An experimental investigation on mechanical and tribological properties of Himalayan nettle fiber composite

The main focus of the present research work was to explore mechanical and tribological properties of Himalayan nettle fiber and unsaturated polyester resin (GP) using hand lay-up method. Four composite laminates were prepared by adding the Himalayan nettle fibers by weight percentage (5%–20%). The various properties (e.g., tensile strength, hardness, impact strength, and abrasion wear) were calculated for the composite laminates. It was found that the significant variation in properties was observed when fiber addition was in the range 15%. The change in the properties was negligible when fiber addition was increased from 15% by weight.     

Electrical Conductivity of Silver Vanadium Tellurite Glasses

We have investigated mixed electronic-ionic conduction in 0.5[ x Ag₂O·(1 − x )V₂O₅]–0.5TeO₂ glasses, where the Ag₂O amount varies over a range of 5–40 mol%. The glass samples have been prepared by quenching the melt. The ac conductivity has been measured at frequencies from 10 Hz to 100 kHz and temperatures of 300–425 K. The data indicate that the conduction mechanism changed from being predominantly electronic to ionic for Ag₂O contents of >27.5 mol%. This transition is due to the change in glass structure, which affects both electronic- and ionic-transport properties. The electronic dc conductivity results have been analyzed in terms of a small polaron-hopping model.     

Examining the best-fit paradigm for FEM at element level

Interestingly, an esoteric branch of pure mathematics called “functional analysis”, more general and profound than variational calculus and originally developed by mathematicians, can be employed to explain clearly how the finite element machinery works. In a very abstract way, finite element results can be portrayed as “shadows” or orthogonal projections on predetermined function subspaces of the analytical results, known or unknown. Herein lies the philosophy of the finite element method. In the present work, an effort has been made to validate this important aspect of the finite element method at the element level through a particular differential equation representing a specific case of equilibrium     

Experimental comparison of solar drying based on evacuated tube collector with desiccant drying for dehydrating potato and ginger

In this article, a comparative study of different drying techniques, namely, open sun drying (OSD), desiccant drying, solar drying (SD), and solar drying with desiccant (SDWD) was done for drying potato and ginger. The thermal efficiency and air temperature differences of the solar dryer based on evacuated tube collectors were also examined. The average efficiency of the solar dryer was 29.01%. Average drying rates of OSD, desiccant drying, SD, and SDWD bed are 0.435, 0.435, 0.59, and 0.635 g/min. The moisture content of the potato was reduced from 79.6% to 32.9% by OSD, 32.6% by desiccant drying, 9.6% by SD, and 6.9% by SDWD. The moisture content of the ginger was reduced from its initial value of 82.3%–25.3% by OSD, 25% by desiccant drying, 10.1% by SD, and 3.2% by SDWD. SD assisted with a desiccant bed proved to be the best method for drying vegetables. Drying with desiccants is not feasible for drying in winter and spring seasons of the Indian climate.     

Enhancing visual question answering with a two-way co-attention mechanism and integrated multimodal features

In Visual question answering (VQA), a natural language answer is generated for a given image and a question related to that image. There is a significant growth in the VQA task by applying an efficient attention mechanism. However, current VQA models use region features or object features that are not adequate to improve the accuracy of generated answers. To deal with this issue, we have used a Two-way Co-Attention Mechanism (TCAM), which is capable enough to fuse different visual features (region, object, and concept) from diverse perspectives. These diverse features lead to different sets of answers, and also, there is an inherent relationship between these visual features. We have developed a powerful attention mechanism that uses these two critical aspects by using both bottom-up and top-down TCAM to extract discriminative feature information. We have proposed a Collective Feature Integration Module (CFIM) to combine multimodal attention features and thus capture the valuable information from these visual features by employing a TCAM. Further, we have formulated a Vertical CFIM for fusing the features belonging to the same class and a Horizontal CFIM for combining the features belonging to different types, thus balancing the influence of top-down and bottom-up co-attention. The experiments are conducted on two significant datasets, VQA 1.0 and VQA 2.0. On VQA 1.0, the overall accuracy of our proposed method is 71.23 on the test-dev set and 71.94 on the test-std set. On VQA 2.0, the overall accuracy of our proposed method is 75.89 on the test-dev set and 76.32 on the test-std set. The above overall accuracy clearly reflecting the superiority of our proposed TCAM based approach over the existing methods.     

