Institute of Engineering

Injection molding industry has evolved over decades and became the most common method to manufacture plastic parts. Monitoring and improvement in the injection molding industry are usually performed separately in each stage, i.e. mold design, mold making and injection molding process. However, in order to make a breakthrough and survive in the industrial revolution, all the stages in injection molding need to be linked and communicated witheachother.Anychangesinonestagewillcauseacertaineffectinotherstagebecausethere is a correlation between each other. Hence, the simulation should not only based on the input of historical data, but it also needs to include the current condition of equipment and prediction of future events in other stages to make the responsive decision. This can be achieved by implementing the concept of Digital Twin that models the entire process as a virtual model and enables bidirectional control with the physical process. This paper presented types of data and technology required to build the Digital Twin for the injection molding industry. The concept includes Digital Twin of each stage and integration of these Digital Twin model as a thoroughgoing model of the injection molding industry.

This perspective provides information on durability challenges and future actions of anion exchange membrane fuel cells.

Himalayan rivers are frequently hit by catastrophic floods that are caused by the failure of glacial lake and landslide dams; however, the dynamics and long-term impacts of such floods remain poorly understood. We present a comprehensive set of observations that capture the July 2016 glacial lake outburst flood (GLOF) in the Bhotekoshi/Sunkoshi River of Nepal. Seismic records of the flood provide new insights into GLOF mechanics and their ability to mobilize large boulders that otherwise prevent channel erosion. Because of this boulder mobilization, GLOF impacts far exceed those of the annual summer monsoon, and GLOFs may dominate fluvial erosion and channel-hillslope coupling many tens of kilometers downstream of glaciated areas. Long-term valley evolution in these regions may therefore be driven by GLOF frequency and magnitude, rather than by precipitation.

Abstract Nano-priming is an innovative seed priming technology that helps to improve seed germination, seed growth, and yield by providing resistance to various stresses in plants. Nano-priming is a considerably more effective method compared to all other seed priming methods. The salient features of nanoparticles (NPs) in seed priming are to develop electron exchange and enhanced surface reaction capabilities associated with various components of plant cells and tissues. Nano-priming induces the formation of nanopores in shoot and helps in the uptake of water absorption, activates reactive oxygen species (ROS)/antioxidant mechanisms in seeds, and forms hydroxyl radicals to loosen the walls of the cells and acts as an inducer for rapid hydrolysis of starch. It also induces the expression of aquaporin genes that are involved in the intake of water and also mediates H 2 O 2, or ROS, dispersed over biological membranes. Nano-priming induces starch degradation via the stimulation of amylase, which results in the stimulation of seed germination. Nano-priming induces a mild ROS that acts as a primary signaling cue for various signaling cascade events that participate in secondary metabolite production and stress tolerance. This review provides details on the possible mechanisms by which nano-priming induces breaking seed dormancy, promotion of seed germination, and their impact on primary and secondary metabolite production. In addition, the use of nano-based fertilizer and pesticides as effective materials in nano-priming and plant growth development were also discussed, considering their recent status and future perspectives. Graphical Abstract

Tailoring of chitosan through the involvement of its amino, acetamido, and hydroxy groups can give derivatives of enhanced solubility and remarkable anticancer activity. The general mechanism of such activity is associated with the disturbances in normal functioning of cell cycle, interference to the central dogma of biological system from DNA to RNA to protein or enzymatic synthesis, and the disruption of hormonal path to biosynthesis to inhibit the growth of cancer cells. Both chitosan and its various derivatives have been reported to selectively permeate through the cancer cell membranes and show anticancer activity through the cellular enzymatic, antiangiogenic, immunoenhancing, antioxidant defense mechanism, and apoptotic pathways. They get sequestered from noncancer cells and provide their enhanced bioavailability in cancer cells in a sustained release manner. This review presents the putative mechanisms of anticancer activity of chitosan and mechanistic approaches of structure activity relation upon the modification of chitosan through functionalization, complex formation, and graft copolymerization to give different derivatives.

