Search Results (14,137)

Due to the complexity of shipyards’ operating scenes and the inconsistency of ship parts’ type and size, current sorting operations for ship parts mainly rely on laborers, resulting in weak control over the production process and key nodes. With the gradual advancement of intelligent manufacturing technology in the shipbuilding process, the trend of machines replacing humans is obvious. In order to promote the automation of the sorting process, intelligent scene recognition and route planning algorithms are needed. In this work, we introduce a localization method based on a laser line profile sensor and ship parts layout analysis algorithm, aiming at obtaining the information needed for sorting route planning. In addition, a heuristic-based route planning algorithm is proposed to solve the built mathematical model of the ship part sorting process. The proposed method can optimize the sorting order of parts, realize stable stacking, shorten sorting distance (taking about 490 m for 43 parts), and thereby improve operation efficiency. These results show that the proposed approach can make intelligent and comprehensible sorting route planning for the ship parts layout. Full article

Predicting future events is crucial for temporal reasoning, providing valuable insights for decision-making across diverse domains. However, the intricate global interactions and temporal–causal relationships at the document level event present significant challenges. This study introduces a novel document-level future event prediction method that integrates an event knowledge graph and a large language model (LLM) reasoning framework based on metacognitive theory. Initially, an event knowledge graph is constructed by extracting event chains from the original document-level event texts. An LLM-based approach is then used to generate diverse and rational positive and negative training samples. Subsequently, a future event reasoning framework based on metacognitive theory is introduced. This framework enhances the model’s reasoning capabilities through a cyclic process of task understanding, reasoning strategy planning, strategy execution, and strategy reflection. Experimental results demonstrate that the proposed approach outperforms baseline models. Notably, the incorporation of the event knowledge graph significantly enhances the performance of different reasoning methods, while the proposed reasoning framework achieves superior performance in document-level future event prediction tasks. Furthermore, the interpretability analysis of the prediction results validates the effectiveness of the proposed method. This study advances research on document-level future event prediction, highlighting the critical role of event knowledge graphs and large language models in temporal reasoning. It offers a more sophisticated future event prediction framework for government management departments, facilitating the enhancement of government safety management strategies. Full article

In response to the growing demand for automation in aerospace harness manufacturing, this study proposes a digital twin-based intelligent monitoring system for robotic wiring operations. The system integrates a seven-degree-of-freedom robotic platform with an adaptive servo gripper and employs a five-dimensional digital twin framework to synchronize physical and virtual entities. Key innovations include a coordinated motion model for minimizing joint displacement, a particle-swarm-optimized backpropagation neural network (PSO-BPNN) for adaptive gripping based on wire characteristics, and a virtual–physical closed-loop interaction strategy covering the entire wiring process. Methodologically, the system enables motion planning, quality prediction, and remote monitoring through Unity3D visualization, SQL-driven data processing, and real-time mapping. The experimental results demonstrate that the system can stably and efficiently complete complex wiring tasks with 1:1 trajectory reproduction. Moreover, the PSO-BPNN model significantly reduces prediction error compared to standard BPNN methods. The results confirm the system’s capability to ensure precise wire placement, enhance operational efficiency, and reduce error risks. This work offers a practical and intelligent solution for aerospace harness production and shows strong potential for extension to multi-robot collaboration and full production line scheduling. Full article

Rapid urbanization across Southern Asia’s coastal regions has significantly increased electricity demand, driving India’s solar sector expansion under the National Solar Mission and positioning the country as the world’s fourth-largest solar market. Nonetheless, methodological limitations remain in applying GIS-based multi-criteria decision analysis (MCDA) frameworks to coastal urban microclimates, which involve intricate land-use dynamics and resilience constraints. To address this gap, this study proposes a multi-criteria GIS- based Analytical Hierarchy Process (AHP) framework, incorporating remote sensing and geospatial data, to assess Solar Farm Sites (SFSs) suitability, supplemented by sensitivity analysis in Thoothukudi coastal city, India. Ten parameters—covering photovoltaic, climatic, topographic, environmental, and accessibility factors—were used, with Global Horizontal Irradiance (18%), temperature (11%), and slope (11%) identified as key drivers. Results show that 9.99% (13.61 km²) of the area has excellent suitability, mainly in the southwest, while 28.15% (38.33 km²) exhibits very high potential along the southeast coast. Additional classifications include good (22.29%), moderate (32.41%), and low (7.16%) suitability zones. Sensitivity analysis confirmed photovoltaic variables as dominant, with GHI (0.25) and diffuse radiation (0.23) showing the highest impact. The largest excellent zone could support approximately 390 MW, with excellent and very high zones combined offering up to 2080 MW capacity. The findings also underscore opportunities for dual-use solar deployment, particularly on salt pans (17.1%), as well as elevated solar installations in flood-prone areas. Overall, the proposed framework provides robust, spatially explicit insights to support sustainable energy planning and climate-resilient infrastructure development in coastal urban settings. Full article

