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Identification of human activity considering social interactions and group dynamics non-intrusively has been one of the fundamental problems and a challenging area of research. In real life, it is required for designing human-centric applications like assisted living, health care, and creating a smart home environment. As human beings spend 90% of time indoors, such a system will be helpful to monitor the behavioral anomalies of the inhabitants. Existing approaches have used intrusive or invasive methods like camera or wearable devices. In this work, we present a device-free, non-invasive, and non-intrusive sensing framework called HumanSense using an array of heterogeneous sensor grid for human activity monitoring. The sensor grids, comprising the ultrasonic and sound sensors, have been deployed for collective sensing combining a person's physical activity and verbal interaction information. The proposed system senses a stream of events when the occupant(s) perform different physical activities categorized as atomic and group activities like sitting, standing, and walking. Simultaneously, it also tracks person-person verbal interactions such as monologue and discussion. Both information are then integrated into a single framework to understand the overall behavioral scenario of the indoor environment. The experimental results have shown that HumanSense can detect different activities with accuracy more than 90% and also improves overall identification accuracy compared to existing works. Our developed system can be further evolved into ready-to-deploy smart sensing panels which can be effective for human activity monitoring in an indoor environment. [ABSTRACT FROM AUTHOR]

Background: The tea plant, Camellia sinensis (L.) O. Kuntze, is an evergreen leafy plant whose tender leaves are used in the manufacturing of the world's second most consumed beverage—tea. The production and consumption of tea worldwide have continually increased over the decades. All parts of the plant—leaf, stem, root, flower and seed, are fed upon by insect pests. This study elucidates the metabolomic changes occurring in tea leaves in response to infestation by two major pests in tea gardens: red spider mites and tea mosquito bugs. These pests significantly impact both the quantity and quality of tea production. The secondary metabolites produced by the tea due to pest attack has been analysed using GC–MS analysis in the laboratory. Results: Mostly fatty acid derivatives were biosynthesized as secondary metabolites due to pest attack as revealed from the result. In both infestations, methyl stearate was found to be produced along with increased chromatographic peaks of compounds such as caffeine, methyl palmitate, methyl linoleate, and stigmasta-7,25-dien-3-ol. In comparison with respective control samples (leaf with no pest attack), the one attacked by red spider mite showed eighteen exclusive metabolites, whereas tea mosquito bug infested leaf showed six such exclusive metabolites. Conclusions: Some metabolites were found to be either increased or decreased in their amount in both the samples. The increased compounds were reported with insecticidal and pesticidal properties with respect to respective controls. Some metabolites were markers of pest attacks i.e. plant defense mechanism induced phytochemicals according to the literature as discussed in this research. [ABSTRACT FROM AUTHOR]

The actual Fig. 13 has been missing and in place of Fig. 13, Fig. 14 has been shown. [ABSTRACT FROM AUTHOR]

Pure and Cu-doped zinc oxide (ZnO) nanoparticles were prepared using a chemical method. The dopant concentration (Cu/Zn in atomic percentage (wt%)) is varied from 0 to 3 wt%. Structural characterization of the samples performed using X-ray diffraction (XRD) confirmed that all the nanoparticles of zinc oxide are having polycrystalline nature. Morphological studies were conducted using field emission scanning electron microscopy (FESEM) to confirm the grain size and texture. Electrical measurements showed that the AC conductivity initially decreases and then rises with increasing Cu concentration. The UV-Vis studies showed absorbance peaks in the 200-800 nm region. It is found that the absorbance does not significantly change with doping. This fact is further confirmed from the band-gap calculations using the reflectance graphs. When analysed in terms of Burstein-Moss shift, an increase of band gap from 3.42 to 3.54 eV with increasing Cu concentration is observed. In the Photoluminescence (PL) studies a red-shift is observed with increasing dopant concentration. [ABSTRACT FROM AUTHOR]

The article presents authors' comments on the increasing investments in the field of research in nanotechnology in India and offers suggestions for country's rapid economic growth. Topics include investments in sectors such as education, infrastructure and entrepreneurship, nanotechnology funding by several Indian government bodies such as the Department of Information Technology, and insufficient human resources in the field of nantechnology in India.

