M S Ramaiah University of Applied Sciences

We present a siamese adaptation of the Long Short-Term Memory (LSTM) network for labeled data comprised of pairs of variable-length sequences. Our model is applied to assess semantic similarity between sentences, where we exceed state of the art, outperforming carefully handcrafted features and recently proposed neural network systems of greater complexity. For these applications, we provide word-embedding vectors supplemented with synonymic information to the LSTMs, which use a fixed size vector to encode the underlying meaning expressed in a sentence (irrespective of the particular wording/syntax). By restricting subsequent operations to rely on a simple Manhattan metric, we compel the sentence representations learned by our model to form a highly structured space whose geometry reflects complex semantic relationships. Our results are the latest in a line of findings that showcase LSTMs as powerful language models capable of tasks requiring intricate understanding.

Environmental contaminants have emerged significantly due to the enormous consumption of medications, personal-care products, antibiotics, and hormones for cosmetic and health reasons. Emerging pollutants (EPs), often alluded to as contaminants, have become a massive concern for the entire populace due to their immense critical environmental and human health hazards. EPs have a broad range of environmental effects. EPs emanate from either human or animal origins, with the ability to permeate streams instantaneously or gradually through soils. Consequently, potable water sources will get tainted, water quality will degrade, and health conditions will emerge. For more than a decade, research has been conducted on various pollutants, but this developing class of contaminants mainly comprises those from the fertilizer, pharmaceutical, and personal care industries. Even in lower quantities, the majority of evolving pollutants may be harmful to people and marine life. These chemicals lack defined limits because potable water treatment facilities require water sources. The prevalence of this deterioration in aquatic environments, particularly surface and groundwater, is a severe problem. EPs treatment technologies utilize a range of methodologies, including physicochemical, biological, and modern oxidation processes, regardless of their benefits and limitations.

Candida species present both as commensals and opportunistic pathogens of the oral cavity. For decades, it has enthralled the clinicians to investigate its pathogenicity and to improvise newer therapeutic regimens based on the updated molecular research. Candida is readily isolated from the oral cavity, but simple carriage does not predictably result in development of an infection. Whether it remains as a commensal, or transmutes into a pathogen, is usually determined by pre-existing or associated variations in the host immune system. The candida infections may range from non-life threatening superficial mucocutaneous disorders to invasive disseminated disease involving multiple organs. In fact, with the increase in number of AIDS cases, there is a resurgence of less common forms of oral candida infections. The treatment after confirmation of the diagnosis should include recognizing and eliminating the underlying causes such as ill-fitting oral appliances, history of medications (antibiotics, corticosteroids, etc.), immunological and endocrine disorders, nutritional deficiency states and prolonged hospitalization. Treatment with appropriate topical antifungal agents such as amphotericin, nystatin, or miconazole usually resolves the symptoms of superficial infection. Occasionally, administration of systemic antifungal agents may be necessary in immunocompromised patients, the selection of which should be based upon history of recent azole exposure, a history of intolerance to an antifungal agent, the dominant Candida species and current susceptibility data.

Tomato (Lycopersicon esculentum) is one of the widely grown vegetables worldwide. Fusarium oxysporum f. sp. lycopersici (FOL) is the significant contributory pathogen of tomato vascular wilt. The initial symptoms of the disease appear in the lower leaves gradually, trail by wilting of the plants. It has been reported that FOL penetrates the tomato plant, colonizing and leaving the vascular tissue dark brown, and this discoloration extends to the apex, leading to the plants wilting, collapsing and dying. Therefore, it has been widely accepted that wilting caused by this fungus is the result of a combination of various physiological activities, including the accumulation of fungal mycelia in and around xylem, mycotoxin production, inactivation of host defense, and the production of tyloses; however, wilting symptoms are variable. Therefore, the selection of molecular markers may be a more effective means of screening tomato races. Several studies on the detection of FOL have been carried out and have suggested the potency of the technique for diagnosing FOL. This review focuses on biology and variability of FOL, understanding and presenting a holistic picture of the vascular wilt disease of tomato in relation to disease model, biology, virulence. We conclude that genomic and proteomic approachesare greater tools for identification of informative candidates involved in pathogenicity, which can be considered as one of the approaches in managing the disease.

