On the polymeric foams: modeling and properties

Polymeric foams are now widely used and researched. The physical properties of polymeric foam can be related to a set of independent structural parameters or variables of the foam. Study of these variables and correlation with commercial FE packages is essential for reliable and faster product development. Some aspects of foam behavior are widely studied while some are little less, like correlation of physical unloading behavior. For example, a lot of work in the area of phenomenological constitutive modeling of uniaxial loading was done, though research in areas of unloading–reloading and their correlation still demands more attention. Increasing number of OEMs and suppliers are moving to computer simulations in the design phase to assess their future products. Hence, different parameters within FE packages play a significant role and also affect the results. Appropriate use of these parameters will narrow down error band and automatically reduce the cycle time and development cost. This brief review is expected to set the perspective for major research work done so far in terms of FE modeling correlation and constitutive modeling of polymeric foam vis-a-vis to its properties.     

Structural,Electronic Properties,Hydrogen Bonding Analyses,and Biological Activity of Two Multiple Myeloma Drugs: Lenalidomide and Pomalidomide

In this article, we made a comparative study of two multiple myeloma drugs: lenalidomide and pomalidomide. We calculated and discussed their geometries at DFT/B3LYP method. Intra-molecular hydrogen bonding in these molecules is confirmed and characterized by QTAIM calculations. Electronic parameters along with HOMO-LUMO and MESP surfaces are calculated in order to compare their chemical reactivity. The effect of structure and bonding on electronic properties and biological activities is discussed and it is established that pomalidomide is more biologically active than lenalidomide. The phenyl ring of these molecules show teratogenic effects, making a possibility of finding another new class of drugs.     

Non-traditional machining processes by means of velocity shear instability in plasma

The material removal within different machining process can be performed in distinct modalities. One of the modality is based on the effect of impact phenomenon. In this paper theoretical model of non-traditional machining process based on impact phenomenon is discussed. The material is removed from the surface due to the impact of ions. The velocity of ions is equal to the velocity at which the electrostatic ion-cyclotron instability driven by parallel flow velocity shear generated by massive ions takes place. The main ways for the material removal as consequence of the impact phenomenon are the microcracking, microcutting, melting and vaporizing of small quantities from the work-piece surface layer.     

Identification of Natural Products as Potential Pharmacological Chaperones for Protein Misfolding Diseases

Defective protein folding and accumulation of misfolded proteins is associated with neurodegenerative, cardiovascular, secretory, and metabolic disorders. Efforts are being made to identify small-molecule modulators or structural-correctors for conformationally destabilized proteins implicated in various protein aggregation diseases. Using a metastable-reporter-based primary screen, we evaluated pharmacological chaperone activity of a diverse class of natural products. We found that a flavonoid glycoside ( C-10 , chrysoeriol-7-O-β-D-glucopyranoside) stabilizes metastable proteins, prevents its aggregation, and remodels the oligomers into protease-sensitive species. Data was corroborated with additional secondary screen with disease-specific pathogenic protein. In vitro and cell-based experiments showed that C-10 inhibits α-synuclein aggregation which is implicated in synucleinopathies-related neurodegeneration. C-10 interferes in its structural transition into β-sheeted fibrils and mitigates α-synuclein aggregation-associated cytotoxic effects. Computational modeling suggests that C-10 binds to unique sites in α-synuclein which may interfere in its aggregation amplification. These findings open an avenue for comprehensive SAR development for flavonoid glycosides as pharmacological chaperones for metastable and aggregation-prone proteins implicated in protein conformational diseases.     

