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General circulation models (GCMs) are limited in their representation of regional climates. Thus, the selection and downscaling of the most suitable models for regional/local studies are crucial prior to climate change impact studies. This study addressed the selection and downscaling of GCM models from 100 ensembles each from the Shared Socioeconomic Pathways (SSP4.5 and SSP8.5) emission scenarios from the CMIP6 archive using an advanced envelop-based selection approach for Northern Nigeria. We used 2021–2050 as the short-term and 2051–2080 as the long-term study periods. The selection approach revealed that CanESM5 models are more skilful in simulating the warm and wet season, while HadGEM3-GC31-LL in the warm and dry season, whereas MPI-ESM1-2-HR and MPI-ESM1-2-LR are skilful in the cold and dry season. Furthermore, we downscaled the three most skilled models from each season and calculated their spatial averages over Northern Nigeria to provide a more precise illustration of the temperature and precipitation patterns. Under the SSP4.5 emission scenario, the ensemble mean of the downscaled and the (raw) GCMs projected about 13% (8–17%) and 20% (11–35%) increase in average annual precipitation during the short-term and long-term periods, respectively. Similarly, for SSP8.5, the models projected about 23% (5–38%) and 41% (29–60%) increase in the average annual precipitation during short-term and long-term periods respectively. For the temperature, under SSP4.5, the GCMs projected a 1.1 °C (0.26–1.6 °C) and 2.5 °C (0.87–4.04 °C) increase in average annual temperature for short-term and long-term periods respectively. Similarly, an increase of 1.2 °C (0.01–1.78 °C) and 2.7 °C (0.01–4.3 °C) is projected for SSP8.5 during the short-term and long-term periods respectively. These findings can be used for climate impact studies in the region.

Skin diseases remain a prevalent issue despite significant advances in diagnosis and treatment. Ayurveda, with its deep understanding of skin disorders, offers promising solutions, particularly through formulations like Shata- Dhauta-Ghrita (SDG). This Ayurvedic remedy is produced by washing pure cow ghee repeatedly 100 times in a copper vessel, resulting in a product with enhanced cell regeneration and healing properties. SDG is effective for treating various skin conditions such as burns, scars, cuts, shingles, and herpes. The process of washing ghee refines it into a more absorbable form with improved moisturizing and scar-healing abilities. SDG’s improved permeation properties make it a superior option for topical applications compared to pure cow ghee, allowing for better absorption, deeper action, and enhanced therapeutic benefits. The purpose of this study was to study the physiochemical evaluation as well as identification of fatty acids is carried out using Gas Chromatography-Mass Spectrometry (GC-MS) analysis in comparison to cow ghee and Shata-Dhauta-Ghrita. The pure cow ghee used for the preparation of Shata-Dhauta-Ghrita was sourced from ‘Shri Shri Radha Goverdhandhari Go Shala’, Nashik, Maharashtra, India. The SDG is evaluated for organoleptic tests, which included assessments of color, odor, taste, appearance, and texture. Additionally, physicochemical properties such as pH, saponification number, iodine number, peroxide value, viscosity, moisture content, copper content, unsaponifiable value and particle size were analyzed. The formulated SDG were also subjected Gas Chromatography-Mass Spectrometry (GC-MS) analysis to further evaluation of their chemical composition and potential efficacy. Shata-Dhauta-Ghrita found as a more refined and effective option for skin treatment, overcoming the limitations of pure cow ghee while retaining its natural benefits.

This study evaluated the performance of five Global Climate Model (GCM) outputs from the Coupled Model Intercomparison Project phase 6 (CMIP6) in reproducing the historical precipitation and temperature. Observational data from the National Meteorological Agency are used for model evaluation and bias correction. Then, the projections from representative GCMs are used to understand the future climate (2031–2060) of the Baro River Basin under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5) with respect to the historical datasets (1985–2014). Statistical metrics (percent of bias, root mean square error, and coefficient of determination) are used to assess the model's performance in reproducing precipitation and temperature and Compromise Programming (CP) was used in ranking GCMs. GFDL-CM4, INM-CM5-0, and INM-CM4-8 models for precipitation; CMCC-ESM2, MRI-ESM2-0, and INM-CM4-8 for maximum temperature; and GFDL-CM4, INM-CM4-8, and INM-CM5-0 for minimum temperature were selected based on their better simulation. The projected annual precipitation shows increases of 6% under SSP2-4.5 and 16.46% under SSP5-8.5. The mean annual maximum and minimum temperature show increases of 1.43 and 1.96 °C under SSP2-4.5, and 1.81 and 3.11 °C under SSP5-8.5, respectively. Overall, the ensemble of three models outperforms the ensemble of all models for the Baro River Basin when utilising the representative GCMs.

