The study of macroscopic discrete granular materials holds significance in hydraulic engineering, geotechnical engineering, as well as road and bridge engineering. Its foundational scientific exploration bears profound theoretical implications and is of pivotal practical value to engineering endeavors. Within the realm of engineering construction, issues such as dam breakages, earth-rock dam damage, and geological disasters involving loose particles pose substantial threats to the safety of both national livelihoods and property. Thus, delving into the examination of the structural stability of granular materials at the mesoscopic scale becomes an imperative pursuit. In this study, the topological structure of granular materials is identified and segmented based on image processing techniques, and the relationship between the compressive capacity of polygonal structures and the number of polygonal sides is studied. The redundancy function is defined to evaluate the structural stability of granular materials. In addition, the definition of structure tensor is introduced, and redundancy and structure tensor are applied to the study of biaxial compression of shale materials. The research results contribute to improving engineering safety and have guiding merits for the research and application of granular materials. Future work could focus on extending these methods to other types of granular materials and exploring their behavior under different loading conditions. (c) 2025 Published by Elsevier B.V. on behalf of Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences.

Electronic waste (e-waste) from nonbiodegradable products present a significant global problem due to its toxic nature and substantial environmental impact. In this study novel electrically conductive biodegradable films of uncured natural rubber (NR) incorporating graphite platelets and chitosan were developed via a latex aqueous microdispersion method. Chitosan was added as a dispersing and thickening agent to encourage the uniform distribution of graphite in the NR matrix at loadings of 20-60 parts per hundred rubbers (phr). FTIR confirmed interactions between NR, graphite, and chitosan. FE-SEM and Synchrotron XTM analyses demonstrated uniform graphite dispersion. The result of XRD revealed the greatest crystallinity at 86.9% with 60 phr graphite loading. Mechanical properties testing indicated a significant increase in Young's modulus to 58.2 MPa, or about 470-fold improvement over the pure NR film. The composite films demonstrated improved thermal and chemical resistance, and their electrical conductivity could rise dramatically to 1.22 x 10-5 S cm-1 at 60 phr graphite loading, or about six orders of magnitude higher than pure NR film. The composite films exhibit antibacterial activity against Staphylococcus aureus and some inhibition against Escherichia coli. In addition, the NR composite films exhibited biodegradability ranging from 16.7% to 25.1% after three months of soil burial, declining with increased graphite loading. These results demonstrate the potential of NR-graphite composites as conductive materials for flexible electronics, such as thin-film electrodes in energy storage devices and sensors.

Flood hazard has resulted in the loss of thousands of lives and large-scale damage to properties. This study has explored, analyzed, and categorized the flood hazard and risk levels of Arba Minch City in South Ethiopia by integrating geospatial and Analytical Hierarchy Process techniques. Data were acquired from DEM with 12.5 m resolution, Landsat 8 OLI, ortho-rectified, and surveyed data from the Municipality. Slope, Elevation, Rainfall, Aspect, Curvature, Topographic Wetness Index, Topographic Roughness Index, Drainage Density, Distance from River, Soil Types, Land Use Land Cover, and Population Density parameters were used. Standard classification criteria were set based on literature and experts' judgment. Data were rasterized, resampled, and reclassified into five classes through the natural break method and readjustment. The flood hazard map was produced using the weighted overlay technique with hazard levels of low (7.39%), moderate (56.13%), and high (36.48%). Whereas, very low and very high remained nil. The flood risk levels were produced ascendingly as 2.4%, 17.3%, 17%, 44%, and 19.4%, respectively. The validity of the model was confirmed by the ROC-AUC Value of 0.923 being fitted with flood damage sites of Shara, Limat, Airport, Agriculture Research Center, Konso Sefer, Ashewamado, Gurba, and Arba Minch University campuses. Slope, elevation, rainfall, aspect and curvature were the top priority flood hazard parameters. The hazard map, population density, and land use land cover inputs have significant weights for flood risks. Thus, the study findings urge that the stakeholders should take integrated and consistent flood risk reduction and management measures.

