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In this article, room temperature synthesis of Bi2O3 nanoparticles in a single‐pot reaction is reported. The nanoparticles were synthesized by reducing Bi(NO3)3·5H2O with NaBH4 as a reducing agent, SDS and oleic acid as stabilizing agents. The synthesized nanoparticles were characterized using UV‐vis absorption spectroscopy, FTIR spectroscopy, XRD, and HR‐TEM. The crystalline nature of the synthesized nanoparticles was confirmed through XRD and HRTEM data analysis. An average particle size of 14 nm (with quasi‐spherical morphology) and a wide band gap were measured for the synthesized nanoparticles. HRTEM image confirmed a highly crystalline growth at individual nanoparticle level. Dielectric measurement indicates a rapid reduction of both real and imaginary dielectric constants as the frequency increases to higher values. The potential application of the synthesized nanoparticles has been demonstrated in photocatalytic degradation of pollutants present in the industrial waste‐water.

Thin layer chromatography (TLC) is considered as an efficient analytical technique used for the monitoring and identification of the adsorption behaviour of different amino acids through soil as a stationary phase amended with polyvinyl acetate at different concentration. The study gives complete idea about the mobility of four different uncharged amino acids namely glycine, alanine, tryptophan and glutamine in terms of retention factor by thin layer chromatography. Among four amino acids, highest mobility was found in case of glycine. The order of mobility was found to be in order of glycine > alanine > tryptophan > glutamine in which distilled water has been used as a mobile phase. It has been observed from the results that pH and electrical conductivity also influence mobility of amino acids. The influence of activation temperature and particle size of soil on the mobility of amino acids was also studied.

The Orange-breasted Green-pigeon is a non-migratory frugivorous bird species from the family Columbidae. It is distributed in India, Nepal, Bhutan, Sri Lanka, Bangladesh, and south-east Asian countries. In this paper, we report the first sighting record of the Orange-breasted Green-pigeon Treron bicinctus from Chittaranjan, West Bengal, India with photographic evidence.

BackgroundThe habitat resources are structured across different spatial scales in the environment, and thus animals perceive and select habitat resources at different spatial scales. Failure to adopt the scale-dependent framework in species habitat relationships may lead to biased inferences. Multi-scale species distribution models (SDMs) can thus improve the predictive ability as compared to single-scale approaches. This study outlines the importance of multi-scale modeling in assessing the species habitat relationships and may provide a methodological framework using a robust algorithm to model and predict habitat suitability maps (HSMs) for similar multi-species and multi-scale studies.ResultsWe used a supervised machine learning algorithm, random forest (RF), to assess the habitat relationships of Asiatic wildcat (Felis lybica ornata), jungle cat (Felis chaus), Indian fox (Vulpes bengalensis), and golden-jackal (Canis aureus) at ten spatial scales (500–5000 m) in human-dominated landscapes. We calculated out-of-bag (OOB) error rates of each predictor variable across ten scales to select the most influential spatial scale variables. The scale optimization (OOB rates) indicated that model performance was associated with variables at multiple spatial scales. The species occurrence tended to be related strongest to predictor variables at broader scales (5000 m). Multivariate RF models indicated landscape composition to be strong predictors of the Asiatic wildcat, jungle cat, and Indian fox occurrences. At the same time, topographic and climatic variables were the most important predictors determining the golden jackal distribution. Our models predicted range expansion in all four species under future climatic scenarios.ConclusionsOur results highlight the importance of using multiscale distribution models when predicting the distribution and species habitat relationships. The wide adaptability of meso-carnivores allows them to persist in human-dominated regions and may even thrive in disturbed habitats. These meso-carnivores are among the few species that may benefit from climate change.

In this article we present a new semantic and syntactic-based method for external plagiarism detection. In the proposed approach, latent dirichlet allocation (LDA) and parts of speech (POS) tags are used together to detect plagiarism between the sample and a number of source documents. The basic hypothesis is that considering semantic and syntactic information between two text documents may improve the performance of the plagiarism detection task. Our method is based on two steps, naming, which is a pre-processing where we detect the topics from the sentences in documents using the LDA and convert each sentence in POS tags array; then a post processing step where the suspicious cases are verified purely on the basis of semantic rules. For two types of external plagiarism (copy and random obfuscation), we empirically compare our approach to the state-of-the-art N-gram based and stop-word N-gram based methods and observe significant improvements.

In this article we present a new semantic and syntactic-based method for external plagiarism detection. In the proposed approach, latent dirichlet allocation (LDA) and parts of speech (POS) tags are used together to detect plagiarism between the sample and a number of source documents. The basic hypothesis is that considering semantic and syntactic information between two text documents may improve the performance of the plagiarism detection task. Our method is based on two steps, naming, which is a pre-processing where we detect the topics from the sentences in documents using the LDA and convert each sentence in POS tags array; then a post processing step where the suspicious cases are verified purely on the basis of semantic rules. For two types of external plagiarism (copy and random obfuscation), we empirically compare our approach to the state-of-the-art N-gram based and stop-word N-gram based methods and observe significant improvements.

