Search Results (454)

This study proposes a multi-objective optimization scheduling method for edible oil transportation in smart manufacturing, focusing on centralized control and addressing challenges such as complex pipelines and shared resource constraints. The method employs the A* and Dijkstra pathfinding algorithm to determine the shortest pipeline route for each task, and estimates pipeline resource usage to derive a node cost weight function. Additionally, the transport time is calculated using the Hagen–Poiseuille law by considering the viscosity coefficients of different oil types. To minimize both cost and time, task execution sequences are optimized based on a Pareto front approach. A 3D digital model of the pipeline system was developed using C#, SolidWorks Professional, and the Helix Toolkit V2.24.0 to simulate a realistic production environment. This model is integrated with a 3D visual human–machine interface(HMI) that displays the status of each task before execution and provides real-time scheduling adjustment and decision-making support. Experimental results show that the proposed method improves scheduling efficiency by over 43% across various scenarios, significantly enhancing overall pipeline transport performance. The proposed method is applicable to pipeline scheduling and transportation management in digital factories, contributing to improved operational efficiency and system integration. Full article

In the absence of appropriate tools and a knowledge base for exploring high-grade metamorphic terrains, felsic gneiss complexes at granulite facies have long been considered barren and have remained undermapped and understudied. This was the case of the Bondy gneiss complex in the southwestern Grenville Province of Canada which consists of 1.39–1.35 Ga volcanic and plutonic rocks metamorphosed under granulite facies conditions at 1.19 Ga. Iron oxide–apatite and Cu-Ag-Au mineral occurrences occur among gneisses rich in biotite, cordierite, garnet, K-feldspar, orthopyroxene and/or sillimanite-rich gneisses, plagioclase-cordierite-orthopyroxene white gneisses, magnetite-garnet-rich gneisses, garnetites, hyperaluminous sillimanite-pyrite-quartz gneisses, phlogopite-sillimanite gneisses, and tourmalinites. Petrological and geochemical studies indicate that the precursors of these gneisses are altered volcanic and volcaniclastic rocks with attributes of pre-metamorphic Na, Ca-Fe, K-Fe, K, chloritic, argillic, phyllic, advanced argillic and skarn alteration. The nature of these hydrothermal rocks and the ore deposit model that best represents them are further investigated herein through lithogeochemistry. The lithofacies mineralized in Cu (±Au, Ag, Zn) are distinguished by the presence of garnet, magnetite and zircon, and exhibit pronounced enrichment in Fe, Mg, HREE and Zr relative to the least-altered rocks. In discrimination diagrams, the metamorphosed mineral system is demonstrated to exhibit the diagnostic attributes of, and is interpreted as, a metasomatic iron and alkali-calcic (MIAC) mineral system with iron oxide–apatite (IOA) and iron oxide copper–gold (IOCG) mineralization that evolves toward an epithermal cap. This contribution demonstrates that alteration facies diagnostic of MIAC systems and their IOCG and IOA mineralization remain diagnostic even after high-grade metamorphism. Exploration strategies can thus use the lithogeochemical footprint and the distribution and types of alteration facies observed as pathfinders for the facies-specific deposit types of MIAC systems. Full article

A green scheduling problem is proposed in this work, where both constraints on intermediate storage capacity and job transportation requirements are simultaneously considered. An improved discrete pathfinder algorithm (IDPFA) with multi-neighborhood local search is proposed to minimize the maximum completion time and total energy consumption. The algorithm addresses the green flow shop scheduling problem with limited buffers and automated guided vehicle (GFSSP_LBAGV). Firstly, based on the machine speed constraints, the transportation time for moving jobs by the automated guided vehicle (AGV) is incorporated to establish a mathematical model. Secondly, the core idea of the pathfinder algorithm (PFA) is applied to the evolutionary process of the discrete PFA, where three different crossover operations are used to replace the exploration process of the pathfinder, the influence of the pathfinder on the followers, and the mutual learning among the followers. Then, a multi-neighborhood local search is employed to conduct a detailed exploration of high-quality solution spaces. Finally, extensive standard test sets are used to verify the effectiveness of the proposed IDPFA in solving GFSSP_LBAGV. Full article