Abstract: The World Conservation Union (IUCN) defined a set of categories for conservation status supported by decision rules based on thresholds of parameters such as distributional range, population size, population history, and risk of extinction. These rules have received international acceptance and have become one of the most important decision tools in conservation biology because of their wide applicability, objectivity, and simplicity of use. The input data for these rules are often estimated with considerable uncertainty due to measurement error, natural variation, and vagueness in definitions of parameters used in the rules. Currently, no specific guidelines exist for dealing with uncertainty. Interpretation of uncertain data by different assessors may lead to inconsistent classifications because attitudes toward uncertainty and risk may have an important influence on the classification of threatened species. We propose a method of dealing with uncertainty that can be applied to the current IUCN criteria without altering the rules, thresholds, or intent of these criteria. Our method propagates the uncertainty in the input parameters and assigns the evaluated species either to a single category (as the current criteria do) or to a range of plausible categories, depending on the nature and extent of uncertainties.

Additive Manufacturing (AM) technologies have been emerged as a fabrication method to obtain engineering components within a short span of time. Desktop 3D printing, also referred as additive layer manufacturing technology is one of the powerful method of rapid prototyping (RP) technique that fabricates three dimensional engineering components. In this method, 3D digital CAD data is converted directly to a product. In the present investigation, ABS + hydrous magnesium silicate composite was considered as the starting material. Mechanical properties of ABS + hydrous magnesium silicate composite material were evaluated. ASTM D638 and ASTM D760 standards were followed for carrying out tensile and flexural tests, respectively. Samples with different layer thickness and printing speed were prepared. Based on the experimental results, it is suggested that low printing speed, and low layer thickness has resulted maximum tensile and flexural strength, as compared to all the other process parameters samples.

." Attempts have been made to understand the wound at the molecular level, mainly through the analysis of signature genes and the influence of several synthetic and natural molecules on these. We have outlined a review of challenges in chronic wound healing and the role of CAMs in chronic wound management. The main focus is on the applications and limitations of currently available treatment options for a non-healing wound and the best possible alternates to consider. This information generates broader knowledge on challenges in chronic wound healing, which can be further addressed using multidisciplinary approach and combination therapies.

While urbanisation has numerous advantages, it causes greater risks to the environment and human health because of the release of heavy metals, various organic and inorganic contaminants, personal care products, and pharmaceuticals. Though several actions are being taken daily to lessen the release of harmful substances, there is still an immediate need to find a suitable solution to protect the environment. Nanotechnology has multifaceted applications, and there is extensive evidence of the emerging applications of nanoremediation, especially for soil and water pollution. Iron nanoparticles showed outstanding removal efficiency towards hexavalent chromium (100 %). Likewise, several publications on soil and water remediation employ nanomaterials based on metals, carbon, and polymers. However, most of the previously conducted works present the key nanoremediation results without depicting each nanomaterial's advantages and disadvantages. Hence, this work critically reviews the pros and cons of each nanomaterial with a special focus towards novel approaches using green synthesised nanomaterials that are completely eco-friendly and hence preferred for the removal of various contaminants without producing harmful effects. However, some bottlenecks exist in fully implementing the green nanoparticles for Nanoremediation. Thus, the review discusses the limitations of green nanomaterials that need to be addressed soon to maintain environmental sustainability. Finally, this review presents opportunities for future work in assessing the eco-safety of each nanomaterial that boosts the further utilisation of nanotechnology in the sustainable remediation of contaminated soil and water.

In recent years, interest in agro polymers has created great interest among researchers and industry alike, as these materials are found to be biodegradable and eco‐friendly. Since the fossil fuel based polymers have created greater environmental concern, these bio‐based polymers are addressing the concerns in some of impactful areas such as food packaging and contribute significantly to the sustainable development with minimum ecological problems. Among agro polymers, starch based polymers have made major stride to marketable products in food packaging field. It is estimated that by the year 2020, the biocomposite materials demand will touch 20% of total plastic utilization. This review enlightens various processing techniques used to produce starch based polymers and composites with their properties to address the poor properties of starch. Low toxic and good compatibility natural plasticizers are of great interest in the processing of thermoplastic starch (TPS). Further emphasis is also given on essential packaging film properties such as barrier, biodegradation, mechanical, and thermal properties for TPS based materials. The overview of literature indicates that, Final properties of the thermoplastic starch can be improved by using different fillers, as well as by changing the source of the starch. Since the quest to produce better, cheaper, and eco‐friendly materials never stops, a multidisciplinary approach is required to achieve further improvement in the existing materials and to produce new class of materials that are eco‐friendly which can extend smarter and efficient services to customers. POLYM. COMPOS., 39:2499–2522, 2018. © 2016 Society of Plastics Engineers

Using MATLAB examples wherever possible, Multi-Sensor Data Fusion with MATLAB explores the three levels of multi-sensor data fusion (MSDF): kinematic-level fusion, including the theory of DF; fuzzy logic and decision fusion; and pixel- and feature-level image fusion. The authors elucidate DF strategies, algorithms, and performance evaluation mainly

