Search Results (948)

This paper introduces the research progress of path planning, trajectory tracking control, and multi-machine collaborative operation systems for agricultural robots. It summarizes the development laws of 3D terrain modeling and adaptive path planning algorithms for complex agricultural environments such as hills and mountains, and analyzes the dynamic disturbance characteristics of agricultural machinery under slip, sideslip, and dynamic load changes. Through comprehensive analysis, it is found that traditional kinematic control models have limitations in complex and unstructured environments. Combining soil mechanics mechanisms, variable load identification, and robust control strategies is key to improving trajectory tracking stability and operational quality. In terms of multi-machine collaboration, this paper discusses master–slave collaboration, distributed control, and task allocation modes. It further identifies that the stability of collaboration and interoperability standards between devices in weak network environments are currently the main bottlenecks limiting the large-scale application of this technology. Finally, this paper provides prospects for future research directions and suggests strengthening the closed-loop integration of perception, decision-making, and dynamic models, establishing industry unified standards, and enhancing the safety of the entire lifecycle of operations, providing suggestions for the unmanned application of agricultural robots. Full article

Whether Kaldor’s three growth laws still operate in commodity-dependent middle-income economies—and through what transmission mechanism—is an open empirical question after three decades of trade liberalisation, financial opening, and the 2002–2014 commodity super-cycle. This paper provides the first bloc-level panel test of the three laws for the Andean Community of Nations (ACN—Bolivia, Colombia, Ecuador, and Peru) over 1993–2019, combining static feasible generalised regressions with dynamic Arellano–Bond difference-GMM and long-run multipliers. The predictions are as follows: manufacturing growth is positively associated with aggregate output (long-run multiplier 0.91), the Verdoorn coefficient is positive and significant at 0.42, and labour reallocation from non-manufacturing activities is associated with rising aggregate productivity over the time. The headline finding, however, is a decomposition failure: the Verdoorn and employment elasticities coefficients sum up to 0.35 rather than 1 as required by the accounting identity, leaving a residual of 0.65. We term this “jobless manufacturing growth” (capital-deepening). This suggests that the Kaldorian regime in the ACN has neither collapsed nor remained intact, but has mutated into a capital-intensive, labour-saving form consistent with Dutch-disease. Thus, industrial policy alone would deepen the jobless pattern: structural transformation in these economies requires pairing subsidy plans with the macroeconomic management of commodity-dependent exchange rates. Full article

This study presents a simulation-assisted engineering framework intended to support comparative machining parameter selection for quartz sintered materials. The approach integrates CAD/CAM-based analysis, an illustrative Design of Experiments (DOE) framework, and preliminary experimental validation to improve process planning and machining quality. The analysis focuses on key technological parameters, including cutting speed (vc), feed rate (f), and depth of cut (ap), evaluated across cutting, milling, and finishing stages. The results indicate that feed rate is the dominant parameter influencing process stability, surface quality, and edge integrity. A practical transition region of approximately 1200 mm/min was identified, above which increased vibration, defect formation, and surface degradation occur. The complementary DOE analysis confirms the relative importance of process parameters and reveals interaction effects, particularly between feed rate and depth of cut, which significantly influence defect formation under high-load conditions. Preliminary industrial observations provide trend-oriented support for the simulation-predicted process behavior. Based on the integrated analysis, a preliminary technological operating region was identified (vc = 1080–1320 m/min, f = 800–1200 mm/min, ap = 0.5–1.0 mm), suggesting a practical compromise between machining efficiency and surface integrity. The proposed methodology provides preliminary engineering support for comparative process planning and defect-reduction-oriented parameter selection in the machining of brittle materials. The novelty of this work lies in the integration of CAD/CAM simulation, DOE-based interaction analysis, and experimental validation for supporting the identification of a practical technological operating region for machining brittle materials. The presented results should therefore be interpreted as engineering-oriented comparative process-planning guidelines rather than statistically generalized machining laws. The presented study should be interpreted as an exploratory simulation-assisted engineering investigation intended to support comparative process planning rather than as a fully experimentally validated machining model. Full article

