Exploring synergies and trade-offs among the sustainable development goals: collective action and adaptive capacity in marginal mountainous areas of India

Global environmental change (GEC) threatens to undermine the sustainable development goals (SDGs). Smallholders in marginal mountainous areas (MMA) are particularly vulnerable due to precarious livelihoods in challenging environments. Acting collectively can enable and constrain the ability of smallholders to adapt to GEC. The objectives of this paper are: (i) identify collective actions in four MMA of the central Indian Himalaya Region, each with differing institutional contexts; (ii) assess the adaptive capacity of each village by measuring livelihood capital assets, diversity, and sustainable land management practices. Engaging with adaptive capacity and collective action literatures, we identify three broad approaches to adaptive capacity relating to the SDGs: natural hazard mitigation (SDG 13), social vulnerability (SDG 1, 2 and 5), and social–ecological resilience (SDG 15). We then develop a conceptual framework to understand the institutional context and identify SDG synergies and trade-offs. Adopting a mixed method approach, we analyse the relationships between collective action and the adaptive capacity of each village, the sites where apparent trade-offs and synergies among SDGs occur. Results illustrate each village has unique socio-environmental characteristics, implying distinct development challenges, vulnerabilities and adaptive capacities exist. Subsequently, specific SDG synergies and trade-offs occur even within MMA, and it is therefore crucial that institutions facilitate locally appropriate collective actions in order to achieve the SDGs. We suggest that co-production in the identification, prioritisation and potential solutions to the distinct challenges facing MMA can increase understandings of the specific dynamics and feedbacks necessary to achieve the SDGs in the context of GEC

Design, Formulation and Evaluation of Drug Loaded Nanoparticles of Naproxen by Using Eudragit Rs-100

In this research work we formulated biodegradable polymethyl metha crylate and eudragit RS-100 nanoparticles (NPs) containing Naproxen by nano-precipitation solvent displacement method to achieve a better free release profile for intra articular injection with improved efficacy. Dissolution study was revealed that increase the release of Naproxen from NPs. The particle size and size distribution of the Naproxen loaded PMMA and Eudragit Rs 100 nanoparticles were characterized by using a Zetasizer. The in vitro drug release indicated that the formulation NA2, NA4, NA5 And NA7 were not suitable for anti-inflammatory agent of drug as maximum amount of drug was released in the physiological environment of stomach and small intestine within 5 hours. Whereas, NA1, NA3 and NA6 formulations have released small amount of drug within 5 hours and 81.16%, 78.12% and 82.54% of drug was targeted to anti-inflammatory region from NA1,NA3and NA7. The results indicated that the prepared formulation was intact upto 12hrs. and transit was clearly seen. Drug release mechanism followed Non-Fickian transport

Analytical method Development and validation of Ivabradine by using RP-HPLC

The RP-HPLC method, which makes use of an XTERR C8 column (150mm × 4.6mm, 3.5μm) and a mobile phase of acetonitrile:0.01N KH2PO4(60:40) of HPLC grade, became created and accepted to be used in Ivabradine analysis. Buffer's pH became stored at 3. After being subjected to a 10-minute sonication, the use of a 0.45μm Nylon clear out, A 0.9mL/min waft charge became used to clear out the cellular section. After 260 nm of detection, it became observed that Ivabradine had a 1.846-minute retention period. Linearity became found with equation y=14200x+106895, from 80–120 μg/mL (R2 became the coefficient of determination). ICH hints had been accompanied with inside the validation of the approach

SMART CRAWLER: A TWO-STAGE CRAWLER FOR EFFICIENTLY HARVESTING DEEP-WEB INTERFACES

Deep web growingat a very fast pace, lot of speculations in techniques this techniques has been added thathelpefficientlylocate deep-web interfaces. However, due to the large volume of web resources and the dynamic nature of deep web, achieving wide coverage and high efficiency is a challenging issue. In this paper author has proposed a two-stage framework, namely Smart Crawler, for efficient harvesting deep web interfaces. Smart Crawler performs site-based searching for center pages by usingsearch engines, avoiding visiting a large number of pages. To achieve more accurate results for a focused crawl, Smart Crawler techniques prioritize websites to highly relevant ones for a given topic. Smart Crawler achieves fast in-site searching by findingmost relevant links with an adaptive link-ranking. To eliminate bias on visiting some relevant links in hidden web directories, author has designeda link tree data structure to achieve wider coverage for a website