Effect of Aggregate Flakiness on the Compressive Strength of Concrete Cubes

In this paper effects of aggregate flakiness on the compressive strength of concrete cubes have been studied using experiments. Total 30 cubes have been cast using normal, 5% of 8 mm, 10 mm and 12 mm size of flaky aggregates and 10% of 12mm size of flaky aggregate. NDT of the cast cubes using rebound hammer and ultrasonic pulse velocity have been also carried out. Aall the cubes were tested for compressive strength. Based on these data, comparative studies have been carried out to quantify the effect of flakiness and salient conclusions are drawn. Most Searchable Keywords what is flaky aggregate, flaky aggregate, the flaky aggregate is when flaky aggregate size,flaky aggregates,flaky aggregate is when, the flaky aggregates is when, mean dimension of aggregate, the flaky aggregate, flakiness of aggregate, flakiness index, effect of flaky aggregates on concrete, flakiness, factors affecting aggregate impact value, flaky shape aggregate, flakiness and elongation test procedure, flakiness and elongation, shape test of aggregate, flakiness and elongation test, flaky aggregate least dimensio

Structure based de novo design of IspD inhibitors as anti-tubercular agents

Tuberculosis is one of the leading contagious diseases, caused by Mycobacterium tuberculosis. Despite improvements in anti-tubercular agents, it remains one of the most prevalent infectious diseases worldwide, responsible for a total of 1.6 million deaths annually. The emergence of multidrug resistant strains highlighted the need of discovering novel drug targets for the development of anti-tubercular agents. 2-C-methyl-D-erythritol-4-phosphate cytidyltransferase (IspD) is an enzyme involved in MEP pathway for isoprenoid biosynthesis, which is considered an attractive target for the discovery of novel antibiotics for its essentiality in bacteria and absence in mammals. In the present study, we have employed structure based drug design approach to develop novel and potent inhibitors for IspD receptor. To explore binding affinity and hydrogen bond interaction between the ligand and active site of IspD receptor, docking studies were performed. ADMET and synthetic accessibility filters were used to screen designed molecules. Finally, ten compounds were selected and subsequently submitted for the synthesis and in vitro studies as IspD inhibitors

An approach for fault detection and location in solar PV systems

The task of fault detection and diagnosis in large-scale photovoltaic (PV) plants is expected to be a major challenge as more and more plants with increasingly large capacities continue to come into existence. To maintain safety, reliability, and productivity of large-scale PV plants it is essential to develop approaches that allow automatic detection and location of any mal-operation among thousands of PV modules. This paper proposes an approach to detect PV plant faults through the generation of fault indicator signals called ‘residuals’ for each string and the comparison of residuals with a threshold value. Furthermore, a regression-based approach is proposed to estimate fault location as a function of fault current and irradiance level measurements. The proposed approach is demonstrated by specifically focusing on intra-string line-line faults. Various line-line fault case studies are verified through simulations and validated on an experimental setup in a solar PV plant. Initially the approach is developed for a fixed size PV array, but subsequently extensions of the proposed approach to any array size are developed and presented. The generalisation potential of the approach is demonstrated through successful validation on multiple PV array configurations

PV module degradation analysis and impact on settings of overcurrent protection devices

Degradation of photovoltaic (PV) modules is inevitable regardless of the size of a PV plant. While it is understood that degradation leads to a reduction in power generation, the effects of module degradation on PV plant protection system remains somewhat unclear. Considering that most of the PV plant protection system settings are based on modules in good conditions without degradation, it is imperative to evaluate the effect of module degradation on fault detectability by conventional protection infrastructure to ensure safety and reliability of PV plants. The purpose of this paper is to investigate the relationship between the levels of module degradation and PV plant faults including fault current levels, fault locations and types of faults. An experimental setup comprising of 16 modules of varying degradation levels is used to generate multiple short circuit fault scenarios. The results indicate that degradation results in a decrease in string current, which may lead to an increased likelihood of fault undetectability using conventional protection settings

A technique for fault detection, identification and location in solar photovoltaic systems

