Search Results (90)

Despite significant advancements in communication systems, inherent limitations persist in providing reliable data transmission for emerging applications with massive data exchanges. Semantic communication offers promising solutions by extracting and transmitting meaningful information rather than raw bit sequences. However, it faces challenges from high mobility and dynamic channel conditions in wireless environments. In this paper, we design a ground-to-air network architecture that integrates a rotary-wing unmanned aerial vehicle (UAV) and ground terminals to maximize semantic transmission efficiency while maintaining low energy consumption. This approach leverages the high mobility of the UAV for flexible deployment and the data reduction capabilities of semantic communication. Therefore, we formulate a multi-objective optimization problem to simultaneously balance the total semantic transmission rate and the UAV propulsion energy consumption by jointly optimizing the UAV hovering position, semantic encoding lengths, and resource block (RB) allocation. The problem is complex, with mixed continuous and discrete variables, which necessitates an advanced optimization method. To address these challenges, we propose a novel greedy-enhanced adaptive multi-objective cellular genetic algorithm (GEAMOCell), which utilizes an adaptive neighborhood selection mechanism to balance exploration and exploitation, and employs a crowding-guided archive feedback mechanism to maintain population diversity. The simulation results demonstrate that the proposed GEAMOCell algorithm outperforms baseline algorithms in terms of convergence, semantic transmission rate, and energy efficiency. Full article

Background: The enzymatic saccharification of cellulose is governed by heterogeneous reaction environments that deviate from classical Michaelis–Menten behavior. Methods: Fractal kinetics were applied to describe the hydrolysis of microcrystalline cellulose (Avicel PH-101) and pretreated hemp hurds using Cellic CTec2. Optimal enzyme loading was first established on Avicel, and the influence of mixing regimes was evaluated. Results: Rotational agitation markedly improved hydrolysis efficiency. Organosolv-based pretreatments generated cellulose-enriched substrates that exhibited higher reactivity than Avicel, while redeposited lignin showed minimal inhibitory effects. Enzyme adsorption studies revealed substantial binding to lignocellulosic substrates, suggesting nonspecific interactions and crowding effects that influence kinetic parameters. Conclusions: Fractal coefficients k and h successfully captured differences in substrate accessibility and reactivity, demonstrating the suitability of fractal models for describing cellulose saccharification in complex solid–liquid systems. Organosolv pretreatment allows a high degree of saccharification, whereas redeposited lignin does not interfere with the enzymatic reaction. Full article

Objectives: This study aimed to investigate preventive management strategies and optimal intervention timing for dental ankylosis of primary teeth complicated by suspected pre-eruptive intracoronal resorption (PEIR), providing an evidence-based framework for clinical diagnosis and management. Methods: This case retrospectively reports a 7-year-old patient with an ankylosed mandibular left second primary molar (tooth 75), exhibiting radiographic features suggestive of pre-eruptive intracoronal resorption. The patient was in the mixed dentition stage with dental crowding. Preventive and interceptive orthodontic management was implemented to address space deficiency and guide occlusal development. The timing of extraction and space maintenance of tooth 75 was guided by space regaining, PEIR lesion progression, and crown development of tooth 35. Results: The permanent successor of tooth 75 (tooth 35) erupted successfully, dental crowding was alleviated, and a favorable occlusion was established. Conclusions: Early diagnosis and timely, individualized intervention for ankylosed primary teeth play an important role in preventing malocclusion and promoting normal eruption of the permanent successor tooth. Full article

