Abstract: Pomegranate cultivation in the Indian peninsular region, particularly in Maharashtra, significantly contributes to farmers' economic well-being but faces threats from microbial diseases, notably bacterial blight caused by Xanthomonas axonopodis pv. punicae. This study aimed to evaluate the antibacterial potential of bacteriocin produced by Lactobacillus helveticus PMP-6 (Genebank accession number MT 444488) against said pathogen. The bacteriocin was purified, resulting in a specific activity increase from 233.849 AU/mg to 3615.81 AU/mg. Antibacterial assays demonstrated that the purified bacteriocin effectively inhibited X. axonopodis Xpp-1 at 40°C and pH 7.0, with a minimal inhibitory concentration (MIC) of 300 mg/ml and a minimum bactericidal concentration (MBC) of 400 mg/ml, particularly in the absence of proteases. SDS-PAGE analysis revealed a molecular weight of approximately 17 kDa for the isolated and purified bacteriocin. The efficacy was validated through the Detached Leaf Assay (DLA), confirming that treated samples exhibited no symptom development over 96 hours. This research represents the first documentation of the antagonistic activity of Lactobacillus helveticus PMP-6 against X. axonopodis, suggesting its potential as an eco-friendly biocontrol agent to enhance Pomegranate production and promote sustainable agriculture while reducing reliance on agrochemicals.

Abstract: This study examines the effectiveness of generalised additive models (GAMs) and log-log linear models for estimating the parameters of the generalised extreme value (GEV) distribution, which are then used to estimate flood quantiles in ungauged catchments. This is known as parameter regression technique (PRT). Using data from 88 gauged catchments in New South Wales, Australia, flood quantiles corresponding to various Annual Exceedance Probabilities (AEP) were estimated, which were then used as dependent variables and several catchment characteristics were used as independent variables. GAMs were employed to capture non-linearities in flood generation processes. The study evaluates different GAM and log-log linear models, identifying the best ones based on significant predictors and various statistical metrics using a leave one out (LOO) validation approach. Results indicate that GAMs provide more accurate and reliable predictions of flood quantiles compared to the log-log linear models, demonstrating better performance in capturing observed values across different quantiles. The absolute median relative error percentage (REr%) ranges from 33% to 39% for the GAMs, and from 36% to 45% for the log-log models. GAM demonstrates better performance compared to log-log linear models for quantiles Q2, Q5, Q10, Q20, and Q50; however, their performance appears to be similar for Q100.

Abstract: Ship emissions significantly impact air quality, particularly in coastal and port regions, contrib-uting to elevated concentrations of PM₂.₅, and PM₁₀, with varying effects observed across differ-ent locations. This study investigates the effectiveness of emission control policies, inland and port-specific contributions to air pollution, and the health risks posed by particulate matter (PM). A regression discontinuity model at Ningbo Port revealed that ship activities show mod-erate PM₂.₅ and PM₁₀ variations. In Busan Port, container ships accounted for the majority of emissions, with social costs from pollutants estimated at USD 31.55 million annually. Inland shipping near the Yangtze River demonstrated significant PM contributions, emphasizing re-gional impacts. Health risks from PM₂.₅, a major global toxic pollutant, were highlighted, with links to respiratory, cardiovascular, and cognitive disorders. Advances in air purification tech-nologies, including hybrid electrostatic filtration systems, showed promising efficiency in re-moving submicron particles and toxic gases, reducing energy costs. A Random Forest machine learning model developed to predict particulate concentrations post-cleaning demonstrated ro-bust performance (MAE=0.49 P/cm³, R²=0.97). These findings underscore the critical need for stringent emission controls, innovative filtration systems, and comprehensive monitoring to mitigate the environmental and health impacts of ship emissions.

