Search Results (83)

The increasing interest in carbon-free fuels has positioned ammonia as a promising energy carrier for Internal Combustion Engines (ICEs), particularly in hard-to-abate sectors such as Heavy-Duty (HD) transport and maritime applications. However, its low reactivity, narrow flammability limits, and intrinsic nitrogen content pose significant challenges for stable combustion and emissions control. This work presents a predictive Quasi-Dimensional (QD) combustion model applied to simulate ammonia-fueled engines operating under both Spark Ignition (SI) and Reactivity Controlled Compression Ignition (RCCI) modes. The proposed framework couples a turbulent premixed combustion sub-model with a diffusive combustion sub-model, including a dedicated fuel-NO_x mechanism to capture nitrogen oxide formation pathways associated with fuel-bound nitrogen. The model accounts for key physical and chemical processes governing combustion, such as ignition delay, mixture stratification, and heat release dynamics, while maintaining computational efficiency suitable for parametric studies. The model is validated against experimental data from a Single-Cylinder Engine (SCE) over a wide range of operating conditions, including variations in equivalence ratio, spark timing, Ammonia Energy Fraction (AEF), and injection strategy. Results demonstrate good agreement in terms of in-cylinder pressure evolution, Apparent Heat Release Rate (AHRR), and NO_x emissions, with peak-pressure errors below 4 bar and peak-pressure locations predicted within 2 crank angle degrees. Notably, the dedicated fuel-NO_x sub-model substantially improves emission predictions, revealing that fuel-bound nitrogen is the dominant source of NO_x in ammonia combustion. Overall, the proposed QD model represents a robust and efficient tool for the analysis and optimization of ammonia-fueled engines, supporting the development of low-carbon combustion strategies for future energy systems. Full article

Against the background of severe wear failure of Rotary Tillage blades restricting agricultural tillage efficiency, this study aimed to explore wear resistance differences, reveal wear mechanisms and locate critical failure zones to support blade material selection, structural optimization and localized strengthening. Five commercial IT195 Rotary Tillage blades made of 65Mn and 60Si2Mn steels were tested via a soil-bin rotary wear test rig. Microstructure, hardness and wear morphology were characterized by metallographic microscopy, Vickers hardness test and SEM, while 3D scanning and stress simulation were adopted to analyze full-cycle wear behavior of the optimal blade. The results showed that the E-type blade with 60Si2Mn possessed the best wear resistance, with minimum mass and dimensional wear loss and the gentlest wear rate, attributed to its single-phase acicular martensite and high hardness of 627.73 HV, forming uniform shallow grooves and suppressing micro-cutting and spalling. Full-cycle wear analysis demonstrated highly uneven wear distribution, with the bend transition zone linking tangential and side cutting regions identified as the critical failure zone featuring the largest wear depth and fastest material loss, verified by stress concentration from simulation. This work provides theoretical support and targeted references for material optimization, structural design and surface strengthening of key regions of Rotary Tillage blades. Full article

The greatest challenge of location recommendation is data sparsity. Some works introduce auxiliary information such as social links and semantics to enrich the representation. However, there are still two main limitations. Firstly, existing models only investigate how a person chooses POIs (Point-of-Interests), highlighting the user interest in locations from a human perspective, limited by users’ sparse trajectory. Secondly, they recommend POIs by one’s trajectory independently. However, it is hard to uncover specific behavior patterns or daily routines individually for each user. To address these problems, we develop a novel method for the next location recommendation via bi-directional inference and similarity-aware enhancement (SimBIN). Specifically, it considers the location recommendation task from both the human and location view, conducting the next POI inference and the next visitor inference synchronously. In particular, we employ the adaptive learning strategy to refine the model based on the conformity of two inference parts. Moreover, for the POI inference, we take the highly similar users to approximate a user’s behavior for enriching the next POI candidates. It is similar for the user inference. Experiments show that the proposed SimBIN significantly outperforms the state-of-the-art approaches. Furthermore, each key component can be refined and generally used in other frameworks. By establishing a bidirectional probabilistic collaboration framework, this study not only advances the theoretical understanding of mutual regularization in spatial-temporal modeling, but also provides a possible solution for personalized location-aware services and urban trajectory planning. Full article