The revitalization of vitality in historic cultural districts can enhance a city’s cultural attractiveness and promote the upgrading of the urban cultural industry and sustainable development. Revealing the threshold and synergistic effects of different districts’ scene elements on district vitality helps to identify the distribution patterns of district vitality and provides a basis for managerial decision-making. This study first uses a geographic information system (ArcGIS) to overlay Baidu heatmaps with the street-network distribution in order to depict the spatiotemporal heterogeneity of district vitality and to compute vitality values by partitions at the district scale. Subsequently, based on an explanatory framework that integrates the physical space and subjective cognition, multi-source data such as street-view panoramas and points of interest (POIs) are quantified to obtain scene-element values for each unit area. Then, the scene-element values and vitality values are integrated into a consolidated database. Additionally, the LightGBM model and the SHAP method are employed to evaluate each element’s marginal contribution and relative importance to district vitality, thereby screening out the key scene elements. Finally, by means of SHAP dependence plots and interaction-effect analysis, the threshold intervals of the key elements and their synergistic relationships are identified, revealing the nonlinear threshold effects and synergies by which scene elements influence spatial vitality. The results show that during rest days, district vitality exhibits stronger diffusion, and the synergistic effect between Leisure-Facility Attractiveness and Street-Network Accessibility is the most prominent in enhancing vitality. High Exhibition-Facility Attractiveness is difficult to sustain crowds on its own; only when Leisure-Facility Attractiveness is likewise high does its effectiveness increase significantly. When Transport Accessibility is within the 0.20–0.40 interval, the positive effect of Leisure-Facility Attractiveness is significantly amplified. An excessive Traditional–Modern Facility Mix readily leads to homogenization of districts; therefore, when introducing modern business formats, local cultural characteristics must be retained. Overall, the generation of district vitality relies more on the synergy between material factors and subjective cognition than on improvements to any single element. The findings of this study provide suggestions for the planning of scene elements and the enhancement of vitality in historic cultural districts. Full article

This study examines how national electricity market structures condition the impact of carbon pricing on green innovation within the European Union. Using two-way fixed-effects panel models, we uncover a central paradox: although liberalized, price-signal markets exhibit the highest baseline levels of green innovation, the marginal effect of carbon pricing in these markets is weakest and often negative. This pattern points to an innovation-substitution effect, whereby market flexibility facilitates short-term compliance strategies, such as fuel switching, that crowd out investment in fundamental research and development (R&D) when carbon prices remain moderate. By identifying this mechanism, the study establishes electricity market structure as a pivotal moderating factor in the carbon pricing–innovation nexus and highlights a critical boundary condition for the Porter Hypothesis. The findings provide important insights for the design of sustainability policy mixes, demonstrating that institutional context plays a decisive role in translating economic instruments into sustained technological change. Effective climate policy therefore cannot be context-blind; instead, it must combine carbon pricing with tailored market design and direct support for long-term R&D to coherently advance the sustainability transition. Full article

A field experiment was conducted in 2019–2020 and 2020–2021 at Rogoza, Fala, and Brežice in Slovenia to examine the biological viability of a mixed intercropping system and the effect of winter catch crops (WCCs) on maize growth parameters. The experiment included Italian ryegrass (IR) in pure stands, fertilized with nitrogen (N) in spring (70 kg N ha⁻¹), mixtures of crimson clover and red clover 50:50 (C), and intercropping between IR and C (IR+C). Neither mixture was fertilized with N in spring. We evaluated different competition indices and biological efficiency. Relative crowding coefficient (RCC) and actual yield loss (AYL) exceeded 1, indicating a benefit of IR+C intercropping. The IR in intercropping was more aggressive, as indicated by positive aggressivity (A) and a competitive ratio (CR) > 1, and it dominated over C in IR+C (that had negative A values and CR < 1). The competitive balance index (Cb) differed from zero, the relative yield total (RYT) was 2.24, the land equivalent coefficient (LEC) exceeded 0.25, the area–time equivalent ratio (ATER) exceeded 1, and land use efficiency (LUE) exceeded 100%. IR+C exhibited the highest total aboveground dry matter yield of maize (29.22 t ha⁻¹), the highest nitrogen content in dry matter grain yield of maize (206.35 kg ha⁻¹), the highest nitrogen and potassium content in maize stover (105.7 and 105.7 kg ha⁻¹, respectively), and the highest nitrogen and potassium content in the total aboveground dry matter of maize (312 and 267.3 kg ha⁻¹, respectively). The C/N ratio in dry matter yield of IR was 45.35, and in IR+C it was 33.43, which means that the mixture had a positive effect on nutrient release in maize. The ryegrass–clover mixture, according to the calculated biological indices, had advantages over pure stands and had a positive effect on maize yield. Full article

