ABSTRACT This paper draws on a selected case study to examine how discretionary decision-making in development control can benefit from operational guidelines so as to become more transparent, consistent and accountable. Adopting an outcomes-centred approach, it investigates a series of discretionary approvals that have permitted the development of 107 tall buildings in Limassol, Cyprus, since 2007. The study analyses the spatial characteristics of the approved developments and situates them within the broader planning and policy framework under which the permissions were granted. In the absence of a local framework regulating the exercise of discretion in development control, the assessment turns to international planning practice and adopts the framework developed in Western Australia as a reference model. The findings reveal that a combination of outdated planning policies, vague provisions, and the absence of development-control guidelines enabled a pattern of decision-making that deviated from the strategic intent of the Limassol Local Plan. The study offers broader lessons for discretionary planning systems, emphasising the need for up-to-date policy frameworks and clearly defined regulatory tools to guide discretion. It also highlights the challenges of ex post evaluation of discretionary decisions and demonstrates the effectiveness of Western Australia’s guidelines in supporting informed and consistent decision-making.

An integrated vulnerability-resilience framework for climate risk assessment in depopulating urban landscapes

To describe intellectual disability inclusion in local health department (LHD) community health assessments (CHAs) and community health improvement plans (CHIPs), this study used a cross-sectional design, analyzing CHAs and CHIPs of Public Health Accreditation Board-accredited LHDs. We find that approximately 5% (n = 17) of CHAs included an intellectual disability (ID) partner in the development process. Less than 2% (n = 3) of CHIPs included a goal, objective, or activity that specifically included people with ID. Many CHAs used language that identified ID as a health outcome to be prevented. CHAs and CHIPs play a key role in informing the work conducted by LHDs. Intellectual disability inclusion and representation in CHAs and CHIPs are limited. These findings identify a gap in ID-inclusive verbiage and community-based participation in developing CHAs and CHIPs and the need to increase ID inclusion in these planning processes and documents.

This article presents a dynamics-based path-planning framework for tensegrity robots that accounts for environmental interaction. A systematic investigation is conducted into the mapping among locomotion gaits, actuations, and ground interaction forces of a six-bar tensegrity robot. The study addresses three coupled challenges within a unified framework: the dynamic effects of flexible-body deformation and environmental interaction, the construction of a finite gait library for realizing discrete motions, and a dynamics-informed local path-planning strategy for varying contact and friction conditions. A general dynamic model is established to describe contact friction and generate interaction-aware gaits. Subsequently, a gait library is developed that maps sequences of gait primitives to commanded motions. A lightweight local planning strategy, denoted as M1L2T3, is then formulated on this gait-primitive graph to enable efficient path selection under local map information. A proof-of-concept prototype is fabricated for experimental validation. Experimental results confirm the effectiveness of the interaction-coupled dynamic model for gait generation and locomotion control, showing reasonable agreement with theoretical predictions and validating the proposed planning strategy. The results demonstrate the value of incorporating interaction-aware gait realization into locomotion planning for tensegrity robots.

ABSTRACT This study develops a framework for assessing socio-cultural inclusiveness in urban planning documents and applies it through a comparative case study of two local government areas in New South Wales, Australia – Blacktown City Council and the City of Parramatta. The framework evaluates planning documents against three indicators: consideration of vulnerable residents’ needs, procedural representation and equity, and just planning outcomes. Each indicator is operationalised through sub-questions that allow systematic evaluation and visual comparison. The comparative analysis reveals substantial differences between the two Community Strategic Plans, with the Parramatta plan articulating inclusion more explicitly across all three indicators. The analysis also surfaces a shared pattern: both plans are stronger on the articulation of inclusive principles than on the specification of operational mechanisms, with the largest gaps clustering at foundational rather than operational sub-questions. This finding suggests that document-based evaluation benefits from attention not only to whether inclusion is acknowledged, but to how it is operationalised. The framework offers a tool for examining this distinction in local planning contexts.

