Development of a behaviour pattern-based testing approach for coupled socioeconomic and environmental models.

Understanding the interactions between human and environmental systems is key to sustainable environmental management. Dynamically Coupled Socioeconomic system dynamics models integrated with physically-based Environmental Models (DCSEMs) are promising tools to appropriately capture the non-linear relationships between complex socioeconomic and biophysical systems, thereby supporting sustainable environmental management. However, existing approaches for testing integrated models are commonly based on the point-to-point analysis of model outputs, which is not suitable for DCSEMs that are behaviour pattern oriented. Consequently, the lack of well-defined behaviour pattern-based approaches has limited the adaptability of DCSEMs. To address this gap, this study proposes a novel behaviour pattern-based model testing approach that includes global sensitivity analysis (GSA), auto-calibration algorithms, and evaluation to assess behaviour pattern similarities between model outputs and real-world trends. The proposed approach is demonstrated through a real-world case study, in which an existing DCSEM is calibrated and evaluated to simulate water table depth in the Rechna Doab region of Pakistan. Compared to the conventional numerical point approach, the proposed approach is better suited for DCSEMs, as it replicates observed system behaviour patterns (as opposed to observed point values) over time. Furthermore, the outcomes of the Theil inequality statistical analysis and parameter distribution analysis provide evidence that the suggested approach is effective in testing and improving the performance of the DCSEM by capturing the spatial heterogeneity within the study area. The proposed behaviour-pattern testing procedure is a useful approach for model testing in data-limited, spatially-distributed DCSEMs.

Elevation-dependent intensification of fire danger in the western United States.

Studies have identified elevation-dependent warming trends, but investigations of such trends in fire danger are absent in the literature. Here, we demonstrate that while there have been widespread increases in fire danger across the mountainous western US from 1979 to 2020, trends were most acute at high-elevation regions above 3000 m. The greatest increase in the number of days conducive to large fires occurred at 2500-3000 m, adding 63 critical fire danger days between 1979 and 2020. This includes 22 critical fire danger days occurring outside the warm season (May-September). Furthermore, our findings indicate increased elevational synchronization of fire danger in western US mountains, which can facilitate increased geographic opportunities for ignitions and fire spread that further complicate fire management operations. We hypothesize that several physical mechanisms underpinned the observed trends, including elevationally disparate impacts of earlier snowmelt, intensified land-atmosphere feedbacks, irrigation, and aerosols, in addition to widespread warming/drying.

Integrated assessment of localized SSP-RCP narratives for climate change adaptation in coupled human-water systems.

The assessment of climate change impacts requires downscaled climate projections and context-specific socioeconomic scenarios. The development of practical climate change adaptation for environmental sustainability at regional and local scales is predicated on a strong understanding of future socio-economic dynamics under a range of potential climate projections. We have addressed this need using integrated assessment of a localized hybrid Shared Socio-economic Pathway - Representative Concentration Pathway (SSP-RCP) framework, through an interdisciplinary and participatory storyline development process that integrates bottom-up local expert-stakeholder knowledge with top-down insights from global SSPs. We use the global SSPs (SSP1 to SSP5) as boundary conditions in conjunction with climate change pathways (RCP4.5, RCP8.5) to create localized SSP narratives in an iterative participatory process, using a storytelling method. By using an integrated socio-economic and environmental system dynamics model developed in collaboration with local stakeholders, we explore the potential impacts of plausible local SSP-RCP narratives and quantify important socio-environmental vulnerabilities of a human-water system (e.g., crop yields, farm income, water security and groundwater depletion) by the mid-century period (i.e., by 2050). The framework is developed to inform climate adaptation for Pakistan's Rechna Doab region, which serves as a representative case of a multi-stakeholder coupled human-water system operating in a developing country. Our results suggest that even under limited socio-economic improvements (e.g., technology, policies, institutions, environmental awareness) water security would be expected to decline and environmental degradation (e.g., groundwater depletion) to worsen. Under RCP 4.5, the average projected increase in water demand in 2030 will be about 7.32% for all SSP scenario narratives, and 10.82% by mid-century. Groundwater use varies significantly across SSPs which results in an average increase of about 29.06% for all SSPs. The proposed framework facilitates the development of future adaptation policies that should consider regional and local planning as well as socio-economic conditions.