Biogrouting, a method to enhance soil properties using microorganisms and mechanical techniques, has shown great potential for soil improvement. Most studies focus on small sand columns in labs, but recent tests used 0.5 m plastic boxes filled with sand stabilized with microorganisms and fly ash. The experiments, conducted over 30 days, applied injection and infusion methods with microbial fluids, maintaining groundwater levels to simulate field conditions. Mechanical properties were analyzed through unconfined compressive strength (UCS) tests on extracted samples. Researchers also assessed calcium carbonate distribution and shear strength. Results showed water saturation significantly influenced vertical stress (qu), while UCS correlated with the permeability of sand containing varying calcium carbonate levels. Bacillus safensis, a resilient bacterium used in this process, can withstand extreme conditions. After completing its task, it enters a dormant state and reactivates when needed. The bacteria produce calcium carbonate by binding calcium with enzymes, which cements soil particles, enhancing strength and stability. center dot Testing enzymes on microbes and natural soil center dot Installation settings for drip tools using infusion center dot Soil resistance testing after stabilization using UCS

This study investigates the impact of cementation on the mechanical behavior of sands with various cement content (CSR) in drained triaxial compression, employing both Acoustic Emission (AE) and Environmental Scanning Electron Microscopy (ESEM) measurements. The experimental findings, encompassing quantitative statistics of stress-strain relations, microstructure variations, and AE characteristics, demonstrate that: the addition of CSR from 1% to 20% leads to an exponential rise in peak strength and stiffness, marking a transition from ductile to brittle mechanical failure, which is pinpointed between CSR levels of 5% to 10%. AE characteristics unveil an upward-opening parabola of normalized AE hits with CSR, a clear transition zone identification, and three distinct types of AE rate evolutions corresponding to failure patterns of ductile bulging, shear banding, and brittle fracturing, respectively. It suggests an intimate correlation with the intrinsic differences in micro-mechanical behaviors and AE propagation properties of cemented sands with varying CSRs. Notably, the bulging and shear banding processes are divided by AE into three stages, whereas fracturing is characterized into five stages. Two precursory AE anomalies associated with incipient failure and complex failure modes are observed, emphasizing the advantage of using AE to reflect the internal micro-mechanical behavior of cemented sands over conventional stress-strain manifestations.

Chemical discharge into water has contaminated various locations globally, endangering humans and aquatic life. Industries, farms, wastewater treatment plants, and stormwater overflows release chemicals. The European Union has set pollutant concentration criteria in drinking, surface, and groundwater to reduce water pollution. To comply with these limits, analytical detection methods must be rapid, reliable, and able to identify even minute levels of chemicals. Agriculture uses pesticides to keep crops safe from illnesses, insects, and weeds. Few chemicals work, while the remainder sink into the soil and damage ground and surface water. Due to the growing emphasis on scene analytes over chromatographic approaches, new pesticide evaluation methods have been prioritized. This report summarises various electrochemical pesticide detection studies in a simple and targeted manner. This study examines the electrochemical detection of carbamates, organophosphorus, organochlorine, pyrethroids, and pyrethrins. Electrochemical diagnostic methods, electrode materials, electrolyte and pH of interesting samples, and sample matrices are examined. This paper will also discuss current advances in the respected study, analytical obstacles, and future opportunities. Many electrochemical investigations and analytical data are summarised in this article, which also describes the linear dynamic range of concentration and limit of detection for electrochemical pesticide sensing. This review discusses electrochemical pesticide sensing advances in the utilization of various nanomaterials.

Soil erosion has both on-farm and off-farm effects. On-farm, reduced soil depth can decrease land productivity, while off-farm, sediment transfer can damage streams, lakes, and estuaries. Therefore, optimal soil erosion modeling is a crucial first step in soil erosion research. One of the most important aspects of this modeling is the accuracy and applicability of the soil erosion factors used. Various methods for calculating these factors are discussed in the literature, but no single method is universally accurate. After an extensive review of the literature, we propose using the existing revised universal soil loss equation (RUSLE) factors for global application. Additionally, we conducted a grassroots-level experiment to demonstrate the effectiveness of the proposed methods. RUSLE is identified as the most suitable model for global-scale soil erosion modeling. We evaluated the potential impacts of climate and land use and land cover (LULC) by utilizing shared socio-economic pathways (SSPs) alongside projected LULC scenarios. A suitable general circulation model (GCM) was selected after comparing it with recorded data from a base period. This model was validated with experimental observations, confirming its effectiveness. This review article outlines the future direction of soil erosion modeling and provides recommendations.Graphical AbstractThe graphical abstract visually summarizes the comprehensive methodology and key findings associated with optimal soil erosion modeling and management. It highlights a structured approach, beginning with identifying optimal methods for assessing soil erosion factors: Rainfall and Runoff Erosivity (R), Soil Erodibility (K), Slope Length and Steepness (LS), Cover and Management (C), and Support Practice (P) integral components of the Revised Universal Soil Loss Equation (RUSLE). It illustrates the detailed methodological framework, emphasizing selecting suitable climate models for projecting future R factors, combined with projected land use and land cover (LULC) scenarios derived from Shared Socio-economic Pathways (SSPs). The scenarios shown range from lower emissions (SSP 126) to higher emissions (SSP 585), indicating progressive increases in future erosion risk. Moreover, it explicitly ties the research findings to policy recommendations, underscoring a holistic approach aligning soil conservation with Sustainable Development Goals (SDGs): specifically, Climate Action (SDG 13), Life on Land (SDG 15), and Zero Hunger (SDG 2). Suggested measures include integrating soil erosion control into broader policy frameworks, promoting sustainable land management practices such as agroforestry and contour plowing, and fostering policy integration and collaboration to enhance conservation effectiveness. Overall, the graphical abstract succinctly depicts how climate change, socio-economic dynamics, and LULC variations amplify future soil erosion risks, reinforcing the need for targeted, sustainable, and integrated soil conservation strategies globally.