The Macaronesian archipelagos host exceptionally well-preserved coastal sedimentary deposits formed during the warmest period of the Last Interglacial episode, the Marine Isotope Substage 5e (MIS 5e). Numerous MIS 5e fossiliferous outcrops occur, scattered across several islands of the Canary Archipelago. Among these is San Juanito, a small outcrop located in the eastern sector of Punta del Hidalgo (northeast Tenerife Island), where MIS 5e sediments are distributed over an area of approximately 480 m². A multidisciplinary study was conducted, aiming to: (i) determine the age of the fossiliferous sediments; (ii) define the stratigraphic relationships between the sedimentary deposit and the underlying/overlying volcanic sequences; (iii) assess the taxonomic richness and the functional palaeobiodiversity of this palaeosite; and (iv) provide a comprehensive palaeoecological reconstruction of the MIS 5e environment. Based on two key ecostratigraphic indicator species for the Canarian MIS 5e, the San Juanito sequence is here assigned to the Last Interglacial. Qualitative sampling yielded forty mollusc taxa, including three gastropods that represent new records—Alvania johannae Moolenbeek & Hoenselaar, 1998, Krachia tiara (Monterosato, 1874), and Barleeia unifasciata (Montagu, 1803)—bringing the current MIS 5e checklist for the Canary Islands to 202 gastropods and 80 bivalves. The highly cemented matrix of the San Juanito deposits prevented the collection of standardized 1 kg bulk sediment samples. Nevertheless, we strongly recommend adopting this quantitative approach in future studies of suitable MIS 5e outcrops across the archipelago. The faunal assemblage indicates that the San Juanito region was dominated by rocky shores during the MIS 5e, much like today. This paleoenvironmental reconstruction is based on the high frequency of species associated with hard substrates—including echinoids, vermetids, fissurellids, and patellids—and the overwhelming dominance (95%) of epifaunal gastropods. Full article

To address severe stress concentration, excessive convergence, and instability of the roadside backfill body (RBB) in gob-side entry retaining (GER) under thick and hard roof conditions, this study investigates the control mechanism of main roof fracture position on surrounding rock stability, using the 3⁻¹01 working face of Huoluowan Coal Mine as a case study. A combined approach integrating theoretical analysis, numerical simulation, and field investigation is adopted. A statically indeterminate mechanical model based on masonry beam theory is established to characterize the lateral roof fracture behavior. The deflection and bending moment distributions are derived, and a criterion for fracture position determination is developed based on the maximum bending moment condition. The theoretical results indicate that the natural fracture position is located approximately 9.4–11.2 m inside the gob boundary. Numerical simulations using UDEC Trigon under different fracture positions (−2 m, 1 m, 5 m, and 9 m) show that fracture location significantly affects the mechanical response of GER. Fractures occurring above the roadway or RBB induce large deformation levels and more extensive plastic zones, while gob-side fracture conditions correspond to relatively lower disturbance levels and improved structural stability. The RBB exhibits shear-dominated failure characteristics, and the displacement distribution is non-uniform along height, with larger deformation in the middle-to-upper region. To improve stability, a coordinated control strategy combining anchor cable reinforcement and directional long-distance hydraulic fracturing (HF) is proposed to regulate the main roof fracture position through the formation of artificial weak planes. Field monitoring results show that the maximum displacements of the roof, floor, and ribs are 558 mm, 233.5 mm, and 71.3 mm, respectively, with a convergence ratio of 19.8%. Borehole imaging confirms the development of hydraulic fractures within the designed roof stratum, supporting the effectiveness of the proposed control approach. These results demonstrate that the fracture position of the main roof plays a key role in controlling GER stability, and its regulation provides an effective means for improving roadway performance under complex geological conditions. Full article

