Simultaneous estimation of Amino acids by using HPLC

Various methods for the individual as well as simultaneous estimation of amino acids using various techniques like HPLC and other way outs like electrophoresis have been described in this review paper. The amino acid determination by using HPLC can either be done by using pre-column or post column derivatization. The amino acid is first derivatized into a particular derivative and then is analysed into the column in the case of pre-column derivatization, whereas in the case of post column derivatization, the amino acid is first passed through the column for the sake of separation and then the separated amino acids are derivatized into their such derivatives which can be detected by fluorescence detector. Out of the above two mentioned techniques, pre-column derivatization is used more oftenly than the post column derivatization. Few of the most commonly used derivatization agents are phenylisothiocyanate, o-phthalaldehyde+2-mercaptoethanol, dansyl chloride, phenylthiohydantoin etc

Performance Evaluation of Workers in a Government Undertaking Company of India

Humans are having unlimited potential for growth and development which is measured in an organisation under Performance appraisal System (PAS). PAS is the process of analyzing and recording information about the relative worth of an employee, that is a two way communication process. It involves an active communication between employee and supervisor about performance. PAS can be measured by a system of evaluation but since there is no unanimous system exists the companies are using any one or their own system. Their system of PAS may be older one and sometime unable to measures the performance of the employees. Hence in this paper a company CCI is selected which has given the time and information to analyse their system and an improved system made by the researchers already were also used by taking a census survey of all employees of the company. To test the hypothesis independent sample t test was used with SPSS-19 software. It was found that the company’s current PA system has some hidden difficulties and the new system is able to measure the employees potential in well manner

Eco-designed recycled newspaper for energy harvesting and pressure sensor applications

We acknowledge the project BRIGHT (Project reference: M-ERA-NET3/0004/2021). This work was also partially financed by FEDER funds through the COMPETE 2020. This work was also partially supported by European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement 101070255 (REFORM, HORIZON-CL4-2021-DIGITAL-EMERGING-01). Partly of this work was also supported by LISBOA-05-3559-FSE-000007 and CENTRO-04-3559-FSE-000094 operations, co-funded by the Lisboa 2020, Centro 2020 programme, Portugal 2020, European Union, through the European Social Fund, as well as by Fundação para a Ciência e Tecnologia (FCT) and Agência Nacional de Inovação (ANI). Publisher Copyright: © 2023 The AuthorsThis study focuses on developing multifunctional electronic paper (e-paper) using a low-cost recycling method to minimize the usage of critical raw materials. The e-paper is designed for various smart applications, such as mechano-responsive energy harvesters and pressure sensors. The emphasis is on adopting an eco-friendly approach by utilizing cellulose extracted from used newspapers, which would otherwise have been discarded. The formulated e-paper contains 100 % recycled cellulose fibers, unlike the more commonly used recycled paper, which contains around 70 % of recycled cellulose and 30 % of new pulp. The recycled paper (RP) was functionalized using polyaniline (PANi), resulting in a conductive e-paper, capable of generating electric current through a charge transfer mechanism at the PANi-Cellulose/electrode interface layer. The resulting devices demonstrate satisfactory energy production, with output voltage ranging from 16.8 to 20.25 V, output current ranging from 0.9 µA to 1.75 µA, and power density ranging from 0.18 to 0.35 Wm−2. The mechanical impulses generated by the device can successfully light up several LEDs in series. Additionally, the e-paper was investigated as a flexible, paper-based pressure sensor. The fabricated device exhibited excellent sensitivity, fast response time, and a wide detection range from 25 Pa to 12.25 kPa. The sensitivity of the pressure sensors achieved 4.21 kPa−1 within a low range of 0–1 kPa and approximately 0.008 kPa-1for a broader pressure range (2 – 12.25 kPa). Additionally, the durability of the pressure sensing devices has undergone rigorous testing, surpassing 2000 cyclic tests.publishersversionpublishe

Air pollution perception in ten countries during the COVID-19 pandemic

NTNU Norwegian University of Science and TechnologypublishedVersionPaid Open AccessUNIT agreemen

Response of Viscoelastic Turbulent Pipeflow Past Square Bar Roughness: The Effect on Mean Flow

