Search

This study evaluated an optimized multi-model ensemble (MME) approach coupled with various objective functions to project the extreme precipitation. This study considered 60 stations in South Korea and used coupled model intercomparison project (CMIP) 6 GCMs under shared socioeconomic pathway (SSP) scenarios. The extreme precipitation characteristics were described by ten precipitation indices from expert team on climate change detection and indices (ETCCDI). The Generalized Reduced Gradient (GRG) algorithm was utilized to optimize the weights of all considered GCMs using four objective functions, namely Nash-Sutcliffe efficiency (NNSE), root mean square error (RMSE), Kling-Gupta efficiency (KGE), and percent bias (Pbias). The performance of optimized MME in extreme precipitation projection was compared to the equal-weighted MME. As a result, the optimized MME in this study demonstrated higher performances than the MME that simply averaged GCMs' output in most regions, regardless of the objective functions. These results indicated that the optimized MME with KGE generally performed better than MMEs using other objective functions. This study emphasized the importance of efficient GCMs subset selection, unequal weights, and the use of appropriate evaluation metrics for the MME approach in extreme precipitation projection. [ABSTRACT FROM AUTHOR]

Jordan is severely affected by climate change, it suffers from significance fluctuation and decrease in the amounts of the annual precipitation basically during the last decade which had dire consequences for farmers and the provision of fresh water. In this study, the impact of climate change on the Al-Wala basin was analyzed during the period 2013 to 2024 using Geomatics techniques, Google Earth Engine (GEE) and machine learning codes. Soil and Water Assessment Tool (SWAT) model was used to simulate the hydrological process up to year 2064. Moreover, the Meteorological Research Institute Earth System Model (MRI-ESM2-0) was used to predict the change of water surface area of the Al-Wala dam lake in the future. Annual satellite images: Lanadsat and sentinel, covering the period of the study area were downloaded and enhanced. They permit to provide the necessary information to carry out this study. As result, an important fluctuation of the amount of annual rainfall quantity was observed as well as, the amounts of annual rainfall expected to increase and decrease wobbly for several years in the future. Overall the average annual runoff will increase by 10% compared to the baseline scenario. The minimum temperature is expected to be higher than their rates throughout the year by 0.09°- 0.11o C, this will increase the evaporation rates with about 0.03%. The analysis of the sensitivity using the SWAT model was identified by 6 parameters out of 17. The regression coefficient (R2), Nash and Sutcliffe efficiency (NSE), on monthly basis, were above 0.60 for both of them which indicates satisfactory model results. [ABSTRACT FROM AUTHOR]

The evaluation of climate models is a crucial step in climate studies. It consists of quantifying the resemblance of model outputs to reference data to identify models with superior capacity to replicate specific climate variables. Clearly, the choice of the evaluation indicator significantly impacts the results, underscoring the importance of selecting an indicator that properly captures the characteristics of a "good model". This study examines the behaviour of six indicators, considering spatial correlation, distribution mean, variance and shape. Monthly data for precipitation, temperature and teleconnection patterns in Central America were utilized in the analysis. A new multicomponent measure was selected based on these criteria to assess the performance of 32 CMIP6 models in reproducing the annual seasonal cycle of these variables. The top six models were determined using multicriteria methods. It was found that even the best model reproduces one derived climatic variable poorly in this region. The proposed measure and selection method can contribute to enhancing the accuracy of climatological research based on climate models. [ABSTRACT FROM AUTHOR]

An increase in the consumer demand and the availability of gluten-free products has led to several brewers investigating brewing with grains other than barley. The primary grain of choice has been sorghum. These new gluten-free beers have a unique flavor and aroma, which previous research has shown is the result of differences in concentration for key chemical compounds, including ethyl butyrate, butyl acetate, isoamyl acetate, ethyl caproate, hexyl acetate, 1-octanol, nonanal, ethyl octanoate, and ethyl decanoate. This study focused looked at the influence different strains of yeast had on the concentration of these key compounds. Beer was brewed using either barley or sorghum malt extract. The concentrations of these key volatile compounds were determined using Solid Phase Microextraction (SPME) with Gas Chromatography and Mass Spectral (GC-MS) detection. Overall, it was found that the concentrations of these compounds were statistically different in the beers brewed from these two grain types. However, the yeast strain had no significant impact on the concentrations. [ABSTRACT FROM AUTHOR]

Micronutrient deficiency is wide spread and highly affects morbidity, mortality, and well-being of human beings. Micronutrient deficiency gradually manifests into diseases, which effects pathophysiology directly or indirectly. There is an imprecision in the diagnosis of micronutrient deficiency because of two causes; the selection of the standard biomarker and the diagnostic technique used. In appropriate diagnosis could increase the severity of the disorder. Instead of a single a combination of biomarkers can give more stringent results for micronutrient testing. Several traditional analytical techniques are used for diagnosis but HPLC, ELISA & LCMS/MS are most sensitive and reliable methods used by CLSIA-certified labs. However, these techniques require well-equipped, centralized laboratory facilities. The diagnostic era moves toward the Point of Care Testing (POCT), a boon in emerging diagnostics, breaking all paradigms of traditional analytical techniques. POCT led us toward the development of biosensors, which encompasses many techniques like paper-based sensors, microfluidic chip, wearable devices, and smartphone-assisted diagnostics, which become more popular diagnostic tools. This outlook summarizes the micronutrients like vitamins A, B5, B6, B7, B9, B12 C, D, and E and Minerals like iron, calcium, zinc, magnesium, and sodium; along with its biomarkers, analytical techniques, and point of care innovation in micronutrients. [ABSTRACT FROM AUTHOR]

In the upcoming decades, precipitation and temperature patterns are expected to shift in the Mediterranean basin due to global warming, potentially having an influence on the environment and the economy in the area. Using monthly precipitation and temperature data from 15 global climate models (GCMs) developed as part of the Coupled Model Intercomparison Project Phase 6 (CMIP6), the Mediterranean Climate Envelop (MCE), as defined by Daget's (1977) criteria, is projected under two climate change scenarios: SSP2-4.5 and SSP5-8.5, and for two future periods: 2050s and 2070s. According to the findings, the MCE is expected to expand by 3.51 and 4.93% in the 2050s under the SSP2-4.5 and SSP5-8.5 scenarios, respectively, in comparison to the current state. This expansion is expected to reach 5.28 and 9.87% for SSP2-4.5 and SSP5-8.5, respectively, in 2070s. For both situations and durations, MCE contraction would be minor, however, at less than 1%. More than 99% of the present MCE would stay stable proportionately. The northern Mediterranean region is mostly concerned by the MCE's expansion. The SSP2-4.5 scenario predicts that by the 2070s, expansion zones will occupy 674,183 km2, with 64% of the area located in Southern Europe and 36% in Western Asia. In SSP5-8.5 scenario, this area is expected to be significantly larger, estimated to be approximately 1,256,881 km2; 67% in Southern Europe and 33% in Western Asia. [ABSTRACT FROM AUTHOR]