Embedding magnetic moments into semiconductor heterostructures offers a tuneable access to various forms of magnetic ordering and phase transitions in low-dimensional electron systems. In general, the moments are introduced artificially, by either doping with ferromagnetic atoms, or electrostatically confining odd-electron quantum dots. Here, we report experimental evidence of an independent, and intrinsic, source of localized spins in high-mobility GaAs/AlGaAs heterostructures with large setback distance (≈80 nm) in modulation doping. Measurements reveal a quasi-regular distribution of the spins in the delocalized Fermi sea, and a mutual interaction via the Ruderman–Kittel–Kasuya–Yosida (RKKY) indirect exchange below 100 mK. We show that a simple model on the basis of the fluctuations in background potential on the host two-dimensional electron system can explain the observed results quantitatively, which suggests a ‘disorder-templated’ microscopic origin of the localized moments. [ABSTRACT FROM AUTHOR]

Background: Metabolomics of Camellia japonica leaf has been studied to identify the terpenoids present in it and their interrelations regarding biosynthesis as most of their pathways are closely situated. Camellia japonica is famous for its anti-inflammatory activity in the field of medicines and ethno-botany. In this research, we intended to study the metabolomics of Camellia japonica leaf by using gas chromatography-mass spectroscopy technique. Results: A total of twenty-nine anti-inflammatory compounds, occupying 83.96% of total area, came out in the result. Most of the metabolites are terpenoids leading with triterpenoids like squalene, lupeol, and vitamin E. In this study, the candidate molecules responsible for anti-inflammatory activity were spotted out in the leaf extract and biosynthetic relation or interactions between those components were also established. Conclusion: Finding novel anticancer and anti-inflammatory medicinal compounds like lupeol in a large amount in Camellia japonica leaf is the most remarkable outcome of this gas chromatography-mass spectroscopy analysis. Developing probable pathway for biosynthesis of methyl commate B is also noteworthy. [ABSTRACT FROM AUTHOR]

Consideration of carbon policies while optimizing supply chain operations has become imperative as governments and regulatory bodies throughout the world have implemented different carbon policies to reduce emissions of greenhouse gasses, especially CO2. “Carbon tax” is one of the major carbon policies, initiated by several governments to curtail emissions. In this study, we have considered this policy to optimize the total expected cost (TEC) of a two-echelon integrated supply chain with stochastic demand, where both backorders and lost sales are permitted. An unconstrained mixed integer non-linear programming (MINLP) problem is formulated and further solved to find the optimal production rate, order quantity, number of shipments and reorder point while minimizing the TEC. Emissions from all the major sources such as production, inventory and transportation have been taken into consideration. It is assumed that the emission from production is a function of production rate, and emission from transportation depends on payload and vehicle type. This study will help organizations to reduce cost and emissions, and regulatory bodies to decide proper tax rate on carbon emission. [ABSTRACT FROM AUTHOR]

