Colourimetric analysis and antimicrobial study of natural dyes and dyed silk

Colourimetric and antimicrobial activities of natural colourants and dyed silk have been studied. The colour strength (K/S) values were increased with increase in dye absorbance. The absorption of dyes on silk yarns was obtained from 10.56 to 39.48% at 5% concentration of dye from different plant extracts. The colourimetric parameters L¹, a¹, b¹, C, and H were measured for depth of the colour. The dyed silk with natural colourants displayed excellent antimicrobial activity (reduction rate: 25–65%) against the bacteria Escherichia coli and (reduction rate: 3–68%) against the fungal strain Aspergillus niger. The dyed silk exhibited good and durable fastness properties.     

Long-term effect of rice-based farming systems on soil health

Integrated rice–fish culture, an age-old farming system, is a technology which could produce rice and fish sustainably at a time by optimizing scarce resource use through complementary use of land and water. An understanding of microbial processes is important for the management of farming systems as soil microbes are the living part of soil organic matter and play critical roles in soil C and N cycling and ecosystem functioning of farming system. Rice-based integrated farming system model for small and marginal farmers was established in 2001 at Central Rice Research Institute, Cuttack, Odisha. The different enterprises of farming system were rice–fish, fish–fingerlings, fruits, vegetables, rice–fish refuge, and agroforestry. This study was conducted with the objective to assess the soil physicochemical properties, microbial population, carbon and nitrogen fractions, soil enzymatic activity, and productivity of different enterprises. The effect of enterprises induced significant changes in the chemical composition and organic matter which in turn influenced the activities of enzymes (urease, acid, and alkaline phosphatase) involved in the C, N, and P cycles. The different enterprises of long-term rice-based farming system caused significant variations in nutrient content of soil, which was higher in rice–fish refuge followed by rice–fish enterprise. Highest microbial populations and enzymatic properties were recorded in rice–fish refuge system because of waterlogging and reduced condition prolonged in this system leading to less decomposition of organic matter. The maximum alkaline phosphatase, urease, and FDA were observed in rice–fish enterprise. However, highest acid phosphatase and dehydrogenase activity were obtained in vegetable enterprise and fish–fingerlings enterprise, respectively.     

Detecting Extinction Risk from Climate Change by IUCN Red List Criteria

Anthropogenic climate change is a key threat to global biodiversity. To inform strategic actions aimed at conserving biodiversity as climate changes, conservation planners need early warning of the risks faced by different species. The IUCN Red List criteria for threatened species are widely acknowledged as useful risk assessment tools for informing conservation under constraints imposed by limited data. However, doubts have been expressed about the ability of the criteria to detect risks imposed by potentially slow‐acting threats such as climate change, particularly because criteria addressing rates of population decline are assessed over time scales as short as 10 years. We used spatially explicit stochastic population models and dynamic species distribution models projected to future climates to determine how long before extinction a species would become eligible for listing as threatened based on the IUCN Red List criteria. We focused on a short‐lived frog species (Assa darlingtoni) chosen specifically to represent potential weaknesses in the criteria to allow detailed consideration of the analytical issues and to develop an approach for wider application. The criteria were more sensitive to climate change than previously anticipated; lead times between initial listing in a threatened category and predicted extinction varied from 40 to 80 years, depending on data availability. We attributed this sensitivity primarily to the ensemble properties of the criteria that assess contrasting symptoms of extinction risk. Nevertheless, we recommend the robustness of the criteria warrants further investigation across species with contrasting life histories and patterns of decline. The adequacy of these lead times for early warning depends on practicalities of environmental policy and management, bureaucratic or political inertia, and the anticipated species response times to management actions. Detección del Riesgo de Extinción a partir del Cambio Climático por medio del Criterio de la Lista Roja de la UICNKeith et al.     

Approaches for prevention and environmental management of novel COVID-19

Environmental Science and Pollution Research - The World Health Organization (WHO) recognized a novel coronavirus as the causative agent of a new form of pneumonia. It was subsequently named...     

Energy management in hybrid electric vehicles using optimized radial basis function neural network

This paper deals with energy management in hybrid electric vehicles. Use of radial basis function neural network (RBFNN) for the problem of energy management gains importance in the present decade. Use of genetic algorithm (GA) and particle swarm optimization (PSO) as optimization algorithms for parameter estimation is also well known. However, none of the researchers in the area tried to use GA and PSO as training algorithms for the problem. Hence in this paper, we propose two novel methods, based on RBFNN. The difference between RBFNN-based approaches in the literature and those used in this paper is the use of GA and PSO (i.e. optimising algorithms) as training algorithm to train RBFNNs. Interestingly, it is seen that the proposed approaches of this paper outperform RBFNN-based approaches in the literature with traditional training.     