Synthetic matrices emulating the physicochemical properties of tissue-specific ECMs are being developed at a rapid pace to regulate stem cell fate. Biomaterials containing calcium phosphate (CaP) moieties have been shown to support osteogenic differentiation of stem and progenitor cells and bone tissue formation. By using a mineralized synthetic matrix mimicking a CaP-rich bone microenvironment, we examine a molecular mechanism through which CaP minerals induce osteogenesis of human mesenchymal stem cells with an emphasis on phosphate metabolism. Our studies show that extracellular phosphate uptake through solute carrier family 20 (phosphate transporter), member 1 (SLC20a1) supports osteogenic differentiation of human mesenchymal stem cells via adenosine, an ATP metabolite, which acts as an autocrine/paracrine signaling molecule through A2b adenosine receptor. Perturbation of SLC20a1 abrogates osteogenic differentiation by decreasing intramitochondrial phosphate and ATP synthesis. Collectively, this study offers the demonstration of a previously unknown mechanism for the beneficial role of CaP biomaterials in bone repair and the role of phosphate ions in bone physiology and regeneration. These findings also begin to shed light on the role of ATP metabolism in bone homeostasis, which may be exploited to treat bone metabolic diseases.

Gold nanoparticles (GNPs) have generated keen interest among researchers in recent years due to their excellent physicochemical properties. In general, GNPs are biocompatible, amenable to desired functionalization, non-corroding, and exhibit size and shape dependent optical and electronic properties. These excellent properties of GNPs exhibit their tremendous potential for use in diverse biomedical applications. Herein, we have evaluated the recent advancements of GNPs to highlight their exceptional potential in the biomedical field. Special focus has been given to emerging biomedical applications including bio-imaging, site specific drug/gene delivery, nano-sensing, diagnostics, photon induced therapeutics, and theranostics. We have also elaborated on the basics, presented a historical preview, and discussed the synthesis strategies, functionalization methods, stabilization techniques, and key properties of GNPs. Lastly, we have concluded this article with key findings and unaddressed challenges. Overall, this review is a complete package to understand the importance and achievements of GNPs in the biomedical field.

Fractional Calculus (FC) goes back to the beginning of the theory of differential calculus. Nevertheless, the application of FC just emerged in the last two decades, due to the progress in the area of chaos that revealed subtle relationships with the FC concepts. In the field of dynamical systems theory some work has been carried out but the proposed models and algorithms are still in a preliminary stage of establishment. Having these ideas in mind, the paper discusses FC in the study of system dynamics and control. In this perspective, this paper investigates the use of FC in the fields of controller tuning, legged robots, redundant robots, heat diffusion, and digital circuit synthesis.

Alkaline anion exchange membrane fuel cells (AAEMFC) are attracting ever-increasing attention, as they are promising electrochemical devices for energy production, presenting a viable opponent to proton exchange membrane fuel cells (PEMFCs).

Innovative approach for producing GDLs of PEM electrolyzers enabling a significant reduction in the manufacturing cost and facilitating higher performance than from the state of the art.

In the present paper, double perovskite Ba₂InTaO₆ was investigated in terms of its structural, electronic, optical, elastic, mechanical, thermodynamic and thermoelectric properties using density-functional theory (DFT).

Stock price prediction has always attracted interest because of the direct financial benefit and the associated complexity. From our literature review, we felt the need of a study having sector specific analysis with a broad range of stocks. In this paper, we have conducted a study on the effectiveness of Autoregressive Integrated Moving Average (ARIMA)model, on fifty six Indian stocks from different sectors. We have chosen ARIMA model, because of its simplicity and wide acceptability of the model. We also have studied the effect on prediction accuracy based on various possible previous period data taken. The comparison and parameterization of the ARIMA model have been done using Akaike information criterion (AIC). The contribution of the paper , are a) coverage of a good number of Indian stocks b) Analysis of the models based on sectors c) Analysis of prediction accuracy based on the varying span of previous period data.

