Search Results (158)

Lateritic nickel deposits exhibit complex weathering-driven geometries, strong vertical variability, and complex multivariate geochemical relationships. These characteristics challenge conventional deterministic resource modeling. This paper presents a unified probabilistic workflow for lateritic nickel mineral resource modeling that integrates lithology and grade simulation within a consistent geostatistical framework. The methodology combines unfolding, plurigaussian simulation, multivariate imputation of incomplete datasets, projection pursuit multivariate transformation (PPMT) for decorrelation, and conditional simulation using the Turning Bands algorithm. Application to an Indonesian lateritic nickel deposit demonstrates reproduction of lithological proportions, spatial continuity, marginal distributions, and complex multivariate relationships. The proposed workflow enables explicit quantification of geological and grade uncertainty, providing a basis for uncertainty assessment in recoverable resource estimation and supporting downstream applications such as resource classification and drillhole spacing analysis. Full article

Power quality disturbance signals must be continuously monitored, stored, and transmitted for effective analysis, protection, and system planning in modern power systems. The large volume of data generated during power quality monitoring necessitates efficient storage techniques. The sparse representation of power quality signals can significantly reduce memory requirements while preserving important signal characteristics. Since several techniques exist for obtaining sparse representations, it is important to identify the most suitable Sparse Signal Decomposition (SSD) technique for different power quality disturbances. This paper presents a comparative study of various SSD techniques, including Orthogonal Matching Pursuit (OMP), Matching Pursuit (MP), Least Squares–Orthogonal Matching Pursuit (LS-OMP), and Thresholding and Basis Pursuit (BP), along with diverse dictionaries for the representation of power quality disturbances such as sag, swell, transients, and harmonics. Mean Square Error (MSE) and the ratio between the actual signals and reconstructed signals (A/R ratio) are used to evaluate the accuracy, while computation time is considered to compare the computational speed of different techniques. Simulation studies are carried out in MATLAB to evaluate the effectiveness of the SSD techniques. From the simulation results, it is observed that OMP and LS-OMP provide accurate representations of power quality disturbance signals. For sag, swell, and transients, the impulse dictionary performs best with OMP, offering faster computation. However, for harmonics, OMP with DCT dictionary is found to be more effective. Full article

The imbalance between water supply and demand is intensified by population growth and economic development. While water diversion projects are capable of mitigating water shortages, multiple ecological and environmental risks, such as accidental pollution and impairment of ecosystem structure, are introduced by their long-distance water transport and complex corridor environments. The reduction in potential losses hinges on the accurate assessment of these risks. This study integrates the Driving Force–Pressure–State–Impact–Response (DPSIR) model with a projection pursuit model optimized by an improved Sparrow Search Algorithm (SSA) based on seagull optimization and whale optimization operators. A comprehensive risk assessment model was constructed and validated using data from the Chuhe Main Canal for the period 2015 to 2024 as a case study. The results indicate that “water resource utilization rate”, “biodiversity index”, and “public satisfaction” are key factors; project risks have gradually escalated from “relatively low risk” to “relatively high risk”. By this model, the key risk factors and evolutionary patterns of ecological and environmental risks in water diversion projects are able to be scientifically identified, thereby providing a quantitative basis for risk early warning and differentiated management strategies, as well as serving as a reference for the ecological risk assessment of similar inter-basin water diversion projects. Full article

In situ coagulation is regarded as the most effective measure in response to the frequent metal spills in China. Excessive coagulant is often used in pursuit of extremely high removal rates of contaminants. Yet the secondary ecological impact of the iron-containing coagulation flocs left on the river sediments after emergency response is still unclear. In the current study, we investigated the impact of flocs derived from three different iron-based coagulants, polymeric ferric sulfate (PFS), polymeric ferric chloride (PFC), and ferric chloride (FeCl₃), on microbial communities in sediment based on microcosm experiments. Metagenomics, quantitative PCR, and determination of ammonia oxidation potential were adopted to elucidate community shifts. The results indicate that the community structure and function of microorganisms in sediments have been affected, especially processes and species related to nitrogen cycling, and the effect was coagulant-specific. Flocs retrieved from FeCl₃ caused a more pronounced decline in diversity, shifts in community composition, and decreased potential ammonia oxidation. Ammonia-oxidizing archaea (AOA) was more sensitive to iron-containing flocs than ammonia-oxidizing bacteria (AOB), while PFS-flocs tended to reduce multiple genes involved in nitrate reduction. This indicates that the pre-polymerization of inorganic coagulants may be the primary factor leading to different microbial ecological effects. Sulfate, on the other hand, may affect specific biogeochemical processes due to its competition for electron donors. Our results confirmed that even without heavy metals as contaminants, coagulant flocs alone could present an effect on nitrogen cycling in sediments. The results will provide a scientific basis for environmental emergency decision-making: in emergency response to metal pollution incidents, the use of coagulants should be limited to only the necessary level. Full article