The Niokolo-Koba National Park (NKNP) was inscribed on the World Heritage List in 1981 for its exceptional biodiversity and unique ecosystem. However, due to poaching, livestock grazing, and dam construction projects in the Sambangalou area, the site was added to the List of World Heritage in Danger in 2007. Through regional and international cooperation, enhanced monitoring, and community engagement in conservation efforts, the site was removed from the List of World Heritage in Danger in 2024. As a typical case of the entire process from inscription on to removal from the World Heritage List in Danger, the NKNP’s threats and successful removal experience profoundly reveal complex internal and external challenges and governance needs in heritage conservation. Its successful experience can provide valuable lessons for World Heritage sites around the world facing similar threats. As part of our qualitative research, we reviewed the literature from UNESCO and IUCN, which annually assessed the state of conservation of the NKNP between 2007 and 2024. In 2024, a field mission assessed on-site conservation progress and discussed challenges and responses to the NKNP management with 30 stakeholders. Our results highlight the lengthy and potentially costly process of removal, such as Senegal’s EUR 4.57 million Emergency Plan, the threats to the park’s integrity by the State itself, and the value placed on World Heritage status, further emphasizing the need for long-term investment from both the national government and international partners. Therefore, ensuring returns on such investment, whether through increased ecotourism, international recognition, or strengthened ecosystem services, is essential for sustainable conservation financing. The case of the NKNP also illustrates the positive impact of improved national governance and partnerships involving international and local NGOs, as well as the private sector, on conservation efforts. It also highlights the importance of a new collaborative governance paradigm for heritage sites facing severe human interference (poaching, illegal development) and governance challenges, particularly in ecologically fragile or socio-economically pressured regions, by strengthening national responsibility, leveraging international mechanisms, and activating local participation. Full article

An experiment with a two interaction modalities (traditional: touch; novel: touch–speech) × two task complexities (low: visual single task; high: audio–visual dual task) within-subjects design was conducted to observe alterations in crew performance (including task performance, subjective workload, and eye responses) in a typical planning task-based on a high-fidelity special vehicle simulation platform. The results revealed that (1) compared to the traditional interaction modality, the novel interaction modality significantly improved task performance, reduced subjective workload, increased mean peak saccade velocity, and decreased fixation entropy; (2) under high task complexity, subjective workload, mean pupil diameter, and the nearest neighbor index showed significant increases, while no significant decline in task performance was observed; (3) no interaction effect of crew performance was observed between interaction modality and task complexity. The foregoing results imply that (1) the novel interaction modality incorporating speech input exhibits advantages over the traditional touch-based modality in terms of enhancing task performance (over 45% improvement) and reducing cognitive workload; (2) leveraging dual-channel audio–visual information processing facilitates the maintenance of task performance under high task complexity and multi-tasking demands; (3) eye movement characteristics may serve as informative indicators for evaluating the benefits of speech-based interaction and the effectiveness of cognitive resource allocation under high-complexity task conditions. The results can provide a basis for the design of the display and control interface in special vehicles. Full article