Intergovernmental transfers play a crucial role in shaping the fiscal position of local governments, especially in countries where municipalities, such as those in Poland, exhibit a high dependence on central funding. Recent reforms and the increasing reliance on discretionary revenues transferred from the central budget have motivated a closer examination of how these instruments influence local fiscal sustainability. This article analyses how different types of transfers—general subsidies and targeted grants—affect the fiscal sustainability of Polish municipalities across several dimensions, including autonomy, solvency, efficiency and economic resilience. Using panel data, five sets of models test the crowding-out effect, developmental impact, pro-cyclicality, fiscal discipline, and fiscal replacement mechanisms. Results show that general subsidies crowd out local tax revenues, particularly in less developed municipalities, while targeted grants strengthen the tax base in rural areas. Transfers have mixed effects: targeted grants strongly stimulate investment and support local development but tend to increase debt; general subsidies weaken local tax capacity and reduce fiscal autonomy, although they improve short-term fiscal discipline. In municipalities with limited fiscal independence, transfers act as short-term compensatory tools, fostering dependence on state aid rather than self-reliance. A macroeconomic crowding-out effect also appears, as higher transfers reduce private sector resources. Regarding fiscal discipline, equalization and compensatory subsidies decrease debt levels, whereas targeted grants can raise debt in urban municipalities with co-financing obligations. General subsidies show fiscal replacement effects, substituting local revenue sources. The findings provide insights for designing transfer systems that balance financial support with incentives for local autonomy and sustainable development. Full article

Farmers’ low-carbon transition has become a critical issue for achieving sustainable agricultural development. Fundamentally, this transition is driven by multi-actor collaboration and is subject to stochastic disturbances. However, the collaborative governance mechanisms that facilitate farmers’ low-carbon transformation remain insufficiently understood, particularly under the influence of random factors. To address this gap, we construct a four-party game model involving farmers, government, enterprises, and financial institutions by employing a stochastic evolutionary game approach that incorporates random disturbance factors to capture real-world uncertainty. Numerical simulations are conducted to examine how different policy tools and external environments shape the system’s evolutionary path. The results show the following: (1) In the early transition stage, external uncertainties cause notable fluctuations in strategy evolution, during which the government, farmers, and enterprises gradually form a collaborative mechanism, while financial institutions remain reluctant to participate due to risk and policy uncertainty. (2) Government subsidies, profit returns, and risk-sharing mechanisms exhibit a substitutive relationship, and an appropriate mix of these tools can effectively enhance the willingness of farmers and enterprises to adopt low-carbon practices. (3) Excessive government incentives may crowd out the role of green credit from financial institutions. (4) The profit-sharing ratio among farmers exerts the strongest motivational effect in the early stage, while higher levels of risk-sharing and reputation benefits are more effective in stabilizing the system structure and enhancing transition resilience. This study reveals the dynamic mechanisms of multi-actor interaction in agricultural low-carbon transition and provides theoretical and policy insights for differentiated government strategies and collaborative emission reduction. Full article

This paper investigates the integration of proximity theory (PT) into the management of public transport service disruptions within sustainable Mobility-as-a-Service (MaaS) systems, an area that is largely underexplored. PT provides a multidimensional framework for analyzing relationships and interactions within complex systems, encompassing five dimensions: geographical, cognitive, institutional, organizational, and social, each influencing coordination, learning, and adaptability. Building on this framework, the study introduces temporal proximity as an original sub-dimension of geographical proximity, forming a spatial–temporal proximity theory (PTST), which highlights the critical role of timing, synchronization, and coordinated responses in transport disruption management. To operationalize these principles, a mixed-integer programming (MIP) model was developed to optimize traveler assignments across 50 routes for 10 travelers, minimizing delays, transfers, walking distance, crowding, and CO₂ emissions. Two scenarios were analyzed: one without environmental considerations and another with CO₂ penalties. Results show that emissions were reduced by up to 50% for certain routes, while maintaining feasible travel times and route choices. The case study demonstrates that PTST can be operationalized as a practical tool, bridging mobility resilience and environmental responsibility, and providing actionable insights for sustainable and intelligent MaaS platforms. Full article

