Spatial Issues Research Articles

Hot-wire spatial resolution issues in adverse pressure gradient turbulent boundary layers

The effect of a finite length of hot-wire probe sensor length on the measured streamwise velocity fluctuations is well understood in canonical wall-bounded flow, where the small-scale energy has been found to be universal and invariant with Reynolds number. A straightforward application of that assumption to non-canonical flows such as strong adverse pressure gradient (APG) flows has, however, been hampered since the effect of Re and APG could not conclusively be studied separately due to the lack of data with a clear scale separation. The present experimental investigation at Reτ≈4000 in weak, moderate and strong APGs with different wire length shows that spatial averaging effects are not only limited to the inner layer. A note of caution is hence warranted for measurements that seemingly try to take the bias effect of spatial attenuation into account by performing measurements with albeit long but fixed viscous-scaled wire length.

Assessing the Spatial Equity of Urban Park Green Space Layout from the Perspective of Resident Heterogeneity

Urban park green spaces (UPGS) are essential resources for improving the urban ecological environment and meeting residents’ recreational needs. However, during rapid urbanization, the layout of UPGS often exhibits spatial inequity, with significant differences in the resources enjoyed by resident groups with different socioeconomic attributes. Accurately assessing the spatial equity of the UPGS layout (the equal accessibility of UPGS) is crucial for optimizing resource allocation and promoting social equity. This study takes the main urban area of Nanjing as an example and utilizes location-based service (LBS) data and multi-source geographic data to conduct an in-depth characterization of residents’ socioeconomic attributes, recreational behaviors, and park green space layout at the street scale. By constructing indicators of resident heterogeneity and UPGS supply–demand matching degree, it reveals the differences in park green space accessibility among different social groups and locations and explores the correlation between resident heterogeneity and UPGS spatial equity. The study finds that the layout of UPGS in the main urban area of Nanjing exhibits significant spatial inequity, with generally poor accessibility to park green spaces in the central urban area and low-income communities. The higher degree of diversification of residents’ socioeconomic attributes leads to a lower level of UPGS spatial equity in their streets. The results of the big data analysis verify the significant impact of resident heterogeneity on the equity of park green space layout. This study reveals the spatial equity issues of UPGS layout from the perspective of resident heterogeneity, providing new ideas and evidence for optimizing the allocation of park green space resources. Future UPGS planning should pay more attention to the diversity of residents’ recreational needs, focus on improving the accessibility of park green spaces in central urban areas and low-income communities, and balance the interests and demands of different stakeholders through public participation mechanisms.

Blindly separated spontaneous network-level oscillations predict corticospinal excitability

Objective. The corticospinal responses of the motor network to transcranial magnetic stimulation (TMS) are highly variable. While often regarded as noise, this variability provides a way of probing dynamic brain states related to excitability. We aimed to uncover spontaneously occurring cortical states that alter corticospinal excitability. Approach. Electroencephalography (EEG) recorded during TMS registers fast neural dynamics—unfortunately, at the cost of anatomical precision. We employed analytic Common Spatial Patterns technique to derive excitability-related cortical activity from pre-TMS EEG signals while overcoming spatial specificity issues. Main results. High corticospinal excitability was predicted by alpha-band activity, localized adjacent to the stimulated left motor cortex, and suggesting a travelling wave-like phenomenon towards frontal regions. Low excitability was predicted by alpha-band activity localized in the medial parietal–occipital and frontal cortical regions. Significance. We established a data-driven approach for uncovering network-level neural activity that modulates TMS effects. It requires no prior anatomical assumptions, while being physiologically interpretable, and can be employed in both exploratory investigation and brain state-dependent stimulation.

Identifikasi Tutupan Lahan Menggunakan Support Vector Machine di Kawasan Perkotaan Cekungan Bandung

The current mapping challenge is to obtain land cover information with a very high level of accuracy. This information can be useful for regional development, especially in the Bandung Basin Urban Area (KPCB). One of the problems in KPCB is spatial planning issues regarding land cover development. One approach to obtaining land cover information is by utilizing remote sensing technology using the Support Vector Machine (SVM) method. The research method employed in this study is remote sensing, with a unit of analysis based on Regency/City administrative boundaries. The data used in this research consists of Landsat imagery recorded in 2023. The aim of this research is to classify land cover and assess accuracy using the SVM method in KPCB. The SVM results provide information on six land covers: water bodies, secondary forests and mixed gardens, wet agricultural land, dry agricultural land, plantations, built-up land, and primary forests. The accuracy test yielded an overall accuracy of 90% and a kappa value of 0.88. The obtained accuracy in land cover classification is very high, indicating that the data used can be employed for further analysis. For instance, spatial analysis reveals that built-up land development in KPCB tends towards the south, highlighting the phenomenon of urban sprawl. Thus, the utilization of remote sensing technology for land cover information can offer valuable policy insights for addressing spatial planning and development in KPCB.

