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Fouling not only deteriorates the membrane structure but also compromises the quality of the permeate and has deleterious consequences on the membrane operation. In the current study, a commercial thin film composite nanofiltration membrane (NF90) was modified by sequentially depositing oppositely charged polycation (poly(allylamine hydrochloride)) and polyanion (poly(acrylic acid)) polyelectrolytes using the layer-by-layer assembly method. The water contact angle was decreased by ~10° after the coating process, indicating increased hydrophilicity. The surface roughness of the prepared membranes decreased from 380 nm (M-0) to 306 nm (M-10) and 366 nm (M-20). M-10 membrane showed the highest permeate flux of 120 L m−2 h−1 with a salt rejection of >98% for MgSO4 and NaCl. The fabricated membranes M-20 and M-30 showed 15% improvement in fouling resistance and maintained the initial permeate flux longer than the pristine membrane.

Abstract The Al-TiC sintered nano composites which are difficult to machining by conventional techniques can be easily machined with Electrical Discharge Machining (EDM). Machining parameters (Current, pulse-on time, gap voltage), output parameters [Metal Removal Rate (MRR) & Tool Wear Rate (TWR)] were taken into consideration & were optimized by Grey relational analysis. Analysis of Variance (ANOVA) is used to determine the most contributing parameters towards the responses. It exhibits that the performance characteristics of the EDM process (MRR & TWR) were improved by using the techniques proposed in this study. The confirmation test was used to evaluate the effectiveness. In a nutshell, the developmental model has good adequacy, which can be used to obtain the future value with minimum error which can be confirmed through validation and also find out the craters evolution on EDM process by Scanning Electron Microscope (SEM) analysis.

AbstractWildlife management in rapid changing landscapes requires critical planning through cross cutting networks, and understanding of landscape features, often affected by the anthropogenic activities. The present study demonstrates fine-scale spatial patterns of genetic variation and contemporary gene flow of red panda (Ailurus fulgens) populations with respect to landscape connectivity in Kangchenjunga Landscape (KL), India. The study found about 1,309.54 km2 area suitable for red panda in KL—India, of which 62.21% area fell under the Protected Area network. We identified 24 unique individuals from 234 feces collected at nine microsatellite loci. The spatially explicit and non-explicit Bayesian clustering algorithms evident to exhibit population structuring and supported red panda populations to exist in meta-population frame work. In concurrence to the habitat suitability and landscape connectivity models, gene flow results supported a contemporary asymmetric movement of red panda by connecting KL—India in a crescent arc. We demonstrate the structural-operational connectivity of corridors in KL—India that facilitated red panda movement in the past. We also seek for cooperation in Nepal, Bhutan and China to aid in preparing for a comprehensive monitoring plan for the long-term conservation and management of red panda in trans-boundary landscapes.

Automated disease prediction has now become a key concern in medical research due to exponential population growth. The automated disease identification framework aids physicians in diagnosing disease, which delivers accurate disease prediction that provides rapid outcomes and decreases the mortality rate. The spread of Coronavirus disease 2019 (COVID-19) has a significant effect on public health and the everyday lives of individuals currently residing in more than 100 nations. Despite effective attempts to reach an appropriate trend to forecast COVID-19, the origin and mutation of the virus is a crucial obstacle in the diagnosis of the detected cases. Even so, the development of a model to forecast COVID-19 from chest X-ray (CXR) and computerized tomography (CT) images with the correct decision is critical to assist with intelligent detection. In this paper, a proposed hybrid model of the artificial neural network (ANN) with parameters optimization by the butterfly optimization algorithm has been introduced. The proposed model was compared with the pretrained AlexNet, GoogLeNet, and the SVM to identify the publicly accessible COVID-19 chest X-ray and CT images. There were six datasets for the examinations: three datasets with X-ray pictures and three with CT images. The experimental results approved the superiority of the proposed model for cognitive COVID-19 pattern recognition with average accuracy 90.48, 81.09, 86.76, and 84.97% for the proposed model, support vector machine (SVM), AlexNet, and GoogLeNet, respectively.

This paper presents a critical synthesis of research on written corrective feedback (WCF) and its effects on second language (L2) learning over the past four decades. WCF is an essential component of L2 teaching. However, whether WCF helps has been an issue of considerable debate in the literature. While many researchers have stressed its importance, some others have expressed doubt concerning its effectiveness. The controversy over the effectiveness of WCF was heightened when Truscott argued in 1996 that error correction is ineffective and harmful and others who strongly countered his argument that feedback is effective (e.g. Chandler 2003; Ferris 1999). This article provides an in-depth synthesis and analysis of this area of research, examining key issues and findings as well as the various contentions and concerns raised regarding the effects of WCF. The article concludes with implications for future research and with insights about how to move forwards.

Collective action is a key driver of social and political change within societies. So far, the main factor mobilizing individuals into collective action remains the extent to which they feel identified with a protesting group (i.e., social identification). Although the link between social identification and collective action is well-established, current evidence relies mostly on self-report data. To tackle this issue, we combined real-life protest counts in the United States (2017–2020) with online search data (Google Trends) for pronouns indicating a “group” mind-set (first-person plural pronouns; e.g., “we,” “us”). Time series analyses indicated that weekly fluctuations in searches ( N = 164) predict both protest and protester counts over time. Confirmatory mixed models then showed that a 1% increase in pronoun searches was linked with +13.67% protests (95% CI [4.02, 23.32]) and +47.45% protesters (95% CI [26.54, 68.36]) the following week. These original results have important implications for the ecological study and quantification of collective action dynamics in psychology.

A series of 16-(α-alkoxyalkane)-17-hydrazino-estra-1(10),2,4-trien[17,16-c]-3-ol (3a–l) and estra-1(10),2,4-trien-[17,16-c]pyrazoline-3-ol derivatives (4a–d) were synthesized from corresponding arylidines 2a,b which was prepared from estrone 1 as starting material. Condensation of 1 with aldehydes gave the corresponding arylidine derivatives 2a,b which were treated with hydrazine derivatives in alcohols to give the corresponding derivatives 3a–l, respectively. Additionally, treatment of 2a,b with methyl- or phenylhydrazine in ethanolic potassium hydroxide afforded the corresponding N-substituted pyrazoline derivatives 4a–d, respectively. All these derivatives showed potent anti-ovarian cancer both in vitro and in vivo. The mechanism of anti-ovarian cancer was suggested to process via topoisomerase II and V600EBRAF inhibition.

The Hunder Dunes occur in the Shyok valley, Ladakh region, north-western India. These barchanoid and transverse dunes consist of sand reworked from the seasonally exposed beds of the river. Wind di...