Warming enabled upslope advance in western US forest fires.

Increases in burned area and large fire occurrence are widely documented over the western United States over the past half century. Here, we focus on the elevational distribution of forest fires in mountainous ecoregions of the western United States and show the largest increase rates in burned area above 2,500 m during 1984 to 2017. Furthermore, we show that high-elevation fires advanced upslope with a median cumulative change of 252 m (-107 to 656 m; 95% CI) in 34 y across studied ecoregions. We also document a strong interannual relationship between high-elevation fires and warm season vapor pressure deficit (VPD). The upslope advance of fires is consistent with observed warming reflected by a median upslope drift of VPD isolines of 295 m (59 to 704 m; 95% CI) during 1984 to 2017. These findings allow us to estimate that recent climate trends reduced the high-elevation flammability barrier and enabled fires in an additional 11% of western forests. Limited influences of fire management practices and longer fire-return intervals in these montane mesic systems suggest these changes are largely a byproduct of climate warming. Further weakening in the high-elevation flammability barrier with continued warming has the potential to transform montane fire regimes with numerous implications for ecosystems and watersheds.

The role of climate change and vegetation greening on the variation of terrestrial evapotranspiration in northwest China's Qilian Mountains.

Terrestrial evapotranspiration (ETa) reflects the complex interactions of climate, vegetation, soil and terrain and is a critical component in water and energy cycles. However, the manner in which climate change and vegetation greening influence ETa remains poorly understood, especially in alpine regions. Drawing on the Global Land Evaporation Amsterdam Model (GLEAM) ETa data, the interannual variability of ETa and its ties to precipitation (P), potential evaporation (ETp) and vegetation (NDVI) were analysed. The Budyko framework was implemented over the period of 1982 to 2015 to quantify the response of ETa to climate change's direct (P and ETp) and indirect (NDVI) impacts. The ETa, P, ETp and NDVI all showed significant increasing trends from 1981 to 2015 with rates of 1.52 mm yr-1, 3.18 mm yr-1, 0.89 mm yr-1 and 4.0 × 10-4 yr-1, respectively. At the regional level, the positive contribution of increases in P and NDVI offset the negative contribution of ETp to the change in ETa (∆ETa). The positive ∆ETa between 1982 and 2001 was strongly linked with the concomitant increase in NDVI. Increases in vegetation contributing to a positive ∆ETa differed among landscape types: for shrub, meadow and steppe they occurred during both periods, for alpine vegetation between 1982 and 2001, and for desert between 2002 and 2015. Climate change directly contributed to a rise in ETa, with P as the dominant factor affecting forested lands during both periods, and alpine vegetation between 2002 and 2015. Moreover, ETp was a dominant factor for the desert between 1982 and 2001, where the variation of P was not significant. The contributions of factors having an impact on ∆ETa are modulated by both the sensitivity of impact factors acting on ETa as well as the magnitudes of factor changes. The greening of vegetation can influence ETa by increasing vegetation transpiration and rainfall interception in forest, brush and meadow landscapes. These findings can help in developing a better understanding of the interaction of ecosystems and hydrology in alpine regions.

Novel multi-targeted nanoparticles for targeted co-delivery of nucleic acid and chemotherapeutic agents to breast cancer tissues.