Due to exponential growth of large-scale PV plants, automatic approaches for PV system protection are gaining prodigious importance. Even with the use of standard protection devices, faults in PV arrays may remain undetected. To address such an important issue, this paper focuses on string level monitoring to develop the functionality of automatic fault detection, location and fault type identification. The fault detection is achieved through the generation of fault indicator signals called residuals and comparison with a pre-set threshold. The automatic identification of fault type is achieved by the development of a procedure reliant on the variations in the string current profiles relative to the type of fault. Finally, the location of faults is estimated through the combination of analytical and regression expressions reliant on fault type, irradiance levels and string current measurements. Various line-line fault cases are tested and verified using the proposed method through simulations and experiments. The proposed method is experimentally evaluated for multiple fault scenarios on an experimental setup located within an existing solar farm to emulate conditions akin to real world solar farms

bddashboard: An infrastructure for biodiversity dashboards in R

The bdverse is a collection of packages that form a general framework for facilitating biodiversity science in R (programming language). Exploratory and diagnostic visualization can unveil hidden patterns and anomalies in data and allow quick and efficient exploration of massive datasets. The development of an interactive yet flexible dashboard that can be easily deployed locally or remotely is a highly valuable biodiversity informatics tool. To this end, we have developed 'bddashboard', which serves as an agile framework for biodiversity dashboard development. This project is built in R, using the Shiny package (RStudio, Inc 2021) that helps build interactive web apps in R. The following key components were developed:Core Interactive Components The basic building blocks of every dashboard are interactive plots, maps, and tables. We have explored all major visualization libraries in R and have concluded that 'plotly' (Sievert 2020) is the most mature and showcases the best value for effort. Additionally, we have concluded that 'leaflet' (Graul 2016) shows the most diverse and high-quality mapping features, and DT (DataTables library) (Xie et al. 2021) is best for rendering tabular data. Each component was modularized to better adjust it for biodiversity data and to enhance its flexibility.Field Selector The field selector is a unique module that makes each interactive component much more versatile. Users have different data and needs; thus, every combination or selection of fields can tell a different story. The field selector allows users to change the X and Y axis on plots, to choose the columns that are visible on a table, and to easily control map settings. All that in real-time, without reloading the page or disturbing the reactivity. The field selector automatically detects how many columns a plot needs and what type of columns can be passed to the X-axis or Y-axis. The field selector also displays the completeness of each field. Plot Navigation We developed the plot navigation module to prevent unwanted extreme cases. Technically, drawing 1,000 bars on a single bar plot is possible, but this visualization is not human-friendly. Navigation allows users to decide how many values they want to see on a single plot. This technique allows for fast drawing of extensive datasets without affecting page reactivity, dramatically improving performance and functioning as a fail-safe mechanism. Reactivity Reactivity creates the connection between different components. The changes in input values automatically flow to the plots, text, maps, and tables that use the input, and cause them to update. Reactivity facilitates drilling down functionality, which enhances the user’s ability to explore and investigate the data. We developed a novel and robust reactivity technique that allows us to add a new component and effectively connect it with all existing components within a dashboard tab, using only one line of code.Generic Biodiversity Tabs We developed five useful dashboard tabs (Fig. 1): (i) the Data Summary tab to give a quick overview of a dataset; (ii) the Data Completeness tab helps users get valuable information about missing records and missing Darwin Core fields; (iii) the Spatial tab is dedicated to spatial visualizations; (iv) the Taxonomic tab is designed to visualize taxonomy; and (v) the Temporal tab is designed to visualize time-related aspects. Performance and Agility To make a dashboard work smoothly and react quickly, hundreds of small and large modules, functions, and techniques must work together. Our goal was to minimize dashboard latency and maximize its data capacity. We used asynchronous modules to write non-blocking code, clusters in map components, and preprocessing and filtering data before passing it to plots to reduce the load. The 'bddashboard' package modularized architecture allows us to develop completely different interactive and reactive dashboards within mere minutes

3D-QSAR and molecular docking analysis of (4-piperidinyl)-piperazines as acetyl-CoA carboxylases inhibitors

Acetyl-CoA carboxylase (ACC) is a crucial metabolic enzyme, which plays a vital role in fatty acid metabolism and obesity induced type 2 diabetes. Herein, we have performed 3D-QSAR and molecular docking analysis on a novel series of (4-piperidinyl)-piperazines to design potent ACC inhibitors. This study correlates the ACC inhibitory activities of 68 (4-piperidinyl)-piperazine derivatives with several stereo-chemical parameters representing steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields. The CoMFA and CoMSIA models exhibited excellent rncv2 values of 0.974 and 0.985, and rcv2 values of 0.671 and 0.693, respectively. CoMFA predicted rpred2 of 0.910 and CoMSIA predicted rpred2 of 0.963 showed that the predicted values were in good agreement with experimental values. Glide5.5 program was used to explore the binding mode of inhibitors inside the active site of ACC. We have accordingly designed novel ACC inhibitors by utilising the LeapFrog and predicted with excellent inhibitory activity in the developed models