Background: Although most amputations caused by diabetes and peripheral artery disease (PAD) are preventable, current limb preservation efforts in the United States remain poorly understood. This study aims to identify key barriers and facilitators to limb preservation from the primary care provider (PCP) perspective. We plan to use the insights from this work to promote targeted intervention strategies. Methods: Using a mixed-methods design, an online 5–10 min survey was distributed to Oklahoma primary care providers who could elect to participate further in a semi-structured, audio-recorded interview. Descriptive analysis was used to summarize survey results. Interviews were transcribed and qualitatively analyzed using grounded theory. Donabedian’s structure, process, and outcome framework was used to categorize how each identified barrier and facilitator increases or reduces the risk of limb loss for at-risk patients at the practice level. Finally, we compared and contrasted survey and interview findings. Results: Thirty surveys were completed (approximately 14% response rate), and seven interviews were conducted with PCPs geographically dispersed across Oklahoma. Most clinicians reported in the survey that they see at-risk limbs at least once every 1–2 months (n = 29, 96.7%). Half of clinicians were satisfied or very satisfied with access to vascular surgery (n = 15, 50.0%), interventional specialists (n = 13, 43.3%), and endocrinologists (n = 12, 40.0%). Finally, survey respondents reported that social needs most often affecting their patients with a limb at risk of amputation include income, health education, transportation, and health insurance. Interviews confirmed PCPs frequently see at-risk limbs. We identified thematic barriers to limb preservation that included limited access to specialty care, limited PCP and patient amputation prevention education, and patient social struggles surrounding transportation, finances, and insurance. Patient advocates (community, clinical, or personal), affordable medications, and more time with patients were reported as facilitators in amputation prevention. Conclusions: Oklahoma PCPs frequently see at-risk feet, realize poor access to care, and desire structural change to support excellent preventive care in diabetes and PAD. Limb preservation in Oklahoma is contingent upon shifting from disempowerment to engagement that requires systemic reform, clinical innovation, and community engagement. We identified several intervention strategies, including increasing education for PCPs to empower them to initiate early prevention, improving early identification and preventive therapy for patients at risk for limb loss, and cultivating specialty care access via networking and policy change. Full article

Polypoid endometriosis is a rare variant of endometriosis that presents as a tumorous mass, making it difficult to differentiate it from a malignant tumor. It usually occurs in perimenopausal women or those undergoing hormone therapy, and its presence in a young pregnant woman is extremely uncommon. This article describes a rare instance of polypoid ovarian endometriosis in a pregnant woman, a condition with few documented cases in the medical literature. An adnexal mass was discovered incidentally during a routine prenatal ultrasound, with imaging features that raised the suspicion of a neoplastic process and prompted surgery to exclude malignancy. However, histopathological examination of the excised lesion confirmed features compatible with polypoid endometriosis, without revealing evidence of cancer. This case highlights the diagnostic challenges of differentiating polypoid endometriosis from ovarian neoplasms, especially during gestation, where imaging findings can be ambiguous. In addition, the hormonal environment inherent in pregnancy may exacerbate the proliferative behavior of endometriotic lesions, thus complicating clinical evaluations. The presence of an adnexal mass in such a setting often requires careful evaluation to balance the risks of surgery with the potential consequences of delayed diagnosis. The data presented emphasize the importance of an accurate diagnosis. In conclusion, a well-coordinated approach ensures the protection of maternal and fetal health. By prioritizing accurate diagnosis and personalized treatment plans, physicians can minimize complications and improve outcomes for both mother and child. Full article

