Texture anisotropy technique in brain degenerative diseases

Structural alterations anisotropy-based measured for different areas for the most common types of dementia diseases could be a biomarker of brain impairment. The current work aims to assess whether texture anisotropy can discriminate both healthy versus Alzheimer’s and Pick’s patients based on regional evaluation while maintaining high predictive power. The investigated area is reduced from the whole-brain surface to three major lobes (i.e., frontal, temporal and parietal). A predictive model was proposed to associate a disease with a specific area in the brain based on the anisotropy values. Simultaneous analysis of 1680 measurements from 105 brain magnetic resonance images acquired as T2w and PD sequences was performed to establish the significance of the model. The cerebral calcinosis disease has been used as artificial ground truth. The association based on textural anisotropy between targeted diseases and control patients was performed by using Pearson’s correlation coefficients. A new proposed consistency index investigated the texture anisotropy relevance for all image’s types and all analyzed classes and regions. The validation study is based on area under the receiver-operating characteristic curve that depicted the overall diagnostic performance of the texture anisotropy in each region. The proposed model demonstrated that texture anisotropy is accurate solution in diagnosis of Alzheimer’s and Pick’s diseases when the investigated area is reduced to major lobes, with sensitivity >90% and specificity >80%.

     

Modelling of start-up time for high temperature polymer electrolyte fuel cells

Start-up time is one of the important factors that limit the application of high temperature polymer electrolyte fuel cells in several areas. Present work involves the analysis of different warm-up methodologies to analyse the start-up time for phosphoric acid doped PBI membrane based fuel cells. With this objective a number of three dimensional thermal models have been developed. Different heating methodologies such as reactant heating, coolant heating and combined heating (reactant and ohmic) are simulated. The ohmic heating is implemented for generating heat in the membrane itself at high current densities. Hence, combining it with other heating techniques is found effective in reducing start-up times significantly.     

Characterization of aluminides formed on superalloy 690 substrate

Ni-Cr-Fe based superalloy 690 substrate, pack aluminized at 1273 K, revealed formation of multilayer comprising (NiCr)Al + Cr₅Al₈, Ni₂Al₃ + Cr₅Al₈, NiAl and γ phases. Knoop hardness number varied from 225 to 1142 along the cross-section. Wear and friction tests on aluminized specimen were performed in dry medium using reciprocating sliding wear and friction machine with tungsten carbide ball at 15 N load with frequencies at 10, 15 and 20 Hz. The coefficient of friction, the static ones were obtained in the vicinity of 0.2, 0.3 and 0.5, while dynamic ones were 0.3, 0.4 and 0.4 respectively. For the ball, the wear rate was 1.9 × 10^?6, 1.2 × 10^?5 and 1.5 × 10^?5 mm³/Nm, whereas the wear rate was 5.8 × 10^?5, 3.8 × 10^?4 and 4.6 × 10^?4 mm³/Nm respectively for the aluminized specimen indicating good adherent surface coating.     

Optimization of bead geometry in electron beam welding using a Genetic Algorithm

Bead-on-plate welds were carried out on austenitic stainless steel plates using an electron beam welding machine. Experimental data were collected as per central composite design and regression analysis was conducted to establish input–output relationships of the process. An attempt was made to minimize the weldment area, after satisfying the condition of maximum bead penetration. Thus, it was posed as a constrained optimization problem and solved utilizing a Genetic Algorithm with a penalty function approach. The Genetic Algorithm was able to determine optimal weld-bead geometry and recommend the necessary process parameters for the same.     

Novel defects in Al–Pd–Fe complex metallic alloys: A micromechanical modelling approach

Transmission electron microscopy investigations have revealed that in the face centred complex metallic alloy of C₂–Al–Pd–Fe, the dislocations mediating plastic flow are decorated by localized regions of body centred structure in the compressive part of their strain field thus forming composite defects. We calculated the properties of these defects using a micromechanical model. The Eshelby method was employed to estimate the energies involved in the formation of such defects in the face-centred C₂ phase. We could reproduce the experimentally observed features of the defects in terms of their size and spatial configuration. The model describes a unique mechanism of a non-equilibrium defect, i.e., a dislocation, being stabilized by the formation and interaction with another non-equilibrium defect, i.e., a nanometre sized inclusion of different structure.     

Evolution of crystallographic texture and microstructure in the orthorhombic phase of a two-phase alloy Ti–22Al–25Nb

Evolution of crystallographic texture in the orthorhombic phase of a two-phase alloy Ti–22Al–25Nb (at%), consisting of orthorhombic (O) and bcc (β/B2) phases, was studied. The material was subjected to deformation in two-phase field as well as in the single β phase field. The resulting evolution of microstructure and crystallographic texture were recorded using scanning electron microscopy and X-ray diffraction. The orthorhombic phase underwent change in morphology (from platelets to equiaxed) on rolling in the two-phase field with the texture getting sharper with the amount of deformation. Rolling above β transus temperature led to hot deformation of single β phase microstructure and its subsequent cooling produced transformed coarse platelets of orthorhombic phase with texture in orientation relation with the high temperature deformed β phase.     

Robust observer based control for plasma glucose regulation in type 1 diabetes patient using attractive ellipsoid method

This paper deals with the design of robust observer based output feedback control law for the stabilisation of an uncertain nonlinear system and subsequently apply the developed method for the regulation of plasma glucose concentration in Type 1 diabetes (T1D) patients. The principal objective behind the proposed design is to deal with the issues of intra‐patient parametric variation and non‐availability of all state variables for measurement. The proposed control technique for the T1D patient model is based on the attractive ellipsoid method (AEM). The observer and controller conditions are obtained in terms of linear matrix inequality (LMI), thus allowing to compute easily both the observer and controller gains. The closed‐loop response obtained using the designed controller avoids adverse situations of hypoglycemia and post‐prandial hyperglycemia under uncertain conditions. Further to validate the robustness of the design, closed‐loop simulations of random 200 virtual T1D patients considering parameters within the considered ranges are presented. The results indicate that hypoglycemia and post‐prandial hyperglycemia are significantly reduced in the presence of bounded (±30% ) parametric variability and uncertain exogenous meal disturbance.Inspec keywords: medical control systems, observers, uncertain systems, nonlinear control systems, robust control, control system synthesis, linear matrix inequalities, feedback, sugar, closed loop systems, diseasesOther keywords: virtual T1D patients, type 1 diabetes patients, closed‐loop simulations, uncertain conditions, post‐prandial hyperglycemia, designed controller, closed‐loop response, controller gains, linear matrix inequality, controller conditions, T1D patient model, control technique, intra‐patient parametric variation, principal objective, plasma glucose concentration, uncertain nonlinear system, robust observer based output feedback control law, attractive ellipsoid method, plasma glucose regulation