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.     

Variable presentation of cerebrovascular disease in monovular twins

We describe twin girls with bilateral cerebrovascular disease. In one child, a diagnosis of moyamoya disease was made after presentation in infancy with an acute hemiparesis; her asymptomatic sibling was found to have significant bilateral cerebrovascular disease after neuropsychological evaluation and assessment with transcranial Doppler ultrasound. Both subjects showed a discrepancy between verbal and performance IQ and deficits on a test of frontal-lobe function suggesting that these domains should be targeted in cognitive assessment. Family members of subjects with moyamoya are at risk of cerebrovascular disease. Clinical symptoms do not reliably predict disease and those at risk should be offered screening with non-invasive vascular imaging.     

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.     

Microwave-Assisted Synthesis of Fine Particle Oxides Employing Wet Redox Mixtures

Interaction of electromagnetic radiation with a physical mixture of metal nitrates and amides/hydrazides is observed to initiate high-temperature reactions, useful for realizing several high-temperature ceramic materials. A judicious choice of such redox mixtures undergoes exothermic reactions when they couple with microwave radiation. The coupling of electromagnetic radiation with metal salts and amides/hydrazides depends on the dielectric properties of the individual components in the reaction mixture. The approach has been used to prepare γ-Fe₂O₃, Fe₃O₄, MgCr₂O₄, α-CaCr₂O₄, and La_0.7Ba_0.3MnO₃.     

A novel dynamic pricing scheme for contributing peers in the VoD system

In this paper we have proposed a dynamic pricing scheme for the contributing peers in the Video on Demand (VoD) system. The scheme provides an effective mechanism to maximize the profit through the residual resources of the contributing peers. A utilization function is executed for each contributing peer to estimate the utility factor based on the parameters such as initial setup cost, holding cost, chaining cost and salvage cost. In this paper, we urge an effective dynamic pricing algorithm that efficiently utilizes a range of parameters with a varying degree of complexity. The key findings of the algorithm are (i) each contributing peers are benefitted by the monetary based on its resource contributions to the VoD system and (ii) a high degree of social optimum is established by proficiently aggregating the contributing peer’s resources with the overall resources of the VoD system. We validate our claim by simulating the proposed dynamic pricing scheme with other standard pricing schemes such as altruism, cost model and game theory perspective. The result of our dynamic pricing scheme shows the best utility factor than other standard pricing schemes.     

Development of compositionally modulated multilayer Zn-Ni deposits as replacement for cadmium

Compositionally modulated multilayer (CMM) Zn-Ni deposits were electrodeposited from single acidic bath (pH = 4.7) by using a potentiostatic sequence. The Zn and Ni composition in the alloy was tailored as a function of distance from the steel substrate. X-ray diffraction studies of the deposit showed the presence of γ-phase with a composition of Ni₅Zn₂₁. The corrosion properties of modulated multilayer coatings were studied in 5% NaCl solution using electrochemical corrosion techniques. The polarization resistance of the deposits varied as a function of Ni content between 1700 and 3440 Ω. CMM Zn-Ni with 20 wt% Ni exposed in ASTM B117 salt spray test did not show any red rust formation after 400 h.     

Isothermal oxidation behavior of FeCo–2V intermetallic alloy

Isothermal oxidation behavior and the nature of oxide layer formed during oxidation of FeCo–2V alloy were characterized in the temperature range of 500–600 °C. Oxidation kinetics of the alloy follows a parabolic rate law. SEM and XRD studies indicate the formation of an iron rich outer oxide layer and an inner solute rich layer containing cobalt and vanadium rich oxides. The oxidation mechanism of the FeCo–2V alloy is similar to that of low alloy steels. During the initial stages, preferential oxidation of iron and cobalt occurs at the alloy surface and leads to the formation of a solute rich inner layer. Continued oxidation occurs through oxidation of iron and cobalt at the outer layer and internal oxidation of inner layer. The iron rich oxide layer formed at the surface on oxidation of FeCo alloy is semi-conducting in nature and may not provide the necessary insulating barrier required at the surface to minimize eddy current losses during A.C. applications.     

Controllability results for damped second-order impulsive neutral integrodifferential systems with nonlocal conditions

In this paper, we establish a set of sufficient conditions for the controllability of damped second-order impulsive neutral integrodifferential systems with nonlocal initial conditions in Banach spaces. The approach used is the Sadovskii fixed point theorem combined with a noncompact condition on the cosine family of operators. An example is presented to illustrate the result.