One of the major impacts of climate change in the agricultural sector relates to changes in the suitability of areas that are used for planting crops. Since peanut (Arachis hypogaea L.) is one of the most important sources of protein, an assessment of the potential shifts in peanut crop planting areas is critical. In this study, we evaluated the effects of climate change on the potential distribution of peanut crops in Australia. The current and potential future distributions of peanut crops were modeled using Species Distribution Models (SDMs) of CLIMatic indEX (CLIMEX). The future potential peanut crop distributions in Australia for 2030, 2050, 2070, and 2100 were modeled by employing CSIRO-Mk3.0 and MIROC-H Global Climate Models (GCMs) under SRES A2 climate change scenarios from CliMond 10' database. The results indicated an increase in unsuitable areas for peanut cultivation in Australia throughout the projected years for the two GCMs. The CSIRO-Mk3.0 projection of unsuitable areas in 2100 was higher (i.e. 76% of the Australian continent) than the MIROC-H projection (i.e. 48% of the Australian continent). It was found that the projected increase in dry stress in the future could cause limitations in areas that are currently suitable for peanut crop cultivation. Looking into the future suitability of existing peanut cultivation areas, both GCMs agreed that some areas will become unsuitable, while they disagreed with the suitability of other areas. However, they agreed on the important point that only a small number of existing peanut cultivation areas would still be suitable in the future. Using CLIMEX, the present study has confirmed the effects of climate change on the shifts in areas suitable for peanut cultivation in the future, and thus may provide valuable information relevant to the long-term planning of peanut cultivation in Australia. [ABSTRACT FROM AUTHOR]

Breast cancer is the most prevalent cause of cancer-related deaths worldwide, and mortality rates are on the increase. This study aims to evaluate the potential of bioactive compounds from Clibadium surinamense L. leaves as inhibitors of AKT1 protein interactions, which play a crucial role in tumor growth mechanisms. Leaves of Clibadium surinamense L., obtained from Padangsidimpuan, North Sumatra, were extracted using methanol at a ratio of 1:20 for 48 h. The resulting extract was analyzed using Gas Chromatography-Mass Spectrometry (GC-MS) to identify the bioactive compounds. Drug likeness was then assessed according to Lipinski's rules, and molecular docking analysis was performed using Autodock Vina. GC-MS results identified 11 bioactive compounds, including 2-Cyclopenten-1-one and Hexadecanoic acid, methyl ester. Of the 8 compounds evaluated, 6 met the criteria for drug candidates. Molecular docking analysis revealed significant interactions between the bioactive compounds and the AKT1 protein. These findings suggest that bioactive compounds from Clibadium surinamense L. have potential as AKT1 interaction inhibitors, which could enhance cancer treatment mechanisms. This research paves the way for further studies on the therapeutic applications of these compounds in breast cancer treatment. [ABSTRACT FROM AUTHOR]

Currently, phylloremediation has emerged as a highly effective method for eliminating air pollutants, particularly polyaromatic hydrocarbons (PAHs). When PAHs accumulate on the phyllosphere, they significantly impact the fungal communities residing on leaf surfaces. This study aimed to investigate how pollution distribution patterns affect the diversity and PAH-degrading abilities of phyllosphere fungi, alongside identifying suitable mathematical models for PAH degradation. Leaf samples from two locations, Maradana and Sapugaskanda, were identified as having the highest PAH concentrations through principal component analysis. The fungal diversity in these highly contaminated regions was varied, with dominant species exhibiting greater PAH-degrading capabilities than those in less polluted areas. Thirty-five morphologically different epiphytic fungal strains were isolated on Potato Dextrose Agar (PDA) medium using the sample leaf wash. Two different fungal strains were selected as the best PAH degraders among those 35 different strains. These fungal strains were identified as Trichoderma harzianum P4M-16, and Fusarium solani P11M-46 based on ITS sequence data. Notably, these fungal species were more prevalent in highly polluted urban areas compared to less contaminated sites. High-Performance Liquid Chromatography (HPLC) analysis revealed that these two fungal species degrade PAHs more efficiently than others. Their kinetics assays demonstrated alignment with four degradation models when breaking down phenanthrene, naphthalene, pyrene, and anthracene. Scanning electron microscopy images showed that these fungi function as endophytes, extending their mycelium into the core leaf tissue layers beyond the epidermis. Gas Chromatography-Mass Spectrometry (GCMS) analysis indicated that F. solani P11M-46 produced non-toxic byproducts during the breakdown of phenanthrene and anthracene, confirming their eco-friendly nature. Overall, our findings suggest the promising potential of using phyllosphere fungi in bioremediation processes for environmental pollutants such as PAHs. [ABSTRACT FROM AUTHOR]

The Sunda porcupine (Hystrix javanica, F.Cuvier, 1823) is a rodent-mammal species native to Indonesia and is utilised in traditional medicine for the treatment of various ailments. Some ethnic communities in Indonesia have traditional beliefs regarding Sunda porcupine's quills, which are thought to relieve back pain and toothache. Despite this traditional knowledge, there is limited scientific research on the topic. The aim of this study was to identify active compound in an ethanolic crude extract of Sunda porcupine's quills, and to evaluate its antioxidant and antimicrobial properties. The antioxidant activity was evaluated using 1,1-diphenyl-2-picrylhydrazyl (DPPH)-free radical scavenging assay while the antimicrobial activity was evaluated through microdilution resazurin assay. The total phenolic and flavonoid contents were also determined to support the antioxidant properties. The active compounds were identified using gas chromatography-mass spectrophotometer (GCMS) with the National Institute of Standards and Technology (NIST-11) library. The result showed that the extract possesses antioxidant properties (IC50 138.93 µg/mL) and antimicrobial properties against Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), Bacillus subtilis (B. subtilis), Pseudomonas aeruginosa (P. aeruginosa) and Candida albicans (C. albicans) (IC50 range 0.40 mg/mL-33.05 mg/mL). Total phenolic content (TPC) and total flavonoid content (TFC) were 27.29 ± 2.20 mgGAE/g and 27.09 ± 1.66 mgQE/g, respectively. A total of 24 active compounds from the crude extract were identified. As much as five compounds serve as antioxidant agents, including: butylated hydroxytoluene; eicosane; 1-iodo-hexadecane; methyl ester hexadecanoic acid; and L-(+)-ascorbic acid 2,6-dihexadecanoate. Furthermore, as much as 11 compounds serve as antimicrobial agents, including: tetradecane; pentadecane; 2-isopropyl-5-methyl-1-heptanol; hexadecane; butylated hydroxytoluene; eicosane; 1-iodo-hexadecane; methyl ester hexadecanoic acid; benzenepropanoic acid, 3,5-bis(1,1-dimethylethyl)-4-hydroxy-, methyl ester; L-(+)-ascorbic acid 2,6- dihexadecanoate; and octadecanoic acid. This study provides scientific validation for the use of the Sunda porcupine's quills in traditional medicine and highlights the potential for further research in animal bioprospecting. [ABSTRACT FROM AUTHOR]

Background: Helminthiasis is a major concern in the livestock sector due to the immense afflictions in the production and economy of the farmer. Chemical anthelmintics are used to combat them and parasites are acquiring resistance against these drugs. Hence, the development of new drugs or alternatives is the need of the hour for combating such infestations. This study was undertaken to determine the effect of methanolic leaf extract of Tectona grandis on strongyles. Materials and Methods: The dried leaves of Tectona grandis were subjected to Soxhlet extraction using methanol, and the extract was tested for its anthelmintic activity in vitro using egg hatch assay and larval motility assay. A dose of 250, 125, 62.5, 31.25, 15.625, and 7.8125 mg/ mL was used for the study. Fresh strongyle ova were exposed to different concentrations of the extract and observed after 48 hours for the hatch. L3 larvae obtained from coproculture were subjected to treatment with extract at different concentrations, and mortality per unit time was calculated. Fourier transform infrared (FTIR) spectroscopic analysis and Gas chromatography-mass spectrometry (GC/MS) were performed to identify the chemical nature of the extract. Results: There was a dose-dependent inhibition of hatch and larval mortality with a maximum inhibition of hatch at 250 mg/mL. There was a cent percent hatch in control wells and no loss of progressive motility in the larval motility test. On exposure to the extract, the larvae progressively lost their motility, and finally, there were caesurae of movement which indicated their death. The extract at 250 mg/mL killed all the larvae by 30 min, whereas, at 31.25 mg/mL, the mortality was 66.6% after 2 hr. Conclusion: The results suggest that methanolic extract from Tectona grandis leaves has a promising anthelmintic property and further studies are required for the isolation of active molecules. [ABSTRACT FROM AUTHOR]

