Hydrochemistry of Lake Rara: A high mountain lake in western Nepal

High altitude ecosystems have important natural ecological functions but are under increasing impacts from human activities and climate change. A detailed analysis of the water chemistry of Lake Rara, a high mountain lake in western Nepal, was carried out in October 2015 and April 2016. A total of 31 water samples were collected. Major ions (Ca²⁺, Mg²⁺, Na⁺, K⁺, SO₄^2?, NO₃^? and Cl^?) were analysed by ion chromatography. Si and PO₄^3? were analysed following the standard protocols. Conductivity, pH, total dissolved solids (TDS), turbidity and dissolved oxygen (DO) were measured on‐site. The lake is oligotrophic characterized by low PO₄^3? concentration (0.06 ± 0.01 mg/L), high DO values (6.73 ± 0.06 and 10.89 ± 0.86 mg/L), alkaline pH (8.42 ± 0.3 and 8.32 ± 0.23) and low conductivity (189.93 ± 5.3 and 189.22 ± 5.8 μS/cm). The concentrations of the major cations were in the order of Ca²⁺ > Mg²⁺ > K⁺ > Na⁺ (during both seasons), and for anions, it was HCO₃^? > SO₄^2? > Cl^? > NO₃^? and HCO₃^? > Cl^? > NO₃^? > SO₄^2? during postmonsoon and premonsoon, respectively. One‐way ANOVA revealed significant seasonal variations (p  < 0.05) in most of the physicochemical parameters. The increased concentrations of most of the ions in the premonsoon time probably reflect long‐range transport of materials through dry deposition, whereas higher concentrations of NO₃^? and Cl^? in some sites possibly reflect the localized impacts of settlement and grazing. The lake water was classified as Ca(Mg)HCO₃. High (Ca²⁺ + Mg²⁺)/Tz⁺ ratio (0.97 in postmonsoon and 0.95 in premonsoon) and low (Na⁺ + K⁺)/Tz⁺ ratio (0.03 in postmonsoon and 0.04 in premonsoon) confirm carbonate weathering as the principal source of major ions with bedrock geology governing the water chemistry. The findings of this study build on the baseline dataset for assessing future anthropogenic influence on the lake and subsequent development for future lake management strategies.     

Deceptive review detection using labeled and unlabeled data

Availability of millions of products and services on e-commerce sites makes it difficult to search the best suitable product according to the requirements because of existence of many alternatives. To get rid of this the most popular and useful approach is to follow reviews of others in opinionated social medias, who have already tried them. Almost all e-commerce sites provide facility to the users for giving views and experience of the product and services they experienced. The customers reviews are increasingly used by individuals, manufacturers and retailers for purchase and business decisions. As there is no scrutiny over the reviews received, anybody can write anything unanimously which conclusively leads to review spam. Moreover, driven by the desire of profit and/or publicity, spammers produce synthesized reviews to promote some products/brand and demote competitors products/brand. Deceptive review spam has seen a considerable growth overtime. In this work, we have applied supervised as well as unsupervised techniques to identify review spam. Most effective feature sets have been assembled for model building. Sentiment analysis has also been incorporated in the detection process. In order to get best performance some well-known classifiers were applied on labeled dataset. Further, for the unlabeled data, clustering is used after desired attributes were computed for spam detection. Additionally, there is a high chance that spam reviewers may also be held responsible for content pollution in multimedia social networks, because nowadays many users are giving the reviews using their social network logins. Finally, the work can be extended to find suspicious accounts responsible for posting fake multimedia contents into respective social networks.     

Self‐recurrent wavelet neural network–based identification and adaptive predictive control of nonlinear dynamical systems

In this paper, the problem of simultaneous identification and predictive control of nonlinear dynamical systems using self‐recurrent wavelet neural network (SRWNN) is addressed. The structure of the SRWNN is a modification of the wavelet neural network (WNN). Unlike WNN, the neurons present in the hidden layer of SRWNN contain the weighted self‐feedback loops. Dynamic back‐propagation algorithm is employed to derive the necessary parameter update equations. To further improve the convergence speed of the parameters, a time‐varying (adaptive) learning rate is used. Four simulation examples are considered for testing the effectiveness of the proposed method. Furthermore, some disturbance rejection tests are also performed on the proposed method. The results obtained through the simulation study confirm the effectiveness of the proposed method.     

Correction to: Efficient room temperature methanol sensors based on polyaniline/graphene micro/nanocomposites

Iranian Polymer Journal - The article listed above was initially published with typo error in Eq.&nbsp;(4).     

Approach to Obtain Electrospun Hydrophilic Fibers and Prevent Fiber Necking

Solution electrospinning of a blend containing a hydrophobic polymer with a hydrophilic functional polymer as an additive is a simple and straight‐forward route to obtain functional and hydrophilic fibers accompanied by the mechanical properties of the hydrophobic polymer. However, this process of thermodynamically unfavored surface segregation of the hydrophilic additive is not well understood. To understand the process the dependencies of the surface hydrophilization on type of hydrophilic polymers, the solvent, and the process, using poly(caprolactone) (PCL) as the matrix polymer is explored. The results show that hydrophilic fibers can be obtained using different additive hydrophilic polymers. The combination of polymer blends which show this effect can be predicted using the Flory–Huggins interaction parameter. In addition mechanical and micromechanical properties of PCL fibers blended with NCO‐terminated star‐shaped poly(ethylene glycol) (sPEG‐NCO) as additive are investigated. In this context blending with sPEG‐NCO turns out to be a powerful tool to prevent fiber necking rendering this method an interesting candidate for tissue engineering application, where it is mandatory to retain the surface properties under mechanical stress.     