Continuous dynamic monitoring of coastline changes is essential for revealing the evolutionary laws and spatiotemporal characteristics of coastal systems. In this study, we employed AlphaEarth Foundations (AEF) data and Sentinel-2 imagery to investigate coastline and land use changes in the Pearl River Estuary (PRE) region over the period 2017–2023. The Random Forest (RF) algorithm was adopted to extract coastlines and classify coastal land-use types, after which their spatiotemporal evolution was quantitatively analyzed. The results demonstrate that the classification performance of AEF data is significantly better than that of Sentinel-2 imagery, with the average overall accuracy and Kappa coefficient exceeding 92% and 89%, respectively. The PRE coastline shows an evolutionary pattern of “overall contraction accompanied by regional differentiation”: its total length first increased and then decreased, peaking at 1029.05 km in 2019, representing a cumulative net reduction of 7.54 km over the 2017–2023 period. Meanwhile, land use expansion driven by reclamation resulted in a cumulative net increase of 25.26 km². Aquaculture ponds (AP) constitute the dominant type of newly reclaimed land, accounting for more than 50%, while the expansion of impervious surface (IS) accounts for 24.52%. This study provides novel insights and a scientific basis for the refined management of coastlines, sustainable land use planning, and coastal-marine ecological protection in the Pearl River Estuary and similar regions worldwide. Full article

This study examines Connecticut’s strategic approach to electric vehicle (EV) workforce development within the framework of the Bipartisan Infrastructure Law (BIL) and its National Electric Vehicle Infrastructure (NEVI) program. Amid the U.S. goal to transition to a zero-emission vehicle fleet by 2050, this research investigates whether Connecticut’s current policies sufficiently address the need to reskill automotive mechanics into qualified EV technicians. Using a qualitative case study methodology, semi-structured interviews were conducted with state workforce representatives and analyzed through inductive coding within Kotter’s 8-Step Change Model. Findings reveal that while Connecticut aligns with federal NEVI goals for infrastructure, it lacks a dedicated budget and clearly defined pathways for technician training. Stakeholder collaboration remains fragmented, and efforts to empower workforce transformation are in the early stages. The study concludes that Connecticut risks falling behind unless it integrates a robust workforce development strategy that includes cross-sector partnerships, pilot training programs, and transparent certification pathways. These findings highlight the importance of aligning state-level EV infrastructure planning with human capital development and offer actionable insights for other states navigating similar transitions. Full article

Rain gauge networks are the core infrastructure for hydrological and water resource monitoring, flood control and disaster mitigation early warning, and water resource planning and regulation. The rationality of their layout directly determines the accuracy, representativeness, and economy of regional precipitation data acquisition. Considering that information entropy can accurately characterize the spatial distribution law and information complexity of rainfall, and spatiotemporal deep learning models have strong capabilities in fitting spatiotemporal features, this paper couples mutual information entropy with a spatiotemporal deep learning model and proposes a novel optimal layout method for rain gauge networks. Daily observed rainfall data from 50 ground-based rain gauges in the upper reaches of the Tuojiang River during 2015–2024, as well as the PERSIANN-CCS remote sensing precipitation product for the same period, were used in the study. A CNN-LSTM spatiotemporal deep learning model integrating spatial features and temporal dependence was constructed, coupled with the mutual information entropy index, and the GA-PSO hybrid optimization algorithm was applied for solution. The superiority of the proposed method was verified by comparison with the calculation results of the traditional mutual information entropy-based greedy optimization algorithm. The results show that the hybrid optimization algorithm driven by the spatiotemporal deep learning model coupled with mutual information entropy is significantly superior to the comparison algorithm in terms of the rationality of the station network structure, the ability to characterize spatial rainfall distribution, the control of average relative error, and the improvement of total information entropy. After optimization, the number of rain gauges in the upper reaches of the Tuojiang River can be reduced from 50 to 25. While greatly reducing the number of stations, the optimized network can still relatively accurately reflect the spatiotemporal characteristics of rainfall in the basin, which can provide a theoretical basis and technical support for the optimal layout of basin rain gauge networks and water resource management. Full article