Climate change poses challenges to maize production and productivity in eastern Ethiopia. Impact assessment using climate predictions is the prime step to design adaptation strategies. Crop Environment Resource Synthesis (CERES)-Maize model in DSSAT (Decision Support System for Agrotechnology Transfer) was calibrated using GenCalc software. The model was used to simulate change in maize yield in the baseline (1988–2017) and future climate periods (2030s and 2050s) under (Representative Concentration Pathways) RCP4.5 and RCP8.5 scenarios using 17 CMIP5 (Coupled Model Inter-comparison Project Phase Five) GCMs (Global Circulation Models). During calibration and evaluation of the model excellent agreement of measured and simulated anthesis, and days to physiological maturity for all the cultivars with normalized root mean square error (nRMSE) of less than 10% and R2 value of 0.99 was obtained. The seasonal leaf area index (LAI) and top weight progressions were also predicted well by the model with d-index of 0.96 and 0.99, respectively. Excellent (nRMSE < 10) to good (nRMSE 10–20) predictions were also obtained for grain yield and tops weight. The average annual temperature would increase by (1.90 ± 0.36) oC, (2.45 ± 0.53) oC and rainfall would increase (8 ± 5) %, (12 ± 8) % under RCP 4.5 in 2030s and 2050s, respectively across GCMs compared to baseline in the study area. As a result in 2030s yield reduction, – 10.6% to – 15.4% and – 7.4% to – 9.3% in 2050s of maize cultivar was projected across GCMs. In 2030s and 2050s under RCP4.5 and RCP8.5 long maturing cultivars (BH661) on 15th May planting with 130.5 kg N ha–1 application predicted the highest maize grain yield.Highlights: Climate change poses challenges to maize production and productivity. Adaptation strategies such as cultivars, planting dates, and nitrogen fertilizer rates were assessed. Under RCP4.5 and 8.5 in 2030s the highest maize grain yield predicted by planting late maturing (BH661) cultivar on 15 May with 130.5 kg ha–1 nitrogen fertilizer application. In 2050s planting late maturing (Raare-1) cultivar with 87 kg ha–1 nitrogen fertilizer application under RCP4.5 and, Planting late maturing (BH661) cultivar with 130.5 kg ha–1 nitrogen fertilizer application under RCP8.5 predicted to give higher yield. [ABSTRACT FROM AUTHOR]

In rainfed areas, precipitation variations directly impact wheat growth stages such as emergence, tillering, jointing and booting, and maturity. Evaluating the impact of climate change on precipitation patterns during these critical growth stages is crucial for adapting climate change and ensuring global food security. In this study, projections of five General Circulation models (GCMs) under two shared socioeconomic pathways (SSPs) were used to predict the changing characteristics of precipitation during four main growth stages of wheat in the rainfed region of the Pothwar Plateau, Pakistan. Historical datasets of daily precipitation at six weather stations were analyzed to check the past changes in the precipitation patterns. During the baseline period (1985–2014), the annual average precipitation decreased at a rate of −9.75 mm/decade, while the amount of precipitation during the rabi season (wheat-growing season) decreased at a rate of −20.47 mm/decade. An increase in the precipitation was found during the fourth (flowering) stage of crop growth, while the first three stages experienced a decrease in the precipitation amount. The multimodal ensembled data, under the SSP2-4.5 scenario, revealed a significant decline (at the rate of −16.63 mm/decade) in the future annual precipitation. However, it is projected that, under SSP2-4.5, there may be a slight increase (4.03 mm/decade) in the total precipitation amount during the future rabi season. Under the SSP5-8.5 scenario, average annual precipitation exhibited a slightly increasing trend, increasing by 1.0 mm/decade. However, during the rabi season, there was a possibility of a decrease in precipitation amount, with a rate of 11.64 mm/decade. It is also expected that the precipitation amount may vary significantly during the crown root initiation, jointing and booting, and flowering stages in the near future. These results provide a framework for the planning of wheat production in the Pothwar region of Pakistan, taking into account the potential impact of shifting weather patterns, particularly in terms of uneven precipitation. [ABSTRACT FROM AUTHOR]

Recent developments in insect science and technology and integrated pest management (IPM) are laying a concrete path for transition from the dreaded chemical-based pest management to biological and biorational-based methods. Herbivore-induced plant volatiles (HIPVs) play an important role in host plant–herbivore–natural enemy interactions and have the potential to enhance the effectiveness of biological and biorational-based controls for integrated pest management (IPM). Synthetic HIPV blends can potentially improve the foraging behavior of predators by attracting them. This study was conducted to explore the emission of plant volatiles under infestation by cotton aphids, Aphis gossypii Glover, and their influence on attraction response of predatory six-spotted ladybird beetle, Cheilomenes sexmaculata (Fab.). Cotton leaf extracts were analyzed by gas chromatography coupled mass spectrometry (GC–MS), and the response of C. sexmaculata to the various extracts was assessed with a Y-tube olfactometer. By comparing the volatile profile of aphid-infested leaf extract with that of uninfested leaf extract, three compounds, namely 3-carene, pentadecane, and α-linolenic acid, were identified as aphid-induced HIPVs. However, the abundance of the other three compounds, heptane, 3-hexenal, and α-copaene significantly increased upon aphid infestation. At a concentration of 5%, aphid-infested leaf extract had the greatest effect on both female (85.9 ± 7.6%) and male (80.9 ± 6.4%) beetles. These results confirmed that HIPVs induced by aphids in cotton could attract C. sexmaculata beetles. Future tests need to be conducted to determine which compounds could be exploited as attractants for C. sexmaculata. [ABSTRACT FROM AUTHOR]

The sustenance of rice cultivation in a region is highly dependent on future water availability under changing climate. The dams and reservoirs can play a major role in regional water availability since their storage capacity can cushion the water stress due to changes in rainfall and temperature patterns. The current study developed a simulation modelling framework to quantify the water availability and demand on a taluk scale in the command area of the Malampuzha Irrigation Project (MIP). The Blue and Green water footprint concept is used to analyse the water availability and demand in the region. The loosely coupled framework of SWAT, DSSAT, and a Reservoir Simulation Module helps to generate the hydrological and crop yield projections of the region according to the CMIP6 climate model projections. The analysis is carried out at a seasonal scale on decadal basis with a historical period spanning from 2016 to 2019 and a future period spanning from 2020 to 2100. The results suggest that eastern side of MIP command area experiences lower water availability due to lower green and blue water distribution, particularly affecting the regions of Palakkad and Chittur taluk. The study introduces an integrated water footprint score (IWFS) at taluk scale, which combines green and blue water footprint to assess the annual water demand variations in the region. The taluks Alathur and Palakkad are in the high risk category towards the end of the century as per the water footprint score. Towards the end of the century, an increase in rainfall by 67% and temperature by 6% has resulted in a decrease in rice yield by 13.2% during kharif and 52.5% during rabi season under SSP585 scenario. The study helps to identify critical water stress zones within the command area and prioritize the implementation of adaptation measures within the command area. [ABSTRACT FROM AUTHOR]