The conservation of large carnivores often requires precise and accurate estimates of their populations. Being cryptic and occurring at low population densities, obtaining an unbiased population estimate is difficult in large carnivores. To overcome the uncertainties in the conventional capture–recapture (CR) methods used to estimate large carnivore densities, more robust methods such as spatially explicit capture-recapture (SECR) framework are now widely used. We modeled the CR data of tiger (Panthera tigris tigris) and leopard (Panthera pardus fusca) in the SECR framework with biotic and abiotic covariates likely believed to influence their densities. An effort of 2,211 trap nights resulted in the capture of 33 and 38 individual tigers and leopards. A total of 95 and 74 detections of tigers and leopards were achieved using 35 pairs of camera traps. Tiger and leopard density were estimated at 4.71 ± 1.20 (3.05–5.11) and 3.03 ± 0.78 (1.85–4.99) per 100 km2. Our results show that leopard density increased with high road density, high terrain ruggedness and habitats with high percentage of cropland and natural vegetation. The tiger density was positively influenced by the mosaic of cropland and natural vegetation. This study provides the first robust density estimates of tiger and leopard within the study area. Our results support the notion that large carnivores can attain moderate densities within human-dominated regions around protected areas relying on domestic livestock. Broader management strategies aimed at maintaining wild prey in the human-dominated areas around protected areas are necessary for large and endangered carnivores’ sustenance in the buffer zones around protected areas.

Time and space are essential niche dimensions along which species tend to coexist. We assessed spatiotemporal resource partitioning between leopards and lions and hypothesized the differential use of spatiotemporal resources by leopards with respect to lions. We used a systematic camera trap survey to collect the data at 50 sites. The data were analyzed using overlap indices, and non-parametric test statistics to assess the spatiotemporal associations. Leopard and lion were crepuscular and nocturnal in their activity pattern. They did not segregate temporally and showed substantially high overlap and strong temporal association. Leopard segregates with lion spatially by overlapping less and showing no association in space use at specific camera trap sites. Leopards showed preference for dense habitats, while the lion preferred both dense and open habitats. Leopard showed moderate-overlap and positive association with key prey species, i.e., chital and sambar. Lion, however showed low site-specific overlap and negative association with its crucial prey species, i.e., sambar and wild pig. We conclude that site-specific spatial partitioning along with differential affinities for habitat is helping leopards to partition their spatio-temporal resources with lions and hence facilitate coexistence of leopards with lions in Gir forest.

Information on the level and distribution of genetic variation is important for conservation plan of captive population of an endangered species such as tiger and cheetah. We assayed the frequency of microsatellites in the genomic and genic sequences of wild cats (Panthera tigris, Acinonyx jubatus) and compared it with the domestic cat (Felis catus). Frequency, relative abundance and density of microsatellites were highest in the domestic cat when compared with wild cats. The frequency of microsatellites was positively correlated with the G+C content of genomic and genic sequences. The maximum frequency of microsatellites among all three sequence sets was of di-nucleotide repeats (genomic—88.1%; genic—70.4%), whereas the hexa-nucleotide repeat represents

In typical IoT systems, sensors and actuators are connected to small embedded computers, called IoT devices, and the IoT devices are connected to one or more appropriate cloud services over the internet through an edge access router. A very important design aspect of an IoT edge router is the size of the output packet buffer of its interface that connects to the access link. Selecting an appropriate size for this buffer is crucial because it directly impacts two key performance metrics: 1) access link utilization and 2) latency. In this paper, we calculate the size of the output buffer that ensures that the access link stays highly utilized and at the same time, significantly lowers the average latency experienced by the packets. To calculate this buffer size, we theoretically model the average TCP congestion window size of all IoT devices while eliminating three key assumptions of prior art that do not hold true for IoT TCP traffic, as we will demonstrate through a measurement study. We show that for IoT traffic, buffer size calculated by our method results in 50% lower queuing delay compared to the state of the art schemes while achieving similar access link utilization and loss-rate.

This paper presents a low cost, low power and wireless wearable solution for real-time analysis and monitoring of cardiac activity co-related with physical activity. Utilizing an analogue filter chain for signal conditioning, the device performs continuous measurement of the Electrocardiogram. The wearable also includes an accelerometer enabling it to detect the current physical activity along with body orientation. The device communicates wirelessly, using Bluetooth Smart /Bluetooth Low Energy, with a smart phone, where a complete analysis can be performed on the received data, and decisions about the current health conditions can be made.

A high speed, low-cost transmitter for visible light communication has been developed. The PCB design has been optimized for high frequency operation using surface-mounted devices. A two-stage on-chip amplifier has been used to amplify the square-wave pulses up to 50 MHz fundamental frequency, which is limited by the measurement setup. The frequency components up to eleventh harmonic have been observed in the amplified signal. The transmitter driver has been used to operate a high-brightness LED and the transmission up to 25 MHz–50 Mbps (using NRZ) has been attained.