A spatio‐temporal water quality assessment of the Beas and Sutlej Rivers at the Harike Wetland: A Ramsar site in Punjab,India

Lakes play a vital role in regulating water storage, flow of river water, and ultimately maintaining a balanced ecosystem. Spatial and temporal variations in physicochemical parameters of water in Harike Wetland, a Ramsar site in the northwestern state of Punjab, India, were studied. This study was conducted on a monthly basis from January to December 2015. The water quality was studied at ten locations from sites 1 to 10 upstream, central and downstream from Harike Lake for ten physicochemical parameters, including temperature, pH, electrical conductivity, turbidity, dissolved oxygen concentration biological oxygen demand, nitrate and phosphate concentrations and salinity. The findings of this study revealed that, except for temperature and pH, all parameters exhibited relatively higher values for the Sutlej River, compared with the Beas River, with sampling sites 5 to site 7 exhibiting intermediate results. The mean seasonal temperature variations ranged from 16.9 to 26.6 °C, the pH from 7.7 to 8.2, electrical conductivity from 223 to 303 μS cm^?1 and TDS concentration from 148.7 to 180.4 ppm. Correlation analysis was conducted to assess the relations between the variables. The electrical conductivity exhibited a high positive correlation with salinity and biological oxygen demand, whereas it correlated negatively with the dissolved oxygen concentration. Box and whisker plots were also plotted for the study results to better examine the data distribution.     

Geospatial technology applied to spatiotemporal assessment of Harike Wetland,Punjab

The Harike Wetland situated in Punjab is a Ramsar site and a wetland of national importance. The present study was undertaken to assess the spatiotemporal dynamics of the wetland on the basis of geospatial technology and ground‐based studies. Landsat images for the years 2002 and 2014 were acquired from the United States Geological Survey and classified digitally to generate landuse/land cover maps involving four classes (water, grassland (including water hyacinth), agriculture, built‐up (settlement), barren land). The total area of the Harike Wetland was found to be 8023.68 ha. Water sampling at eleven sites was carried out and evaluated for physicochemical parameters. The water quality at several sampling points was found to be severely degraded. Change detection analysis revealed the submerged area (area under water) and grassland (including water hyacinth) had decreased over the past 12 years, whereas that area under agriculture and built‐up land has increased, indicating a shrinkage in the total wetland area. The present study also indicated that the near‐infrared band is a good indicator of water quality parameters, as indicated by the significant positive correlation between the near‐infrared band and relevant water parameters. Because the wetland is important from both an ecological perspective and economic perspective, regular monitoring is recommended, for which geospatial technology has proven to be very useful.     

A statistical framework for few-shot action recognition

Along with the exponential growth of online video creation platforms such as Tik Tok and Instagram, state of the art research involving quick and effective action/gesture recognition remains crucial. This work addresses the challenge of classifying short video clips, using a domain-specific feature design approach, capable of performing significantly well using as little as one training example per action. The method is based on Gunner Farneback’s dense optical flow (GF-OF) estimation strategy, Gaussian mixture models, and information divergence. We first aim to obtain accurate representations of the human movements/actions by clustering the results given by GF-OF using K-means method of vector quantization. We then proceed by representing the result of one instance of each action by a Gaussian mixture model. Furthermore, using Kullback-Leibler divergence (KL-divergence), we attempt to find similarities between the trained actions and the ones in the test videos. Classification is done by matching each test video to the trained action with the highest similarity (a.k.a lowest KL-divergence). We have performed experiments on the KTH and Weizmann Human Action datasets using One-Shot and K-Shot learning approaches, and the results reveal the discriminative nature of our proposed methodology in comparison with state-of-the-art techniques.

     

Reserves Accumulated in Non-Photosynthetic Organs during the Previous Growing Season Drive Plant Defenses and Growth in Aspen in the Subsequent Growing Season

Plants store non-structural carbohydrates (NSC), nitrogen (N), as well as other macro and micronutrients, in their stems and roots; the role of these stored reserves in plant growth and defense under herbivory pressure is poorly understood, particularly in trees. Trembling aspen (Populus tremuloides) seedlings with different NSC and N reserves accumulated during the previous growing season were generated in the greenhouse. Based on NSC and N contents, seedlings were assigned to one of three reserve statuses: Low N–Low NSC, High N–Medium NSC, or High N–High NSC. In the subsequent growing season, half of the seedlings in each reserve status was subjected to defoliation by forest tent caterpillar (Malacosoma disstria) while the other half was left untreated. Following defoliation, the effect of reserves was measured on foliar chemistry (N, NSC) and caterpillar performance (larval development). Due to their importance in herbivore feeding, we also quantified concentrations of phenolic glycoside compounds in foliage. Seedlings in Low N-Low NSC reserve status contained higher amounts of induced phenolic glycosides, grew little, and supported fewer caterpillars. In contrast, aspen seedlings in High N-Medium or High NSC reserve statuses contained lower amounts of induced phenolic glycosides, grew faster, and some of the caterpillars which fed on these seedlings developed up to their fourth instar. Furthermore, multiple regression analysis indicated that foliar phenolic glycoside concentration was related to reserve chemistry (NSC, N). Overall, these results demonstrate that reserves accumulated during the previous growing season can influence tree defense and growth in the subsequent growing season. Additionally, our study concluded that the NSC/N ratio of reserves in the previous growing season represents a better measure of resources available for use in defense and growth than the foliar NSC/N ratios.     

