Determination of zonal boundaries in articular cartilage using infrared dichroism

To determine the sub-tissue structural zonal boundaries in articular cartilage, a novel infrared (IR) microscopic imaging method based on the dichroic nature of the amide components has been developed and is discussed in this article. Thin canine cartilage-bone sections embedded in paraffin as well as in poly(methyl methyacrylate) (PMMA) were imaged under two orthogonal polarization states at 6.25 mum pixel size. The depth-dependent anisotropy of the amide components at perpendicular polarization states attributed by the collagen constituent in cartilage was analyzed. Since the transitional zone fibers are randomly arranged and the dichroic ratio value reaches unity in this zone, it is possible to identify the transitional zone boundaries, thus dividing the whole-depth tissue into three structural zones (superficial, transitional and radial). The zone division results from the infrared method agree well with the results from the established polarized light microscopy (PLM) method, which promises the potential of infrared imaging as an independent technique for the zonal boundary determination. The advantages of this dichroic ratio method are (1) it is independent of mode of operation (transmission/reflection), (2) it is independent of sample thickness, (3) either a polarizer or an analyzer can be used in experiments to determine zonal boundaries, and (4) it is sample orientation independent.     

Intangible capital,knowledge and new product development competence in supply chains: process,interaction and contingency effects among SMEs

Leveraging the strengths of a firm’s supply chain partners for new product development (NPD) has become essential to satisfy rapidly changing customer demands and to remain competitive. Firms are, therefore, aiming to further their NPD competence, which we define as the ability of the supply chain to improve and generate new products and services, based on the processes and relationships established with suppliers and customers. This study examines how intangible capital and knowledge further the development of NPD competence within the context of a supply chain. A theoretical model, based upon resource-advantage theory, is tested via structural equation modelling utilising survey data collected from 195 small- and medium-sized enterprises in the manufacturing industry reporting on their primary supply chain. Our findings indicate that more easily transferable capital manifests itself in explicit knowledge and less easily transferable capital manifests itself in tacit knowledge. We further identify complementarities of the two types of intangible capital as influencing knowledge type development. More importantly, we find that the two types of knowledge differ in their ability to influence NPD competence in the supply chain, and that these links are moderated by relationship length. Supply chain management implications for academics and practitioners are presented.     

Water‐blown polyurethane–clay nanocomposite foams from biopolyol—effect of nanoclay on the properties

The present work deals with the development of polyurethane–clay nanocomposite foams by replacing part of the synthetic polyol with castor oil derivative. Hydroxylated castor oil was converted into diethanol amide by transamidation and the resulting polyol was formulated into water‐blown foams. Modified montmorillonite clay was used as nanofiller in different amounts viz. 0.5%, 1.0%, 2.0%, and 5.0% by total weight of the foam formulation. Rheological measurements on the polyol–clay mixtures indicated that up to 1% clay loading there is no significant change in the viscosity with shear rate and beyond 2%, shear thinning occurred. X‐ray diffraction studies further substantiated these results. The effect of the modified clay on the density, mechanical properties such as compression strength, compression modulus, and microstructure of the foams were investigated. The filler thus added had a reinforcing effect on the foam as observed in the density and compression strength measurements. Differential scanning calorimetric studies on T_g and dynamic mechanical analyses on the modulus clearly indicated that 1% clay loading and above led to exfoliation and plasticizing effect. Exfoliated nanocomposites in compositions containing 1% clay and more yielded a much higher nucleation rate than intercalated ones leading to reduced cell size as observed by optical and scanning electron microscopy. Thus, castor oil, which is readily available, relatively inexpensive, and environmentally benign nonedible oil, has been successfully used to prepare filled semirigid foams which can find application in insulation and packing. POLYM. COMPOS. 34:1306–1312, 2013. © 2013 Society of Plastics Engineers     

Variable power adaptive MIMO OFDM system under imperfect CSI for mobile ad hoc networks

Future high speed mobile applications require diverse Quality of Service (QoS). To provide flexible data rate services while satisfying the low delay requirements, adaptive MIMO OFDM is a promising technique over time varying channels. In this paper a variable power adaptive MIMO OFDM system under imperfect CSI using cross layer design for mobile ad hoc networks is proposed. Data throughput is maximized while maintaining the delay QoS requirements in the presence of channel estimation errors. Numerical results show that the variable power adaptive MIMO OFDM system provides better spectral efficiency than its constant power counterpart.     

Suppression of Pain in the Late Phase of Chronic Trigeminal Neuropathic Pain Failed to Rescue the Decision-Making Deficits in Rats

Trigeminal neuropathic pain (TNP) led to vital cognitive functional deficits such as impaired decision-making abilities in a rat gambling task. Chronic TNP caused hypomyelination in the anterior cingulate cortex (ACC) associated with decreased synchronization between ACC spikes and basal lateral amygdala (BLA) theta oscillations. The aim of this study was to investigate the effect of pain suppression on cognitive impairment in the early or late phases of TNP. Blocking afferent signals with a tetrodotoxin (TTX)-ELVAX implanted immediately following nerve lesion suppressed the allodynia and rescued decision-making deficits. In contrast, the TTX used at a later phase could not suppress the allodynia nor rescue decision-making deficits. Intra-ACC administration of riluzole reduced the ACC neural sensitization but failed to restore ACC-BLA spike-field phase synchrony during the late stages of chronic neuropathic pain. Riluzole suppressed allodynia but failed to rescue the decision-making deficits during the late phase of TNP, suggesting that early pain relief is important for recovering from pain-related cognitive impairments. The functional disturbances in ACC neural circuitry may be relevant causes for the deficits in decision making in the chronic TNP state.     