Background: The Himalaya hotspot, habitat to numerous indigenous species, harbours an endemic and endangered, cucurbit climber Herpetospermum darjeelingense (C.B.Clarke) H.Schaef. & S.S.Renner [Edgaria darjeelingensis C.B.Clarke]. Seeds of this plant have traditionally been used for ethno-veterinary treatment. The present probe aims to provide an insight into the antioxidant-related biochemical attributes of this phytochemically unexplored plant. Results: DPPH scavenging activity of solvent extracts showed more potential towards the polar end with its maximum activity in methanolic extract (84.64%). Acetone extract showed more ferric reducing power than the ethanol fractions. Maximum flavonoid quantification was recorded in ethanol extract. GC–MS of methanolic extract detected 39 compounds of which 22 have preventive and curing properties for several ailments. Thirteen compounds were reported with antioxidant activity and cover an area of 63.92% among the total detected compounds by GC–MS. 1,3,4,5-Tetrahydroxy-cyclohexanecarboxylic acid; Hexadecanoic acid, methyl ester; ß sitosterol and Phytol are present in significant quantity and are the prime candidates conferring antioxidant potential. Chromatographically fractionalized methanol extract with non-polar to polar solvents and their subsequent DPPH scavenging analysis exhibited a major peak in ethanol fraction due to the presence of Phytol in considerable high quantity and some other compounds. Further sub-fractionation of ethanolic fraction provides a supportive evidence of ethanol solubility of the compounds. Biosynthetic lineage reveals fatty acid synthesis, intermediates of Shikimate pathway and terpenoid metabologenesis schemes lead to the several antioxidant molecules detected in our extract. Conclusion: Metabolomics of antioxidants will provide a better understanding in its intracellular free radical quenching activity and isolation of these bioactive compounds can boost pharmaceutical industry. [ABSTRACT FROM AUTHOR]

Anastomotic leak (AL) is a major morbid complication after colorectal surgery. There are only few articles to find the predictors of leak after colorectal anastomoses that have been published in the literature. The aim of this study is to identify different predictors for colorectal AL in Indian set up. Historical data were collected from the hospital record of patients from June 2005 to April 2014. In prospective period, from May 2014 to February 2016, colorectal surgery patients were recruited to collect the data. Various preoperative, intraoperative, and postoperative factors for AL were analyzed using Student's t test and Chi square test. The p value less than 0.05 was considered statistically significant for all results. The AL rate was 9.1%. The predictors for AL were comorbidities like cerebrovascular accident (CVA) (p < 0.05), alcohol intake and smoking habit (p = 0.006), preoperative low albumin (AL in 21.2%), emergency surgery (AL in 25% with p = 0.016), jejuno-colic anastomosis − 1/1 (100%), and maximum AL in ligation of ileocolic artery (p = 0.019). History of CVA, smoking, alcohol, hypoalbuminemia, emergency surgery, type of surgery, and high artery ligation have significant role in causing AL in a patient of colorectal surgery. Raised temperature and tachycardia are the significant clinical signs to diagnose AL after colorectal surgery. [ABSTRACT FROM AUTHOR]

Present study deals with molecular expression patterns responsible for post-harvest shelf-life extension of mulberry leaves. Quantitative profiling showed retention of primary metabolite and accumulation of stress markers in NS7 and CO7 respectively. The leaf mRNA profiles was sequenced using the Illumina platform to identify DEGs. A total of 3413 DEGs were identified between the treatments. Annotation with Arabidopsis database has identified 1022 DEGs unigenes. STRING generated protein–protein interaction, identified 1013 DEGs nodes with p < 1.0e−16. KEGG classifier has identified genes and their participating biological processes. MCODE and BiNGO detected sub-networking and ontological enrichment, respectively at p ≤ 0.05. Genes associated with chloroplast architecture, photosynthesis, detoxifying ROS and RCS, and innate-immune response were significantly up-regulated, responsible for extending shelf-life in NS7. Loss of storage sucrose, enhanced activity of senescence-related hormones, accumulation of xenobiotics, and development of osmotic stress inside tissue system was the probable reason for tissue deterioration in CO7. qPCR validation of DEGs was in good agreement with RNA sequencing results, indicating the reliability of the sequencing platform. Present outcome provides a molecular insight regarding involvement of genes in self-life extension, which might help the sericulture industry to overcome their pre-existing problems related to landless farmers and larval feeding during monsoon. [ABSTRACT FROM AUTHOR]