General circulation models (GCMs) allow the analysis of potential changes in the climate system under different emissions scenarios. However, their spatial resolution is too coarse to produce useful climate information for impact/adaptation assessments. This is especially relevant for regions with complex orography and coastlines, such as in Chile. Downscaling techniques attempt to reduce the gap between global and regional/local scales; for instance, statistical downscaling methods establish empirical relationships between large-scale predictors and local predictands. Here, statistical downscaling was employed to generate climate change projections of daily maximum/minimum temperatures and precipitation in more than 400 locations in Chile using the analog method, which identifies the most similar or analog day based on similarities of large-scale patterns from a pool of historical records. A cross-validation framework was applied using different sets of potential predictors from the NCEP/NCAR reanalysis following the perfect prognosis approach. The best-performing set was used to downscale six different CMIP5 GCMs (forced by three representative concentration pathways, RCPs). As a result, minimum and maximum temperatures are projected to increase in the entire Chilean territory throughout all seasons. Specifically, the minimum (maximum) temperature is projected to increase by more than 2 °C (6 °C) under the RCP8.5 scenario in the austral winter by the end of the twenty-first century. Precipitation changes exhibit a larger spatial variability. By the end of the twenty-first century, a winter precipitation decrease exceeding 40% is projected under RCP8.5 in the central-southern zone, while an increase of over 60% is projected in the northern Andes.

We employ a large ensemble of Regional Climate Models (RCMs) from the COordinated Regional-climate Downscaling EXperiment to explore two questions: (1) what can we know about the future precipitation characteristics over Africa? and (2) does this information differ from that derived from the driving Global Climate Models (GCMs)? By taking into account both the statistical significance of the change and the models’ agreement on its sign, we identify regions where the projected climate change signal is robust, suggesting confidence that the precipitation characteristics will change, and those where changes in the precipitation statistics are non-significant. Results show that, when spatially averaged, the RCMs median change is usually in agreement with that of the GCMs ensemble: even though the change in seasonal mean precipitation may differ, in some cases, other precipitation characteristics (e.g., intensity, frequency, and duration of dry and wet spells) show the same tendency. When the robust change (i.e., the value of the change averaged only over the land points where it is robust) is compared between the GCMs and RCMs, similarities are striking, indicating that, although with some uncertainty on the geographical extent, GCMs and RCMs project a consistent future. Potential added value of downscaling future climate projections (i.e., non-negligible fine-scale information that is absent in the lower resolution simulations) is found for instance over the Ethiopian highlands, where the RCM ensemble shows a robust decrease in mean precipitation in contrast with the GCMs results. This discrepancy may be associated with the better representation of topographical details that are missing in the large scale GCMs. The impact of the heterogeneity of the GCM–RCM matrix on the results has been also investigated; we found that, for most regions and indices, where results are robust or non-significant, they are so independently on the choice of the RCM or GCM. However, there are cases, especially over Central Africa and parts of West Africa, where results are uncertain, i.e. most of the RCMs project a statistically significant change but they do not agree on its sign. In these cases, especially where results are clearly clustered according to the RCM, there is not a simple way of subsampling the model ensemble in order to reduce the uncertainty or to infer a more robust result.

Background: Amaranthus caudatus herb is popularly known as Inca wheat. Amaranthus caudatus leaves are used by the indigenous tribes for treating various pulmonary ailments and hepatorenal conditions. Besides it is also used as an antidiarrheal and anti-ulcer agent but there is lack in literature about the compounds responsible for these actions. Previous researches have shown the preliminary phytocomponents present in cold methanolic leaf extract of Amaranthus caudatus by GC-MS analysis. This study was conducted to reveal the difference in bioactive materials and the antioxidant properties present in hot methanolic leaf extract of Amaranthus caudatus along with its uses. Aim: To gain knowledge about the specific bioactive materials present in the hot methanolic leaf extract of Amaranthus caudatus by various analysis and its application in various ailments. Material and Methods: The seeds of Amaranthus caudatus were collected from NBPGR - Shimla Center. GC-2010 and QP-2020 SHIMADZU Japan corporation analyzers were used to find the list of phytochemicals with the help of National Institute of Standards and Technology 20M Library Search Programmes. DPPH, total phenol and total flavonoid present in current plant extract were detected with standard methods. The statistical analysis was done by linear correlation with content in graph pad prism software and statistical significance was finalized by one way ANOVA in SPPS software. Results: The presence of 74 different phytochemicals, major compounds which shows a retention time above 20 include octadecanoic acid (20.258), benzene acetic acid (20.342), 9H-pyridol (3,4-b) indole, cis-sinapyl alcohol (20.741), 6-methylheptanoicacid (21.010), chondrillasterol (25.610), hexadecenoic acid (26.220), 1-heptanol (28.24), 13-docosenamide Z(28.984). The mean value of total flavonoid present was detected as 0.44mg/ml in terms of quercetin after triplication per gram of dried plant extract. The mean value of total phenol content was detected as 0.58 mg/ml in terms of gallic acid after triplication from dried plant extract. The total antioxidant percentage inhibition detected in terms of ascorbic acid by DPPH assay was 48.93mg/ml. Conclusion: The methanolic leaf extract of Amaranthus caudatus has shown better antioxidant properties due to the presence of Phenol, Flavonoid and various bioactive compounds. The selection of compounds from current plant extracts depends on the target application. The compounds of interest can be isolated and used in various in vivo models.