Practical failures of cryptographic key management rarely stem from weak algorithms: they arise from the difficulty users face in memorizing and reliably recalling high-entropy secrets. Password-based and brainwallet approaches collapse under selection bias, while machine-generated mnemonics such as BIP-39 impose a significant memory burden. This paper introduces GeoVault, a key derivation framework that uses remembered geographic locations as the cryptographic input. Keys are derived from a small set of user-selected map points, encoded deterministically using a geospatial scheme and hardened with the Argon2id memory-hard function. We develop a formal entropy model that distinguishes nominal from effective spatial entropy under attacker-prioritized geographic dictionaries and quantifies the additional reduction caused by demographic selection bias. Through information-theoretic analysis and CPU-GPU benchmarking, we show that spatial secrets carry a substantially higher effective entropy floor than human-chosen passwords, and that Argon2id creates a strong asymmetry between legitimate users and offline adversaries: at a memory cost of 1 GiB, an attacker using a high-end GPU can test approximately 66 candidate secrets per one defender key derivation. This residual throughput advantage is, however, overwhelmed by the exponential growth of the search space when multiple locations are selected. Selecting $n\ge 3$ geographic points is necessary and sufficient to achieve cryptographic-strength brute-force resistance under the global attacker prior across all evaluated Argon2id configurations. Against a demographically targeted attacker with city-level knowledge of the user, $n=3$ maintains Human-Scale Secure resistance; $n=4$ with a chaining depth of $k=6$ restores the Super Secure zone at an ≈8 s user-side wait. Single-point configurations remain insecure regardless of memory cost hardening. Full article

Tick-borne diseases are a growing public health concern in the Mediterranean. Brijuni National Park (BNP), a unique, highly visited island ecosystem characterized by increased large game host density and diverse Mediterranean habitats, presents an elevated risk for pathogen co-circulation. This study addresses the lack of spatial and epidemiological data to accurately assess human exposure risk in this environment. We performed a detailed geospatial and epidemiological risk mapping of pathogen co-circulation in BNP. A total of 587 hard ticks were collected across 26 georeferenced micro-locations (2020–2022). Ticks were morphologically identified and subsequently screened for six key zoonotic bacterial pathogens using qPCR. The Minimal Infection Rate (MIR) and a Co-infection Rate (CR) were calculated. Geographic Information System (GIS) mapping was utilized to map ecological determinants of risk. Ixodes ricinus was the overwhelmingly dominant vector (94.0%), peaking in spring, with activity absent in summer. Recorded diverse tick fauna also included Hyalomma marginatum (3%), Haemaphysalis punctata (2%), Ixodes frontalis (0.8%) and Rhipicephalus sanguineus (0.2%). Active circulation of Borrelia burgdorferi s.l. (Bbsl), Anaplasma phagocytophilum, and Ehrlichia canis were confirmed. Bbsl presented the highest MIR (3.05). The Co-infection Rate (CR) was notably high at 29.41%, with triple co-infections (Bbsl, A. phagocytophilum, E. canis) concentrated in cultivated mosaics and holm oak forests (Quercus ilex L.). The highest number of ticks was recovered from ecotone zones, accounting for 50.0% of the total catch, confirming them as high-risk interfaces. The absence of Rickettsia conorii may be attributed to the strict control/absence of its primary host (domestic dogs). The presence of the exotic vector H. marginatum was also confirmed. The high rate of co-infection and the spatial concentration of risk in specific habitats underscore an elevated and complex public health risk in BNP, closely linked to habitat structure and increased game host density. This research provides an essential geospatial framework for targeted ‘One Health’ management, prioritizing vector control in ecotone zones and dense forest refugia. Urgent surveillance for the exotic H. marginatum is warranted to monitor the potential risk of Crimean-Congo Hemorrhagic Fever. Full article

To address the technical challenge of large-area roof hanging and induced strong strata behaviors in deep mines with hard roof strata, a study on pressure relief using hydraulic fracturing technology was conducted, taking the 1012006 working face in the Yuanzigou Coal Mine as the engineering background. Through geological survey and key stratum theory analysis, a low-position key stratum located 23 m above the roadway roof was identified as the target layer for fracturing. True triaxial hydraulic fracturing experiments coupled with acoustic emission (AE) monitoring revealed a synchronous response characterized by a sudden drop in injection pressure and a rapid increase in AE counts. This established a quantitative correlation between rock mass fracturing and AE characteristics, providing a theoretical basis for field microseismic monitoring. Based on the “dual-borehole synergy” borehole layout principle, a fracturing network comprising 6 drilling fields and 12 directional long boreholes was designed, with a total drilling length of 5727 m and 120 planned fracturing stages. Specialized equipment was selected for implementation. Field monitoring results demonstrated: a maximum fracturing influence radius of 27.8 m; that the average daily frequency and total energy of microseismic events decreased by 50.65% and 27.73%, respectively; and that the stress in the deep part of the roadway decreased by 17.69%. These results confirm the effective improvement of the roof stress environment and the successful achievement of the expected pressure relief and rockburst prevention effect. Full article