This paper demonstrates the synthesis and storage of molecular-imprinted polymers (MIP) at room temperature using bulk polymerization of atenolol (Ate), which is characterized by high sensitivity, low costs, and high stability. The research used 0.99:6:20 mmol ratios of template, monomer, and cross-linking agents for the polymerization in order to ensure an appropriate adsorption capacity. By making MIP for atenolol as Ate-MIP, which could be looked at with a UV-VIS spectrophotometer at 276 nm, Fourier- transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM), a functional monomer of allyl chloride with cross-linking ethylene glycol dimethyl acrylate was made. Mass spectrometric (MS) detection may use allyl chloride to determine atenolol levels in pharmaceutical preparations. The GC/MS methods developed in this study are accurate, sensitive, and precise and can be easily applied to (NOVATEN/India and ATENOIOI/U.K.) tablets in pharmaceutical preparation. The elution process was applied to the template (Ate) from the Ate-MIP, which developed cavities, caused by using porogenic solutions of methanol, chloroform, and acetic acid (70:20:10, respectively). The maximum adsorption capacity of Ate-MIP was 2.9957 µmol/g, and the ratio of template to monomer was 1:1 in adherence to the Langmuir isotherm model. A solid-phase extraction (SPE) syringe packed with molecular imprinted polymers (MIPs) was used to selectively separate and pre-concentrate Ate from aqueous solutions and estimations of atenolol. [ABSTRACT FROM AUTHOR]

Water scarcity is a major challenge facing many regions worldwide, especially arid and semi‐arid areas that are increasingly vulnerable to climate change. This study aimed to project water availability in the Amu Darya Basin (ADB) of Central Asia under four Shared Socioeconomic Pathways (SSPs) from the Coupled Model Intercomparison Project Phase Six (CMIP6) during two upcoming periods (2020–2059 and 2060–2099). The study used a robust machine learning approach, namely a Random Forest (RF) model, to simulate Gravity Recovery and Climate Experiment (GRACE) Terrestrial Water Storage (TWS) data from precipitation and maximum and minimum temperatures (Tmax and Tmin). It then incorporated precipitation, Tmax and Tmin from four selected CMIP6 GCMs, into a water storage model to project spatiotemporal changes in water availability across the basin. The study also evaluated the relative impacts of land use and population on TWS. Results indicate an increase in TWS by approximately 4 cm in the basin's eastern, northwestern and southwestern regions in both future periods, while a decrease by approximately −4 cm in the remaining areas. These projections suggest that TWS will decline in densely populated regions and increase in certain intensively cultivated areas. The most pronounced increase in TWS is anticipated in the snow‐covered Tundra climate zone of the basin. This is attributed to the melting of glaciers, which contributes to runoff in the tributaries of the Amu River. The findings highlight the importance of considering climate change and socioeconomic factors when projecting water availability in arid and semi‐arid regions. The projected changes in TWS have important implications for water resources management in the ADB, particularly in densely populated and intensively cultivated areas. [ABSTRACT FROM AUTHOR]

Soursop leaves (Annona muricata) contain various secondary metabolite compounds with pharmacological benefits. This study foccused on the activity and chemical components cytotoxic active fraction of soursop leaf dichloromethane extract. From maceration of 535.8 g dried sample of A. muricata leaves we obtained extracts of n-hexane (18.4 g; 3.43 %). dichloromethane (11.4 g; 2.23 %). and methanol (48.7 g; 9.95 %). The dichloromethane extract was separated for its chemical components using gravity column chromatography resulting in 9 combined fractions. Toxicity screening test was done based on Bhrine Shrimp Lethality Test (BSLT) and cytotoxic test using MTT method 3-(4.5-dimethylthiazol-2-yl)-2.5-diphenyltetrazolium bromide. The highest toxicity and cytotoxic test results were found in DMD 1 dichloromethane extract of A. muricata leaves with LC50 of 19.05 µg/mL and IC50 of 824.09 µg/mL. The results of DMD 1 gravity column re-chromatography produced 6-combined subfractions with the best separation pattern on DMD 1.4 and the results of GC-MS chromatogram analysis showed 29 peaks with the main component of fatty acid compounds namely Carbonic acid. but-2-yn-1-yl octadecyl ester (70.46 %). Potential anticancer compounds found were Phytol; 2-Hydroxy-1.1.10-trimethyl-6.9-epidioxydecalin and 2-Piperidinone. N-(4-bromo-n-butyl). [ABSTRACT FROM AUTHOR]

The phytochemical compounds in the leaf extracts of Castanopsis indica and C. tribuloides were evaluated, and their antioxidant and antimicrobial potential were assessed. The TPC was found to be 193.12 and 159.49 mg GAE g−1 dry weight, and the TFC was 108.12 and 96.49 mg QE g−1 dry weight, for C. indica and C. tribuloides, respectively. C. indica had higher DPPH scavenging activity, with an IC50 value of 15.10 μg mL−1. Both extracts showed substantial antimicrobial activity against the tested bacteria. GC-MS analysis showed the presence of 76 VoCs in C. indica leaf, and 71 VoCs in C. tribuloides. [ABSTRACT FROM AUTHOR]

High‐resolution climate projections are critical to assessing climate risk and developing climate resilience strategies. However, they remain limited in quality, availability, and/or geographic coverage. The Seasonal Trends and Analysis of Residuals empirical statistical downscaling model (STAR‐ESDM) is a computationally‐efficient, flexible approach to generating such projections that can be applied globally using predictands and predictors sourced from weather stations, gridded data sets, satellites, reanalysis, and global or regional climate models. It uses signal processing combined with Fourier filtering and kernel density estimation techniques to decompose and smooth any quasi‐Gaussian time series, gridded or point‐based, into multi‐decadal long‐term means and/or trends; static and dynamic annual cycles; and probability distributions of daily variability. Long‐term predictor trends are bias‐corrected and predictor components used to map predictand components to future conditions. Components are then recombined for each station or grid cell to produce a continuous, high‐resolution bias‐corrected and downscaled time series at the spatial and temporal scale of the predictand time series. Comparing STAR‐ESDM output driven by coarse global climate model simulations with daily temperature and precipitation projections generated by a high‐resolution version of the same global model demonstrates it is capable of accurately reproducing projected changes for all but the most extreme temperature and precipitation values. For most continental areas, biases in 1‐in‐1000 hottest and coldest temperatures are <0.5°C and biases in the 1‐in‐1000 wet day precipitation amounts are <5 mm/day. As climate impacts intensify, STAR‐ESDM represents a significant advance in generating consistent high‐resolution projections to comprehensively assess climate risk and optimize resilience globally. Plain Language Summary: The STAR‐ESDM tool is able to quickly and accurately generate future climate projections for weather stations and high‐resolution grids anywhere in the world. It does this by breaking down global or regional climate model output into different components, from the long‐term trend to the day‐to‐day variability, then merging projected changes with observations. When tested against projections generated by a complex and computationally expensive dynamical global model, STAR‐ESDM produced almost the same output, even for extreme temperature and precipitation values, at a fraction of the computational cost. Moreover, unlike most statistical downscaling models, this method isn't tied to any specific geographic area or predictand and/or predictor data set. It can be applied to any regional or global data set, whether generated by a climate or reanalysis model, derived from satellite observations, recorded at weather stations, and more. As climate impacts escalate, STAR‐ESDM offers a flexible and effective way to generate the high‐resolution climate projections needed to better gauge climate risk and enhance resilience anywhere in the world where reliable observational or quasi‐observational data, including reanalysis or satellites, are available. This is particularly relevant to under‐resourced regions, which are often most vulnerable to climate impacts as well as most lacking in future projections. Key Points: STAR‐ESDM is a rapid, flexible and generalizable approach to bias‐correct and downscale climate model output to any finer‐resolution data setPredictors/predictands can be derived from global or regional models, satellites, reanalysis, gridded observations and weather stationsProjected changes in temperature and precipitation mirror those of a high‐resolution global model at a fraction of the computational cost [ABSTRACT FROM AUTHOR]