Evaluating the aquatic ecological and environmental consequences of dredging projects with precision is essential for reconciling engineering objectives with the long-term health of aquatic ecosystems. This study establishes an evaluation system for the aquatic ecological and environmental impacts of dredging engineering based on the Pressure–State–Response (PSR) analytical framework, and constructs a comprehensive assessment system through Velocity Pausing Particle Swarm Optimization–Projection Pursuit (VPPSO-PP) coupled with fuzzy pattern recognition. Taking the Pinglu Canal project as a case study, the objective weights of indicators are obtained via the VPPSO-PP method, and the impact levels are determined by combining the fuzzy pattern recognition model. Case studies show that the quality of discharged residual water is the most critical factor affecting the aquatic ecological environment, ranking highest with a weight of 0.0839, followed by the proportion of aquatic ecological restoration investment at 0.0685. Among the five typical dredging sections of the Pinglu Canal, the Shaping River section and the Offshore Estuary Section were rated as having a “mild impact.” In contrast, the Main Stream of Qinjiang River section, the Watershed section, and the Qinzhou urban section were rated as having a “moderate impact.” These evaluation results are consistent with the actual engineering conditions. The model developed in this study enables a quantitative and objective assessment of the aquatic ecological impacts of dredging projects. It provides a scientific basis and a practical tool for ecological management and decision-making in dredging operations. Full article

The deployment of solar and other renewable energy technologies (RETs) plays a central role in the global energy transition and the pursuit of sustainable development. Beyond reducing greenhouse gas emissions, these technologies generate far-reaching societal co-benefits that shape environmental quality, social equity, and economic growth. This study systematically reviews peer-reviewed literature published between 2009 and 2025 to identify, integrate, and assess empirical evidence on how RET deployment contributes to societal welfare. Following the SALSA framework and PRISMA guidelines, 147 studies were selected from Scopus and Web of Science. The evidence reveals a consistent welfare triad: environmental gains (emission and pollution reduction, climate mitigation), social gains (improved health, affordability, energy security, and inclusion), and economic gains (employment and income growth, local development). These benefits are, however, heterogeneous and depend on enabling conditions such as policy stability, financial development, grid integration, innovation capacity, and social acceptance. The review highlights that solar energy, in particular, acts as both an environmental and social catalyst in advancing sustainable welfare outcomes. The findings provide a comprehensive basis for policymakers and researchers seeking to design equitable and welfare-enhancing renewable energy transitions. Full article

To address the low trajectory tracking accuracy and limited robustness of conventional reinforcement learning algorithms under complex marine environments involving wind, wave, and current disturbances, this study proposes a proximal policy optimization (PPO) algorithm incorporating an intrinsic curiosity mechanism to solve the unmanned surface vehicle (USV) trajectory tracking control problem. The proposed approach is developed on the basis of a three-degree-of-freedom (3-DOF) USV model and formulated within a Markov decision process (MDP) framework, where a multidimensional state space and a continuous action space are defined, and a multi-objective composite reward function is designed. By incorporating a pure pursuit guidance algorithm, the complexity of engineering implementation is reduced. Furthermore, an improved PPO algorithm integrated with an intrinsic curiosity mechanism is adopted as the trajectory tracking controller, in which the exploration incentives provided by the intrinsic curiosity module (ICM) guide the agent to explore the state space efficiently and converge rapidly to an optimal control policy. The final experimental results indicate that, compared with the conventional PPO algorithm, the improved PPO–ICM controller achieves a reduction of 54.2% in average lateral error and 47.1% in average heading error under simple trajectory conditions. Under the complex trajectory condition, the average lateral error and average heading error are reduced by 91.8% and 41.9%, respectively. These results effectively demonstrate that the proposed PPO–ICM algorithm attains high tracking accuracy and strong generalization capability across different trajectory scenarios, and can provide a valuable reference for the application of intelligent control algorithms in the USV domain. Full article

This study compared CO₂ emissions during a WLTP (Worldwide Harmonized Light-Duty Vehicles Test Procedure) test performed on a chassis dynamometer for the same flex-fuel vehicle, fuelled sequentially with E10 gasoline and E85 fuel. Based on the test data, a CO₂ emissions map was created, describing its dependence on speed and acceleration. The use of a 3D surface enabled the visualisation of the whole dynamics of emissions as a function of engine load in the WLTP cycle, including the identification of distinct emission peaks in areas of high positive acceleration. Analysis of the emission surface enabled the identification of structural differences between the fuels. For E85, more pronounced emission increases are observed in areas of intense acceleration, a consequence of the higher fuel demand resulting from the lower calorific value of bioethanol. In steady-state and moderate-load driving, CO₂ emissions for both fuels are similar. The results confirm that the main differences between E10 and E85 are not simply a shift in emission levels per se, but stem from variations in engine load during the dynamic cycle. Although E85 emits measurable CO₂ emissions, its carbon is not of fossil origin, highlighting the importance of biofuels in the context of greenhouse gas emission reduction strategies and the pursuit of climate neutrality. The presented methodology, combining chassis dynamometer tests with analysis of the speed-acceleration emission map, provides a tool for clearly identifying emission zones and can serve as a basis for further optimisation of engine control strategies and assessing the impact of fuel composition on emissions under dynamic conditions. Full article

