nonsequential counterparts.     

Explainable,Domain-Adaptive,and Federated Artificial Intelligence in Medicine

Artificial intelligence(AI) continues to transform data analysis in many domains.Progress in each domain is driven by a growing body of annotated data,increased computational resources,and technological innovations.In medicine,the sensitivity of the data,the complexity of the tasks,the potentially high stakes,and a requirement of accountability give rise to a particular set of challenges.In this review,we focus on three key methodological approaches that address some of the particular challenges...     

Prediction of protein cellular localization sites using a hybrid method based on artificial immune system and fuzzy k-NN algorithm

The use of artificial intelligence methods in biological data analysis has been increased recent since performance of the classification and detection systems have improved considerably to help medical experts in diagnosing. In this paper, we investigate the performance of an artificial immune system (AIS) based fuzzy k-NN algorithm with and without cross validation in a class of imbalanced problems in bioinformatics. Furthermore, we devise an unsupervised AIS algorithm in a supervised manner which contains a training stage for data reduction and a classification stage using fuzzy k-NN algorithm. The experiments show the efficacy of the proposed method with promising results. Using the Escherichia coli and yeast database, we compare the classification accuracy of the proposed method with those of other methods which have been proposed in the literature. The proposed hybrid system produced much more accurate results than the Horton and Nakai's method [P. Horton, K. Nakai, Better prediction of protein cellular localization sites with the k-nearest neighbors classifier, in: Proceedings of Intelligent Systems in Molecular Biology, Halkidiki, Greece, 1997, pp. 368–383]. Besides the improvement on the classification accuracy, one of the important aspects of the proposed method is the complexity. As the proposed AIS method incorporates data reduction in the training stage, the training complexity is considerably low comparing with the k-NN classifier.     

Persistent left superior vena cava: Two case reports and a review from nephrologists’ perspective

Thoracic venous anomalies without congenital heart anomalies are present in minority of the population, but they are frequent enough to be encountered while placing hemodialysis catheters through the jugular or subclavian veins. Persistent left superior vena cava is the most commonly seen anomaly and it is rarely noticed before the observation of an unusual course of hemodialysis catheter or guidewire on chest X‐ray. We present two patients with previously unspotted persistent left superior vena cava and uncomplicated hemodialysis catheter insertions through the internal jugular veins with good catheter functions. Review of the relevant literature from a nephrologists’ perspective with technical aspects is provided.     

Synthesis and characterization of cryogels of p(HEMA-N-vinylformamide) and p(HEMA-N-Vinylpyrrolidone) for chemical release behaviour

Journal of Porous Materials - Macroporous polymeric gels has received great attention in many fields focused on biotechnological applications. In this study, two new HEMA-based cryogel columns were...