Selective delivery of drugs to damaged tissues favorable to reduce the side effects while enhancing the therapeutic efficacy. The purpose of the present study was the design and synthesis of multi-targeted nanoparticles for co-delivery of both drug and nucleic acid to cancer cells. In this study biocompatible compounds such as chitosan, polyethylene glycol (PEG), polycaprolactone (PCL), folic acid (FA) and glucose (Glu) were used to synthesize the FA-PEG-Chitosan-PCL-Chitosan-PEG-FA (FPCP) and Glu-PEG-Chitosan-PCL-Chitosan-PEG-Glu (GPCP) copolymers. Then, paclitaxel (PTX), oleic acid-coated FeCO nanoparticles (FeCO-OA) and 6-carboxy-fluorescein phosphoramidate (FAM)-labeled siRNA (siRNA-FAM) were encapsulated into either FPCP or GPCP, or both FPCP and GPCP (GFPCP), using the solvent evaporation technique. In vitro and in vivo biocompatibility and drug delivery efficiency of FPCP/FeCO-OA/PTX, GPCP/FeCO-OA/PTX and GFPCP/FeCO-OA/PTX nanoparticles were determined by recording the MTT assay, weight loss and tumor volume respectively. In addition, the ability of FPCP/FeCO-OA/siRNA-FAM, GPCP/FeCO-OA/siRNA-FAM, and GFPCP/FeCO-OA/siRNA-FAM gene transfer was determined using flow cytometry analysis. Moreover, the effects of applying an external magnetic field to the tumor site on the efficiency of drug delivery using FPCP/FeCO-OA/siRNA-FAM/PTX (NPsA), GPCP/FeCO-OA/siRNA-FAM/PTX (NPsB) and GFPCP/FeCO-OA/siRNA-FAM/PTX (NPsAB) were also investigated in the present study. No significant toxicity was observed for the FPCP and GPCP copolymers. Meanwhile, PTX encapsulated FPCP, GPCP and GFPCP exhibited greater anticancer activities against MCF-7 cells. The in vivo and in vitro results showed that the nanoparticles targeted with both folic acid and glucose increased drug and RNA transfer efficiency compared to when folic acid or glucose alone used. Also, the efficiency of PTX and siRNA-FAM delivery to tumor tissues by nanoparticles increased significantly by applying an external magnetic field to the tumor area. The hydrophobic interactions between different amphipathic copolymers in appropriate is an efficient and easy technique to synthesize complex and multifunctional nanoparticles.

A century of observations reveals increasing likelihood of continental-scale compound dry-hot extremes.

Using over a century of ground-based observations over the contiguous United States, we show that the frequency of compound dry and hot extremes has increased substantially in the past decades, with an alarming increase in very rare dry-hot extremes. Our results indicate that the area affected by concurrent extremes has also increased significantly. Further, we explore homogeneity (i.e., connectedness) of dry-hot extremes across space. We show that dry-hot extremes have homogeneously enlarged over the past 122 years, pointing to spatial propagation of extreme dryness and heat and increased probability of continental-scale compound extremes. Last, we show an interesting shift between the main driver of dry-hot extremes over time. While meteorological drought was the main driver of dry-hot events in the 1930s, the observed warming trend has become the dominant driver in recent decades. Our results provide a deeper understanding of spatiotemporal variation of compound dry-hot extremes.

Modification of the DRASTIC Framework for Mapping Groundwater Vulnerability Zones.

The DRASTIC technique is commonly used to assess groundwater vulnerability. The main disadvantage of the DRASTIC method is the difficulty associated with identifying appropriate ratings and weight assignments for each parameter. To mitigate this issue, ratings and weights can be approximated using different methods appropriate to the conditions of the study area. In this study, different linear (i.e., Wilcoxon test and statistical approaches) and nonlinear (Genetic algorithm [GA]) modifications for calibration of the DRASTIC framework using nitrate (NO3 ) concentrations were compared through the preparation of groundwater vulnerability maps of the Meshqin-Shahr plain, Iran. Twenty-two groundwater samples were collected from wells in the study area, and their respective NO3 concentrations were used to modify the ratings and weights of the DRASTIC parameters. The areas found to have the highest vulnerability were in the eastern, central, and western regions of the plain. Results showed that the modified DRASTIC frameworks performed well, compared to the unmodified DRASTIC. When measured NO3 concentrations were correlated with the vulnerability indices produced by each method, the unmodified DRASTIC method performed most poorly, and the Wilcoxon-GA-DRASTIC method proved optimal. Compared to the unmodified DRASTIC method with an R2 of 0.22, the Wilcoxon-GA-DRASTIC obtained a maximum R2 value of 0.78. Modification of DRASTIC parameter ratings was found to be more efficient than the modification of the weights in establishing an accurately calibrated DRASTIC framework. However, modification of parameter ratings and weights together increased the R2 value to the highest degree.

