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Gel electrophoresis (GE) is the most preferred and adapted technique for the separation and identification of biological molecules like proteins/peptides and nucleic acids from diverse types of organisms. All over the world, researchers, educators, and students aspiring to work in biochemistry and molecular biology disciplines use the polyacrylamide gel electrophoresis (PAGE) technique for resolving proteins/nucleic acids for understanding the structure and function of any cell. A simple PAGE technique requires a wide range of chemicals/reagents along with a well-equipped and well-spaced laboratory. We have developed a compact and impeccable mobile electrophoresis kit suitable for any vertically oriented PAGE technique. This comprehensive and portable laboratory set-up provides the complete advantages of safety, cost-efficiency, space management, and utility to the researchers for high-throughput research. All new equipment of the mobile electrophoresis kit is fabricated using inexpensive and off-the-rack components. Overall performance of the mobile kit was verified through a practical exercises executed by high school students with positive outcomes.

Introduction: Bottom sediments play a pivotal role in wetland productivity, and here, eight Gangetic floodplain wetlands of India were studied to assess the sediment physicochemical characteristics and textural analysis. Methods: Sediment samples that were collected from each wetland in monsoon and non-monsoon seasons were analysed. ANOVA, Principal component analysis and multiple correlation analysis were used for statistical analysis. Results and Discussion: Throughout the study period, pH (6.90-8.04), EC (0.20-1.64 dS/m), CaCO3 (1.75%-14.50%), available nitrogen (10.22-22.23 mg/ 100 g sediment), total nitrogen (80.4-333.8 mg/100 g sediment), available phosphorus (0.20-5.61 mg/100 g sediment), and total phosphorus (19.63-173.33 mg/100 g sediment) were recorded. The sediment quality parameters differ significantly (p > 0.05) among the wetlands. Seasonal variation was only observed on total nitrogen and total phosphorus contents. Sediments were dominated by sand. Sediment nutrient (C, N, and P) stoichiometry of wetlands depicted a comparatively little higher C/P (5.96-66.32) ratio and lower C/N (3.34-22.76) and N/P (1.12-9.25) ratios, which revealed that the physicochemical characteristics of the sediments are influenced by anthropogenic sources. Principal component analysis showed the influence of both natural and anthropogenic causes on wetland ecosystems. The geographic information system (GIS) interpolation approach was used in combination with laboratory analysis methods to give a complete spatial resolution of the sediment quality of each wetland. The study suggests that these wetlands' sediment quality is favorable for fish culture but requires proper management practices to achieve sustainable production. As it is the first time where monitoring physicochemical properties of sediments of these wetlands are presented, this study can be used as a baseline data for comparison in future environmental assessments of the wetlands. [ABSTRACT FROM AUTHOR]

Rainfall serves as a lifeline for crop cultivation in many agriculture-dependent countries including India. Being spatio-temporal data, the forecasting of rainfall becomes a more complex and tedious process. Application of conventional time series models and machine learning techniques will not be a suitable choice as they may not adequately account for the complex spatial and temporal dependencies integrated within the data. This demands some data-driven techniques that can handle the intrinsic patterns such as non-linearity, non-stationarity, and non-normality. Space–Time Autoregressive Moving Average (STARMA) models were highly known for its ability to capture both spatial and temporal dependencies, offering a comprehensive framework for analyzing complex datasets. Spatial Weight Matrix (SWM) developed by the STARMA model helps in integrating the spatial effects of the neighboring sites. The study employed a novel dataset consisting of annual rainfall measurements spanning over 50 (1970–2019) years from 119 different locations (grid of 0.25 × 0.25 degree resolution) of West Bengal, a state of India. These extensive datasets were split into testing and training groups that enable the better understanding of the rainfall patterns at a granular level. The study findings demonstrated a notable improvement in forecasting accuracy by the STARMA model that can exhibit promising implications for agricultural management and planning, particularly in regions vulnerable to climate variability. [ABSTRACT FROM AUTHOR]

Pinus gerardianaWall. is an important nut-producing pine having restricted distribution in the world. It has been observed that natural regeneration in the species is extremely poor or entirely lacking. The species has erratic and infrequent seed years, dormancy-related problems, and slow growth of seedling, which reduces its regeneration process in natural habitats. Therefore, we investigated the effect of growing medium and seed size on germination and seedling growth of thePinus gerardiana. The seeds were categorized into two sizes, viz, small (<2.35 cm) and large (>2.35 cm) and five growing medium treatments were used, viz, Soil:Sand:FYM; Soil:Sand:Moss:FYM; Soil:Moss:Vermicompost; Soil:Sand:Vermicompost; and Soil:Sand:Moss:Vermicompost, for assessing their impact on germination and seedling growth. It was observed that, among different growing medium treatments, higher germination and seedling growth parameters were recorded, when Soil:Sand:Moss:Vermicompost was used for the study. Between different seed sizes, higher germination and seedling growth were recorded when seed size was large. [ABSTRACT FROM AUTHOR]