Monitoring the changes and fluctuations of precipitation in geographical areas can give a better view of the behavior of this phenomenon in the coming years. The purpose of this research is to investigate the precipitation situation in Ardabil Plain (Ardabil, Bileh-Daragh, and Kolour stations) and forecast it in the coming years based on the output of CMIP6 models by the CMhyd downscaling model. Then, using R2, MAE, MSE, RMSE, and Taylor diagram, the observational data of the base period were compared with the historical data of 5 GCM models from CMIP6, and the best model was selected for each studied station. The output of the top models was corrected for skewness by linear scaling method and based on SSP126, SSP245, and SSP585 scenarios, the precipitation of 2050-2023 for each station, forecast, and its trend were drawn with the Mann-Kendall statistic. The results showed that in the eastern and western areas of Ardabil Plain (leading to the heights of Talesh and Sablan mountains), the rainfall changes were increasing (2.80 mm). In the Ardabil station, the MIROC6 model with a correlation coefficient of 0.94%, and in Bileh-Daragh and Kolour stations, the MPIESM1-2-HR model with a correlation coefficient of 0.88% and 0.92%, respectively, have the highest accuracy in simulating the precipitation. Also, the results of the scenarios showed that the precipitation changes in Ardabil station in the future period compared to the base period under the SSP126, SSP245, and SSP585 scenarios will be 0.24, -6.36, and -2%, respectively. [ABSTRACT FROM AUTHOR]

Study region: Mokgam River watershed, South Korea Study focus: In this study, the uncertainty contribution of three sources and their interaction effects on future climate and runoff projections were quantified. General circulation models (GCMs), shared socioeconomic pathways (SSPs), and bias correction (BC) methods were considered as the three sources. 20 GCMs under four SSPs (SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5) were used to project the future climate of the study area. Seven BC methods were used to adjust the GCMs’ daily climate data. The storm water management model (SWMM) was used as a hydrological model to simulate runoff, incorporating both natural and conduit flows according to GCMs’ climate projection. The normalized Nash-Sutcliffe efficiency (NNSE), normalized root mean square error (NRMSE), Kling-Gupta efficiency (KGE), and modified index of agreement (MD) were used to evaluate the performance of the GCMs’ climate simulations and the SWMM runoff simulations, which were based on the GCMs’ climate data. The analysis of variance (ANOVA) method was used to quantify the uncertainty. New hydrological insights for the study region: The results showed that the assumptions of the BC method had a significant impact on the variation in climate and runoff projections. In the uncertainty of future climate and runoff projection results, BC methods exhibited the predominant contribution, while SSPs showed the least contribution. However, the uncertainty contribution from SSPs and GCMs was predominant in temperature projections, and these results could vary depending on the assumptions and the number of BC methods used. Overall, this study emphasizes not only the influence of GCMs but also the impact of BC methods on future climate and runoff projections.

This study investigates the medicinal properties of Rhodomyrtus tomentosa by extracting its bioactive compounds with n-hexane, ethyl acetate, and ethanol. Ethyl acetate extract had the highest total phenolic content, while hexane extract had the lowest. The ethanol extract had the highest total flavonoid content, with hexane extract having the lowest. Ethanol extract showed the highest antioxidant activity with an IC50 value of 28.61 ± 0.56 μg/mL. Gas Chromatography-Mass Spectrometry profiling identified major compounds like menthol and salicylic acid. Fraction 6, with rhodomyrtone content of 728 μg/mL, had the most dominant rhodomyrtone compound. Higher solvent polarity correlated with higher total phenolic content, total flavonoid content, and antioxidant activity, but lower saponin content. Based on its contents, further studies are needed to investigate its ability to reduce enteric methane, enhance immunity, and adapt to climate change, both in vitro and in vivo in ruminant livestock.

Background: Piper chaba has been traditionally using for its potential health benefits. The principal goal of this investigation was to assess the pharmacological characteristics of the EEPCS, focusing on investigating its potential antihyperuricemic effects, ability to inhibit xanthine oxidase (XO) enzyme, and antioxidant properties. Methods: The antioxidant capability of the extract was assessed using the DPPH radical assay. The extract was evaluated in vitro aimed at its xanthine oxidase inhibitory (XOI) action and further experimented for its antihyperuricemic effect on the Potassium oxonate (PO) induced hyperuricemia murine model. Besides, molecular docking techniques were employed to interpret the inhibitory mechanism of the compounds identified through GCMS analysis of the EEPCS. Results: There was no safety concern at doses up to 3000 mg/kg of the extract as confirmed by mice model studies. The extract displayed potent the antioxidant properties during quantitative antioxidant test (IC50=104.9 ± 0.99 µg/mL). In XOI test, the extract was found to be effective with an IC50 value of 26.14 μg/mL. In addition, the extract was found to decrease the Serum uric acid (SUA) levels by 36.72 and 61.84 % at 100 and 200 mg/kg body weight respectively, compared to the hyperurecaemic animals. The GCMS analysis of the extract revealed eighteen distinct compounds, which were docked against human peroxiredoxin 5 and xanthin oxidase proteins. Selina-3,7(11)-diene (CID: 6429221) was the most effective phytochemical for the human peroxiredoxin 5 protein having binding score −6.2 Kcal/mol compared to standard ascorbic acid (5.6 Kcal/mol). Besides, gamma-muurolene (-7.9 Kcal/mol) was the most effective phytochemical for the XO protein compared to standard allopurinol (−6.4 Kcal/mol). Conclusion: Our experimental data showed that the EEPCS has potentiality as an antioxidant and hypouricemic agent that could be contributed to treat and manage oxidative stress (OS), gout and hyperuricemia.

Long-acting local anaesthetics have demonstrated effectiveness in managing intraoperative and postoperative pain. However, substances like lidocaine and paraben preservatives can trigger allergic reactions and methemoglobinemia in susceptible individuals. While bupivacaine shares common side effects with other local anesthetics, its adverse effects are amplified due to the physicochemical properties of long-acting local anesthetics. Recently, there has been growing interest in utilizing saliva as a potential bio matrix for drug testing because the drug concentration in saliva directly reflects the free, non-protein-bound drug in plasma. This study involved extracting lidocaine and bupivacaine from saliva collected from healthy male patients using a liquid-liquid extraction method. Gas Chromatography-Mass Spectrometry (GC-MS) with ropivacaine as an internal standard was employed for simultaneous determination of both drugs. The results demonstrated high precision and accuracy, with a limit of detection (LOD) and limit of quantification (LOQ) of 3 ng/ml and 10 ng/ml for lidocaine, and 20 ng/ml and 62 ng/ml for bupivacaine, respectively. This non-invasive and user-friendly method provides highly accurate drug analysis results.