Regulatory sandboxes have evolved from specialised FinTech tools into broader mechanisms of regulatory experimentation. As artificial intelligence (AI) applications become embedded in credit decisioning, payment-fraud detection, identity verification, crypto-asset compliance, customer-facing advice and supervisory analytics, sandbox design increasingly affects how legal and institutional responsibility is allocated among regulators, participating firms, technology vendors and users. This article provides a comparative doctrinal and institutional analysis of accountability and liability in AI-related financial regulatory sandboxes. It clarifies the relevant AI modalities, distinguishes accountability (answerability and enforceability during sandbox participation) from liability (contractual, tort/product and regulatory/public law responsibility after harm), and maps framework-level safeguards across the European Union, the United Kingdom, Singapore, Norway and Hungary. The analysis does not seek to measure sandbox effectiveness empirically. Instead, it examines how publicly available legal and regulatory materials structure the allocation of duties before, during and after sandbox testing. The article shows that sandboxes generally do not operate as liability shields. Their legal significance lies in reallocating ex ante accountability duties—documentation, disclosure, monitoring, human oversight and exit planning—while preserving baseline liability rules. An Accountability and Liability Protocol is proposed to clarify roles, protect baseline consumer rights, support evidentiary traceability and connect sandbox learning to enforceable post-sandbox obligations. Full article

Background/Objectives. Country-level evidence on the economic footprint of home care nursing is still scarce, particularly in systems where tariffs for community-based nursing are lacking. In Italy, recent laws have expanded home care; yet planning and funding remain constrained by the absence of robust micro-costing evidence. Objectives. To estimate the accounting cost of home care nursing visits in Italy using a bottom-up micro-costing approach and to identify the main cost drivers influencing expenditure. Methods. A multicentre, cross-sectional study was conducted. Data were collected in two phases: (1) a national survey of 3949 home care nurses from 70 Local Health Authorities (April–October 2023), describing workload, travel time, and the most frequently performed activities; and (2) a time-and-motion study of 527 consecutive home visits performed by 83 nurses in three Local Health Authorities (March 2024). Direct costs were estimated from the Italian National Health Service perspective and included nursing time, travel time and transportation, back-office activities, and materials. Personnel costs were derived from national collective labour agreements and inflation-adjusted. A base-case scenario estimated accounting costs directly measured in the study. An extended, illustrative scenario explored the economic value of nursing activities by applying existing outpatient tariffs. Deterministic and probabilistic sensitivity analyses (10,000-iteration Monte Carlo simulation) were performed. Results. The mean accounting cost of home care nursing was €27.78 per patient per day. At the provider level, the corresponding daily cost per nurse was €190.00, assuming a mean caseload of 6.84 patients per nurse per shift. In the extended scenario, the imputed economic value of nursing activities increased the estimated daily cost to €120.81 per patient and €826.32 per nurse. Sensitivity analyses identified organizational factors (particularly the number of patients per shift and the number of activities per visit) as the dominant cost drivers, while material and transportation costs had a comparatively limited impact. Conclusions. Home care nursing in Italy appears to be delivered at a relatively low accounting cost, with organizational factors playing a greater role than unit prices in determining expenditure. The absence of a dedicated reimbursement framework for nursing activities may result in a substantial under-recognition of the economic value of home-based nursing care. These findings provide preliminary evidence to support workforce planning, reimbursement policies, and the sustainable development of territorial care services. Full article

To address the challenges of dynamic obstacles, limited perception, and multi-UAV coordination constraints in complex urban environments, a hierarchical control framework based on a virtual leader-follower architecture is proposed, covering global planning, local obstacle avoidance, and formation coordination. In the global planning layer, a dynamic adaptive strategy rapidly exploring random tree star (DASRRT*) algorithm is proposed. To address the low sampling efficiency and limited path extension in dense environments that affect traditional RRT*, a hybrid guided sampling strategy, inefficient node optimization strategy, and perception-based adaptive step size strategy are designed. Additionally, a multi-objective cost function is introduced to provide smoother trajectories that better comply with dynamic constraints for trajectory tracking. In the local obstacle-avoidance layer, a distributed controller is constructed based on an improved artificial potential field method, integrating collision avoidance control laws derived from a spring-damper model, dynamic obstacle-avoidance laws that account for obstacle velocities, and formation coordination control laws grounded in consensus theory. In the coordination control layer, a real-time local target selection strategy is established to guide the virtual leader to precisely track the global path, and a dual-mode switching mechanism based on environmental complexity is constructed to dynamically adjust the priority between formation maintenance and autonomous obstacle-avoidance tasks. Comparative experimental results show that the proposed DASRRT* algorithm reduces path planning time by an average of 34.78% and shortens path length by 1.15%. Simulation results for formation flight demonstrate that the proposed hierarchical control framework can adaptively adjust control modes in response to changes in environmental complexity, exhibiting strong adaptability to complex environments and a good ability to generalize to various scenes. Full article