Role of particle size in visible light photocatalysis of Congo Red using TiO<Subscript>2</Subscript>·[ZnFe<Subscript>2</Subscript>O<Subscript>4</Subscript>]<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript> nanocomposites

TiO₂·[ZnFe₂O₄] _x (x = 0·0-0·5) nanocomposites (NCs) with an average particle size of 72·4 nm were synthesized by the method of co-precipitation/hydrolysis (CPH). For the comparison of particle-size dependent effects, a set of polycrystalline samples with similar compositions was also prepared by solid state reaction (SSR) route. Average particle size for SSR prepared samples was about 3·0 μm. All the samples were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), particle size analyzer, Raman spectroscopy and Fourier transform infra-red (FTIR) spectroscopy. Their visible light photocatalytic activity was tested for the degradation of Congo Red dye. Maximum photodegradation was observed for the NC with x = 0·1 synthesized by CPH (particle size, 71 nm). Similar composition prepared by SSR method (particle size, 6·19 μm) showed lower photoactivity in comparison even with that observed for pure TiO₂ (particle size, 4·03 μm). It was, therefore, concluded that enhanced photodegradation is directly related to the reduced particle size of the composites, which implies that photosensitization is the process primarily involved. Although, doping of TiO₂ with ZnFe₂O₄ does extend the cut-off wavelength towards visible parts of the spectrum, its contribution in the enhancement is not as significant as that due to the photosensitization.     

Phase Separation and Structural Differences between Alkali Silicate Glasses Prepared by the Sol-Gel and Melt-Quench Methods

Glasses of composition x M₂O:(1- x )SiO₂ [M = Na, Li] with x = 0.15 and 0.2 have been prepared both by the melt-quench and the sol-gel methods. X-ray photoelectron spectroscopy shows that with increasing sintering temperature the structure of gels approaches that of the melt-quench glass but does not become identical even on heating above the glass transition temperature ( T _g). Phase separation occurs in gel much below T _g, and before it evolves into the structure of melt-quench glass. Thus phase separation is achieved more readily in sintered gels than in the corresponding melt-quench glass.     

Application of multiple‐response optimization methods for the ergonomic evaluation of carpet weaving knife

The aim of this study is to evaluate several weaving knife configurations in response to multiple criteria’s for optimum design. Nine different knife combinations were tested over ten female weavers in a field experiment. Three levels of blade width and angular orientations were taken as the independent variables. Output response about goniometry and electromyography were taken as dependent variables. Multivariate analysis was carried out to estimate the effect of independent variables on output responses. To tackle the difficulty of knife selection with several output responses, three multicriteria optimization approaches have been compared. Multivariate analysis of variance results showed that the effect of both blade width and angle were significant at wrist angles. Also, the magnitude of effect size on both blade width and the angle was highest for the wrist angles. Despite the same weighing criteria, a slight difference was evident between the ranks from optimization methods. The higher blade widths and smaller angular orientations should be recommended for reduction of wrist deviation and muscle activity during weaving. The best possible combination of knife evaluated using multicriteria optimization was 25 mm × 100°.     

Mathematical approach to compute the molecular composition of hydrothermal liquefaction-derived renewable crude oil

Hydrothermal liquefaction (HTL), a thermo-chemical conversion process, uses water as a reaction medium at elevated pressure and temperature, to convert biomass to renewable liquid fuel and recovers fertilizer-rich water. To assess the techno-economic screening of HTL oils from various feedstock, it is crucial to have information on molecular composition of the feed and products. There are limitations of existing analytical methods to identify and quantify all the molecules present in the bio-fuel. Therefore, there is a need to find alternate ways to quantify the molecular composition of feed and expected products. The modeling work on bio-oil is developed and validated on mathematical approach using simple analytical results like CHNO along with structural analysis of oil like Fourier-transform infrared, nuclear magnetic resonance analysis for HTL derived oil from microalgae. This mathematical framework is further extended to predict the molecular composition of oil obtained from HTL of feedstocks like mixed plastic waste, sludge, and so on. A multi-dimensional molecular matrix is developed based on the distributions of side chains, aromatic rings, and olefinic carbon on top of core molecules. The parameters of the distributions are estimated computationally using global optimization algorithm (genetic algorithm) and local optimization algorithm to predict a mixture composition that matches closely with bulk properties of the product.     

Understanding the Blockchain technology adoption in supply chains-Indian context

Blockchain technology (BT) is expected to bring a revolutionary paradigm shift in the manner the transactions are carried in the supply chains. BT provides better visibility and transparency by removing the disadvantages of trust related issues in a supply chain. In this paper, we advance the literature on BT and its adoption in the supply chain by developing, and statistically validating a model for understanding the user perceptions on BT adoption. The model is based on the integration of three adoption theories- technology acceptance model (TAM), technology readiness index (TRI) and the theory of planned behaviour (TPB). Based on a survey of 181 supply chain practitioners in India the proposed model was tested using structural equation modelling. The study found that the TRI constructs- Insecurity and discomfort have an insignificant effect on the perceived ease of use and usefulness. Perceived usefulness, attitude, and perceived behavioural control affect the behavioural intention. Subjective norm has a negligible impact on behavioural intention. This is one of the preliminary studies on BT adoption in supply chain and the findings imply that the supply chain practitioners perceive BT adoption free of efforts and would help them to derive maximum benefits for improving the supply chain effectiveness.