Dual-Layer Oxidation-Protective Plasma-Sprayed SiC-ZrB<Subscript>2</Subscript>/Al<Subscript>2</Subscript>O<Subscript>3</Subscript>-Carbon Nanotube Coating on Graphite

Graphite is used in high-temperature gas-cooled reactors because of its outstanding irradiation performance and corrosion resistance. To restrict its high-temperature (>873 K) oxidation, atmospheric-plasma-sprayed SiC-ZrB₂-Al₂O₃-carbon nanotube (CNT) dual-layer coating was deposited on graphite substrate in this work. The effect of each layer was isolated by processing each component of the coating via spark plasma sintering followed by isothermal kinetic studies. Based on isothermal analysis and the presence of high residual thermal stress in the oxide scale, degradation appeared to be more severe in composites reinforced with CNTs. To avoid the complexity of analysis of composites, the high-temperature activation energy for oxidation was calculated for the single-phase materials only, yielding values of 11.8, 20.5, 43.5, and 4.5 kJ/mol for graphite, SiC, ZrB₂, and CNT, respectively, with increased thermal stability for ZrB₂ and SiC. These results were then used to evaluate the oxidation rate for the composites analytically. This study has broad implications for wider use of dual-layer (SiC-ZrB₂/Al₂O₃) coatings for protecting graphite crucibles even at temperatures above 1073 K.     

Effect of nanofiber on material properties of vapor-grown carbon nanofiber reinforced thermoplastic polyurethane (TPU/CNF) nanocomposites prepared by melt compounding

The present work deals with the preparation of the CNF based TPU nanocomposites by melt blending to explore the effect of state of dispersion and wt.% loading of CNF on material properties. In addition, the morphology, mechanical, thermal, rheological, and electrical properties of the nanocomposites have been evaluated through various characterization techniques with an aim to find the suitability of the nanocomposites for industrial applications. Transmission electron microscopy (TEM) study reveals that the CNFs exhibited a uniformly dispersed in TPU matrix. The thermal stability of the TPU evaluated by thermogravimetric analysis (TGA) showed significant increase with increased CNF content. It is observed that storage modulus (E′) and glass transition temperature (T_g) of the TPU matrix increases by the incorporation of CNF. The melting point (T_m) and the T_g of soft segments observed from the differential scanning calorimetry (DSC) were found to shift towards higher temperature with the inclusion of CNF.     

Efficient hydrogen evolution catalysis triggered by electrochemically anchored platinum nano-islands on functionalized-MWCNT

We report the electrochemical deposition (ECD) of platinum nano-islands (Pt NIs) on functionalized multi-walled carbon nanotubes (ECD Pt NIs@f-MWCNT) as an efficient electrocatalyst for the hydrogen evolution reaction (HER). Pristine MWCNT was acid treated to induce the number of oxygen functional groups on the surface and enhances the wettability. Thereafter, Pt nanoparticles (Pt Nps) were deposited by a simple electrodeposition technique on the oxygen enriched MWCNT surface. The Pt NIs@f-MWCNT has been physicochemically characterized using X-ray diffraction (XRD), high resolution transmission electron microscopy (HRTEM), Raman spectroscopy and X-ray photoelectron Spectroscopy (XPS). The TEM analysis showed the presence of Pt NIs on MWCNT wherein, the NIs were made up of small Pt nanoclusters of ～4 nm in dimension. The electrochemical HER studies were carried out using linear sweep voltammetry (LSV), Tafel polarization and electrochemical impedance spectroscopy (EIS). An overpotential (?) of ?84 mV was obtained at a current density (j) of ?10 mA/cm². The amount of Pt loading has been optimized through electrodeposition. Enhanced HER activity was observed with a Pt loading of 3.8 μg/cm². In order to ascertain the durability of the catalyst, accelerated degradation test (ADT) was carried out for 10,000 cycles at a scan rate (?) of 100 mV/s. The turnover frequency (TOF) was estimated to be 6.3 s^?1 at ? = ?70 mV.     

A NEW EYENET MODEL FOR DIAGNOSIS OF DIABETIC RETINOPATHY

Diabetic retinopathy (DR) is an eye disease caused by complications of diabetes and it should be detected early for effective treatment. As diabetes progresses, the vision of a patient may start to deteriorate and lead to diabetic retinopathy. Two types were identified: nonproliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR). In this study, to diagnose diabetic retinopathy, we have proposed a new EYENET model that was obtained by combining the modified probabilistic neural network (PNN) and a modified radial basis function neural network (RBFNN), and hence, it possesses the advantages of both models. The features such as blood vessels and hemorrhages of the NPDR image and exudates of the PDR image are extracted from the raw images using image-processing techniques and are fed to the classifier for classification. A total of 600 fundus images were used, out of which 400 were used for training, and 200 images were used for testing. Experimental results show that PNN has an accuracy of 96%, modified PNN has an accuracy of 97.5%, RBFNN has an accuracy of 93.5%, modified RBFNN has an accuracy of 95.5%, and the proposed EYENET model has an accuracy of 98.5%. This infers that our proposed model outperforms all other models.     

Stub Column Tests of Cold-Formed Steel Built-Up Square Sections with Intermediate Stiffeners

Strength of Materials - This paper describes the experimental and theoretical investigation on ultimate strength of cold-formed steel built-up square stub columns under axial compression. In total,...