Looking toward the future, governments around the world have started to change their energy mix due to climate change. The new energy mix will consist mainly of Inverter-Based Resources (IBRs), such as wind and solar power. This transition from a synchronous to a non-synchronous grid introduces new challenges in stability, resilience, and synchronization, necessitating advanced control strategies. Among these, Grid-Forming (GFM) control techniques have emerged as an effective solution for ensuring stable operations in microgrids and large-scale power systems with high IBRs integration. This paper presents a systematic review of GFM control techniques, focusing on their principles and applications. Using the PRISMA 2020 methodology, 75 studies published between 2015 and 2025 were synthesized to evaluate the characteristics of GFM control strategies. The review organizes GFM strategies, evaluates their performance under varying operational scenarios, and emphasizes persistent challenges like grid stability, inertia emulation, and fault ride-through capabilities. Furthermore, this study examines real-world implementations of GFM technology in modern power grids. Notable projects include the UK’s National Grid Pathfinder Program, which integrates GFM inverters to enhance stability, and Australia’s Hornsdale Power Reserve, where battery energy storage with GFM capabilities supports grid frequency regulation. Full article

The robotic exploration of space began only five decades ago, and yet in the intervening years, a wide and diverse ecosystem of robotic explorers has been developed for this purpose. Such devices have greatly benefited from miniaturization trends and the increased availability of high-quality commercial off-the-shelf (COTS) components. This review outlines the specific taxonomic distinction between planetary surface rovers and other robotic space exploration vehicles, such as orbiters and landers. Additionally, arguments are made to standardize the classification of planetary rovers by mass into categories similar to those used for orbital satellites. Discussions about recent noteworthy trends toward the miniaturization of planetary rovers are also included, as well as a compilation of previous planetary rovers. This analysis compiles relevant metrics such as the mass, the distance traveled, and the locomotion or actuation technique for previous planetary rovers. Additional details are also examined about archetypal rovers that were chosen as representatives of specific small-scale rover classes. Finally, potential future trends for miniature planetary surface rovers are examined by way of comparison to similar miniaturized orbital robotic explorers known as CubeSats. Based on the existing relationship between CubeSats and their Earth-based simulation equivalents, CanSats, the importance of a potential Earth-based analog for miniature rovers is identified. This research establishes such a device, coining the new term ‘CanBot’ to refer to pathfinding systems that are deployed terrestrially to help develop future planetary surface exploration robots. Establishing this explicit genre of robotic vehicle is intended to provide a unified means for categorizing and encouraging the development of future small-scale rovers. Full article

The Tuztaşı low-sulfidation epithermal Au–Ag deposit (Biga Peninsula, Türkiye) records a multi-stage hydrothermal history that can be interpreted through the trace and rare-earth-element (REE) chemistry of quartz. High-precision LA-ICP-MS analyses of five representative quartz samples (23 ablation spots; 10 analytically robust) reveal two fluid stages. Early fluids were cold, dilute meteoric waters (δ¹⁸O₍H₂O₎ ≈ −6.8 to +0.7‰), whereas later fluids circulated deeper, interacted with felsic basement rocks, and evolved in composition. Mineralized quartz displays marked enrichment in As (raw mean = 2854 ± 6821 ppm; filtered mean = 70 ± 93 ppm; one spot 16,775 ppm), K (498 ± 179 ppm), and Sb (57.8 ± 113 ppm), coupled with low Ti/Al (<0.005) and elevated Ge/Si (0.14–0.65 µmol mol⁻¹). Chondrite-normalized REE patterns show pronounced but variable LREE enrichment ((La/Yb)_n ≤ 45.3; ΣLREE/ΣHREE up to 10.8) and strongly positive Eu anomalies (δEu ≤ 9.3) with slightly negative Ce anomalies (δCe ≈ 0.29); negligible Ce–Eu covariance (r² ≈ 0.05) indicates discrete redox pulses. These signatures indicate chemically evolved, reducing fluids conducive to Au–Ag deposition. By contrast, barren quartz is characterized by lower pathfinder-element contents, less fractionated REE profiles, higher Ti/Al, and weaker Eu anomalies. A composite exploration toolkit emerges: As > 700 ppm, As/Sb > 25, Ti/Al < 0.005, Ge/Si > 0.15 µmol mol⁻¹, and δEu ≫ 1 reliably identify ore-bearing zones when integrated with δ¹⁸O data and fluid-inclusion microthermometry from earlier studies on the same vein system. This study provides one of the first systematic applications of integrated trace-element and REE analysis of quartz to a Turkish low-sulfidation epithermal system, offering an applicable model for vectoring mineralization in analogous settings worldwide. Full article