The hydroalcoholic extract of Sphaeranthus amaranthoides (Asteraceae) entire part was screened for hepatoprotective activity on carbon tetrachloride-induced hepatotoxic in Wistar rats. Plant extract was screened for phytochemicals and GC MS study was also carried out for identification of compounds. Further, hepatoprotective activity was performed where carbon tetrachloride and corn oil mixture (1:1 v/v) was injected at 2 ml/kg body weight on the 6th day. The rats were treated with hydroalcoholic extract of SA at the doses of 250 mg/kg and 500 mg /kg body weight daily for 14 days, orally. Results were compared with standard silymarin (10 mg/kg b.w). After completion of observation duration (up to 21 day), all rats were sacrificed and blood was collected. The level of biomarkers of liver injury viz. serum glutamate pyruvate transaminase (SGPT), oxaloacetate transaminase (SGOT), alkaline phosphate (ALKP), total protein (TP), total bilirubin was analysed. Further, change in body weight, liver weight, and histopathologic examination were conducted. Finally, the result concluded that SA extract is an useful therapeutic herb to prevent hepatic impairment due to the presence of various terpenoids, acid esters, phenolics, phytosterols etc. as major groups of compounds identified by GCMS in the plant.

In recent years, many studies on the analysis of microplastics (MP) in environmental samples have been published. These studies are hardly comparable due to different sampling, sample preparation, as well as identification and quantification techniques. Here, MP identification is one of the crucial pitfalls. Visual identification approaches using morphological criteria alone often lead to significant errors, being especially true for MP fibers. Reliable, chemical structure-based identification methods are indispensable. In this context, the frequently used vibrational spectroscopic techniques but also thermoanalytical methods are established. However, no critical comparison of these fundamentally different approaches has ever been carried out with regard to analyzing MP in environmental samples. In this blind study, we investigated 27 single MP particles and fibers of unknown material isolated from river sediments. Successively micro-attenuated total reflection Fourier transform infrared spectroscopy (μ-ATR-FTIR) and pyrolysis gas chromatography-mass spectrometry (py-GCMS) in combination with thermochemolysis were applied. Both methods differentiated between plastic vs. non-plastic in the same way in 26 cases, with 19 particles and fibers (22 after re-evaluation) identified as the same polymer type. To illustrate the different approaches and emphasize the complementarity of their information content, we exemplarily provide a detailed comparison of four particles and three fibers and a critical discussion of advantages and disadvantages of both methods.

The aim of the current investigation was the isolation and characterization of two active constituents i.e. Gulonic acid and Shikimic acid from the leaf extract of the newly discovered medicinal plant of Crinum solapurense (Amaryllidaceae). The Crinum solapurense was collected from the local areas of Solapur, Maharashtra, India. The Gulonic acid and Shikimic acid were isolated using column-chromatography and TLC (Thin Layer Chromatography) and characterized by using UV spectroscopy, FTIR, 1H-NMR,13C-NMR, and GCMS. The isolated compounds showed positive results for various alkaloidal tests like Dragendroff’s, Mayer’s, Wagner’s and Hager’s tests. The first isolated active constituent i.e. Gulonic acid in UV spectroscopy showed ƛ max at 261 nm; in FTIR spectroscopy showed O-H stretching, aliphatic O-H, C=O carbonyl functional groups, in 1H-NMR showed C-H group attached to –OH, C-H & -OH groups; 13C-NMR showed O-H stretching and carbon attached to –OH group and adjacent to carbonyl group; GCMS showed 196g/mol molecular weight. The second isolated active constituents i.e. Shikimic acid in UV spectroscopy showed ƛ max at 235nm; in FTIR spectroscopy showed O-H stretching, aliphatic O-H, C=C functional groups; in 1H-NMR showed C-H group attached to methylene group, C-H group attached to C=C, C-H group attached to –OH, C-H group attached to methylene group; 13C-NMR showed C=O of –COOH group, C=C attached to –COOH group, carbon adjuvant to C=C; GCMS showed 181 g/mol molecular weight. These results showed that two isolated compounds i.e. Gulonic acid and Shikimic acid have never been reported from the leaves extract of the Crinum solapurense plant.

We systematically evaluate the high‐latitude Joule heating of the recently released version 3.0 Thermosphere Ionosphere Electrodynamics General Circulation Model (TIE‐GCM) by comparison to EISCAT incoherent scatter radar measurements. The model performance is examined using normalized root mean square deviations derived from test runs driven by different convection patterns from empirical and data‐assimilated models. The following features are revealed: (a) Data‐assimilated geomagnetic forcing improves the agreement between modeled and EISCAT‐derived Joule heating rates by 8%, 28%, and 54% for low, moderate, and high geomagnetic activity. (b) Increasing model grid resolution from 2.5° to 1.25° leads to ∼${\\sim} $ 20% higher Joule heating rates. (c) AMIE‐driven runs better reproduce the magnitude of the Joule heating rates, AMGeO‐driven runs the vertical profile. (d) Internal model time step resolution has no effect on the Joule heating rates.