Conductive wool yarns by continuous vapour phase polymerization of pyrrole

Conducting polypyrrole (PPy) coated wool yarns were prepared by a continuous vapour polymerization technique, using a speed of 1 m/min with different iron(III) chloride (FeCl₃) as the oxidant at different concentrations. The resistivities, tensile properties, longitudinal and cross-sectional views of PPy-coated wool yarns were investigated. Optimum specific electrical resistances of 2.96 Ω g/cm² at 80 g/L FeCl₃ and 1.69 Ω g/cm² at 70 g/L FeCl₃ were obtained for 500 and 400 twist per meter (TPM) yarns, respectively. PPy-coated wool yarns exhibited higher elongation than uncoated yarns. Longitudinal and cross-sectional views of the yarns indicate that PPy coating penetrated deep into the yarn cross-section and a uniform coating was obtained on the surface of the yarn surface.     

Viscosity estimation of mixed oil using RBF-ANN approach

Diluting the bitumen and heavy oil with a liquid solvent such as tetradecane is one way to decrease the viscosity. The accurate estimation for the viscosity of the aforesaid mixture is serious due to the sensitivity of enhanced oil recovery method. The main aim of this study was to propose an impressive relation between the viscosity of heavy n-alkane and Athabasca bitumen mixtures based on pressure, temperature, and the weight percentage of n-tetradecane using radial basis function artificial neural network (RBF-ANN). Also, this model has been compared with previous equations and its major accuracy was evidenced to estimate the viscosity. The amounts of mean relative error (MRE %) and R-squared received 0.32 and 1.00, respectively. The endeavors confirmed amazing forecasting skill of RBF-ANN for the approximation of the viscosity as a function of temperature, pressure, and the weight percentage of n-tetradecane.     

PEOPL: A knowledge-based system for the evaluation of personnel

Abstract: A project is underway to increase the effective use of personnel by creating a knowledge-based assistant for supervisors. The Programmed Evaluation of Personnel (PEOPL) is designed to permit the combination of quantitative and qualitative data to standardize supervisory ratings. The full scope of the project will combine subjective experience with data from psychological research which assesses employee performance. Peopl combines heuristic, subjective experience with experimental data to establish performance standards for use in a comprehensive system for personnel use. In this way, organizations can assess corporate needs, evaluate the current pool of employees, place them where they may be used more efficiently, and determine what jobs remain undone.     

Study on thickness loss of cut-pile carpet produced with heat process-modified polyester pile yarn. Part I: static loading

Carpet as a home textile is usually subjected to static loading. Therefore, compression behavior or thickness loss after a long-term loading is important from point of view of carpet appearance as well as its lifetime. In this study, four types of cut-pile carpet were woven based on face-to-face weaving system. Pile yarns were air-jet textured polyester filament yarns that were modified by different heat processes. Then, the carpets’ compression behavior was investigated by static loading test. Results show that by increasing the temperature in setting of pile yarns twist at the autoclave process, the carpet static recovery increases. However, the friezing and heat-setting processes of pile yarns have no significant effect on the carpet static recovery.     

Application of air‐jet nozzle in short staple Siro spinning system

With the objective of reducing the hairiness of Siro spun yarns, two types of air‐jet nozzle differing in the angle of sub‐holes and suitable for an air vortex ring spinning system were designed and fabricated. The performance of the JetSiro spinning system on short staple fiber materials and the effects of the different parameters on the hairiness of JetSiro spun yarns, such as nozzle pressure of compressed air, distance between front roller nip and inlet of nozzle, and nozzle structure, were investigated using the Taguchi method. The physical properties of JetSiro spun yarns with those of conventional Siro spun yarns were compared. The results show that the parameters, air pressure and distance between front roller nip and inlet of nozzle have the strongest and weakest effect on yarn hairiness. In addition, the optimum spinning conditions were determined. The application of the air‐jet nozzle exhibits significant reductions in yarn hairiness of 40%. The results revealed no significant effect of the air‐jet nozzle on the yarn tensile properties and evenness.