Route planning under uncertain traffic conditions requires accounting for not only expected travel times but also the risk of late arrivals. This study proposes a mean-upper partial moment (MUPM) framework for pathfinding that explicitly considers travel time unreliability. The framework incorporates a benchmark travel time to measure the upper partial moment (UPM), capturing both the probability and severity of delays. By adjusting a risk parameter ($\theta$), the model reflects different traveler risk preferences and unifies several existing reliability measures, including on-time arrival probability, late arrival penalty, and semi-variance. A bi-objective model is formulated to simultaneously minimize mean travel time and UPM. Theoretical analysis shows that the MUPM framework is consistent with the expected utility theory (EUT) and stochastic dominance theory (SDT), providing a behavioral foundation for the model. To efficiently solve the model, an SDT-based label-correcting algorithm is adapted, with a pre-screening step to reduce unnecessary pairwise path comparisons. Numerical experiments using GPS probe vehicle data from Louisville, Kentucky, USA, demonstrate that varying $\theta$ values lead to different non-dominated paths. Lower $\theta$ values emphasize frequent small delays but may overlook excessive delays, while higher $\theta$ values effectively capture the tail risk, aligning with the behavior of risk-averse travelers. The MUPM framework provides a flexible, behaviorally grounded, and computationally scalable approach to pathfinding under uncertainty. It holds strong potential for applications in traveler information systems, transportation planning, and network resilience analysis. Full article

Chemical leakage accidents in chemical industrial parks pose significant threats to personnel safety, particularly during evacuation processes, where individual behavior and evacuation strategies have a considerable impact on overall efficiency. This study takes a leakage incident at an alkylation unit as a case study. First, ALOHA5.4.7 software was used to simulate the influence of meteorological conditions across different seasons on the dispersion range of toxic gases, thereby generating an annual comprehensive risk zone distribution map. Subsequently, different evacuation scenarios were constructed in Pathfinder2024.1.0605, with the integration of trigger mechanisms to simulate individual behaviors during evacuation, such as variations in risk perception and peer influence. Furthermore, this study expanded the conventional application scope of Pathfinder—typically limited to small-scale building evacuations—by successfully adapting it for large-scale evacuation simulations in chemical industrial parks. The feasibility of such simulations was thereby demonstrated, highlighting the software’s potential. According to the simulation results, exit configuration, shelter placement, and individual behavior modeling significantly affect the total evacuation time. This study provides both theoretical insights and practical guidance for emergency response planning in chemical industrial parks. Full article

The Sidi Aissa Pb-Zn-(Ag) District, located within the Nappe Zone of northern Tunisia, has been reinterpreted as a typical intermediate-sulfidation (IS) epithermal mineralization system based on field observations and lithogeochemical analyses. Previously described as vein-style Pb-Zn deposits, the local geological framework is dominated by extensional normal faults forming half-grabens. These faults facilitated the exhumation of deep Triassic autochthonous rocks and the extrusion of 8-Ma rhyodacites and Messinian basalts. These structures, functioning as pathways for magmatic-hydrothermal fluids, facilitated the upward migration of acidic fluids, which interacted with the surrounding wall rocks, forming a subsurface alteration zone. The mineralization, shaped by Miocene extensional tectonics and magmatic activity, occurred in three stages: early quartz-dominated veins, an intermediate barite-rich phase, and late-stage supergene oxidation. Hydrothermal alteration, characterized by silicification, argillic, and propylitic zones, is closely associated with the deposition of base metals (Pb, Zn) and silver. The mineral assemblage, including barite, galena, sphalerite, and quartz, reflects dynamic processes such as fluid boiling, mixing, and pressure changes. Full article

As parking congestion at airport parking lots intensifies, high-density parking (HDP) systems with multiple parking robots are gaining attention for improving operational efficiency. However, conventional multi-agent pathfinding (MAPF) methods primarily focus on overall efficiency improvement, often neglecting the priority of individual parking tasks. Additionally, these methods assume robots are ideal agents, resulting in physically infeasible paths for parking robots. We propose a multi-robot path planning approach that balances efficiency and priority. The proposed method improves priority-based search (PBS) by dynamically adjusting priorities, thereby ensuring both operational efficiency and priority of individual vehicles. A simulator replicating a real airport parking environment with 100 parking slots and parking robots under development was implemented to validate the approach. Real-world parking data from an airport was used as input, demonstrating that the proposed autonomous parking system can effectively handle peak-season parking demand. The proposed method achieves a throughput exceeding 41 vehicles per hour with appropriate weight value, meeting the peak-season demand while maintaining acceptable fairness. Our approach provides a practical foundation for establishing time-based parking operation strategies and estimating the number of robots recommended for a given parking scenario. Full article