Extraction of complex head and hand movements along with their constantly changing shapes for recognition of sign language is considered a difficult problem in computer vision. This paper proposes the recognition of Indian sign language gestures using a powerful artificial intelligence tool, convolutional neural networks (CNN). Selfie mode continuous sign language video is the capture method used in this work, where a hearing-impaired person can operate the SLR mobile application independently. Due to non-availability of datasets on mobile selfie sign language, we initiated to create the dataset with five different subjects performing 200 signs in 5 different viewing angles under various background environments. Each sign occupied for 60 frames or images in a video. CNN training is performed with 3 different sample sizes, each consisting of multiple sets of subjects and viewing angles. The remaining 2 samples are used for testing the trained CNN. Different CNN architectures were designed and tested with our selfie sign language data to obtain better accuracy in recognition. We achieved 92.88% recognition rate compared to other classifier models reported on the same dataset.

Polymer membranes imbibed with KOH represent a novel way to achieve ionic conductivity and show promise for alkaline electrolyzers.

The improved energy band alignment of Pt/TiO₂/Ga₂O₃/Cu₂O structure results in a positive onset potential of ∼1 V<italic>vs.</italic>RHE and a stable cathodic photocurrent under appropriate TiO₂deposition temperature.

Peanut shells were transformed into porous carbon with a high surface area through a simple ZnCl₂-molten salt synthesis process.

Determining both cation and oxygen sublattices of grain boundaries is essential to understand the properties of oxides. Here, with scanning transmission electron microscopy, electron energy-loss spectroscopy, and first-principles calculations, both the Ce and oxygen sublattices of a (210)Σ5 CeO(2) grain boundary were determined. Oxygen vacancies are shown to play a crucial role in the stable grain boundary structure. This finding paves the way for a comprehensive understanding of grain boundaries through the atomic scale determination of atom and defect locations.

Environmentally beneficial composites can be made by replacing synthetic fibers with various types of cellulosic fibers. Fibers from pine wood, coir, sisal, abaca, coir, etc. are all good candidates. The most important factor in finding good fiber reinforcement in the composites is the strength of adhesion between matrix polymer and fiber. Due to the presence of hydroxyl groups and other polar groups in various constituents of abaca, the moisture absorption is high, which leads to poor wettability and weak interfacial bonding between fibers and the more hydrophobic matrices. Therefore, it is necessary to impart a hydrophobic nature to the fibers by suitable chemical treatments in order to develop composites with better mechanical properties. In the present work, the effect of alkali treatment on the moisture absorption tendency of single abaca fiber was investigated. The results shown that the alkali treated fiber absorbs less moisture than the untreated raw fiber.

This work reviews the operating principles of ICP-tandem mass spectrometry (ICP-MS/MS) and the key applications reported on since the introduction of the technique in 2012.

Purpose The purpose of this paper is to propose an integrated supply chain performance measurement framework for the case of small and medium scale enterprises (SMEs) using set of qualitative and quantitative insights gained during the case study research. Design/methodology/approach This paper develops the supply chain performance measurement framework using the facts revealed through case study analysis, secondary data specific to various SME clusters in India and detailed contemporary studies reported on supply chain management in SMEs. It integrates the salient features of balanced scorecard (BSC) and supply chain operation reference (SCOR) model to deliver a comprehensive performance measurement framework for SMEs. Findings This paper reports set of performance indicators for the supply chain processes like “source,” “make,” and “deliver” in SMEs. It also relates the measures with various supply chain cycles like “procurement,” “manufacturing,” “replenishment,” and “customer order.” As a result, paper delivers an integrated performance measurement framework for supply chain evaluation and planning in SMEs. It also outlines the detailed guideline for the implementation and use of the framework. Practical implications This paper is expected that the developed framework: will help SME managers to improve the visibility of their supply chain amongst interacting partners; and will help SME firms to explain the basis of their decisions to the other supply chain partners and specifically, origingal equipment manufacturer organizations where less bargaining power exist. Originality/value This paper integrates the spirit of two well‐known contributions in the field of performance measurement namely BSC and SCOR. The proposed framework is deduced using the findings of real life case study research and hence establishes an adequate platform for its application. It would help the managers or decision makers in SMEs to gain a systematic insight into their supply chain problems and hence undertake the necessary improvements.