Abstract: Bioinputs are natural products applied to crops that contribute to a more sustainable agriculture by boosting yields and reducing environmental impacts. This study explores the effect of complementary inoculation with growth-promoting bacteria on soybean development and yield. Five treatments with growth-promoting bacteria were evaluated: T1 - Control (no inoculation), T2 - Azospirillum brasilense strains CNPSo 2083 and CNPSo 2084, T3 - Pseudomonas fluorescens strain CNPSo 2719; Azospirillum brasilense strains CNPSo 2083 and CNPSo 2084, T4 - Priestia aryabhattai strain CBMAI 1120; Bacillus haynesii strain CCT 7926; Bacillus circulans strain CCT 0026 and T5 - Priestia megaterium strain BRM 119; Bacillus subtilis strain BRM 2084. In comparison with the control, all treatments with growth-promoting bacteria of the genera Azospirillum, Pseudomonas, Priestia and Bacillus, applied after soybean emergence, induced higher grain yield. Co-inoculation with Priestia megaterium and Bacillus subtilis (treatment T5) resulted in a higher 1000-grain weight, while Priestia aryabhattai, Bacillus haynesii and Bacillus circulans (treatment T4) increased the number of pods and shoot dry weight.

Abstract: This experimental study analyses the extent of chemo-mineralogical changes that occur when a building stone encounters a cycling isothermal treatment at 600 °C. Therefore, four carbonate and two silicate European building stones have been analysed in their fresh quarried and thermally treated conditions by means of colour measurements, in-situ X-ray diffraction (XRD) and optical microscopy. Furthermore, powdered samples have been characterised by Fourier-transform infra-red spectroscopy, simultaneous thermal analysis and cycling thermogravimetry (TG). In-situ XRD spectra reveal a surface limited phase transformation of solid calcite and dolomite at isothermal conditions during the first 10 min at 600 °C and 500 °C, respectively. The onset of thermal de-composition and extend of phase transformation is governed by the microstructure of the solid samples. Inter- and intragranular micro cracks are induced in varying degrees and their incidence depends likewise on the stone’s microstructure. Discolouration indicates a transformation of minor elements across the entire analysed sample volumes. Kaolinite is preserved even after three hours of thermal treatment at its dehydroxylation temperature due to its sheltering in confined pore spaces. Mass loss is more pronounced when cyclic treatment is employed as compared to a nonperiodic treatment, as determined by TG analysis performed at same time intervals.

Abstract:

Enhancing sustainable agricultural practices and water resources management calls for this study, which focuses on calibrating and validating the SWAT model using data from CMIP6. The SWAT model was validated using Bernam streamflow data from 1985-2022, divided into three categories: category 1 (10 years calibration- and 5 years validation), category 2 (15 years calibration- and 10 years validation), and category 3. The SWAT model performed "GOOD" in the Bernam watershed, as indicated by statistical analysis during calibration and validation phases, utilizing statistical indices. The results for the p-factor, r-factor, R2, NSE, PBIAS, and KGE were 0.82, 0.88, 0.72, 0.70, -1.1%, and 0.85 during the calibration period and 0.8, 1.04, 0.75, 0.65, -6.6%, and 0.79 during the validation period. The result of the simulation after adjusting the SWAT model parameters with calibrated best-fit values indicated that the inflow (rainfall) and the outflow (water yield + ET) are 2,873.36mm and 2,592.78mm respectively, with difference of 9.8% for the period of 1991-2005 while 2,921.98 mm and 2,586.07 mm for the inflow and outflow, during 2006-2020 period with difference of 11.5%. The SWAT model effectively predicts agro-hydrological processes, aiding decision-makers in UBRB's agricultural water management and guiding sustainable agriculture through advanced climate projections.

Abstract:

Restoration practitioners specify targets for what the ecosystem will look like to reach recovery goals. Targets may be influenced by the level of degradation, surrounding landscape conditions, societal choice, and a changing and uncertain climate regime. The Society for Ecological Restoration’s International Principles and Standards for the Practice of Ecological Restoration recommends that targets be informed by reference models of site conditions that include biotic composition, environmental setting, and dynamic processes—had anthropogenic degradation not occurred—while accounting for anticipated change. Models optimally reflect a variety of information sources and are based where possible on multiple reference sites of similar native ecological conditions. Using a project site from Colorado National Monument, we illustrate a stepwise process for compiling and synthesizing map, text, and tabular information from reference materials and sites. Reference materials include multiple ecosystem classifications and site inventories to describe composition, structure, and dynamics of the target ecosystems. An ecological integrity framework aids in identifying key ecological attributes and indicators for site measurement. Climate change vulnerability assessment specifies risks to anticipate, while adaptation frameworks point to appropriate strategies. By systematically utilizing existing frameworks and available data, practitioners can streamline the establishment of reference models for ecological restoration.