Bed separation is a common geological phenomenon in the overburden strata during coal mining, which easily induces water inrush hazards, surface subsidence hazards, and other engineering disasters, thus seriously threatening the safety and efficiency of coal mining operations. This paper presents the spatiotemporal evolution characteristics and dynamic prediction of bed separation. The different boundary conditions before and after coal mining disturbance are considered to calculate and predict the location, spatial dimension and spatiotemporal evolution process of bed separation development. Theoretical analysis and scale model tests are used to study the distribution and process of bed separation development with comparisons made between the pre- and post-mining conditions. Formulas for the dynamic prediction of bed separation and a criterion for identifying bed separation development locations are proposed. The vertical propagation coefficient (K_s) and the horizontal development coefficient (K_l) of bed separation are proposed to quantitatively predict the vertical propagation extent and horizontal expansion scale of bed separation space with the advancement of the panel, providing key indicators for the dynamic prediction of bed separation evolution. The results show that the size and duration of bed separation space increase abnormally in the presence of thick and hard strata. This study provides a theoretical basis and practical guidance for the design and optimization of bed separation water hazard prevention and overburden grouting for subsidence control. Full article

In this study, we examine an ex-service, Ni-base single-crystal blade made of alloy PWA1483, which was in service for 6000 h. Using light optical, scanning, and transmission electron microscopy, we analyzed the microstructure at the blade’s tip, middle, and root. Key focus areas included surface features, dendrite spacings, γ’-particle sizes, and dislocation densities. The findings reveal that the bulk microstructure hardly evolved. Dendrite spacings exhibited a consistent microstructure across all locations and there were no significant differences between the local alloy chemistries of dendritic and interdendritic regions, indicating high-quality processing. A bimodal γ’-particle distribution was observed. Variations in γ’-sizes and γ-channel widths were noted, with the tip showing rounded γ’-particles. Small spherical particles occurred only in the root and middle of the blade. The middle location exhibited the highest hardness. Dislocation densities were low and uniform, with the highest density correlating with the highest hardness. Full article

Existing research on green transformation predominantly emphasizes “hard constraints” such as carbon taxes and environmental regulations, while neglecting “soft constraints” shaped by environmental sentiment expressions from key actors such as the public, financial institutions, media, and government. In particular, the collective influence of these multi-actor environmental sentiments remains insufficiently explored. This study fills that gap by constructing a collaborative governance framework using multi-source heterogeneous data from China spanning 2013–2023, including 330 provincial government work reports, 1862 bank annual reports, 2472 newspaper articles, and 68,519 Weibo posts, matched to 4708 firm-year observations of Chinese A-share energy companies. We quantify environmental sentiment tendencies through natural language processing, calculating the index as (negative word frequency − positive word frequency)/total word frequency at the province-year level, thus higher index value indicates more negative sentiment tendency, while green transformation is proxied by ln(green patent applications + 1). The results reveal the following: (1) More negative environmental sentiment tendencies from financial institutions, media, public, and government significantly promote green transformation in energy enterprises, with stronger effects observed from financial institutions and government. (2) Economic and climate policy uncertainty selectively weaken the impact of financial institutions’ sentiment, while the moderating effects for other actors are statistically insignificant. (3) The effect of multi-actor environmental sentiment is more pronounced for firms located in eastern China, operating under high competition or stricter environmental regulations. This study provides a novel, quantified approach to assessing multi-actor environmental sentiment tendencies, affirms the effectiveness of informal governance, and highlights the importance of stable policy in guiding corporate green transformation in emerging economies. Full article

This paper investigates the effectiveness of a coal mine methane drainage system in hard coal mining, with particular emphasis on coal seam 501 at the Staszic–Wujek coal mine (Polska Grupa Górnicza S.A., Katowice, Poland) in the Upper Silesian Coal Basin (USCB), Poland. The study evaluates methane drainage efficiency considering geo-mechanical conditions governing the optimal location of drainage boreholes. Conventional and long directional boreholes are analyzed. Opposite to conventional static analytical approaches, the proposed integrated analysis framework incorporates multi-physics processes, improving forecasting accuracy and enabling dynamic optimization of methane control in deep coal mines. The framework reproduces the geometry of the mining system and the mechanical properties of the surrounding rock mass, allowing the influence of geo-mechanical processes on methane drainage efficiency to be assessed. The methane content of coal seam 501 and methane sorption kinetics on representative coal samples are analyzed together with key characteristics of the mine ventilation system, including air and pressure distribution in workings and goafs and migration paths of methane–air mixtures within coal panel II/C. Full article

