Deep Learning Based Process Analytics Model for Predicting Type 2 Diabetes Mellitus

Process analytics is one of the popular research domains that advanced in the recent years. Process analytics encompasses identification, monitoring, and improvement of the processes through knowledge extraction from historical data. The evolution of Artificial Intelligence (AI)-enabled Electronic Health Records (EHRs) revolutionized the medical practice. Type 2 Diabetes Mellitus (T2DM) is a syndrome characterized by the lack of insulin secretion. If not diagnosed and managed at early stages, it may produce severe outcomes and at times, death too. Chronic Kidney Disease (CKD) and Coronary Heart Disease (CHD) are the most common, long-term and life-threatening diseases caused by T2DM. Therefore, it becomes inevitable to predict the risks of CKD and CHD in T2DM patients. The current research article presents automated Deep Learning (DL)-based Deep Neural Network (DNN) with Adagrad Optimization Algorithm i.e., DNN-AGOA model to predict CKD and CHD risks in T2DM patients. The paper proposes a risk prediction model for T2DM patients who may develop CKD or CHD. This model helps in alarming both T2DM patients and clinicians in advance. At first, the proposed DNN-AGOA model performs data preprocessing to improve the quality of data and make it compatible for further processing. Besides, a Deep Neural Network (DNN) is employed for feature extraction, after which sigmoid function is used for classification. Further, Adagrad optimizer is applied to improve the performance of DNN model. For experimental validation, benchmark medical datasets were used and the results were validated under several dimensions. The proposed model achieved a maximum precision of 93.99%, recall of 94.63%, specificity of 73.34%, accuracy of 92.58%, and F-score of 94.22%. The results attained through experimentation established that the proposed DNN-AGOA model has good prediction capability over other methods.     

Mixed oxide supported hydrodesulfurization catalysts—a review

Support effects form important aspect of hydrodesulfurization (HDS) studies and mixed oxide supports received maximum attention in the last two decades. This review will focus attention on studies on mixed oxide supported Mo and W catalysts. For convenience of discussion, these are divided into Al₂O₃ containing mixed oxide supports, TiO₂ containing mixed oxide supports, ZrO₂ containing mixed oxide supports and other mixed oxide supports containing all the rest. TiO₂ containing mixed oxides received maximum attention, especially TiO₂–Al₂O₃ supported catalysts. A brief discussion about their prospects for application to ultradeep desulfurization is also included. An overview of the available literature with emphasis on research carried out in our laboratory form the contents of this publication.     

Prostate enlargement in mice due to fetal exposure to low doses of estradiol or diethylstilbestrol and opposite effects at high doses

On the basis of results of studies using high doses of estrogens, exposure to estrogen during fetal life is known to inhibit prostate development. However, it is recognized in endocrinology that low concentrations of a hormone can stimulate a tissue, while high concentrations can have the opposite effect. We report here that a 50% increase in free-serum estradiol in male mouse fetuses (released by a maternal Silastic estradiol implant) induced a 40% increase in the number of developing prostatic glands during fetal life; subsequently, in adulthood, the number of prostatic androgen receptors per cell was permanently increased by 2-fold, and the prostate was enlarged by 30% (due to hyperplasia) relative to untreated males. However, as the free serum estradiol concentration in male fetuses was increased from 2- to 8-fold, adult prostate weight decreased relative to males exposed to the 50% increase in estradiol. As a model for fetal exposure to man-made estrogens, pregnant mice were fed diethylstilbestrol (DES) from gestation days 11 to 17. Relative to controls, DES doses of 0.02, 0.2, and 2.0 ng per g of body weight per day increased adult prostate weight, whereas a 200-ng-per-g dose decreased adult prostate weight in male offspring. Our findings suggest that a small increase in estrogen may modulate the action of androgen in regulating prostate differentiation, resulting in a permanent increase in prostatic androgen receptors and prostate size. For both estradiol and DES, prostate weight first increased then decreased with dose, resulting in an inverted-U dose-response relationship.     

Evaluation of solid-desiccant-based evaporative cooling cycles for typical hot and humid climates

This paper presents an evaluation of various solid desiccant cycles for air conditioning in hot and humid climates. Psychometric evaluation of potential cycles for 16 typical Indian cities has been carried out with the objective of achieving standard comfort conditions in the room. Computer simulation is based on constant effectiveness of heat exchangers and evaporative coolers and actual performance data of a commercially available desiccant wheel dehumidifier. The influence of various outdoor conditions, the effectiveness of heat exchangers/evaporative coolers on the cooling coefficient of performance and volumetric air flowrate per unit cooling capacity have been investigated. It is found that amongst ventilation, recirculation and Dunkle cycles, the Dunkle cycle is better for a wide range of outdoor conditions. However, cycles using wet surface heat exchangers give even higher performance.     

Comparative study of crystallization processes in Sb2Te3 films using laser and thermal annealing techniques

Adherent and pin-hole free amorphous Sb₂Te₃ thin films have been obtained by vacuum evaporation at substrate temperatures ≤25 °C. The films have been crystallized by thermal and laser annealing, and the crystallization processes monitored as a function of annealing temperature and laser scan speed. A comparative study of topography reveals disk-shaped crystallized areas in thermal crystallization and dendrite growth in the laser induced process. The crystallized films in both cases contain a single Sb₂Te₃ phase. Activation energy of 2 eV for crystallization, determined using differential scanning calorimetery indicates good room temperature stability of the amorphous states.     

ERD facility for analysis of hydrogen and deuterium in solids

Hydrogen is the lightest element in nature, and so, its detection and quantitative analysis is difficult by the conventional methods utilized for other elements. In the recent years the technique of elastic recoil detection analysis (ERD) using 1–2 MeV He⁺ beam has been developed to quantitatively and simultaneously analyze hydrogen and its isotopes in solids. Such a facility has been set up using the 2 MeV Van-de-Graaff accelerator at IIT Kanpur. It facilitates H and D analysis in a material up to a depth of ∼ 1μm with a detection sensitivity of 0·1 at.% and depth resolution of about 300 ?. The application potential of this setup is illustrated by presenting the results of measurements performed on Al:H:D systems prepared by plasma source ion implantation and highT _c YBCO pellets exposed to humid atmosphere.     

Plasma immersion ion implantation for SOI synthesis: SIMOX and ion-cut

We have demonstrated feasibility to form silicon-on-insulator (SOI) substrates using plasma immersion ion implantation (PIII) for both separation by implantation of oxygen and ion-cut. This high throughput technique can substantially lower the high cost of SOI substrates due to the simpler implanter design as well as ease of maintenance. For separation by plasma implantation of oxygen wafers, secondary ion mass spectrometry analysis and cross-sectional transmission electron micrographs show continuous buried oxide formation under a single-crystal silicon overlayer with sharp Si/SiO₂ interfaces after oxygen plasma implantation and high-temperature (1300°C) annealing. Ion-cut SOI wafer fabrication technique is implemented for the first time using PIII. The hydrogen plasma can be optimized so that only one ion species is dominant in concentration and there are minimal effects by other residual ions on the ion-cut process. The physical mechanism of hydrogen induced silicon surface layer cleavage has been investigated. An ideal gas law model of the microcavity internal pressure combined with a two-dimensional finite element fracture mechanics model is used to approximate the fracture driving force which is sufficient to overcome the silicon fracture resistance.