Brazil has a deficit of 27 Mha of native vegetation in rural properties and the ambition to restore 12 Mha by 2030 (Nationally Determined Contributions—Paris Agreement), while the state of São Paulo has committed to reforesting 1.5 Mha by 2025. The regulation of payment for environmental services (PES) is a new topic in the Brazilian legal system that also aims to contribute to this commitment. In 2021, a federal law established the national PES policy. For São Paulo state, the current regulation is a decree from 2022. This study analyzes whether the regulation of PES made by São Paulo state conveys all the actions provided for in the federal law, as well as whether there is effective public governance in this state’s regulation. This analysis is essential, since São Paulo regulated this through a decree and not specifically through legislation, which, in theory, reduces public participation and governance. We used an exploratory and deductive method to evaluate whether São Paulo’s regulation adequately reflects federal provisions and governance principles, ensuring the planning and implementation of PES. Full article

The Carpathian Mountains are an important hotspot of European biodiversity, where geological history, climatic diversity, and altitudinal heterogeneity have determined a great diversity and endemism of vascular plants. The study was conducted in the national park of Piatra Craiului, a distinctive limestone massif in the Southern Carpathians. The dataset included 731 vascular plant species from the study area, of which 35 taxa are endemic to the Carpathians (of the 47 reported in this area), and 18 are classified as species of conservation interest in the Management Plan of the National Park (MP). The distribution of endemic species showed different habitat and altitudinal specificity across 15 vegetation types, including 14 Natura 2000 habitats and one outside the EUR 28 classification. The endemic species showed a bell-shaped altitudinal distribution, peaking at 1600–1700 m and concentrated in high-altitude open habitats rather than forested mid-elevations. The PCA separates endemic species along a main gradient from open, disturbed, light-rich habitats to stable, nutrient- and moisture-rich forest environments, and a secondary gradient related to temperature and soil reaction linked to altitude. Endemic species are predominantly associated with calcareous rocky and grassland habitats and are almost absent from mesophilic and hygrophilous habitats. A positive association between endemic species frequency and the total number of species of conservation interest per plot was detected. We concluded that species of conservation interest (such endemic species) are unevenly distributed among habitat types in the Carpathians, with the greatest diversity and abundance in subalpine rocky and grassland habitats, shaped by altitude and isolation. Although the threatened endemic species are not officially listed by national law, they are indirectly protected by management zonation. In Piatra Craiului the richest habitats in endemic species are included in the designated zones of the national park with the highest protection regime, according to the National Park’s Management Plan. Moreover, this territory is included in a Natura 2000 site (ROSAC0194 Piatra Craiului) ensuring an additional level of protection for the habitats where endemic species are found. Full article

The Yangtze River Economic Belt supports over 400 million people and contributes nearly half of China’s GDP, yet decades of industrialization, urbanization, and agricultural intensification have resulted in severe contamination and pressing environmental challenges. This systematic review synthesizes three decades of peer-reviewed and governmental data to examine the spatiotemporal distribution, sources, and ecological and human health risks of major pollutants, including heavy metals, microplastics, persistent organic pollutants, and excess nutrients. While point-source emission of heavy metals such as cadmium, lead, and mercury have decreased by 35–42% since 2013 following policy interventions like the 10-Point Water Plan and the Yangtze River Protection Law, legacy contaminants in sediments and diffuse agricultural inputs continue to pose significant risks. Cadmium levels in rice still exceed food safety standards, arsenic in groundwater surpasses health guidelines, and microplastic flux into the East China Sea has reached 8.3 × 10¹² particles per year. Nutrient surpluses also drive extensive algal blooms, causing substantial economic losses. This review evaluates remediation strategies such as dredging, phytoremediation, wetland restoration, and AI-enhanced monitoring, which show removal efficiencies of 60–90% at reduced costs. However, critical gaps remain in understanding chronic mixture toxicity, the long-term fate of emerging contaminants, and pollutant–climate interactions. We propose an integrated basin-wide roadmap combining zero-liquid-discharge mandates, green infrastructure, and adaptive, performance-based governance to secure the Yangtze’s ecological and economic sustainability. This framework offers a transferable model for large-scale watershed management worldwide. Full article