Multi-target optimization management of reservoirs plays a crucial role in balancing multiple scheduling objectives, thereby contributing to watershed sustainability. In this study, a model was developed for the multi-target optimization scheduling of water–sediment, ecological, and socioeconomic objectives of reservoirs with multi-dimensional scheduling needs, including flood control, sediment discharge, ecological protection, and socio-economic development. After obtaining the Pareto solution set by solving the optimization model, a decision model based on cumulative prospect theory (CPT) was constructed to select optimal scheduling schemes, resulting in the development of a multi-target decision framework for reservoirs. The proposed framework not only mitigates multi-target conflicts among water–sediment, ecological, and socioeconomic objectives but also quantifies the different preferences of decision-makers. The framework was then applied to six cascade reservoirs (Longyangxia, Liujiaxia, Haibowan, Wanjiazhai, Sanmenxia, and Xiaolangdi) in the Yellow River basin of China. A whole-river multi-target decision model was developed for water–sediment, ecological, and socioeconomic objectives, and the cooperation–competition dynamics among multiple objectives and decision schemes were analyzed for wet, normal, and dry years. The results demonstrated the following: (1) sediment discharge goals and ecological goals were somewhat competitive, and sediment discharge goals and power generation goals were highly competitive, while ecological goals and power generation goals were cooperative, and cooperation–competition relationships among the three objectives was particularly pronounced in dry years; (2) the decision plans for abundant, normal, and low water years were S293, S241, and S386, respectively, and all are consistent with actual dispatch conditions; (3) compared to local models, the whole-river multi-target scheduling model achieved increases of 71.01 × 10⁶ t in maximum sediment discharge, 0.72% in maximum satisfaction rate of suitable ecological flow, and 0.20 × 10⁹ kW·h in maximum power generation; and (4) compared to conventional decision methods, the CPT-based approach yielded rational results with substantially enhanced sensitivity, indicating its suitability for selecting and decision-making of various schemes. This study provides insights into the establishment of multi-target dispatching models for reservoirs and decision-making processes for scheduling schemes. Full article

Wound infection significantly hinders the healing process. Clinical signs and symptoms (CSS) of infection are used to assess the presence of infection and guide whether to intervene. However, CSS may not be dependable, lacking sensitivity and specificity, and may not accurately reflect bacterial load. The interpretation of CSS can be subjective and can vary between clinicians since they depend on patient characteristics, type of wound, and stage of infection. In addition, conditions such as peripheral vascular disease or diabetes can mask the signs and symptoms of infection. Inaccurate or late diagnosis of infected wounds can be costly to the patient and to healthcare systems. Fluorescence imaging (FLI) provides a safe, objective, highly sensitive approach to detect clinically significant bacterial levels in wounds. This information allows individualized treatment plans and a way to monitor bacterial burden and wound healing longitudinally. This publication reviews the evidence for point-of-care FLI as a means of improving wound identification with a high bacterial burden and the clinical and healthcare economic benefits of earlier and more accurate detection of bacteria. Full article

Given that the increasing non-agricultural conversion of cultivated land (NACCL) endangers food security, studying the spatial and temporal variation characteristics and driving mechanisms of NACCL in Sichuan Province can offer a scientific foundation for developing local farmland preservation measures and controlling further conversion. Guided by the theoretical framework of land use transition, this study utilizes land use datasets spanning multiple periods between 2000 and 2023. Comprehensively considering population scale factors, natural geographical factors, and socioeconomic factors, the county-level annual NACCL rate is calculated. Following this, the dynamic evolution and underlying driving forces of NACCL across 183 counties in Sichuan Province are examined through temporal and spatial dimensions, utilizing analytical tools including Nonparametric Kernel Density Estimation (KDE) and the Geographical Detector model with Optimal Parameters (OPGD). The study finds that: (1) Overall, NACCL in Sichuan Province exhibits phased temporal fluctuations characterized by “expansion—contraction—re-expansion—strict control,” with cultivated land mainly being converted into urban land, and the differences among counties gradually narrowing. (2) In Sichuan Province, the spatial configuration of NACCL is characterized by the expansion of high-value agglomerations alongside the dispersed and stable distribution of low-value areas. (3) Analysis through the OPGD model indicates that urban construction land dominates the NACCL process in Sichuan Province, and the driving dimension evolves from single to synergistic. The findings of this study offer a systematic examination of the spatiotemporal evolution and underlying drivers of NACCL in Sichuan Province. This analysis provides a scientific basis for formulating region-specific farmland protection policies and supports the optimization of territorial spatial planning systems. The results hold significant practical relevance for promoting the sustainable use of cultivated land resources. Full article