Mediterranean diet (MD) can play a major role in decreasing the risks of non-communicable diseases and preventing overweight and obesity. In order for a person to follow the MD and assess their adherence to it, proper dietary assessment methods are required. We have developed an Artificial Intelligence-powered system that recognizes the food and drink items from a single meal photo and estimates their respective serving size, and integrated it into a smartphone application that automatically calculates MD adherence score and outputs a weekly feedback report. We compared the MD adherence score of four users as calculated by the system versus an expert dietitian, and the mean difference was 3.5% and statistically not significant. Afterwards, we conducted a feasibility study with 24 participants, to evaluate the system's performance and to gather the users' and dietitians' feedback. The image recognition system achieved 61.8% mean Average Precision for the testing set and 57.3% for the feasibility study images (where the ground truth was taken as the participants' annotations). The feedback from the participants of the feasibility study was also very positive. [ABSTRACT FROM AUTHOR]

Moiré superlattices of two-dimensional (2D) materials oriented at low twist angles generate a large-scale interference pattern leading to strong interlayer coupling, which influences the band structure and introduces flatbands. Conventional electronic transport measurements have shown the effects of flatband physics, manifesting as correlated insulating states and emergent superconductivity. In this study, we probe the electronic states in a trinary hybrid of graphene and twisted bilayer (tbl) MoS2. Graphene acts as a sensing layer, which captures the electronic effects of the underlying substrate, and we observe certain anomalies in the electronic characteristics of graphene only in the presence of an underlying 58.5 ∘ tbl MoS2, at low temperatures. Interestingly, graphene on tbl MoS2, with twist angle near 0 ∘ or on natural bilayer MoS2, does not show any anomalies. Density functional theory calculations show several distinguishable peaks in the density of states at the conduction band edge of twisted MoS2 near 60 ∘ . We speculate that the anomaly appears due to fermi level pinning of graphene owing to a large density of states in the flatbands of twisted bilayer MoS2. An analysis of the energetics in the graphene-MoS2 hybrid quantitatively agree with theoretical predictions. [ABSTRACT FROM AUTHOR]

Modern data-driven spoken language systems (SLS) require manual semantic annotation for training spoken language understanding parsers. Multilingual porting of SLS demands significant manual effort and language resources, as this manual annotation has to be replicated. Crowdsourcing is an accessible and cost-effective alternative to traditional methods of collecting and annotating data. The application of crowdsourcing to simple tasks has been well investigated. However, complex tasks, like cross-language semantic annotation transfer, may generate low judgment agreement and/or poor performance. The most serious issue in cross-language porting is the absence of reference annotations in the target language; thus, crowd quality control and the evaluation of the collected annotations is difficult. In this paper we investigate targeted crowdsourcing for semantic annotation transfer that delegates to crowds a complex task such as segmenting and labeling of concepts taken from a domain ontology; and evaluation using source language annotation. To test the applicability and effectiveness of the crowdsourced annotation transfer we have considered the case of close and distant language pairs: Italian–Spanish and Italian–Greek. The corpora annotated via crowdsourcing are evaluated against source and target language expert annotations. We demonstrate that the two evaluation references (source and target) highly correlate with each other; thus, drastically reduce the need for the target language reference annotations. [ABSTRACT FROM AUTHOR]

Combining the electronic properties of graphene and molybdenum disulphide (MoS2) in hybrid heterostructures offers the possibility to create devices with various functionalities. Electronic logic and memory devices have already been constructed from graphene-MoS2 hybrids, but they do not make use of the photosensitivity of MoS2, which arises from its optical-range bandgap. Here, we demonstrate that graphene-on-MoS2 binary heterostructures display remarkable dual optoelectronic functionality, including highly sensitive photodetection and gate-tunable persistent photoconductivity. The responsivity of the hybrids was found to be nearly 1 × 1010 A W−1 at 130 K and 5 × 108 A W−1 at room temperature, making them the most sensitive graphene-based photodetectors. When subjected to time-dependent photoillumination, the hybrids could also function as a rewritable optoelectronic switch or memory, where the persistent state shows almost no relaxation or decay within experimental timescales, indicating near-perfect charge retention. These effects can be quantitatively explained by gate-tunable charge exchange between the graphene and MoS2 layers, and may lead to new graphene-based optoelectronic devices that are naturally scalable for large-area applications at room temperature. [ABSTRACT FROM AUTHOR]