The attainment of Sustainable Development is a daunting task globally. In the Sub-Saharan Africa region, it becomes even more unsettling given the resource constraints that may delay or deter its smooth pursuit. This research seeks to explore the contributions of green innovation, digitalization, natural resources rents and institutional quality towards the advancement of sustainable development in African countries. The adoption of the sustainable development index of Hickel, provides the basis for the originality of this paper given the analytical merging of the human development index and ecological footprint that provides for a comprehensive exploration of sustainable development. The data of the forty-three Sub-Saharan African nations is considered in this analysis for the time spanning from 2000 to 2021 and the ‘Method of Moments Quantile Regression’ is employed in the analysis. Major findings indicate that green innovation, digital technology, natural resources rents and renewable energy support sustainable development. These findings are consistent with reducing environmental damage and improving human development. The robust findings establish that while Income per capita and Institutional Quality support the advancement of human development, these variables are however, detrimental to the environment and reduce overall sustainable development. Our paper provides policy makers in African countries a basis to advocate for sustainable development with an inclination toward green technologies, renewable energy, digitalization, and natural resources rents. Full article

A single-plunger two-dimensional electro-hydraulic pump is an integrated unit in which a two-dimensional plunger pump is embedded inside the rotor of a permanent magnet synchronous motor, significantly improving the power density and power-to-weight ratio of electro-hydraulic pumps. The pursuit of a higher power-to-weight ratio has made high-speed operation and high-pressure output persistent research priorities. However, during the iterative design process of electro-hydraulic pumps, cavitation has been identified as a common issue, leading to difficulties in oil suction and even severe backflow. Based on the structure and motion characteristics of the single-plunger two-dimensional electro-hydraulic pump, a CFD numerical model was established to analyze the influence of different working conditions on the cavitation characteristics inside the pump. The study shows that cavitation mainly occurs in the plunger chamber, the distribution groove, and the triangular damping groove. The location and intensity of cavitation are directly reflected by the gas volume fraction. The simulation analysis of variable operating conditions has verified that suction pressure and rotational speed have a significant impact on cavitation—an increase in suction pressure can effectively suppress cavitation, while an increase in rotational speed will exacerbate cavitation development. Specifically, the non-cavitation working boundary of this type of pump was determined through theoretical derivation, and the coupling relationship between critical suction pressure and critical speed was clarified. This work provides an important theoretical basis for the optimization design of the new integrated electro-hydraulic pump. Full article

The Earth is facing an extinction crisis caused by anthropogenic activities, with a primary goal of today’s conservation management being the protection of species from being lost to the Anthropocene. What is missing from the debate surrounding extinction, and how humanity grapples with this issue, is an acknowledgement that it is a natural phenomenon that has always accompanied biological life, including prior to human evolution. Despite the importance of continued efforts to save species from extinctions, there is a need to differentiate extinctions caused by humans (anthropogenic extinctions) from extinctions that would have occurred in our absence (natural extinctions). We propose that there is a dilemma in halting extinctions altogether and in perpetuity if this also prevents non-anthropogenic extinctions that are a key component of life on Earth, particularly when considering much longer timescales than the current extinction crisis necessitates. From this perspective, we argue that non-anthropogenic extinctions should be allowed if they can be distinguished from anthropogenic extinctions. This perspective is intended for managers to consider the ways in which they actively manipulate ecosystems moving forward in the pursuit of conservation and how extinction needs to be considered on a case-by-case basis to fulfil this process of management. Full article

The diesel particulate filter (DPF) is among the most effective measures for controlling particulate emissions from diesel vehicles. Therefore, resource-efficient DPF design and operation are critical to sustainable deployment. In practical engineering, the pursuit of high filtration efficiency inevitably leads to excessively high pressure drop, which in turn impairs the fuel economy and operational reliability of the engine. To address this pair of conflicting objectives, this study introduces a hybrid GRA-MLR-WOA approach, with the initial filtration efficiency and pressure drop at an 80 g soot capture amount as the optimization objectives, to optimize the structural parameters of the DPF. Firstly, based on a computational fluid dynamics (CFD) model and orthogonal experimental design, combined with grey relational analysis (GRA), the effects of key structural parameters on filtration efficiency and pressure drop were evaluated. Secondly, Box–Behnken Design (BBD) was integrated with multiple linear regression (MLR) to establish mathematical regression models describing the relationships between structural parameters, filtration efficiency, and pressure drop. Finally, the whale optimization algorithm (WOA) was employed to obtain the Pareto frontier of the regression models. Through screening with the goal of maximizing initial filtration efficiency, the optimized DPF achieved a 46.85% increase in initial filtration efficiency and a 34.88% reduction in pressure drop compared to the original model. This study targets sustainable filtration design and proposes an optimization framework that jointly optimizes pressure drop and the initial filtration efficiency. The results provide a robust empirical basis for engineering practice and demonstrate strong reproducibility. Full article