This study addresses the problem of minimizing cable costs in Standardized Photovoltaic Power Units (SPPUs) by proposing an integrated inverter placement optimization framework. A high-precision economic model is first established to quantify the cost of both direct current (DC) and low-voltage alternating-current (LV-AC) cables as a function of inverter location. To improve solution accuracy and efficiency, an enhanced particle swarm optimization algorithm, termed the Adaptive Classification Method PSO (ACM-PSO), is developed, featuring population classification strategies as well as adaptive inertia weighting and neighborhood learning strategies. The optimization process incorporates hierarchical trench planning, dynamic combiner-unit partitioning, and multi-scheme layout generation, ensuring that both spatial and economic factors are systematically considered. A case study on Unit 19 of a 350 MW flat-ground PV plant in Xinjiang, China, demonstrates that the proposed method reduces total cable investment to CNY 292,945, achieving a cost saving of 2.3–3.8% compared with conventional layouts. These results confirm not only the methodological innovation of ACM-PSO for constrained nonlinear PV layout problems, but also its practical generalizability, offering a replicable and scalable design paradigm for large-scale PV plants. Full article

Stone cultural heritage structures built from pyroclastic rocks are susceptible to deterioration due to their sensitivity to atmospheric processes. Detecting such deterioration and periodically examining it using non-destructive testing (NDT) techniques is one of the most critical measures for ensuring its transmission to future generations. In recent years, assessing the properties of building stones through NDT methods has been widely applied in planning the preservation of stone cultural heritages. In this study, deterioration observed on the interior walls of the Emir Ali Tomb, a structure distinguished from other tombs in the region by its exceptional architecture, was investigated through laboratory tests and NDT techniques, including deep moisture measurement, P-wave velocity, and infrared thermography. It was determined that the monument was constructed from four different types of pyroclastic rock, classified according to their textural and geomechanical characteristics. Using data obtained from in situ tests, NDT distribution maps were generated. The deep moisture, P-wave velocity, and infrared thermography maps revealed that the primary cause of deterioration in the monument was related to capillary water rise. Full article

Probabilistic roadmap (PRM) methods are widely used for robot navigation in both 2D and 3D environments; however, a major drawback is that the raw paths tend to be jagged. Executing a trajectory along such paths can lead to significant overshoots and tight turns, making it difficult to achieve a near-optimal solution under motion constraints. This paper presents an enhanced PRM-based path planning approach designed to improve path quality and computational efficiency. The method integrates advanced sampling strategies, adaptive neighbor selection with spatial data structures, and multi-stage path post-processing. In particular, shortcut smoothing and polynomial fitting are used to generate smoother trajectories suitable for motion-constrained robots. The proposed hybrid sampling scheme biases sample generation toward critical regions—near obstacles, in narrow passages, and between the start and goal—to improve graph connectivity in challenging areas. An adaptive k-d tree-based connection strategy then efficiently builds a roadmap using variable connection radii guided by PRM* theory. Once a path is found using an any-angle graph search, post-processing is applied to refine it. Unnecessary waypoints are removed via line-of-sight shortcuts, and the final trajectory is smoothed using a fitted polynomial curve. The resulting paths are shorter and exhibit gentler turns, making them more feasible for execution. In simulated complex scenarios, including narrow corridors and cluttered environments, the advanced PRM achieved a 100% success rate where standard PRM frequently failed. It also reduced calculation time to 30% and peak turning angle by up to 50% compared to conventional methods. The approach supports dynamic re-planning: when the environment changes, the roadmap is efficiently updated rather than rebuilt from scratch. Furthermore, the use of an adaptive k-d tree structure and incremental roadmap updates leads to an order-of-magnitude speedup in the connection phase. These improvements significantly increase the planner’s path quality, runtime performance, and reliability. Quantitative results are provided to substantiate the performance gains of the proposed method. Full article

This article explores a participatory and Geomedia-based approach to urban planning through the concept of place design. Place design as an approach emphasises the integration of collective knowledge, sociocultural values, and digital representation into planning processes. The integration of Geomedia studies further enriches this approach by examining how media technologies influence spatial experiences, representations, and power relations. By introducing place design as a transformative and participatory approach, physical, digital, and social dimensions of place bridge heritage and future aspirations. Through case studies from Kristinehamn, Sunne, and Sysslebäck in Sweden, the article examines methods for in-depth interviewing, capturing diverse representations. The article advocates for a participatory planning approach, establishing the groundwork for more democratic, inclusive, and context-aware development. It concludes by urging urban planners to adopt working methods that respond to the complexity of place, people and technology, promote new ways of thinking and working with design, and make a clear shift from planning for places to designing with people and places. Full article