Since the 1980s, South Korea has continuously supplied public rental housing alongside the development of new towns. However, systematic studies examining the relationship between qualitative changes in floor plan design and the institutional factors influencing them remain limited. This study is based on the premise that floor plans in public rental housing are not merely the result of design improvements, but are structurally shaped by legal and institutional frameworks. It systematically analyzes changes in floor plan types and planning elements according to development periods and housing sizes. To achieve this, this study examines public rental housing supplied in Korean new towns from the 1990s to the 2010s, classifying floor plan types by period and housing size and analyzing their planning characteristics. The analysis focuses on the composition and arrangement of interior spaces, the size of each space, bay structure, and aspect ratio. A comparative analysis further examines the relationship between floor plan changes and relevant laws and institutional frameworks. The results show that floor plan configurations evolved in distinct phases in response to institutional changes and housing size differentiation. In the 1990s, standardized one-bay layouts with integrated living and sleeping spaces were predominant under strict regulatory conditions, including spatial dimension constraints. In the 2000s, following the legalization of balcony extensions, floor plans diversified into two-bay and three-bay configurations. In the 2010s, floor plan types became increasingly diversified and complex under the influence of district unit plans and detailed design guidelines issued by public agencies. In terms of housing size, smaller units (around 20 m²) maintained simplified one-room configurations, while medium-sized units (around 30–40 m²) exhibited a clear transition from integrated to functionally separated layouts, and larger units (around 50 m²) showed a significant increase in spatial diversity and variation in layout composition. These findings indicate that floor plan evolution is not a linear process of design improvement, but a structurally conditioned transformation shaped by regulatory frameworks, institutional changes, and path dependency. The persistence and gradual modification of earlier standardized layouts suggest that floor plan configurations are continuously reproduced and adapted within institutional constraints. By empirically identifying the structural relationship between institutional frameworks and floor plan design, this study reveals the mechanisms through which institutional conditions shape housing design. Furthermore, it contributes to an interdisciplinary understanding that integrates architecture, urban planning, and housing policy, and provides important implications for design guidelines and policy development aimed at improving the quality of public rental housing. Full article

Despite their excellent torsional and bending strength, the economical production of hypotrochoidal profiles (H-profiles) remains an obstacle to their use. Due to the tool clearance angle, the commercially available twin-spindle turning process has limited ability to manufacture many of the profiles standardized according to DIN 3689 (Deutsches Institut für Normung). On the other hand, the manufacturing of cycloidal as a non-involute special geometry using generating processes (hobbing or continuous generating grinding) depends critically on the accuracy of the tool geometry—whether a hobbing cutter or a grinding worm. Conventional tool design methods—based on approximations, involute-derived profiles, or iterative trial-and-error corrections—face fundamental limitations: unpredictable cutting force variations, elevated surface roughness, and limited process capability. However, if the exact tool geometry has been determined analytically, the same machine achieves significantly better performance. In this work, the exact tool geometry conjugated to the H-profile for profile manufacturing is determined based on the gearing law. This provides modular H-profile manufacturing without deviations. Consequently, a design concept that enables the implementation of all existing rolling processes—including gear hobbing, gear shaping, gear planning, and other variants such as gear grinding—is presented. For profile shaping of hollow contours, the transfer ratio is considered and a curve conjugated to the profile contour is determined for the tool. A CAD-based simulation shows very good consistency with the analytically determined tool geometry. Full article

Permanency planning, an approach to the placement of children in out-of-home care, is central to child and family system practice, policy and law. Using the example of legislative reforms in New South Wales (NSW), Australia, this article explores how privileging legal permanence leads to ongoing failures to account for Aboriginal worldviews and child-rearing practices. Drawing on qualitative research, including Yarning Circles and semi-structured interviews that I conducted with Aboriginal community members in NSW, the findings contribute to limited evidence on permanence from Indigenous perspectives, revealing how familial and cultural connectedness shape belonging and social and emotional wellbeing and highlighting the importance of children’s ongoing connections with extended Aboriginal family, community and culture. Aboriginal understandings of permanence align more closely with cultural, relational and physical domains than with the construct of legal permanence that predominates in permanency planning approaches. Prioritizing legally permanent care arrangements above other domains poses long-term risks to Aboriginal children’s social and emotional wellbeing, demonstrating the need for “deep-level” cultural adaptation in child welfare law, policy and practice. The findings have implications for decolonizing child protection and repositioning Aboriginal conceptualizations of permanence as the foundation for legislation, policy and practice—reforms that must be Indigenous-led, culturally grounded from the outset, and anchored in full implementation of principles embedding self-determination and Indigenous children’s fundamental rights. Full article