The Community-Based Monitoring System (CBMS) serves as an important tool for local evidence-based planning. Using a stratified survey of 106 planning division employees across three strata of LGUs, this study measured the extent of CBMS utilization on a 5-point scale. A deep understanding of CBMS data will provide a more robust basis for local governance, thereby improving precision in socio-economic planning, fairness in fiscal distribution, and the efficacy of poverty-alleviation projects. Given these considerations, this study examined the extent to which CBMS data are used in local government planning, budgeting, and program implementation. between age, digital adaptability, and engagement with data systems. While both younger and older employees can effectively utilize CBMS data, younger employees demonstrated notably higher utilization in program implementation, possibly reflecting greater familiarity with digital technologies and data-driven processes. Furthermore, female employees exhibited significantly higher utilization of CBMS data in budgeting activities. These results indicate that although CBMS is broadly utilized across demographic groups, differences in specific areas of application may be influenced by age-related competencies and gender-related roles in local governance functions. Despite overall high utilization, gaps in specific indicators highlight the need for capacity building. Such as health service delivery, youth development, skills training, and age-specific interventions highlight gaps in data application, which need to strengthen technical capacity, training, and data integration processes for effective, evidence-based planning, budgeting, and program implementation. Keywords: Planning, budgeting, program implementation

Accurate outbreak forecasts are critical for timely and effective public health response. In the United States, however, most forecasts are produced at the state level, which can mask substantial sub-state heterogeneity and limit their utility for local planning. We generated and evaluated forecasts of the percentage of Emergency Department visits attributable to influenza across 173 large metropolitan Health Service Areas (HSAs) using a gradient boosting quantile regression (GBQR) model, and compared their accuracy to forecasts derived from state-level data alone. At a one-week, two-week and three-week horizon, local forecasts outperformed state-based forecasts in 98.8%, 90.8%, and 78.6% of HSAs, respectively, achieving mean weighted interval scores that were on average a 39.2% lower (95% range: 5.9% to 76.7%), 19.6% lower (−6.3% to 59.5%), and 11.4% lower (−11.7% to 44.9%), respectively. The performance advantage of local forecasting was strongest in HSAs representing a smaller share of their state’s population and increased with the proportion of the HSA population living in urban areas and the number of metropolitan areas within a state. These results, based on an analysis of HSAs with populations greater than 250,000, demonstrate that fine-scale modeling can substantially improve forecast accuracy and highlight the potential value of local forecasts for outbreak preparedness and response.Significance StatementDuring severe influenza seasons and pandemics such as COVID-19, anticipating the timing and severity of local peaks is critical for managing healthcare surges and communicating risk—yet these dynamics can vary substantially across local areas within the same state. However, most forecasting efforts in the United States provide only state-or national-level projections. This study shows that local influenza forecasts are both feasible and consistently more accurate than state-level projections, particularly in metropolitan areas that make up a small share of large states with multiple metropolitan areas.

To characterise adult tonsillectomy procedures conducted in the NHS from routine administrative data in England and investigate trends in their associated complications over time. Retrospective observational cohort study using routine data from Hospital Episode Statistics (HES). Acute NHS trusts in England are conducting adult tonsillectomy. Adults (> 16 years old) undergoing tonsillectomy procedure with a primary diagnosis of any non-malignant indication, and with no current or historic cancer, or benign neoplasm. Number of procedures, in-hospital complications, readmissions within 28 days and trends over time. A total of 198 130 adult patients had a tonsillectomy between 1 April 2008 and 31st March 2023 in NHS trusts in England. The total number of procedures is falling over time. It is more commonly undertaken in women (68.3%), with 79.3% performed for tonsillitis. The majority (59.6%) are discharged on the same day, with 37.5% staying 1 night in hospital. 1.5% of patients had an in-hospital complication, with a total of 1967 patients having a haemorrhage or surgical arrest of post-operative bleeding from the tonsillar bed or adenoid; occurring more frequently in men (1.7% versus 0.7%, p < 0.001). A total of 33 934 patients were readmitted as an emergency within 28 days of surgery, almost doubling between 2008/09 and 2022/23. Readmission with bleeding within 28 days has also increased from 8.8% in 2008/09 to 15.6% in 2022/23. The return to theatre rate during readmissions has been relatively stable over the study time period with a higher proportion of admissions being managed without a further operative procedure. Tonsillectomy is a very common operation in the NHS in England. It currently has a readmission rate of 1 in 5 adults and this information is important for informed consent and local resource planning.