Bemisia tabaci (Gennadius) is crital pest of chili plants. Besides using chemical insecticides to control B. tabaci, the actions that can be taken for B. tabaci management include applying repellent compounds. This research aims to study the potential of various commercial corn varieties in producing repellent compounds for B. tabaci. The method used in this research involved testing the response of B. tabaci using a Y tube olfactometer and GCMS analysis on varieties P-21, Bisi-18, NK-212, and Pertiwi 3 on a laboratory scale. Volatile compounds were collected from corn plants aged 3–10 weeks after planting (WAP). The results showed that Bisi-18, P-21, NK-212, and Pertiwi 3 maize exhibited repellency against B. tabaci. The highest repellency for all corn varieties was observed at 10 WAP. The P-21 variety exhibited 80% repellency, followed by Pertiwi 3 and Bisi-18 with 78% repellency, while NK-212 showed the weakest repellencyat 60%. Results from volatile compounds identification of each maize varieties demonstrated revealed several compounds with repellent properties against B. tabaci, including 9-otadecenoic acid (Z)-, 9-octadecenamide, (Z)-, delta-guaiene, alpha-guaiene, beta caryophyllene, and patchouli alcohol. Using maize plants to manage B. tabaci has the potential to be an environmentally friendly management technique. Further research is needed on B. tabaci management technique to achieve a more effective and efficient combination.

The rapid increase in the number of motorized vehicles has resulted in the depletion of the availability of fossil-based fuel oil. Bioethanol from sugarcane molasses waste is an alternative that can be applied to vehicles with the condition that it has 99.95% ethanol fuel grade. The study used a bioethanol sample fuel blend BE10 (Bioethanol 10%+90% Pertalite), and then conducted property testing and Gas Chromatography Mass Spectrometry (GCMS) to observe the compound structure of the fuel. Modification of the ignition timing forward 2o (+2) was done by reprogramming the Engine Control Module (ECM). The addition of up to 20% bioethanol to pertalite increased the octane number from 90 to 93.1. However, the heating value decreased from 42.5 to 39.18 MJ/kg. In the GC-MS test, the number of compounds in the fuel increased to 52 and 51 compounds, respectively. The highest improvement in engine performance of all parameters using bioethanol and advance ignition was sample (BE10+2). The thermal efficiency was 6.16%. Thus, the use of bioethanol fuel blends and ignition timing modifications can be applied to vehicles to get good performance and be more environmentally friendly.

Identifying best performing climate models is indispensable for better understanding of the future climate and its impact as well as for planning effective climate change adaptation and mitigation measures. This research aims to identify the best performing Global Climate Models (GCMs) products from the Coupled Model Inter-comparison Project phase 6 (CMIP6) in simulating rainfall and temperature in the Bale Eco-Region (BER), Southern Ethiopia. In this study, evaluations were performed for ten CMIP6 GCMs against observed and reanalysis rainfall and temperature products in terms of how well the GCMs reproduce rainfall, maximum temperature (Tmax) and minimum temperature (Tmin) from daily to annual temporal scales during 1995–2014 period. Performance evaluations were performed using the Comprehensive Rating Index (CRI), which is based on four statistical metrics. The best performing CMIP6 model(s) were bias-corrected by Distribution Mapping (DM) for future climate analysis at different agro-ecological zones (AEZs) and at the eco-region level. The study used projections of climate variables in the near future (2021–2040), mid-century (2041–2060) and late century (2081–2100) periods. Three shared socioeconomic pathways (SSP2-4.5, SSP3-7.0, and SSP5-8.5) were considered as future climate scenarios. The result indicated that BCC-CSM2-MR, CNRM-CM6-1 and MRI-ESM2-0 are relatively better for simulating the rainfall climatology of the BER from the daily to annual temporal scales. EC-Earth3, Ec-Earth3-Veg and MPI-ESM1-2-LR are also comparatively better for simulating Tmax while CNRM-CM6-1, EC-Earth3-Veg and EC-Earth3 outperformed for simulating Tmin in the studied temporal scales. After careful evaluations, climate change analysis was performed using the ensemble mean of BCC-CSM2-MR, CNRM-CM6-1 and MRI-ESM2-0 for rainfall, EC-Earth3 for Tmax and the ensemble mean of CNRM-CM6-1 and EC-Earth3-Veg for Tmin. Accordingly, the annual rainfall is expected to decrease in the near future in the three scenarios in the alpine (2–5%), temperate (11–14%) and sub-tropical (7–9%) AEZs as well as the BER spatial scales (2–5%), but rainfall is expected to increase in the late century period. In contrast, rainfall is expected to increase in the tropical AEZ in both the near future (3–11%) and late century (25–45%) periods. In the mid-century period, rainfall is expected to increase in the tropical AEZ in all the three scenarios, but it exhibits different directions of changes in the remaining AEZs and BER scale at different scenarios. The finding also revealed an expected increase in both Tmax and Tmin in the different AEZs as well as the BER scale, but the projected temperature increase is high in temperate AEZ. The projected increase of rainfall in the near future in tropical AEZ may reduce the frequently occurring droughts mainly in the lowland parts of the BER. Conversely, the reductions of rainfall in the remaining AEZs may introduce challenges for agriculture, water resources as well as endemic animals. The findings of this study justifies the need for climate models evaluation for each climate variables in order to choose the most appropriate models for localized climate change impact and adaptation studies. In addition, this study also suggested projections of future climate for different AEZs for better decision-making process for the specific AEZs. [ABSTRACT FROM AUTHOR]

The global climate models (GCMs) are sophisticated tools for determining how the climate system will respond. However, the output of GCMs has a coarse resolution, which is unsuitable for basin-level modelling. Global climate models need to be downscaled at a local/basin scale to determine the impacts of climate change on hydrological responses. The present study attempted to evaluate how effectively various large-scale predictors could reproduce local-scale rain in 35 different locations in India using artificial neural networks (ANN), change-factors (CF), K-nearest neighbour (KNN), and multiple linear regression (MLR). The selection of predictors is made based on the correlation value. As potential predictors, air temperature, geo-potential height, wind velocity component, and relative humidity at specific mean sea-level pressure are selected. The comparison of four different downscaling methods concerning the reproduction of various statistics such as mean, standard deviation at chosen locations, quantile–quantile plots, cumulative distribution function, and kernel density estimation of the PDFs of daily rainfall for selected stations is examined. The CF approach outperforms the other methods at almost all sites (R2 = 0.92–0.99, RMSE = 1.37–28.88 mm, and NSE = –16.55–0.99). This also closely resembles the probability distribution pattern of IMD data. [ABSTRACT FROM AUTHOR]

Garcinia spp. have been used in traditional medicine to treat various ailments, and recent studies have confirmed their pharmacological activities. In this context, the present study focused on three Garcinia spp., namely Garcinia rostrata, Garcinia dryobalanoides and Garcinia cuneifolia, which gain less attention in terms of their phytoconstituent and biological activity data. Methodologically, in this study, the phytochemical constituents of the three Garcinia sp. was determined through gas chromatography mass spectrometry (GC-MS) whereby the antimicrobial activity was evaluated using the Disc diffusion and Dilution method. The results showed that the extract from Garcinia dryobalanoides exhibited the most potent antibacterial activity against Bacillus amyloliquefaciens compared to the other species. The phytochemical analysis found that Garcinia dryobalanoides extract contained significant amounts of (Z)-18-Octadec-9-enolide and n-hexadecanoic acid, which are known to possess antibacterial properties. These major constituents were found to interact synergistically to produce the observed antibacterial activity. The findings suggested that Garcinia dryobalanoides could be a promising source for developing new antibiotics to combat bacterial infections. Overall, this study highlights the potential of Garcinia spp. for discovering new bioactivities, particularly their antibacterial properties. Further research is needed to explore the full range of phytochemical constituents and biological activities of these plants, which could lead to the development of new drugs to combat antibiotic resistance. [ABSTRACT FROM AUTHOR]