Crown width (CW) is a critical metric for characterizing tree-canopy dimensions; however, its direct measurement remains labor-intensive and is often impractical in inaccessible crowns. Consequently, CW is frequently derived from projections, which are susceptible to multiple sources of imprecision, including canopy density, crown irregularity, terrain heterogeneity, and the observer’s vantage point, especially in structurally complex natural forests. While deep neural network (DNN) models show substantial potential for CW prediction, their performance in heterogeneous forests remains uncertain. We developed DNN models integrated with a Height Threshold Method (HTM) to predict individual-tree CW in the natural mixed forests of Northern China, dominated by Larix principis-rupprechtii and Picea asperata. Our study further compared the relative importance of feature engineering versus model architectural complexity in predictive accuracy and identified the key ecological variables governing CW. The model performance was evaluated through the coefficient of determination (R²), mean square error (MSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). Field surveys of 34 representative sample plots produced 1884 individual-tree records. The main results were as follows: (1) all DNNs avoided overfitting, and were statistical stable under ten-fold cross-validation; (2) the optimized DNN3-2 model (tuned hidden layer count, neurons/hidden layer, L₂ regularization, and dropout) achieved peak performance, explaining 69% of CW variance with residuals with stable variance and excellent coverage properties; (3) tree size, neighborhood competition, species identity, and site quality were the most important predictors; and (4) stand parameters calculated from competitive neighborhoods defined by the HTM, particularly mean stand crowding, Simpson’s index (1-D), and Shannon’s index (H′), significantly improved prediction accuracy. By integrating DNN with the HTM, our approach allows for accurate prediction of individual-tree CW in natural mixed forests of Northern China, dominated by Larix principis-rupprechtii and Picea asperata. Full article

The rapid growth of technology has introduced robots into daily life, necessitating navigation frameworks that enable safe, human-friendly movement while accounting for social aspects. Such methods must also scale to situations with multiple humans and robots moving simultaneously. Recent advances in Deep Reinforcement Learning (DRL) have enabled policies that incorporate these norms into navigation. This work presents a socially aware navigation framework for mobile robots operating in environments shared with humans and other robots. The approach, based on single-agent DRL, models all interaction types between the ego robot, humans, and other robots. Training uses a reward function balancing task completion, collision avoidance, and maintaining comfortable distances from humans. An attention mechanism enables the framework to extract knowledge about the relative importance of surrounding agents, guiding safer and more efficient navigation. Our approach is tested in both dynamic and static obstacle environments. To improve training efficiency and promote socially appropriate behaviors, Imitation Learning is employed. Comparative evaluations with state-of-the-art methods highlight the advantages of our approach, especially in enhancing safety by reducing collisions and preserving comfort distances. Results confirm the effectiveness of our learned policy and its ability to extract socially relevant knowledge in human–robot environments where social compliance is essential for deployment. Full article

This study develops an integrated bi-level operations–assignment model to optimise express service on the Gyeongin Line, a core corridor connecting Seoul and Incheon. The upper level jointly selects express stops and time-of-day headways under coverage constraints—a minimum share of key stations and a maximum inter-stop spacing—while the lower level assigns passengers under user equilibrium using a generalised time function that incorporates in-vehicle time, 0.5× headway wait, walking and transfers, and crowding-sensitive dwell times. Undergrounding and alignment straightening are incorporated into segment run-time functions, enabling the co-design of infrastructure and operations. Using automatic-fare-collection-calibrated origin–destination matrices, seat-occupancy records, and station-area population grids, we evaluate five rail scenarios and one intermodal extension. The results indicate substantial system-wide gains: peak average door-to-door times fall by approximately 44–46% in the AM (07:00–09:00) and 30–38% in the PM (17:30–19:30) for rail-only options, and by up to 55% with the intermodal extension. Kernel density estimation (KDE) and cumulative distribution function (CDF) analyses show a leftward shift and tail compression (median −8.7 min; 90th percentile (P90) −11.2 min; ≤45 min share: 0.0% → 47.2%; ≤60 min: 59.7% → 87.9%). The 45-min isochrone expands by ≈12% (an additional 0.21 million residents), while the 60-min reach newly covers Incheon Jung-gu and Songdo. Backcasting against observed express/local ratios yields deviations near the ±10% band (PM one comparator within and one slightly above), and the Kolmogorov–Smirnov (KS) statistic and Mann–Whitney (MW) test results confirm significant post-implementation shifts. The most cost-effective near-term package combines mixed stopping with modest alignment and capacity upgrades and time-differentiated headways; the intermodal express–transfer scheme offers a feasible long-term upper bound. The methodology is fully transparent through provision of pseudocode, explicit convergence criteria, and all hyperparameter settings. We also report SDG-aligned indicators—traction energy and CO₂-equivalent (CO₂-eq) per passenger-kilometre, and jobs reachable within 45- and 60-min isochrones—providing indicative yet robust evidence consistent with SDG 9, 11, and 13. Full article