Understanding tortuosity is essential for accurately modeling fluid flow in complex porous media, particularly in the sub-surface reservoir rock; therefore, tortuosity estimation was evaluated using three approaches: Streamline streamline simulations via the Lattice Boltzmann Method (LBM), geometric pathfinding using Dijkstra’s algorithm, and empirical modeling based on pore-structure parameters. The analysis encompassed 1963 micro-Computed Tomography (micro-CT) images of Brazilian pre-salt carbonate and sandstone samples, with the effective porosity extracted from LBM velocity fields, isolating flow-contributing pores, establishing streamline tortuosity as the reference standard. Sandstones exhibited relatively narrow tortuosity ranges (Dijkstra: 1.29–1.75; Streamline: 1.18–2.61; Empirical: 1.18–4.42), whereas carbonates display greater heterogeneity (Dijkstra: 1.00–3.18; Streamline: 1.00–3.68; Empirical: 1.59–4.93). Model performance assessed using the corrected Akaike Information Criterion (AICc) revealed that the best agreement with the data was achieved by the semi-empirical model incorporating coordination number and minimum throat length (AICc = −113.11), followed by the Dijkstra-based geometrical approach (−99.74) and the empirical porosity-based model (202.23). There was a nonlinear inverse correlation between tortuosity and effective porosity across lithologies. This comprehensive comparison underscores the importance of incorporating multiple pore-scale parameters for robust tortuosity prediction, improving the understanding of flow behavior in heterogeneous reservoir rocks. Full article

This study presents a global aerosol climatology derived from six years (October 2018–October 2024) of the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) observations, using a U-Net Convolutional Neural Network (CNN) machine learning algorithm for Cloud–Aerosol Discrimination (CAD). Despite ICESat-2’s design primarily as an altimetry mission with a single-wavelength, low-power, high-repetition-rate laser, ICESat-2 effectively captures global aerosol distribution patterns and can provide valuable insights to bridge the observational gap between the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) missions to support future spaceborne lidar mission design. The machine learning approach outperforms traditional thresholding methods, particularly in complex conditions of cloud embedded in aerosol, owing to a finer spatiotemporal resolution. Our results show that annually, between 60°S and 60°N, 78.4%, 17.0%, and 4.5% of aerosols are located within the 0–2 km, 2–4 km, and 4–6 km altitude ranges, respectively. Regional analyses cover the Arabian Sea (ARS), Arabian Peninsula (ARP), South Asia (SAS), East Asia (EAS), Southeast Asia (SEA), the Americas, and tropical oceans. Vertical aerosol structures reveal strong trans-Atlantic dust transport from the Sahara in summer and biomass burning smoke transport from the Savanna during dry seasons. Marine aerosol belts are most prominent in the tropics, contrasting with earlier reports of the Southern Ocean maxima. This work highlights the importance of vertical aerosol distributions needed for more accurate quantification of the aerosol–cloud interaction influence on radiative forcing for improving global climate models. Full article

This study utilized Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite level-2 data with high-confidence cloud–aerosol discrimination (|CAD| > 70) to investigate the optical properties, vertical distributions, seasonal variations, and aerosol interactions of near-surface cloud layers (cloud base height < 2.5 km) over Australia from 2006 to 2021. This definition encompasses both traditional low clouds and part of mid-level clouds that extend into the lower troposphere, enabling a comprehensive view of cloud systems that interact most directly with boundary-layer aerosols. The results showed that the optical depth of low clouds (CODL) exhibited significant spatial heterogeneity, with higher values in central and eastern regions (often exceeding 6.0) and lower values in western plateau regions (typically 4.0–5.0). CODL values demonstrated clear seasonal patterns with spring peaks across all regions, contrasting with traditional summer-maximum expectations. Pronounced diurnal variations were observed, with nighttime CODL showing systematic enhancement effects (up to 19.29 maximum values compared to daytime 11.43), primarily attributed to surface radiative cooling processes. Cloud base heights (CBL) exhibited counterintuitive nighttime increases (41% on average), reflecting fundamental differences in cloud formation mechanisms between day and night. The geometric thickness of low clouds (CTL) showed significant diurnal contrasts, decreasing by nearly 50% at night due to enhanced atmospheric stability. Cloud layer number (CN) displayed systematic nighttime reductions (18% decrease), indicating dominance of single stratiform cloud systems during nighttime. Regional analysis revealed that the central plains consistently exhibited higher CODL values, while eastern mountains showed elevated cloud heights due to orographic effects. Correlation analysis between cloud and aerosol layer properties revealed moderate but statistically significant relationships (|R| = 0.4–0.6), with the strongest correlations appearing between cloud layer heights and aerosol layer heights. However, these correlations represent only partial influences among multiple factors controlling cloud development, suggesting measurable but modest aerosol effects on cloud properties. This study provides comprehensive observational evidence for cloud optical property variations and aerosol–cloud interactions over Australia, contributing to an improved understanding of Southern Hemisphere cloud systems and their climatic implications. Full article