The present study is to understand how climatic variables such as precipitation and temperature vary over time and how those changes affect stream flow in the Jhelum River basin in Pakistan under different emission scenarios A2 and B2. The simulation results of HadCM3 were employed to create potential climate change scenarios with the Statistically Downscale Model (SDSM). The calibrated model Soil and Water Assessment Tool (SWAT) was used to forecast imminent stream flow to develop a proposed future climate change scenario. Results indicated that cooling patterns were identified in the north portion of the study area whereas warming patterns were detected in the south portion. The projected mean annual maximum temperature (Tmax) of 2020's 2050's and 2080's would be 0.3 °C, 0.8 °C, and 0.99 °C, respectively, under the A2 scenario. The changes in mean annual minimum temperature (Tmin) were also observed as it would be 0.4 °C, 0.7 °C, and 1.4 °C during 2020's (2021-2040), 2050's (2041-2070) and 2080's (2071-2100), respectively. Similarly, it was observed that average annual rainfall would rise by 14%, 10%, and 20% during the 2020s, 2050s, and 2080s, respectively, in the Mangla basin. The results showed an increase in annual stream flows of 100% (1545 m³/sec), with increases in the winter and autumn seasons of up to 409% and 211%, respectively, and a drop in the spring and summer seasons of up to 29% and 25%, respectively, in the 2080's compared to baseline. Water managers should consider the current trends and variability brought on by climate change to improve water management where water is scarce. [ABSTRACT FROM AUTHOR]

Curcuma caesia Roxb. is an ethnomedicinally important, essential oil (EO) yielding aromatic plant. A total of twelve accessions of this plant rhizome were collected from six different agro-climatic zones of West Bengal, India and evaluated for their antimicrobial activities against eight disease-causing, multi-drug-resistant pathogenic strains of urinary-tract infection and respiratory-tract infection. The EO and extracts demonstrated antibacterial activity, with the highest inhibition zone of 18.00 ± 0.08 and 17.50 ± 0.14 mm against Klebsiella pneumoniae by accession 06, even where all the broad-spectrum antibiotics failed to respond. In this study, we employed high-performance thin-layer chromatography (HPTLC) to quantify curcumin, the primary secondary metabolite of C. caesia, and the highest 0.228 mg/gm of curcumin resulted from accession 06. Hence, on the basis of all aspects, accession 06 was identified as the elite chemotype among all twelve accessions. The chemical profiling of EO from accession 06 was done using gas chromatography-mass spectroscopy (GC–MS). Conceivably, about 13 medicinally significant compounds were detected. As this plant species is seasonal and has difficulties in conventional breeding due to dormancy, it must be conserved through in vitro tissue culture for a steady supply throughout the year in massive amounts for agricultural demand. A maximum number of 19.28 ± 0.37 shoots has been obtained in MS medium fortified with 6-Benzylaminopurine, Kinetin, and Naphthalene acetic acid. The genetic uniformity of the plants has been studied through Start Codon Targeted Polymorphism. Therefore, this study must help meet the need for essential phytoactive compounds through a simple, validated, and reproducible plant tissue culture protocol throughout the year. [ABSTRACT FROM AUTHOR]

This study explored how the water balance components of the Middle Tapi Basin (MTB) might alter between 2010 and 2100 as an outcome of climate change. We used an approach were Statistically downscaled future predicted data for temperature and rainfall for five different Global circulation models were employed under two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). The baseline and future scenarios' monthly analyses of multiple water balance indicators also showed that RCP 4.5 and RCP 8.5 will see an increase in maximum temperature of 5.2% and 9.5%, respectively, by the end of the century. The baseline period contribution from monsoonal rainfall and streamflow was also 89.3% and 90.6%, but in future scenarios, the figures are likely to reduce to 75.2% and 57.8% for RCP 4.5 and 70.8% and 54.7% for RCP 8.5. While the average inflow estimates at the Ukai dam tend to rise by 19.2% and 46.8% till the distant future scenario for RCP 4.5 and RCP 8.5, respectively. In future scenarios, the percentage of groundwater flow and surface runoff contributions will be lesser due to the higher evapotranspiration rate and revaporisation of water to the root zone. Even though the monsoonal rainfall tends to reduce, the flow duration curves for the future scenarios exhibited a consistent increase in water availability compared to their respective historical counterparts, possibly due to more frequent and severe rainfall events. [ABSTRACT FROM AUTHOR]

We analyzed the biochemical compounds by GCMS and did bioassay of leaf extracts of five tree species viz., Aegle marmellos (L.) Correa, Annona squamosa L., Mangifera indica L., Morinda tinctoria Roxb and Moringa oleifera Lam. on germination and associated characteristics of kodomillet (Paspalum scrobiculatum L) and prosomillet (Panicum miliaceum L.). Response Index was used for comparison, and by GCMS, the compounds found in the leaves were determined and studied their effects on germination and seedling growth. The 5 % Moringa oleifera leaf extract, followed by extracts from A. squamosa and Mangifera indica, improved millets' seed germination. Perhaps because the extracts contained the dominant compounds 2- Piperidinone and 2-Pyrrolidinone. Tree leaf extracts from the above-donor species had a synergistic effects in prosomillet, stimulating germination by 14-18 %, than kodomillet. However, Morinda tinctoria and Aegle marmellos leaf extracts inhibited the germination of both millets than control. [ABSTRACT FROM AUTHOR]

Currently, mosquito control programs primarily rely on the utilization of chemically based insecticides. The objective of this study was to evaluate the efficacy of the plant Stemodia viscosa Roxb. against the early life stages of Culex quinquefasciatus, Anopheles stephensi and Aedes aegypti mosquitoes. The larvae, pupae and eggs of the mosquitoes were exposed to four different concentrations (62.5 to 500 ppm). After 120 h of treatment, the hexane and ethyl acetate extracts of S. viscosa exhibited 100% ovicidal activity against the eggs of the treated mosquitoes. The hexane and ethyl acetate extracts showed significant larvicidal activity against all three mosquitoes. The LC50 values of the hexane extract were 272.5, 233.5, 217.9 ppm and the LC50 values of the ethyl acetate extract were 238.6, 230.5 and 169.1 ppm respectively, after 24 h. The hexane and ethyl acetate extracts of S. viscosa exhibited promising pupicidal activity with LC50 values of 286.6, 265.3, 257.9 and 192.2, 290.9 and 238.1 ppm, respectively, after 24 h against all three mosquitoes. Additionally, histopathological and growth disruption studies revealed severe damage in the midgut cells of the treated larvae. The suitability index (SI) or predator safety factor (PSF) values indicated that the extracts from S. viscosa could be safely utilized in Integrated Mosquito Management (IMM) without harming the predators. Furthermore, formulations based on hexane and ethyl acetate extracts demonstrated strong activity while exhibiting no toxicity towards non-target organisms. The results imply that the extract holds potential as an eco-friendly substitute for synthetic insecticides in mosquito control. However, additional research is required to identify the most potent components of the plant extract to enhance product efficacy and stability. [ABSTRACT FROM AUTHOR]