In fresh produce cold chain last-mile delivery, the highly dispersed customer base leads to exorbitant delivery costs, posing the greatest challenge for cold chain enterprises. Achieving a symmetrical balance between cost-efficiency, environmental sustainability, and service quality is a fundamental pursuit in logistics system optimization. This paper proposes integrating the crowd-shipping logistics model—characterized by internet platform sharing and flexibility—into the delivery service. It incorporates and extends features such as cold chain delivery, mixed fleets using gasoline and diesel vehicles (GDVs), electric vehicles (EVs), partial charging strategies for EVs, and time-of-use electricity pricing into the crowd-shipping model. A joint delivery mode combining traditional professional delivery (using GDVs and EVs) with crowd-shipping is proposed, creating a symmetrical collaboration between centralized fleet management and distributed social resources. The challenges associated with utilizing occasional drivers (ODs) are analyzed, along with the corresponding compensation decisions and allocation-related constraints. A route optimization model is constructed with the objective of minimizing total cost. To solve this model, an Improved Whale Optimization Algorithm (IWOA) is proposed. To further enhance the algorithm’s performance, an adaptive variable neighborhood search is embedded within the proposed algorithm, and four local search operators are applied. Using a case study of 100 customer nodes, the joint delivery mode with OD participation reduces total delivery costs by an average of 24.94% compared to the traditional professional vehicle delivery mode, demonstrating a more symmetrical allocation of logistical resources. The experiments fully demonstrate the effectiveness of the joint delivery model and the proposed algorithm. Full article

Background: Supplemental teeth are a rare subtype of supernumerary elements that closely resemble the morphology of normal dentition. Their occurrence in the mandibular anterior region is extremely uncommon. Aim: To describe the clinical features, diagnosis, and phased orthodontic management of a rare case involving bilateral supplemental mandibular incisors in a pediatric patient. Case report: A 7-year-old female patient presented with early mixed dentition and significant lower anterior crowding due to the presence of two fully erupted supplemental mandibular incisors. Treatment phase I included extraction of the malpositioned supplemental teeth and rapid maxillary expansion to transversally coordinate the arches. By the end of phase I, spontaneous alignment of the remaining lower incisors was observed. Discussion: The presence of two supplemental mandibular incisors is extremely rare in Caucasian populations. Supernumerary teeth can cause crowding, impaction, or delayed eruption of adjacent permanent teeth. Timely extraction can prevent such complications and often allows spontaneous alignment. Conclusions: The prompt removal of supplemental mandibular incisors, when they have just erupted, might lead to the alignment of the other incisors, considering that they spontaneously occupy the extractive spaces often without the aid of fixed appliances first line. Full article

Background and Clinical Significance: Patients with a neurodegenerative condition known as posterior cortical atrophy (PCA) can present with attention impairments across a variety of cognitive contexts, but the consequences of these are little explored in example of single word reading. Case Presentation: We present a detailed single-case study of KL, a local resident of South Wales, a patient diagnosed with posterior cortical atrophy (PCA) in 2018, whose reading and letter-naming abilities are selectively disrupted under non-canonical visual presentations. In particular, KL shows significantly impaired accuracy performance when reading words presented in tilted (rotated 90°) format. By contrast, his reading under conventional horizontal (canonical) presentation is nearly flawless. Whilst other presentation formats including, mixed-case text (e.g., TaBLe) and vertical (marquee) format led to only mild performance decrements—even though mixed-case formats are generally thought to increase attentional ‘crowding’ effects. Discussion: These findings indicate that impairments of word reading can emerge in PCA when visual-attentional demands are sufficiently high, and access to ‘top down’ orthographic information is severely attenuated. Next, we explored a cardinal feature of attentional dyslexia, namely the word–letter reading dissociation in which word reading is superior to letter-in-string naming. In KL, a similar dissociative pattern could be provoked by non-canonical formats. That is, conditions that similarly disrupted his word reading led to a pronounced disparity between word and letter-in-string naming performance. Moreover, different orientation formats revealed the availability (or otherwise) of distinct compensatory strategies. KL successfully relied on an oral (letter by letter) spelling strategy when reading vertically presented words or naming letters-in-strings, whereas he had no ability to engage compensatory mental rotation processes for tilted text. Thus, the observed impact of non-canonical presentations was moderated by the success or failure of alternative compensatory strategies. Conclusions: Importantly, our results suggest that an attentional ‘dyslexia-like’ profile can be unmasked in PCA under sufficiently taxing visual-attentional conditions. This approach may prove useful in clinical assessment, highlighting subtle reading impairments that conventional testing might overlook. Full article