Soybean peroxidase catalyzed polymerization and removal of 2,4-dimethylphenol from synthetic wastewater

Enzymatic treatment of synthetic wastewater containing 2,4-dimethylphenol (2,4-DMP) was investigated in the presence and absence of polyethylene glycol (PEG) by the enzyme soybean peroxidase. The optimum pH both in the absence and in presence of PEG was 8.0. The optimum [hydrogen peroxide]/[2,4-DMP] was between 0.9-1.2. A linear relationship existed in presence of PEG between the minimum SBP concentration and initial 2,4-DMP concentrations. In the absence of PEG, a linear relationship did exist at lower substrate concentrations up to 2.0 mM, beyond which the minimum enzyme concentration remained constant and independent of the initial substrate concentration. At lower 2,4-DMP concentrations, there was PEG effect which decreased to almost nil with increase in substrate concentrations. Minimum PEG concentration for 1 mM of 2,4-DMP was found to be 45-50 mg/L. Preliminary kinetic study of the enzyme-catalyzed reaction yielded the values of Michaelis-Menten constants for 2,4-dimethylphenol, in the presence and absence of PEG

A Design of Digital Microfluidic Biochip along with Structural and Behavioural Features in Triangular Electrode Based Array

AbstractDigital microfluidic based biochip manoeuvres on the theory of microfluidic technology, having a broad variety of applications in chemistry, biology, environmental monitoring, military etc. Being concerned about the technological advancement in this domain, we have focused on equilateral triangular electrodes based DMFB systems. Accepting the associated design issues, here, we have addressed many facets of such electrodes regarding their structural and behavioural issues in comparison to the existing square electrodes. As the requisite voltage reduction is a key challenging design issues, to implement all the tasks using triangular electrodes that are possible in square electrode arrays as well, is a tedious job. Furthermore, to deal with this new design deploying triangular electrodes, we have analyzed all the necessary decisive factors including fluidic constraints to ensure safe droplet movements and other modular operations together with mixing and routing. Moreover, an algorithm has been developed to find a route for a given source and destination pair in this newly designed DMFB. Finally, we have included a comparative study between this new design and the existing one while encountering the above mentioned issues

Data Uncertainty Guided Noise-aware Preprocessing Of Fingerprints

The effectiveness of fingerprint-based authentication systems on good quality fingerprints is established long back. However, the performance of standard fingerprint matching systems on noisy and poor quality fingerprints is far from satisfactory. Towards this, we propose a data uncertainty-based framework which enables the state-of-the-art fingerprint preprocessing models to quantify noise present in the input image and identify fingerprint regions with background noise and poor ridge clarity. Quantification of noise helps the model two folds: firstly, it makes the objective function adaptive to the noise in a particular input fingerprint and consequently, helps to achieve robust performance on noisy and distorted fingerprint regions. Secondly, it provides a noise variance map which indicates noisy pixels in the input fingerprint image. The predicted noise variance map enables the end-users to understand erroneous predictions due to noise present in the input image. Extensive experimental evaluation on 13 publicly available fingerprint databases, across different architectural choices and two fingerprint processing tasks demonstrate effectiveness of the proposed framework.Comment: IJCNN 2021 (Accepted

Sensor-invariant Fingerprint ROI Segmentation Using Recurrent Adversarial Learning

A fingerprint region of interest (roi) segmentation algorithm is designed to separate the foreground fingerprint from the background noise. All the learning based state-of-the-art fingerprint roi segmentation algorithms proposed in the literature are benchmarked on scenarios when both training and testing databases consist of fingerprint images acquired from the same sensors. However, when testing is conducted on a different sensor, the segmentation performance obtained is often unsatisfactory. As a result, every time a new fingerprint sensor is used for testing, the fingerprint roi segmentation model needs to be re-trained with the fingerprint image acquired from the new sensor and its corresponding manually marked ROI. Manually marking fingerprint ROI is expensive because firstly, it is time consuming and more importantly, requires domain expertise. In order to save the human effort in generating annotations required by state-of-the-art, we propose a fingerprint roi segmentation model which aligns the features of fingerprint images derived from the unseen sensor such that they are similar to the ones obtained from the fingerprints whose ground truth roi masks are available for training. Specifically, we propose a recurrent adversarial learning based feature alignment network that helps the fingerprint roi segmentation model to learn sensor-invariant features. Consequently, sensor-invariant features learnt by the proposed roi segmentation model help it to achieve improved segmentation performance on fingerprints acquired from the new sensor. Experiments on publicly available FVC databases demonstrate the efficacy of the proposed work.Comment: IJCNN 2021 (Accepted