Urban commercial restructuring, driven by the closure of traditional supermarkets and the expansion of new-format superstores, creates a large-scale spatial reallocation challenge requiring scientific location-allocation methods. Traditional heuristic algorithms such as Genetic Algorithm (GA) struggle with discrete spatial optimization under 400+ candidate sites and complex geographic mask constraints: they converge slowly and easily fall into local optima. This study proposes a Deep Reinforcement Learning (DRL) framework named GeoPPO (Geospatial Proximal Policy Optimization) to address this gap. Using Xi’an’s retail restructuring as a case setting—427 candidate locations and multidimensional geographic features—the approach models spatial constraints via a gridded environment encoded as a five-channel state tensor. Key innovations include a dynamic action-constraint mechanism that masks invalid actions based on boundary rules and competition avoidance, and a curriculum learning strategy that enables stable convergence. The framework fills the need for methods that handle hard spatial constraints in large-scale location-allocation. Tests demonstrate rapid convergence within 1,000 epochs, achieving 75% average demand coverage—2.7% and 5.5% higher than GA and Particle Swarm Optimization (PSO), respectively. Ablation experiments confirm that Vanilla PPO without dynamic action masking fails to produce feasible solutions. The framework offers a feasible technical path for handling highly dynamic urban facility spatial configuration with geographic mask constraints. Full article

Energy transition, including the transition away from fossil fuels, is a difficult and complex process, particularly in emerging and developing economies. One of the key factors determining its effectiveness is the acceptance of its course and consequences by local communities. Taking into account these circumstances, as well as the ongoing period of profound energy sector transformation in Poland, the main objective of this article is to diagnose the perception of energy transition and assess the preparedness of local authorities for its consequences from the perspective of a representative sample of 1863 residents from 19 cities with county rights located in the Upper Silesian Coal Basin. The research was conducted in the second quarter of 2025. In analyzing the survey results, descriptive statistics, identification of interdependencies, and non-parametric statistical tests (Mann–Whitney U, Kruskal–Wallis, and Wilcoxon) were employed. The obtained results indicate relative acceptance of decarbonization; however, there is significantly lower support for closing hard-coal mines. Respondents rate the preparedness of local authorities for the consequences of hard-coal mining liquidation in the region as low. Moreover, they believe that the local labor market is better prepared for restructuring changes than the local governments of Silesian cities. The respondents’ answers differ primarily according to gender and education, although the identified relationships are neither obvious nor linear. Furthermore, the age of respondents only influences the perception of the necessity of closing hard-coal mines and the assessment of city authorities’ preparedness for the consequences of this process. The results of the conducted research contribute to the analysis of socio-economic processes accompanying energy transition and may be useful in conducting social consultations and communication and information activities, as well as in developing regional restructuring strategies. Full article

Museums are key institutions for cultural communication and public education, and their operating concept is shifting from exhibit-centered to experience-centered. As expectations for exhibition experience rise, museum fatigue has become a major constraint on visitors. Existing studies rely on questionnaires and other subjective measures, which makes it difficult to locate fatigue in specific spaces. At the same time, body pose detection and fatigue recognition techniques remain hard to apply in museums because of complex spatial configurations and dense visitor flows. Effective methods for quantifying and mitigating museum fatigue are still lacking. This study proposes a contact-free sensing scheme based on computer vision and builds a coupled analytical framework with three stages: Human Pose Estimation (HPE) for visitor posture detection, fatigue assessment, and fatigue mitigation. A Fatigue Index (FI) quantifies bodily fatigue. Applying this index to the exhibition space in both the baseline and adjusted configurations guides the formulation of mitigation strategies and shows a consistent reduction in FI, which indicates that the adopted measures are effective. The proposed approach establishes a complete frame from fatigue quantification to fatigue mitigation, supports evaluation of exhibition space design, and provides theoretical and methodological support for future improvements to museum experience. Full article