Fire Management,Managed Relocation,and Land Conservation Options for Long‐Lived Obligate Seeding Plants under Global Changes in Climate,Urbanization, and Fire Regime

Most species face multiple anthropogenic disruptions. Few studies have quantified the cumulative influence of multiple threats on species of conservation concern, and far fewer have quantified the potential relative value of multiple conservation interventions in light of these threats. We linked spatial distribution and population viability models to explore conservation interventions under projected climate change, urbanization, and changes in fire regime on a long‐lived obligate seeding plant species sensitive to high fire frequencies, a dominant plant functional type in many fire‐prone ecosystems, including the biodiversity hotspots of Mediterranean‐type ecosystems. First, we investigated the relative risk of population decline for plant populations in landscapes with and without land protection under an existing habitat conservation plan. Second, we modeled the effectiveness of relocating both seedlings and seeds from a large patch with predicted declines in habitat area to 2 unoccupied recipient patches with increasing habitat area under 2 projected climate change scenarios. Finally, we modeled 8 fire return intervals (FRIs) approximating the outcomes of different management strategies that effectively control fire frequency. Invariably, long‐lived obligate seeding populations remained viable only when FRIs were maintained at or above a minimum level. Land conservation and seedling relocation efforts lessened the impact of climate change and land‐use change on obligate seeding populations to differing degrees depending on the climate change scenario, but neither of these efforts was as generally effective as frequent translocation of seeds. While none of the modeled strategies fully compensated for the effects of land‐use and climate change, an integrative approach managing multiple threats may diminish population declines for species in complex landscapes. Conservation plans designed to mitigate the impacts of a single threat are likely to fail if additional threats are ignored. Manejo de Incendios, Reubicación Administrada y Opciones de Conservación de Suelo para Plantas de Vida Larga con Sembrado Obligado bajo los Cambios Globales en el Clima, la Urbanización y el Régimen de Incendios     

Molecular identification and nanoremediation of microbial contaminants in algal systems using untreated wastewater

Wastewater-algal biomass is a promising option to biofuel production. However, microbial contaminants constitute a substantial barrier to algal biofuel yield. A series of algal strains, Nannochloris oculata and Chlorella vulgaris samples (n = 30), were purchased from the University of Texas, and were used for both stock flask cultures and flat-panel vertical bioreactors. A number of media were used for isolation and differentiation of potential contaminants according to laboratory standards (CLSI). Conventional PCR amplification was performed followed by 16S rDNA sequencing to identify isolates at the species level. Nanotherapeutics involving a nanomicellar combination of natural chitosan and zinc oxide (CZNPs) were tested against the microbial lytic groups through Minimum Inhibitory Concentration (MIC) tests and Transmission Electronic Microscopy (TEM). Results indicated the presence of Pseudomonas spp., Bacillus pumilus/ safensis, Cellulosimicrobium cellulans, Micrococcus luteus and Staphylococcus epidermidis strains at a substantial level in the wastewater-fed algal reactors. TEM confirmed the effectiveness of CZNPs on the lytic group while the average MICs (mg/mL) detected for the strains, Pseudomonas spp, Micrococcus luteus, and Bacillus pumilus were 0.417, 3.33, and 1.458, respectively. Conclusively, CZNP antimicrobials proved to be effective as inhibitory agents against currently identified lytic microbial group, did not impact algae cells, and shows promise for in situ interventions.     

Methane and nitrous oxide emissions from an integrated rainfed rice–fish farming system of Eastern India

Integration of fish stocking with rice (Oryza sativa L.) cultivation promises an ecologically sound and environmentally viable management of flooded ecosystem. Rice agriculture contributes to the emission of greenhouse gases CH₄ and N₂O, but little is known on the effect of fish rearing in fields planted to rice on the emission of these two greenhouse gases. In a field study, CH₄ and N₂O fluxes were measured from a sub-humid tropical rice field of Cuttack, eastern India, as affected by integrated rice–fish farming under rainfed lowland conditions. Three Indian major carps, Catla catla H., Labeo rohita H. and Cirrhinus mrigala H., and Puntius gonionotus B. were stocked in rice fields planted to two rice cultivars in a split-plot design with no fish and fish as the main treatments and two rice varieties as sub-treatments with three replicates each. Fish rearing increased CH₄ emission from field plots planted to both the rice cultivars with 112% increase in CH₄ emission in cv. Varshadhan and 74% in case of cv. Durga. On the contrary, fish stocking reduced N₂O emission from field plots planted to both the rice varieties. Movement of fish and associated bioturbation coupled with higher dissolved organic-C and CH₄ contents, and lower dissolved oxygen could be the reasons for release of larger quantities of CH₄ from rice + fish plots, while higher dissolved oxygen content might have influenced release of more N₂O from the rice alone treatment. The total greenhouse gas emission, expressed as CO₂ equivalent global warming potential (GWP), was considerably higher from rice + fish plots with CH₄ contributing a larger share (91%) as compared to rice alone plots (78–81%). On the contrary, N₂O had a comparatively lesser contribution with 19–22% share in rice alone plots that was further reduced to 9% in rice + fish plots. However, considering the profit-loss analysis based on the market price of the produce, rice–fish system provided a net profit of $453.36 ha^?1 over rice alone system in spite of higher carbon credit compliance of a rice–fish ecosystem due to larger cumulative GWP.     

Differential pulse adsorptive stripping voltammetric determination of simeton in its formulations and vegetables

A sensitive adsorptive stripping voltammetric method for the determination of simeton with universal buffer solution has been described. The method was based on the adsorption accumulation of simeton at a hanging mercury drop electrode. The overall reduction process is under controlled diffusion. The adsorptive peak was observed at ?0.8 V vs SCE in acidic solution 2 < pH < 6. The peak response was characterized with respect to pH, accumulation potential, time, and scan rate. The calibration plot was found to be linear from 1.13 × 10^???5 to 3.5 × 10^???8 M with a limit of detection of 2.0 × 10^???8 M. Finally, the method has been applied for the determination of simeton in its formulations and vegetable samples.