Background: The PATHFINDER-CHD Registry is a prospective, multicenter, non-interventional registry across tertiary care centers in Germany. The aim is to analyze real-world data on adults with congenital heart defects (ACHD) or hereditary connective tissue disorders who have manifest heart failure (HF), a history of HF, or are at significant risk of developing HF. This analysis investigates the prevalence and clinical impact of overweight and obesity in this unique population. Methods: As of 1st February, 2025, a total of 1490 ACHD had been enrolled. The mean age was 39.4 ± 12.4 years, and 47.9% were female. Patients were categorized according to Perloff’s functional class and the Munich Heart Failure Classification for Congenital Heart Disease (MUC-HF-Class). Results: The most common congenital heart disease (CHD) in this cohort was Tetralogy of Fallot, transposition of the great arteries, and congenital aortic valve disease. Marfan syndrome was the most common hereditary connective tissue disease. Of the patients, 46.1% were classified as overweight (32.8%) or obese (13.3%), while 4.8% were underweight. The highest prevalence of overweight (47.1%) was observed among patients who had undergone palliative surgery, whereas untreated patients showed the highest proportion of normal weight (57.2%). Cyanotic patients were predominantly of normal weight. Patients with univentricular circulation exhibited significantly lower rates of overweight and obesity (35%; p = 0.001). Overweight and obesity were statistically significantly associated with arterial hypertension, diabetes mellitus, and sleep apnea (all p < 0.001). High BMI was linked to increased use of HF-specific medications, including SGLT2 inhibitors (p = 0.040), diuretics (p = 0.014), and angiotensin receptor blockers (p = 0.005). Conclusions: The data highlight the clinical relevance of overweight and obesity in ACHD with HF, emphasizing the need for individualized prevention and treatment strategies. The registry serves as a critical foundation for the optimization of long-term care in this population. Full article

Aerosols play a critical role in modulating the land–atmosphere energy balance, influencing regional climate dynamics, and affecting air quality. Xinjiang, a typical arid and semi-arid region in China, frequently experiences dust events and complex aerosol transport processes. This study provides a comprehensive analysis of the spatiotemporal evolution and potential source regions of aerosols in Xinjiang from 2005 to 2023, based on Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products (MCD19A2), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) vertical profiles, ground-based PM_2.5 and PM₁₀ concentrations, MERRA-2 and ERA5 reanalysis datasets, and HYSPLIT backward trajectory simulations. The results reveal pronounced spatial and temporal heterogeneity in aerosol optical depth (AOD). In Northern Xinjiang (NXJ), AOD exhibits relatively small seasonal variation with a wintertime peak, while Southern Xinjiang (SXJ) shows significant seasonal and interannual variability, characterized by high AOD in spring and a minimum in winter, without a clear long-term trend. Dust is the dominant aerosol type, accounting for 96.74% of total aerosol content, and AOD levels are consistently higher in SXJ than in NXJ. During winter, aerosols are primarily deposited in the near-surface layer as a result of local and short-range transport processes, whereas in spring, long-range transport at higher altitudes becomes more prominent. In NXJ, air masses are primarily sourced from local regions and Central Asia, with stronger pollution levels observed in winter. In contrast, springtime pollution in Kashgar is mainly influenced by dust emissions from the Taklamakan Desert, exceeding winter levels. These findings provide important scientific insights for atmospheric environment management and the development of targeted dust mitigation strategies in arid regions. Full article