Diversity Awareness in Software Engineering Participant Research

Diversity and inclusion are necessary prerequisites for shaping technological innovation that benefits society as a whole. A common indicator of diversity consideration is the representation of different social groups among software engineering (SE) researchers, developers, and students. However, this does not necessarily entail that diversity is considered in the SE research itself. Our study examines how diversity is embedded in SE research, particularly research that involves participant studies. To this end, we selected 79 research papers containing 105 participant studies spanning three years of a renowned SE conference. Using a content analytical approach, we identified how SE researchers report the various diversity categories of their study participants and investigated: 1) the extent to which participants are described, 2) what diversity categories are commonly reported, and 3) the function diversity serves in the SE studies. Our results demonstrate that even though most SE studies report on the diversity of participants, SE research often emphasizes professional diversity, such as occupation and work experience, over social diversity, such as gender or location of the participants. Furthermore, our results show that participant diversity is seldom analysed or reflected upon when SE researchers discuss their study results, outcomes, or limitations. To help researchers self-assess their study diversity awareness, we propose a diversity awareness model and guidelines that SE researchers can apply to their research. Furthermore, our research contributes to the United Nations Sustainable Development’s Goals 5, 9, and 10. With this study, we hope to shed light on a new approach to tackling the diversity and inclusion crisis in the SE field

Editorial: Editorial - Mapana Journal of Sciences

Mapana J Sci, 15, 2 (2016)ISSN 0975-3303|http://dx.doi.org/10.12723/mjs.37.0EditorialThis issue of Mapana—Journal of Sciences is devoted to research articles from Chemical Sciences. Researchers from various universities have contributed to the present issue. The first article is on ‘Studies on Ruthenium and Rhodium Complexes Containing 1,2- bis(N-Methylbenzimidazolyl) Benzene and Catalytic Transfer Hydrogenation’ by Hunasekatte G Bheemanna et al. The second article by Rita Bhattacharjee et al. is on ‘Synthesis and Characterization of Palladium(II) Complexes with Substituted Dihydrobenzoimidazoquinazoline Derivatives’. The third article on ‘Kinetic Study on Oxidation of Thiodipropionic Acid by Iron (III)-bipyridine Complex’ is authored by Selva Priya et al. The last article by Sumana V S et al. is about ‘Miscibility of Starch and Low Molecular Weight Poly(ethyleneglycol) Blends in Aqueous Medium’. All the articles were peer reviewed by experts in their respective fields. The suggestions given by them have been incorporated. We thank all the reviewers for spending their precious time in reviewing the articles and giving valuable suggestions. We also take this opportunity to thank all the authors for their valuable contributions. To improve the quality of our journal we expect the cooperation and expert guidance of the researchers. We have been continually striving to meet the global standards for journal publication. Thus support and cooperation from the academic community is of utmost importance in improving the quality of the journal. Riya Datta Issue Edito

Resonant Enhancement of Photoluminescence Intensity and Anisotropy of Quantum Dot Monolayers with Self-Assembled Gold Nanorods

Quantum dot (QD) films are well known as promising materials for photo-detectors and photovoltaic and next generation display devices. In this study, we show, experimentally, how compact monolayer films of cadmium selenide (CdSe) QDs having compact assemblies of partially aligned metal nanorods placed in close proximity can be used to enhance the photoluminescence (PL) emission intensity by greater than ten times while the PL anisotropy can be increased to almost 0.9. Finite difference time domain (FDTD) simulations on smaller scale gold nanorod (GNR) arrays on CdSe QD layer not only explain this huge emission enhancement and anisotropy observed experimentally but also provide insight into the parameters which if further optimized can lead to even larger enhancement and emission anisotropy in similar hybrid systems. Our work paves the way for creation of large scale, simple and inexpensive, but highly efficient, metal nanorod-QD hybrid films which can find wide ranging potential applications in displays, detectors, and photovoltaics

Large emission enhancement and emergence of strong coupling with plasmons in nanoassemblies: Role of quantum interactions and finite emitter size

The Purcell effect has been the basis for several decades in understanding enhancement of photonic efficiency and decay rates of emitters through their coupling to cavity modes and metal nanostructures. However, it is not clear whether this regime of radiative enhancements can be extended to ultrasmall nanoparticle sizes or interparticle distances. Here we report large radiative enhancements of quantum dot assemblies with extremely small metal nanoparticles and emitter-particle separations R of a few nanometers, where Purcell effect would lead to either no enhancements or quenching. We invoke a new regime of radiative enhancements to explain the experimental data and also correctly predict the emergence of strong coupling below certain R, as observed in experiments. In addition, we show that the widely used point emitter approximations diverge from actual observations in the case of finite size emitters at such small separations