Abstract:

Rain backscatter corrupts Ku-band scatterometer wind retrieval by mixing with the signatures of the backscatter measurements (${\sigma }^{\circ }$) on the sea surface. The measurements are sensitive to rain clouds due to the short wavelength, and the rain-contaminated measurements in a WVC (Wind Vector Cell) deviate from the measurements that are simulated using the wind GMF (Geophysical Model Function). Therefore, QC (Quality Control) is essential to guarantee the retrieved winds' quality and consistency. The normalized MLE (Maximum Likelihood Estimator) residual ($R_{\text{n}}$​) is a QC indicator representing the distance between the measurements and the wind GMF; it works locally for one WVC. $J_{\text{OSS}}$ is another QC indicator. It is the speed component of the observation cost function, which is sensitive to spatial inconsistencies in the wind field. $R_{\text{n}}J$ is a combined indicator, and it takes both local information ($R_{\text{n}}$) and spatial consistency ($J_{\text{OSS}}$​) into account. This paper focuses on WindRAD on the FY-3E (Fengyun-3E) satellite, a dual-frequency (C and Ku band) rotating-fan-beam scatterometer. The $R_{\text{n}}$ and $R_{\text{n}}J$​ have been established and thoroughly investigated for Ku-band-only and combined C&Ku wind retrieval. A polynomial fit is applied to select the optimal $R_{\text{n}}$​ threshold. The C-band measurements are hardly influenced by rain, so the Ku-based $R_{\text{n}}$​ is proposed for the C&Ku wind retrieval instead of the total $R_{\text{n}}$​ from both C and Ku bands. In conclusion, the $R_{\text{n}}J$ gives the optimal QC result for the Ku-band-only and C&Ku wind retrieval. Adding the C-band into the retrieval suppresses the rain effect; therefore, a promising QC skill can be achieved with fewer rejected winds.

Abstract: Decarbonizing buildings globally requires accurately quantifying the global warming impact of construction materials. However, standard carbon accounting methods and metrics undermine the potential of fast-growing biogenic materials because they ignore the timing of carbon uptake. The consequence is that analyses can indicate a building material is carbon-neutral when it is not climate-neutral. Here, we investigated the time-dependent effect of using fast-growing fibers in durable construction materials. The study estimated the material stock and flow and associated cradle-to-gate embodied emissions for four residential framing systems in the US: concrete masonry units, light-frame dimensional timber, and two framing systems that incorporate fast-growing fibers (bamboo and Eucalyptus). The carbon flows for these four framing systems were then scaled across four adoption scenarios, ranging from business-as-usual (no adoption of fast-growing fibers) to highly optimistic (full adoption of fast-growing materials in new construction within 10 years). Dynamic Life Cycle Assessment modeling was used to project radiative forcing and global temperature change potential. The results show that adoption of fast-growing biogenic construction materials can significantly reduce the climate impact of new US residential buildings within this century under reasonable adoption scenarios. However, net climate-cooling from residential framing will require highly aggressive, immediate adoption of fast-growing biogenic materials.

Abstract: The analyzed data set on the problem of geophagy-lithophagy shows that the instinctive desire, preserved in many groups of animals and humans, to eat mineral-crystalline substances - products of hypergenic transformation of various rocks in the most general form, is a manifestation of evolutionarily conditioned universal way of regulating the material composition of the internal environment, as well as many biological and physiological processes in the body. The effect of minerals on the organism can be divided into their main and secondary functions. The main cause of geophagy-lithophagy in animals and humans all over the world is the regulation of concentration and ratio of rare earth elements in the neuroimmunoendocrine system, which controls metabolic processes and provides immune defense of the body. More than ten secondary causes of consumption of rare earth elements have been identified.