Urban sprawl is one of the major challenges facing urbanizing societies. This study quantifies the extent of urban sprawl in southern Poland's four most populous metropolitan areas, encompassing 164 municipalities, and assesses the effectiveness of spatial planning strategies aimed at limiting sprawl. The first phase of the research establishes comparative parameters for evaluating sprawl across these urban regions. To measure it, we apply the weighted urban proliferation (WUP) method, which comprises three indicators: the proportion of built-up land, the degree of spatial dispersion, and land consumption per capita. The most dispersed metropolitan areas are Rzeszów and Upper Silesia-Zagłębiowska and the most compact are Kraków and Wrocław. In the second phase, we analyze sprawl at the municipal level and examine how specific planning instruments—namely local spatial development plans (MPZPs) and decisions on land development and management conditions (WZs)—influence its occurrence. We correlate the WUP metrics for each municipality with the percentage of land covered by MPZPs in 2018 and the total number of WZs issued from 2009 to 2018. The analysis reveals diverse sprawl patterns, shaped by differing historical contexts, planning coverage (MPZPs), and intensity of WZ decisions. Notably, the number of WZs per square kilometer appears to exert a stronger impact on sprawl dynamics than the mere extent of MPZP coverage. Our findings indicate only weak to moderate correlations between the presence of MPZPs and sprawling development, suggesting the need for more targeted and effective anti-sprawl planning policies. This study highlights the critical role of well-designed spatial management tools for coping with urban expansion. • Weighted urban proliferation (WUP), integrating land use, dispersion, and population density, is applied in Poland. • The most dispersed metro areas are Rzeszów and Upper Silesia-Zagłębiowska and the most compact are Kraków and Wrocław. • Certain regions are more dispersed due to historical legacies, weak planning, and high intensity of land development. • Due to the low effectiveness of local spatial development plans, new tools should be used to limit urban sprawl. • The WUP method enables new empirical evidence of planning effectiveness in Polish cities.

The built environment is a critical component in shaping urban areas and their resilience. While existing studies frequently discuss how different built environment elements can enhance a city's capacity to respond quickly and effectively to external shocks, limited research has validated these effects through actual disaster event outcomes. This study aims to empirically investigate the relationship between the built environment and urban resilience, focusing on the context of the COVID-19 pandemic in Singapore. Using urban vitality, approximated by public transit passenger data, as an indicator of the resilience process, we quantified urban resilience through three metrics: robustness, recovery degree, and total performance loss, derived from temporal changes in urban vitality. Multiple linear regression (MLR), spatial lag model (SLM), and geographically weighted regression (GWR) were applied to examine how built environment factors relate to these metrics. The results across models indicate that higher residential density, more diverse land use, and greater distance to CBD are positively associated with resilience, whereas greater transit service is associated with lower resilience. Moreover, GWR explains the highest variations in all resilience metrics compared to MLR and SLM. By mapping spatially varying associations, the findings offer insights to support localized and data-driven planning for building resilient urban environments capable of withstanding and adapting to future shocks. • A new approach assesses built environment's impact on urban resilience. • Urban vitality from human mobility effectively captures resilience processes. • Proposed resilience metrics reveal intra-city disparities in resilience. • Higher density and land use mix are linked to better resilience outcomes. • Proximity to CBD and transit service relate to lower resilience during COVID-19.

This paper intends to address the challenges of mobile intelligent agents in complex three-dimensional environments, specifically the difficulties in obtaining a globally feasible path and avoiding dynamic obstacles. For this purpose, a hybrid global dynamic path planning approach is proposed, which incorporates a neural network based six-direction search (SDS) algorithm and an improved dynamic window approach (DWA). Initially, the SDS algorithm is utilized to rapidly plan an initial feasible path. Subsequently, key nodes from this feasible path are extracted as sub-goal points for the DWA algorithm, ensuring that the path achieves global feasibility. When encountering dynamic obstacles, the mobile agent employs an improved dynamic window approach for local path planning. However, to enhance the environmental adaptability of the mobile intelligent, fuzzy logic is incorporated to dynamically adjust the weight of each parameter in the evaluation function. This combined approach enables the mobile agent to plan a globally feasible path in real-time within complex three-dimensional environments. Finally, both simulations and robotic experiments demonstrate that the proposed algorithm consistently enables mobile end-effector of the robotic arm to find a globally feasible obstacle-avoiding paths in complex three-dimensional spaces.