Globally, billions of people are experiencing food insecurity and malnutrition. The United Nations has set a global target to end hunger by 2030, but we are far from reaching it. Over the decade, climate change, population growth and economic slowdown have impacted food security. Many countries are facing the challenge of both undernutrition and over nutrition. Thus, there is a need to transform the food system to achieve food and nutrition security. One of the ways to reach closer to our goal is to provide an affordable healthy and nutritious diet to all. Millets, the nutri-cereals, have the potential to play a crucial role in the fight against food insecurity and malnutrition. Nutri-cereals are an abundant source of essential macro- and micronutrients, carbohydrates, protein, dietary fiber, lipids, and phytochemicals. The nutrient content and digestibility of millets are significantly influenced by the processing techniques. This review article highlights the nutritional characteristics and processing of Indian millets, viz. foxtail, kodo, proso, little, and pearl millets. It also envisages the effect of traditional and modern processing techniques on millet's nutritional properties. An extensive literature review was conducted using the research and review articles related to processing techniques of millets such as fermentation, germination, dehulling, extrusion, cooking, puffing, popping, malting, milling, etc. Germination and fermentation showed a positive improvement in the overall nutritional characteristics of millets, whereas excessive dehulling, polishing, and milling resulted in reduction of the dietary fiber and micronutrients. Understanding the changes happening in the nutrient value of millets due to processing can help the food industry, researchers, and consumers select a suitable processing technique to optimize the nutrient value, increase the bioavailability of nutrients, and help combat food and nutrition security.

Agriculture sector plays a key role in the economic development of India. The task of fruit grading is vital in the agricultural industry because there is a great demand for high quality fruits in the market. However, fruit grading by human is inefficient, labor intensive and prone to error. The automated grading system not only speeds up the time of processing, but also minimizes error. There is a great demand for tomatoes in both local and foreign markets. The tomato fruit is very delicate and hence careful handling of this fruit is required during grading. Thus, this paper proposes an automatic and effective tomato fruit grading system based on computer vision techniques. The proposed quality evaluation method consists of two phases: development of hardware and software. The hardware is developed to capture the image of the tomato and move the fruit to the appropriate bins without manual intervention. The software is developed using image processing techniques to analyze the fruit for defects and ripeness. Experiments were carried out on several images of the tomato fruit. It was observed that the proposed method was successful with 96.47% accuracy in evaluating the quality of the tomato.

Electric mobility has become an essential part of the future of transportation. Detection, diagnosis and prognosis of fault in electric drives are improving the reliability, of electric vehicles (EV). Permanent magnet synchronous motor (PMSM) drives are used in a large variety of applications due to their dynamic performances, higher power density and higher efficiency. In this study, health monitoring and prognosis of PMSM is developed by creating intelligent digital twin (i‐DT) in MATLAB/Simulink. An artificial neural network (ANN) and fuzzy logic are used for mapping inputs distance, time of travel of EV and outputs casing temperature, winding temperature, time to refill the bearing lubricant, percentage deterioration of magnetic flux to compute remaining useful life (RUL) of permanent magnet (PM). Health monitoring and prognosis of EV motor using i‐DT is developed with two approaches. Firstly, in‐house health monitoring and prognosis is developed to monitor the performance of the motor in‐house. Secondly, Remote Health Monitoring and Prognosis Centre (RHMPC) is developed to monitor the performance of the motor remotely using cloud communication by the service provider of the EV. The simulation results prove that the RUL of PM and time to refill the bearing lubricant obtained by i‐DT twins theoretical results.

studies to examine their effectiveness versus COVID-19.

Natural fiber polymer composites have been largely used in applications like aerospace, automotive, marine, and other civil structures, where mechanical and tribological properties are of prime consideration. The performance of hybrid composites can be improved by using different natural fibers and adding particulate fillers to them. In this study, mechanical and tribological properties of jute/sisal/E-glass fabrics reinforcing matrix such as natural rubber and epoxy filled with different proportion of tungsten carbide (WC) powder were studied. Mechanical properties like tensile strength, flexural strength, impact strength, and also tribological behavior like two-body abrasive wear of composite were studied. Taguchi technique was employed for wear analysis. Results revealed that there is a significant change in the mechanical properties and enhancement of wear behavior was noticed due to the incorporation of filler (WC) particles.