Statistical analysis of manual segmentations of structures in medical images

The problem of extracting anatomical structures from medical images is both very important and difficult. In this paper we are motivated by a new paradigm in medical image segmentation, termed Citizen Science, which involves a volunteer effort from multiple, possibly non-expert, human participants. These contributors observe 2D images and generate their estimates of anatomical boundaries in the form of planar closed curves. The challenge, of course, is to combine these different estimates in a coherent fashion and to develop an overall estimate of the underlying structure. Treating these curves as random samples, we use statistical shape theory to generate joint inferences and analyze this data generated by the citizen scientists. The specific goals in this analysis are: (1) to find a robust estimate of the representative curve that provides an overall segmentation, (2) to quantify the level of agreement between segmentations, both globally (full contours) and locally (parts of contours), and (3) to automatically detect outliers and help reduce their influence in the estimation. We demonstrate these ideas using a number of artificial examples and real applications in medical imaging, and summarize their potential use in future scenarios.     

Enhancement of Corrosion Resistance of Zinc Coatings Using Green Additives

In the present work, morphology, microstructure, and electrochemical behavior of Zn coatings containing non-toxic additives have been investigated. Zn coatings were electrodeposited over mild steel substrates using Zn sulphate baths containing four different organic additives: sodium gluconate, dextrose, dextrin, and saccharin. All these additives are “green” and can be derived from food contents. Morphological and structural characterization using electron microscopy, x-ray diffraction, and texture co-efficient analysis revealed an appreciable alteration in the morphology and texture of the deposit depending on the type of additive used in the Zn plating bath. All the Zn coatings, however, were nano-crystalline irrespective of the type of additive used. Polarization and electrochemical impedance spectroscopic analysis, used to investigate the effect of the change in microstructure and morphology on corrosion resistance behavior, illustrated an improved corrosion resistance for Zn deposits obtained from plating bath containing additives as compared to the pure Zn coatings.     

Magnetic Behaviour of Granular GdMnO<Subscript>3</Subscript> Film

The present study deals with the investigation of magnetic properties along with morphological and microstructure analyses of a multiferroic GdMnO₃ film fabricated on Si(100) substrate by the pulsed laser deposition technique. Rutherford backscattering spectroscopic analysis suggests that the film is fabricated in the form of diffused layers having different stoichiometric proportions. Raman spectroscopy signifies that few modes present in the film are associated with MnO₆ octahedra and some extra peaks indicating the mixed phase formation in tuning with the Rutherford backscattering spectroscopy. Atomic force microscopy confirms the granular nature of the film. Field-cooled and zero-field-cooled thermal magnetization curves show irreversible behaviour extending well above room temperature, which is associated with spin disorder. The presence of Gd⁺³ state and Mn⁺³/Mn⁺⁴ mixed states in the uppermost layers of the film was confirmed by near-edge X-ray absorption fine structure. Subsequently, in association with these observations, the film is a weak ferromagnetic at 5 K and even at room temperature.     

Linguistic frequent pattern mining using a compressed structure

Traditional association-rule mining (ARM) considers only the frequency of items in a binary database, which provides insufficient knowledge for making efficient decisions and strategies. The mining of useful information from quantitative databases is not a trivial task compared to conventional algorithms in ARM. Fuzzy-set theory was invented to represent a more valuable form of knowledge for human reasoning, which can also be applied and utilized for quantitative databases. Many approaches have adopted fuzzy-set theory to transform the quantitative value into linguistic terms with its corresponding degree based on defined membership functions for the discovery of FFIs, also known as fuzzy frequent itemsets. Only linguistic terms with maximal scalar cardinality are considered in traditional fuzzy frequent itemset mining, but the uncertainty factor is not involved in past approaches. In this paper, an efficient fuzzy mining (EFM) algorithm is presented to quickly discover multiple FFIs from quantitative databases under type-2 fuzzy-set theory. A compressed fuzzy-list (CFL)-structure is developed to maintain complete information for rule generation. Two pruning techniques are developed for reducing the search space and speeding up the mining process. Several experiments are carried out to verify the efficiency and effectiveness of the designed approach in terms of runtime, the number of examined nodes, memory usage, and scalability under different minimum support thresholds and different linguistic terms used in the membership functions.