The role of paradiplomacy for cultural heritage preservation: The cosmological axis of yogyakarta

Neighborhoods are critical arenas where urban form, accessibility, and daily life intersect, yet most megacities rely on coarse administrative boundaries that obscure local spatial and social dynamics. There is a persistent gap in objective, multicriteria, and data-driven methods for defining neighborhoods and supporting local planning. This paper proposes a transferable, data-light framework that clusters urban blocks into contiguous neighborhood units, contributing to a consistent socioterritorial definition. The framework incorporates barrier-aware adjacency constraints, PCA and multi-index/ARI-stability evidence based protocol to enable urban delineation. The method integrates three key planning dimensions: (A) built environment, (B) accessibility, and (C) sociodemographic context. After standardization and dimensionality reduction via Principal PCA, clustering is performed using three different algorithms. The algorithm dynamically adjusts the k-optimal value for each case. Applied to São Paulo, a 11.4-million–inhabitant city in Brazil, results indicate distance to high-capacity public transit as the most influential factor, correlating strongly with land value and commercial-service concentration. Population density remains relevant but not deterministic, underscoring the importance of a multi-criteria approach to neighborhood analysis. The clustering reveals socio-spatially cohesive areas that cut across formal administrative boundaries, exposing neighborhood-scale structures often obscured in conventional planning units. Core transit-rich clusters concentrate up to 75% of built area in commercial or service use, while peripheral zones remain underserved. The framework identifies neighborhood areas of influence that can support the delineation of reference perimeters for guiding the public policies, and offers planners a flexible tool for neighborhood-scale policy design, inclusive urban governance, and equitable spatial interventions. • Delimits objectively neighborhoods through unsupervised learning method • Replicable clustering approach strengthens neighborhood delineation in cities • Multi-metric clustering and validation method to analyse urban dynamics • São Paulo application evidences clustering’s relevance to neighborhood planning • Results showed strong alignment between cluster patterns and transit accessibility

UAV path planning in dynamic environments requires balancing global path quality, local obstacle avoidance, and motion smoothness. To address the premature convergence and unsmooth paths of the Grey Wolf Optimizer (GWO) and the local-optimum tendency and evaluation imbalance of the Dynamic Window Approach (DWA), this paper proposes CRGWO-DWA, a structured global-local collaborative planning framework. In the global planning stage, CRGWO enhances population diversity and search performance through piecewise linear chaotic initialization, periodic regeneration of the control parameter, and adaptive leadership weighting, while cubic spline interpolation is used to generate a smooth reference path. In the local planning stage, DWA is improved using min-max normalized evaluation and redesigned weighting to enhance trajectory discrimination and responsiveness under dynamic obstacle interference. Experimental results show that CRGWO achieves the best or tied-best performance in most reported benchmark metrics, reduces path length and redundant turning nodes in static environments, and produces more compact and smoother paths in three-dimensional scenarios. In dynamic multi-obstacle environments, CRGWO-DWA enables safe and smooth UAV navigation with stable velocity profiles. These results indicate that the proposed framework provides an effective solution for UAV path planning in dynamic environments.

With the rapid development of artificial intelligence technology, the application of intelligent robotics technology in the field of library services is becoming increasingly widespread. This paper systematically reviews key advancements in robot recognition technology, path planning, service innovation, and the development of smart libraries. By leveraging neural networks and deep learning technologies, combined with image recognition and data processing techniques, it is possible to achieve accurate book identification, rapid localization, and intelligent path planning, thereby optimizing the library’s circulation management system. Research indicates that intelligent robot technology can effectively drive the intelligent transformation and upgrading of university libraries, providing theoretical references and practical pathways for the development of smart libraries.

Home indoor environments are characterized by alternating open spaces and obstacle-cluttered regions, which pose critical challenges to the autonomous navigation of home service robots. Existing hybrid path planning algorithms generally suffer from three core limitations: low global search efficiency, weak global-local planning coordination, and poor dynamic scene adaptability. To tackle these issues, this paper presents a novel hierarchical path planning framework combining an enhanced Jump Point Search (JPS) and a fuzzy-optimized Dynamic Window Approach (DWA). In the global planning layer, an adaptive Octile heuristic JPS based on local obstacle density is designed to reduce redundant node expansion and accelerate global path search, with a bounded suboptimality guarantee. To bridge global and local planning, a look-ahead distance-based dynamic waypoint selection strategy is developed to match the optimal waypoint in real time according to the robot’s motion state and environmental complexity, enabling seamless coordination between global path guidance and local trajectory generation. In the local planning layer, a fuzzy logic controller is introduced to dynamically tune the weights of the DWA trajectory evaluation function, which significantly improves the robot’s dynamic obstacle avoidance capability and motion smoothness. Comparative simulation experiments verify that the proposed method not only outperforms the conventional hybrid path planning algorithm, reducing expanded nodes by 68.09% and global planning time by 52.94%, while improving dynamic obstacle avoidance success rate by 31.43% and overall navigation efficiency by 23.95%, it also achieves better comprehensive navigation performance than the widely adopted PSO-DWA comparison algorithm. The proposed framework shows superior comprehensive performance and is well suited for the indoor autonomous navigation of home service robots.