The influence of viscoelastic polymer additives on response and recovery of turbulent pipeflow over square bar roughness elements was examined using Direct Numerical Simulations at a Reynolds number of 5×103. Two different bar heights for the square bar roughness elements were examined, h/D=0.05 and 0.1. A Finitely Extensible Non-linear Elastic-Peterlin (FENE-P) rheological model was employed for modeling viscoelastic fluid features. The rheological parameters for the simulation corresponded to a high concentration polymer of 160 ppm. Recirculation regions formed behind the bar elements by the viscoelastic fluid were shorter than those associated with Newtonian fluid, which was attributed to mixed effects of viscous and elastic forces due to the added polymers. The recovery of the mean viscoelastic flow was faster. The pressure losses on the surface of the roughness were larger compared to the Newtonian fluid, and the overall contribution to local drag was reduced due to viscoelastic effects

XBRL Acceptance in India: A Behavioral Study

XBRL is fast becoming the new paradigm for reporting of financial information digitally. XBRL brings structure to business information with comprehensive description and contextual information for advanced analysis. It enhances the efficiency of financial reporting, accuracy, timeliness and reliability of financial data. Many Indian companies still resist using it. The present research uses technology acceptance model to analyze the perception of financial experts in respect of acceptance of XBRL as reporting method. The result revealed that using XBRL increases productivity but interacting with the XBRL requires lot of mental efforts. These findings can be an empirical and theoretical foundation to accelerate the adoption of XBRL in India. &nbsp

Data_Sheet_1_Investigation and evidence of high-episodic groundwater recharge events in tropical hard-rock aquifers of southern India.docx

Processes controlling groundwater recharge have been a topic of pursuit in the hydrological research community. The groundwater recharge in hard-rock aquifers is significantly impacted by rainfall patterns, aquifer characteristics, weathering/soil conditions, topography, land use, and land cover. Analysis of the recharge process in tropical semi-arid hard-rock aquifer regions of southern India is crucial due to several factors, including (a) a heavily tailed monsoon system prevailing in the region, which is characterized by very few episodic storm events; (b) heterogeneity of aquifers in terms of fractures; and (c) the presence of several man-made irrigation lakes/tanks along with the drainage network. This study uses a lumped unconfined aquifer model to estimate the groundwater recharge for nine locations in Gundlupet taluk and 150 locations in Berambadi Experimental Watershed (EWS) in the south Indian state of Karnataka. Analysis of estimated recharge factors identifies 30 high-episodic recharge events out of 292 observations (around 10%) in Gundlupet taluk and 80 out of 150 locations in 2017 in Berambadi EWS. Partial information correlation (PIC) analysis is used to select the significant predictors out of potential predictors based on rainfall intensity distribution and climatological indices. PIC analysis reveals that the number of rainfall events with 15–30 mm daily rainfall intensity are most significant for normal recharge events in Gundlupet taluk and Berambadi EWS. The combined information on daily rainfall distribution, daily rainfall events of 20–40 mm, and the number of La Niña months in a particular year can explain the variability of high-episodic recharge events in Gundlupet taluk. These high-intensity rainfall events can be potential sources of alternate recharge pathways resulting in faster indirect recharge, which dominates the diffused recharge and results in high-episodic recharge events. Rainfall intensity distribution and climatological indices contain the potential information required to disaggregate normal and high-episodic recharge factors for future rainfall projections, which is useful for future groundwater level projections.</p

FloodNet-to-FloodGAN : Generating Flood Scenes in Aerial Images

A global rise in the occurrences of natural disasters and human-borne conflicts has put a spotlight on the need for Earth Observation (EO) data in designing practical Humanitarian Assistance and Disaster Relief (HADR) interventions. Novel techniques that leverage remotely sensed data are leading to a paradigm shift in our understanding of such situations and improving the efficacy of our response. Aerial flood maps can provide localized insight into the extent of flood-related damage and the degree to which communities' access to shelter, clean water, and communication channels have been compromised. Unfortunately, such insights typically only emerge hours or days after a flooding event has occurred. Moreover, a dearth of available historical data restricts the development of practical machine learning based methods. This work examines the use of Generative Adversarial Networks (GANs) in simulating flooding in aerial images. We first introduce the Houston UAV dataset, an extension of the FloodNet dataset. Our dataset accommodates more well-defined semantic classes and significantly reduces the label noise in semantic masks. We propose a GAN-based pipeline to generate flood conditions in non-flooded regions, generating synthetic flooding scenes for predictive mapping. Code and dataset are available at https://github.com/granularai/flood-synthesis