Vehicle-to-everything (V2X) communication, a current key area of research, has a large impact on traffic safety, traffic efficiency, autonomous driving technology development, and intelligent transport. In order to achieve the low-latency performance and high transmission efficiency required for V2X communication, channel estimation for transmission channels is particularly important. In this regard, this paper proposes an improved general orthogonal match pursuit (GOMP) channel estimation algorithm based on the base extension model for an orthogonal time frequency space (OTFS) system. Firstly, the channel matrix is decomposed using the basis expansion model. Then, the strong sparsity of the basis function is exploited for channel estimation using the GOMP algorithm, while the ordinal difference restriction method and the weak selectivity principle are introduced to improve the system. The obtained improved GOMP algorithm not only shows a greater improvement in terms of normalized mean square error (NMSE) and bit error rate (BER) performance but also greatly reduces computational complexity, enabling it to better satisfy the needs of V2X communication. Full article

This study, grounded in the Stimulus-Organism-Response (S-O-R) model and incorporating a sustainable consumption perspective, investigates how the characteristics and marketing strategies of blind box products influence continuous purchase behavior through perceived value and perceived needs. Empirical evidence reveals that perceived needs are crucial for sustained purchases, with significant impacts from intellectual property (IP) characteristics and uncertainty, highlighting the core role of emotional resonance and experiential stimulation. In the context of sustainable consumption, long-term consumption is based on rational cognition of product value. Consumers form a dual cognitive understanding of “value” and “needs” regarding blind boxes, with these two acting as mediating variables linking antecedents and behaviors. Perceived sustainable value is increasingly becoming an important factor in decision-making. IP and economic attributes positively influence continuous purchases, while social attributes have an insignificant effect on perceived needs, reflecting the priority of individual needs recognition, with sustainable consumption pursuits gradually integrating. Identity recognition indirectly influences continuous purchases through perceived value and needs, validating the “identity–perception–behavior” logic, with sustainable consumption concepts also participating in this transmission. This research constructs an S-O-R framework suitable for blind boxes, enriching the model’s application in emerging industries. It reveals a dual-driving mechanism, providing a basis for understanding the rational logic of “irrational consumption” and the practice of sustainable consumption in the blind box field. It clarifies the priority of individual and group needs and the path of sustainable consumption. The conclusions offer references for blind box product design (strengthening IP, balancing attributes, integrating sustainable concepts), marketing (reasonable use of uncertainty, focusing on individuals, guiding sustainable behavior), and industry development (guiding rational consumption, promoting transformation, and fostering sustainable development). Full article

Sugar beet (Beta vulgaris L.) is a biennial herbaceous plant belonging to the genus Beta within the family Amaranthaceae. Its root tuber can be used as an effective source for sucrose production. In the pursuit of sustainable development and maximizing the economic value of crops, the full utilization of crop germplasm resources and efficient production is necessary. To better facilitate the collection and utilization of sugar beet germplasm resources, this study used 106 accessions of multigerm sugar beet germplasm provided by the Key Laboratory of Molecular Genetic Breeding for sugar beet as materials. We evaluated the core collections constructed under various strategies using relevant genetic parameters and ultimately established two core collection construction strategies based on morphological and molecular markers. The optimal strategy based on morphological data was “Euclidean distance + Multiple clustering deviation sampling + UPGMA + 25% sampling proportion”, while the optimal strategy based on molecular marker data was “Jaccard distance + Multiple clustering random sampling + UPGMA + 20% sampling proportion”. In addition, representativeness evaluation of the core collection was conducted based on parameters related to both morphology and molecular markers. Principal component analysis (PCA) was utilized for the final determination of the core collection. The results showed that for both the morphological parameters and molecular marker-related parameters, there were no significant differences between the constructed core collection and the original germplasm; the phenotypic distribution frequencies were basically similar. Principal component analysis indicated that the core collection possessed a population structure similar to that of the original germplasm. The constructed core collection had good representativeness. This study, for the first time, proposed a core collection construction approach suitable for sugar beet by integrating morphological and molecular marker methodologies. It aimed to provide a scientific basis for the utilization and development of sugar beet germplasm resources, genetic improvement, and the breeding of new cultivars. Full article