Real-time flood forecasting updating is essential in improving the forecasting performance and preventing flood damages. The advanced dynamic system response curve (DSRC) method has been validated to be effective by adjusting precipitation based on simulated streamflow errors. However, the time lag between input-output signals is not explicitly considered in the original DSRC, resulting in the problem that the most recent precipitation information is not utilized in updating the forecasting. Moreover, regularization techniques are normally introduced in DSRC to ensure the numerical stability of error estimation, however, the commonly used Ridge estimator can result in excessive adjustment of precipitation. To address these critical issues, we proposed an improved precipitation adjustment framework (DSRC-ARMA) that integrated the DSRC method and the autoregressive-moving average (ARMA) model, such that the most recent precipitation information can be used for a complete precipitation adjustment. Moreover, alternative regularized estimators (i.e., the Lasso and Elastic Net estimators) were introduced and cross-compared to prevent the excessive adjustment issue. The performance of the proposed framework was evaluated in two basins in China. The results showed that the DSRC-ARMA method outperformed the original DSRC method in terms of overall goodness-of-fit (e.g., Nash-Sutcliffe efficiency improved from 0.94 f 0.03 to 0.95 f 0.04 and 0.89 f 0.05 to 0.91 f 0.05, respectively in Dapoling (DPL) and Jianyang (JY) basin) and particularly capturing the peak flows (relative error of peak flow decreased from 13.6 f 7.3 % to 5.2 f 3.7 % and from 10.1 f 7.8 % to 5.9 f 3.5 % in DPL and JY, respectively). For different regularized estimators, the Ridge estimator was most suitable for the rainfall events without intermittent non-rainfall time segments (due to its veracity feature); while the Lasso estimator performed better for intermittent rainfall events, due to its feature of sparsity that can confine non-rainfall period errors to be zeros and thus avoid excessive adjustment. Overall, the proposed precipitation adjustment framework holds the potential to enhance the real-time flood forecasting accuracy, thereby offering a valuable approach for flood mitigation.

Drainage is a common practice in geotechnical engineering concerning dredged marine soils. Current drainage techniques, including surcharge preloading, vacuum preloading, and combined vacuum-surcharge preloading, have been proven to be effective in soft soil treatment, but are also criticized for their high energy consumption. This paper made a brief review on existing drainage techniques and proposed some prospects for the next-generation techniques in response to the public concern of sustainability. It is found that all conventional preloading techniques have been well studied from tests to modeling, and improved vacuum preloading tends to be used in combination with other techniques. Drainage techniques with lower energy consumption can be realized either by using renewable energy or designing biomimetic devices. The paper is expected to provide a comprehensive while concise report on recent advances in drainage techniques for dredged marine soils and in the meanwhile give an insight into the further development towards a more sustainable future.

For six decades the African Journal of Range & Forage Science and its precursors have contributed to understanding drivers of rangeland degradation and development of approaches for restoration of damage by grazing, mining and other forms of land use. Of the 857 articles selected by the keyword search, only around 150 focused on reversing loss of natural capital, including soil, water and biodiversity and or resilience, and were cited in this review. Restoration approaches ranged from grazing management such as resting, rotational grazing and grazing intensification, to interventions such as burning, browsing and clearing of encroaching woody or non-native plants, resource capture, reseeding and replanting. Global change brings novel challenges for restoration research. Major knowledge gaps include assessment of restoration progress, development of policy and incentives to promote and fund restoration, and identification of unintended risks posed by restoration interventions.