Drug repurposing is an unconventional drug discovery approach to explore new therapeutic benefits of existing, shelved and the drugs in clinical trials. This approach is currently emerging to overcome the bottleneck constraints faced during traditional drug discovery in grounds of financial support, timeline and resources. In this direction, several efforts were made for the construction of stratagems based on bioinformatics and computational tools to intensify the repurposing process off-late. Further, advanced research has succeeded in widening its boundaries in identification of gene targets and subsequent molecular interactions of the drugs depending on available omics data. Currently, the advent of data repositories like Connectivity Map (CMap), Library Integrated Network based Cellular Signatures (LINCS), Genome Wide Association Studies (GWAS), Side Effect Resource (SIDER), and Directionality Map (DMAP) has bestowed great oppurtunity to the researchers in improving their drug repurposing research exponentially. On the otherhand, in silico approaches like pharmacophore modelling and docking techniques circumvent the routine tedious in vitro and in vivo techniques involved in former screening phases of the drugs and disease specific targets. This review elaborates on currently designed contemporary tools, databases and strategies with relevant case studies.

Effluent water from dyeing industries has now for long been a taxing issue. Of the various dyes which are extremely toxic, Crystal Violet which is used in the dyeing industry is known for its mutagenic and mitotic poisoning nature. Water hyacinth (Eichhornia crassipes) is a perennial aquatic plant notorious for its rapid invasive growth on the surface of water bodies causing ill-effects on the biodiversity. The potential of powdered roots of water hyacinth was studied for decolorization of Crystal Violet dye. Influence of parameters such as initial pH (2.0-10.0), initial dye concentration (100-500 ppm), biosorbent dosage (0.5-5 g/l), contact time (10-240 min) and temperature (300-323 K) were examined. Maximum removal of dye was observed at pH 7.8. The obtained data were fit into different kinetic models and the biosorption was found to follow pseudo second order kinetic model. The Langmuir monolayer biosorption capacity of water hyacinth was estimated as 322.58 mg/g. The study has demonstrated water hyacinth as a potential low cost biosorbent for effective removal of Crystal Violet dye from aqueous solution.

Enhanced use of heavy metals for commercial and non-commercial applications has resulted in industrial and domestic discharge loaded with toxic metal ions creating increased environmental concern. Owing to the wide array of heavy metals that can be effectively removed, relatively low cost and economical process conditions, removal of heavy metals by adsorption has attracted the scientific community over years. Search for novel adsorbents which are cost-effective with higher adsorption affinity and reusability has been an area of active research. Carbon based adsorbents, which offer enhanced surface area, higher surface to volume ratio and ease of surface functionalization, have proven to be more effective than conventional adsorbents for removal of both inorganic and organic contaminants. Among the various carbon based adsorbents, carbon nanotubes, graphene and modified graphene oxide composites are gaining increasing importance as effective adsorbents for heavy metal removal from waste waters. This paper presents a comprehensive review on use of these adsorbents for adsorptive removal of various heavy metals. Optimal conditions for maximum removal of various metal ions are highlighted. Case studies on approach to surface functionalization of adsorbents and the mechanism of metal ion removal by the functionalized surface are discussed for practical application.

Nitrate contamination of ground water resources has increased in Asia, Europe, United States, and various other parts of the world. This trend has raised concern as nitrates cause methemoglobinemia and cancer. Several treatment processes can remove nitrates from water with varying degrees of efficiency, cost, and ease of operation. Available technical data, experience, and economics indicate that biological denitrification is more acceptable for nitrate removal than reverse osmosis and ion exchange. This paper reviews the developments in the field of nitrate removal processes which can be effectively used for denitrifying ground water as well as industrial water.

Red light emitting cubic Y1.95Eu0.05O3 nanophosphors have been synthesized by a low temperature solution combustion method using ethylene diamine tetra acetic acid (EDTA) as fuel. The systematic studies on the effect of calcination temperature on its structural, photoluminescence (PL), and thermoluminescence (TL) properties were reported. The crystallinity of the samples increases, and the strain is reduced with increasing calcination temperature. SEM micrographs reveal that samples lose their porous nature with an increase in calcination temperature. PL spectra show that the intensity of the red emission (611 nm) is highly dependent on the calcination temperature and is found to be 10 times higher when compared to as-formed samples. The optical band gap (Eg) was found to reduce with an increase of calcination temperature due to reduction of surface defects. The thermoluminescence (TL) intensity was found to be much enhanced in the 1000 °C calcined sample. The increase of PL and TL intensity with calcination temperature is attributed to the decrease of the nonradiative recombination probability, which occurs through the elimination of quenching defects. The trap parameters (E, b, s) were estimated from Chen’s glow peak shape method and are discussed in detail for their possible usage in dosimetry.