Standardizing nursing care plan data from electronic health records is critical for interoperability and large-scale research but is often hindered by the heterogeneity of local terminologies. This study evaluates an optimized Retrieval-Augmented Generation (RAG) pipeline using large language models to map local care plan problems, goals, and interventions from two health systems to standardized nursing terminologies. We compared multiple prompt engineering techniques. Structured Prompts combined with Few-Shot Learning achieved the highest performance, with moderate accuracy (45-70%). Although full automation remains out of reach, this approach reduced human workload and supports scalable, human-in-the-loop semantic interoperability of nursing data.

ABSTRACT Australia is one of the most heat-vulnerable and multicultural countries in the world. It is vital that diverse communities receive information about heat in accessible language. Local councils play an important role in facilitating this. It is unknown how local councils cater for their diverse communities to provide multilingual communication, considering scattergun heat policies. This research aims to understand how local governments plan and manage heatwave communication for multilingual communities in Australia. We share insights from interviews with sixteen local council representatives from twelve local government areas (LGAs) identified as highly multilingual and heat-vulnerable. We draw on language planning and management theory and undertake reflexive thematic analysis to explore advocacy, autonomy, and accountability. Our analysis suggests that local councils play a liminal role in the language management of multilingual heat communication by operating within and beyond existing policies, their communities, and other government departments. Local councils enact this liminality by antagonising (un)official requirements for standardised language practices and depoliticised messaging, and by complementing existing approaches with creative bilingual solutions, triangulation of data, and leveraging climate discourse to develop culturally responsive communication. Further consideration is needed regarding training in communication for translatability, developing critical heat literacy, and funding for multilingual staff.

ABSTRACT California’s Fifth Regional Housing Needs Allocation provides forecasts of new housing units needed across four household income levels in cities for the periods 2013–2015 to 2021–2023 to address the state’s housing shortage, along with the permits issued for these units. Using regression analysis, we examine how local factors related to potential “Not in My Back Yard” (NIMBY) demographics and motivations, as well as housing allocation and approval processes, may influence a city’s number of permitted housing units. Our analysis shows that many of these factors exert the expected correlation with the number of housing units permitted. Cities with a higher percentage of young adults and adults who voted in the 2016 presidential election and who voted Republican are more likely to permit additional housing units than needed. Fewer than needed permits are issued in cities with a greater proportion of long‑term residents and a local comprehensive plan that does not adequately accommodate the housing needed in a city. These findings highlight two important policy considerations for regions experiencing a shortage of affordable housing: (1) local jurisdictions often resist measures to increase housing supply, and (2) effective institutional interventions from a higher level of government are required to improve housing affordability.

Landslides are a significant geomorphological hazard in Indonesia that can damage infrastructure and disrupt social activities. In Majalengka Regency, variations in topographic conditions result in different levels of landslide susceptibility, which may affect public facilities, including educational institutions. This study aims to analyze the spatial distribution of landslide susceptibility and evaluate the exposure of educational facilities using a GIS-based Weighted Overlay method with seven parameters. The results indicate that High and Very High susceptibility areas cover approximately 33,284 hectares and 17,388 hectares, respectively, and are mainly concentrated in the southern part of Majalengka Regency. Of the 672 educational facilities, 162 schools (24.1%) are located within landslide-prone zones, including 47 schools in Very High susceptibility areas. These findings highlight the influence of terrain conditions, rainfall, soil characteristics, and proximity to infrastructure in shaping landslide susceptibility. This study provides a spatially explicit evaluation of educational facility exposure, offering empirical baseline data to support local disaster mitigation strategies and school safety planning.