Where do I stand? Examining the effects of leader–member exchange social comparison on employee work behaviors.

Taking an approach integrating principles of leader–member exchange (LMX) differentiation with social comparison theory, we contend that subjective ratings by individuals of their LMX compared to the LMXs of coworkers (labeled LMX social comparison, or LMXSC) explain unique and meaningful variance in outcomes beyond LMX and the actual standing of those individuals in the LMX distribution, referred to as relative LMX, or RLMX. Our findings demonstrate that employees' perceptions of LMXSC are positively related beyond the effects of LMX and RLMX to job performance and citizenship behaviors. Further, we argue that LMXSC mediates the RLMX→outcomes relationships. Analyses showed that, in a sample of 254 employees nested in 50 work groups, a significant part of the effects of RLMX on job performance and citizenship behaviors was mediated through LMXSC after controlling for LMX. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Photopolymerization of methyl methacrylate by 2,2′‐dithiodiethanol: Effect of reaction conditions

The photopolymerization of methyl methacrylate (MMA) through the use of a novel disulphide, 2,2′‐dithiodiethanol (DDE), was studied. This photoinitiator is of special interest because of its possible use in the synthesis of polyurethane macrophotoinitiator. The photopolymerization was carried out in the Heber multilamp photochemical reactor (COMPACT‐LP‐MP88) at 254 nm. The effects of reaction conditions on the polymerization of MMA were studied. It was observed that the percentage conversion and molecular weight increased with the increases of monomer concentration and reaction time. However, for the initiator to monomer molar ratio, there was a critical molar ratio for maximum conversion. The results suggested the living radical nature of the photoinitiator, which was further investigated by the preparation of block copolymer with acrylonitrile. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 1601–1606, 2006     

Electrophoretic deposition of nanobiocomposites for orthopedic applications: influence of current density and coating duration

Frequently metal implants undergo detachment from the host tissue due to inadequate biocompatibility and poor osteointegration. In view of this, bioactive porous apatite-wollastonite/chitosan nanocomposite coating was prepared using electrophoretic deposition (EPD) technique in the present work. The effect of coating duration and current density on surface characteristics of the nanocomposite coating was assessed using optical microscope and scanning electron microscope. EPD led to the formation of thick and homogeneous coating. Adhesion of the composite coating on titanium substrate was evaluated using tape test and bioactivity of the coatings was studied by immersing in simulated body fluid (SBF). The coating with higher current density and longer coating duration was found to be suitable with improved adhesion and bioactivity for intended metal implants.     

Core/shell nanoassembly of amphiphilic naproxen‐polyethylene glycol: synthesis,characterisation and evaluation as drug delivery system

Small molecule‐based amphiphiles self‐assemble into nanostructures (micelles) in aqueous medium which are currently being explored as novel drug delivery systems. Here, naproxen‐polyethylene glycol (N‐PEG), a small molecule‐derived amphiphile, has been synthesised, characterised and evaluated as hydrophobic drug carrier. ¹ H, ¹³ C Nuclear magnetic resonance (NMR), mass spectrometry (MS) and Fourier‐transform infrared spectroscopy (FTIR) confirmed the formation of N‐PEG and dynamic light scattering (DLS) revealed the formation of nano‐sized structures of ∼228 nm. Transmission electron microscope (TEM) analysis showed aggregation behaviour of the structures with average size of ∼230 nm. Biodegradability aspect of the micellar‐structured N‐PEG was demonstrated by lipase‐mediated degradation studies using DLS and TEM. High encapsulation efficiency followed by release in a sustained manner of a well‐known anticancer drug, doxorubicin, demonstrated the feasibility of the new drug delivery system. These results advocate the promising potential of N‐PEG micelles as efficient drug delivery system for specific delivery to cancerous cells in vitro and in vivo.Inspec keywords: cancer, biodegradable materials, cellular biophysics, encapsulation, biomedical materials, drugs, nanofabrication, drug delivery systems, nanomedicine, self‐assembly, nanoparticles, transmission electron microscopy, colloids, molecular biophysics, light scattering, hydrophobicity, biochemistry, enzymes, core‐shell nanostructures, nanocomposites, proton magnetic resonance, Fourier transform infrared spectra, mass spectroscopic chemical analysisOther keywords: hydrophobic drug carrier, nanosized structures, transmission electron microscope analysis, doxorubicin, N‐PEG micelles, core/shell nanoassembly, amphiphilic naproxen‐polyethylene glycol, drug delivery system, small molecule‐based amphiphiles self‐assemble, small molecule‐derived amphiphile, ¹ H NMR, ¹³ C NMR, MS, FTIR, dynamic light scattering, aggregation behaviour, biodegradability aspect, lipase‐mediated degradation studies, encapsulation efficiency, cancerous cells