Our study aims to understand how the hydrological cycle is affected by climate change in river basins. This study focused on the Karnali River Basin (KRB) to examine the impact of extreme weather events like floods and heat waves on water security and sustainable environmental management. Our research incorporates precipitation and temperature projections from ten Global Circulation Models (GCMs) under the Coupled Model Intercomparison Project Phase 6 (CMIP6). We applied thirteen statistical bias correction methods for precipitation and nine for temperatures to make future precipitation and temperature trend projections. The research study also utilized the Soil and Water Assessment Tool (SWAT) model at multi-sites to estimate future streamflow under the Shared Socioeconomic Pathway (SSP) scenarios of SSP245 and SSP585. Additionally, the Web-based Hydrograph Analysis Tool (WHAT) was used to distinguish between baseflow and streamflow. Our findings, based on the Multi-Model Ensemble (MME), indicate that precipitation will increase by 7.79–16.25% under SSP245 (9.43–27.47% under SSP585) and maximum temperatures will rise at rates of 0.018, 0.048, and 0.064 °C/yr under SSP245 (0.022, 0.066, and 0.119 °C/yr under SSP585). We also anticipate that minimum temperatures will increase at rates of 0.049, 0.08, and 0.97 °C/yr under SSP245 (0.057, 0.115, and 0.187 °C/yr under SSP585) for near, mid, and far future periods, respectively. Our research predicts an increase in river discharge in the KRB by 27.12% to 54.88% under SSP245 and 45.4% to 93.3% under SSP585 in different future periods. Our finding also showed that the expected minimum monthly baseflow in future periods will occur earlier than in the historical period. Our study emphasizes the need for sustainable and adaptive management strategies to address the effects of climate change on water security in the KRB. By providing detailed insights into future hydrological conditions, this research serves as a critical resource for policymakers and stakeholders, facilitating informed decision-making for the sustainable management of water resources in the face of climate change. [ABSTRACT FROM AUTHOR]

Porous wood-based boards, like any lignocellulosic material, are susceptible to biocorrosion caused by mold fungi. Their durability can be extended by using biocides. Due to the fact that porous boards are considered an ecological material, it would be beneficial to also use natural agents to protect them. For this purpose, the surface of softboards was protected with a 30% solution of cinnamon bark oil in ethanol. Three application levels were used: 75 g/m2, 120 g/m2, and 200 g/m2 of solution. It has been shown that the cinnamon bark oil solution used at an application rate of 200 g/m2 is an effective fungicide, protecting softboards (SBs) against the development of mold fungi: T. viride and C. globosum. The dominant volatile component of cinnamon oil identified in the boards turned out to be cinnamaldehyde. Three months after treatment, this substance constituted 74% of the volatile components. The proposed treatment method allows for short-term preventive protection of boards against mold fungi. [ABSTRACT FROM AUTHOR]

Abstract High‐resolution climate projections are critical to assessing climate risk and developing climate resilience strategies. However, they remain limited in quality, availability, and/or geographic coverage. The Seasonal Trends and Analysis of Residuals empirical statistical downscaling model (STAR‐ESDM) is a computationally‐efficient, flexible approach to generating such projections that can be applied globally using predictands and predictors sourced from weather stations, gridded data sets, satellites, reanalysis, and global or regional climate models. It uses signal processing combined with Fourier filtering and kernel density estimation techniques to decompose and smooth any quasi‐Gaussian time series, gridded or point‐based, into multi‐decadal long‐term means and/or trends; static and dynamic annual cycles; and probability distributions of daily variability. Long‐term predictor trends are bias‐corrected and predictor components used to map predictand components to future conditions. Components are then recombined for each station or grid cell to produce a continuous, high‐resolution bias‐corrected and downscaled time series at the spatial and temporal scale of the predictand time series. Comparing STAR‐ESDM output driven by coarse global climate model simulations with daily temperature and precipitation projections generated by a high‐resolution version of the same global model demonstrates it is capable of accurately reproducing projected changes for all but the most extreme temperature and precipitation values. For most continental areas, biases in 1‐in‐1000 hottest and coldest temperatures are

Abstract Mosquitoes are notorious insects that transmit a wide range of infectious diseases, including zika, malaria, chikungunya, filariasis, and dengue. The overuse and incorrect application of synthetic pesticides to control mosquitoes has resulted in resistance development and environmental contamination, both of which have had a negative impact on human health. To address this issue, the larvicidal and pupicidal potential of acetone extract from Casearia tomentosa fruits was investigated. The extract was evaluated in a lab setting against all larval instars and pupa of Culex quinquefasciatus and Aedes albopictus, as well as against third instar larvae in a semi-field condition. Purified compounds through TLC were also tested against 3rd instar larvae of both mosquito and non-target organisms. The FT-IR and GC-MS analyses were used to characterise the extract. Morphological aberration caused by the acetone extract was observed using FESEM. The anal gills and respiratory siphon of both mosquitoes showed significant deformation from their normal state. 100 ppm was found to cause 100% larval mortality at 24 h of exposure in case of Cx. quinquefasciatus and at 72 h of exposure in Ae. albopictus larvae. After 72 h of exposure under in vitro conditions, the extract demonstrated considerable larvicidal activity with LC50 values of 38.33 and 47.56 against 3rd instar larvae of Culex quinquefasciatus and Aedes albopictus, respectively. The acetone extract can be considered as a highly effective mosquito larvicidal agent that is safe for the environment. Graphical abstract

An increase in the consumer demand and the availability of gluten-free products has led to several brewers investigating brewing with grains other than barley. The primary grain of choice has been sorghum. These new gluten-free beers have a unique flavor and aroma, which previous research has shown is the result of differences in concentration for key chemical compounds, including ethyl butyrate, butyl acetate, isoamyl acetate, ethyl caproate, hexyl acetate, 1-octanol, nonanal, ethyl octanoate, and ethyl decanoate. This study focused looked at the influence different strains of yeast had on the concentration of these key compounds. Beer was brewed using either barley or sorghum malt extract. The concentrations of these key volatile compounds were determined using Solid Phase Microextraction (SPME) with Gas Chromatography and Mass Spectral (GC-MS) detection. Overall, it was found that the concentrations of these compounds were statistically different in the beers brewed from these two grain types. However, the yeast strain had no significant impact on the concentrations.

Background Sea cucumbers can be explored as alternative raw materials by the pharmaceutical and fishery industries as anticancer agents because they contain potential bioactive compounds. Methods This study aimed to determine the anticancer activity of Paracaudina australis extract against breast cancer cells (T47D) using an MTT assay. The secondary metabolites found in P.australis are steroids, terpenoids, saponins, and phenolics. The Thin-Layer Chromatography test results are indicated by Rf values, and steroid compounds in the ethyl acetate fraction are included in the standard Rf values. The isolates obtained were identified by Gas Chromatography-Mass Spectrometry, Fourier-Transform Infrared Spectroscopy, High-performance liquid chromatography, and UV-Visual spectrophotometry. Results The isolated compounds were Dihydrocholesterol and Cholestan-3-ol, with a molecular formula (C 27H 48O). The ion weight and molecular mass of the compound were m/z 388,7. Conclusions This compound may be responsible for the anticancer activity of P.australis. The IC 50 of Isolate F4 was 25,3 μg/ml, and IC 50 of Isolate F7,8 was 13,76 μg/ml.