Graphene, a two-dimensional nanomaterial, has gained immense interest in biosensing applications due to its large surface-to-volume ratio, and excellent electrical properties. Herein, a compact and user-friendly graphene field effect transistor (GraFET) based ultrasensitive biosensor has been developed for detecting Japanese Encephalitis Virus (JEV) and Avian Influenza Virus (AIV). The novel sensing platform comprised of carboxy functionalized graphene on Si/SiO2 substrate for covalent immobilization of monoclonal antibodies of JEV and AIV. The bioconjugation and fabrication process of GraFET was characterized by various biophysical techniques such as Ultraviolet–Visible (UV–Vis), Raman, Fourier-Transform Infrared (FT-IR) spectroscopy, optical microscopy, Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM). The change in the resistance due to antigen–antibody interaction was monitored in real time to evaluate the electrical response of the sensors. The sensors were tested in the range of 1 fM to 1 μM for both JEV and AIV antigens, and showed a limit of detection (LOD) upto 1 fM and 10 fM for JEV and AIV respectively under optimised conditions. Along with ease of fabrication, the GraFET devices were highly sensitive, specific, reproducible, and capable of detecting ultralow levels of JEV and AIV antigen. Moreover, these devices can be easily integrated into miniaturized FET-based real-time sensors for the rapid, cost-effective, and early Point of Care (PoC) diagnosis of JEV and AIV. [ABSTRACT FROM AUTHOR]

Neuromorphic architectures have become essential building blocks for next-generation computational systems, where intelligence is embedded directly onto low power, small area, and computationally efficient hardware devices. In such devices, realization of neural algorithms requires storage of weights in digital memories, which is a bottleneck in terms of power and area. We hereby propose a biologically inspired low power, hybrid architectural framework for wake-up systems. This architecture utilizes our novel high-performance, ultra-low power molybdenum disulphide (MoS2) based two-dimensional synaptic memtransistor as an analogue memory. Furthermore, it exploits random device mismatches to implement the population coding scheme. Power consumption per CMOS neuron block was found to be 3 nw in the 65 nm process technology, while the energy consumption per cycle was 0.3 pJ for potentiation and 20 pJ for depression cycles of the synaptic device. The proposed framework was demonstrated for classification and regression tasks, using both off-chip and simplified on-chip sign-based learning techniques. [ABSTRACT FROM AUTHOR]

Chlorpyrifos is one of the most widely used pesticides that acts on the nervous system by inhibiting acetylcholinesterase. Prolonged use of chlorpyrifos causes severe neurological, autoimmune, and persistent developmental disorders in humans. Therefore, in this study, a highly sensitive and robust biosensor platform was devised by fabricating graphene field effect transistors (graFET) on Si/SiO2 substrate for the detection of chlorpyrifos in real samples. Anti-chlorpyrifos antibodies were immobilized successfully on the graphene surface. Under optimal conditions, graFET sensor showed an excellent response for chlorpyrifos detection in the linear range of 1 fM to 1 µM with a limit of detection up to 1.8 fM in spiked samples. The developed graFET biosensor is highly stable, sensitive, and specific for chlorpyrifos as confirmed by its significant ability to detect changes in electrostatic potential. These findings signify useful efficacy of immunobiosensors for the detection of chlorpyrifos and other organophosphates in fruits and vegetables. [ABSTRACT FROM AUTHOR]

We report quantum transport measurements on two dimensional (2D) Si:P and Ge:P δ-layers and compare the inelastic scattering rates relevant for weak localization (WL) and universal conductance fluctuations (UCF) for devices of various doping densities (0.3-2.5 × 1018 m−2) at low temperatures (0.3-4.2 K). The phase breaking rate extracted experimentally from measurements of WL correction to conductivity and UCF agree well with each other within the entire temperature range. This establishes that WL and UCF, being the outcome of quantum interference phenomena, are governed by the same dephasing rate. [ABSTRACT FROM AUTHOR]