Stochastic Modeling of Groundwater Fluoride Contamination: Introducing Lazy Learners.

While it remains the primary source of safe drinking and irrigation water in northwest Iran's Maku Plain, the region's groundwater is prone to fluoride contamination. Accordingly, modeling techniques to accurately predict groundwater fluoride concentration are required. The current paper advances several novel data mining algorithms including Lazy learners [instance-based K-nearest neighbors (IBK); locally weighted learning (LWL); and KStar], a tree-based algorithm (M5P), and a meta classifier algorithm [regression by discretization (RBD)] to predict groundwater fluoride concentration. Drawing on several groundwater quality variables (e.g., Ca 2 + , Mg 2 + , Na + , K + , HCO 3 - , CO 3 2 - , SO 4 2 - , and Cl - concentrations), measured in each of 143 samples collected between 2004 and 2008, several models predicting groundwater fluoride concentrations were developed. The full dataset was divided into two subsets: 70% for model training (calibration) and 30% for model evaluation (validation). Models were validated using several statistical evaluation criteria and three visual evaluation approaches (i.e., scatter plots, Taylor and Violin diagrams). Although Na+ and Ca2+ showed the greatest positive and negative correlations with fluoride (r = 0.59 and -0.39, respectively), they were insufficient to reliably predict fluoride levels; therefore, other water quality variables, including those weakly correlated with fluoride, should be considered as inputs for fluoride prediction. The IBK model outperformed other models in fluoride contamination prediction, followed by KStar, RBD, M5P, and LWL. The RBD and M5P models were the least accurate in terms of predicting peaks in fluoride concentration values. Results of the current study can be used to support practical and sustainable management of water and groundwater resources.

Qualitative classification of milled rice grains using computer vision and metaheuristic techniques.

Qualitative grading of milled rice grains was carried out in this study using a machine vision system combined with some metaheuristic classification approaches. Images of four different classes of milled rice including Low-processed sound grains (LPS), Low-processed broken grains (LPB), High-processed sound grains (HPS), and High-processed broken grains (HPB), representing quality grades of the product, were acquired using a computer vision system. Four different metaheuristic classification techniques including artificial neural networks, support vector machines, decision trees and Bayesian Networks were utilized to classify milled rice samples. Results of validation process indicated that artificial neural network with 12-5*4 topology had the highest classification accuracy (98.72 %). Next, support vector machine with Universal Pearson VII kernel function (98.48 %), decision tree with REP algorithm (97.50 %), and Bayesian Network with Hill Climber search algorithm (96.89 %) had the higher accuracy, respectively. Results presented in this paper can be utilized for developing an efficient system for fully automated classification and sorting of milled rice grains.

The therapeutic effect of Tarentula cubensis extract (Theranekron®) in foot-and-mouth disease in cattle: a randomised trial in an endemic setting.

BACKGROUND: Foot-and-mouth disease (FMD) is a contagious viral disease of ruminant animals. Eradication of disease in western countries is by slaughter of infected and in contact animals but this is not possible in endemic countries. There is no standard treatment for FMD in endemic countries, but anti-inflammatory drugs and mild disinfectant and protective dressing to inflamed areas to prevent secondary infection is recommended. METHOD: A randomised controlled clinical trial of a homeopathic preparation of Tarentula cubensis (Theranekron®) was conducted during an outbreak of FMD in cattle in Iran. A single subcutaneous injection of Theranekron® was used as sole treatment in 50 infected animals (treatment group). The control group comprised 15 infected animals treated with standard medication including: daily injection of flunixin meglumine and oxytetracycline and daily dressing of lesions with 4% sodium carbonate. Systemic and local signs were recorded over 14 days. RESULTS: Rectal temperature in treatment group subsided to normal range within 1 day of homeopathic treatment, and was significantly lower in test group than in control group on several successive days (P < 0.05). Healing of inflamed mucosal areas and appetite score of the treatment was significantly better than control during first 3 days of treatment (P < 0.05). CONCLUSION: It appears that Theranekron® is effective for treatment of systemic and local signs of FMD-infected cattle. Further research is justified.