The Mechanism of Socio-Spatial Evolution in Rural Areas Driven by the Development of the Planting Industry—A Case Study of Yuezhuang Village in Shandong Province, China

Rural industrialisation in China, which has historically been restricted by urban–rural dual development policies, has been largely encouraged since the Rural Revitalisation Strategy released in 2018. Industrialisation has deeply influenced socio-spatial evolution by providing job opportunities and promoting the construction of infrastructure and public services, accelerating the two-way flow of urban–rural factors in rural areas. However, this may lead to social and spatial issues, such as social inequalities and unsuitable living conditions, to some extent. This research aims to investigate how the socio-spatial evolution of rural areas was influenced by rural industrialisation and the two-way flow of urban–rural factors. The cherry planting industry and an active “industrial centre”, Yuezhuang Village, in Linqu County, Shandong Province, China, were selected for the empirical study. This research analysed the evolution of the cherry planting industry, the formulation of rural social networks, and the spatial adaptation of the two using mixed qualitative and quantitative methods, followed by a discussion on the current rural planning policies in China. The results show that the cherry industrial chain largely extended the planting areas, and the categories of land use generally increased in Yuezhuang Village over the 30 years studied. The average output value per mu (mu is unit of area measurement used in China, where it is officially standardised. It corresponds to 1/15 of a hectare, or about 666.67 m2). In 2021 was 25 times larger than that in 1996. The population involved in industrial activities increased to over 5000 people countrywide from the initial 17 households. The results also show that urban–rural factors, such as capital, population, techniques, and information, rapidly accelerated in the annual peak season of the cherry industry. This research indicates that small-scale, characteristic, and traditional agriculture could become one of the main driving forces in urban–rural integration and may contribute to sustainable and inclusive rural communities and urban–rural partnerships. This provides the theoretical mechanism of socio-spatial interaction in rural industrialisation in China based on the empirical case study.

Thymic Imaging Pitfalls and Strategies for Optimized Diagnosis.

Thymic imaging is challenging because the imaging appearance of a variety of benign and malignant thymic conditions are similar. CT is the most commonly used modality for mediastinal imaging, while MRI and fluorine 18 fluorodeoxyglucose (FDG) PET/CT are helpful when they are tailored to the correct indication. Each of these imaging modalities has limitations and technical pitfalls that may lead to an incorrect diagnosis and mismanagement. CT may not be sufficient for the characterization of cystic thymic processes and differentiation between thymic hyperplasia and thymic tumors. MRI can be used to overcome these limitations but is subject to other potential pitfalls such as an equivocal decrease in signal intensity at chemical shift imaging, size limitations, unusual signal intensity for cysts, subtraction artifacts, pseudonodularity on T2-weighted MR images, early imaging misinterpretation, flow and spatial resolution issues hampering assessment of local invasion, and the overlap of apparent diffusion coefficients between malignant and benign thymic entities. FDG PET/CT is not routinely indicated due to some overlap in FDG uptake between thymomas and benign thymic processes. However, it is useful for staging and follow-up of aggressive tumors (eg, thymic carcinoma), particularly for detection of occult metastatic disease. Pitfalls in imaging after treatment of thymic malignancies relate to technical challenges such as postthymectomy sternotomy streak metal artifacts, differentiation of postsurgical thymic bed changes from tumor recurrence, or human error with typical "blind spots" for identification of metastatic disease. Understanding these pitfalls enables appropriate selection of imaging modalities, improves diagnostic accuracy, and guides patient treatment. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Spatial issues in social work education in Chile: curriculum analysis of universities and professional institutes

ABSTRACT In response to the growing use of spatial concepts in social work, this article addresses their incorporation in the curriculum of undergraduate programmes and the differences among diverse types of higher education institutions. The aims were 1) to identify how spatial issues are incorporated in social work curriculums in Chile and 2) to compare how this incorporation is made in social work programmes in different higher education institutions. The method was a quantitative and descriptive analysis of the curricula of the totality of the programmes in the country (N = 45). We defined 11 concepts to search: community, spatial concepts (territory, environment, place, space), spatial phenomena (city, rural, housing), and social concepts associated with spatial issues (networks, poverty, citizenship). The results show that community is the most relevant concept. Nevertheless, when viewed collectively, spatial concepts hold similar significance. However, there are noticeable differences in how different higher education institutions use spatial concepts. Professional institutes often overlook spatial concerns compared to universities. We recommend regulating social work education to incorporate a minimum curriculum that addresses these issues. Further research is needed to evaluate course content, references, and scientific publications in Chilean social work.

An integrated causal framework to evaluate uplift value with an example on change in public transport supply

Many empirical applications aim to isolate the impact of implementing new public transport on real estate uplift value. While their conclusions generally point to positive impact, due to reduction in transportation cost, the methodological framework to investigate uplift value has largely evolved over time. This paper reviews the different methodological challenges in measuring causal uplift value and proposes an adjusted parametric approach inspired from the Alonso-Muth-Mills model, returning a complex 2-D price premium function allowing for spatial heterogeneous patterns of the average treatment effect. The proposed framework also accounts for other methodological challenges underlined by literature such as spatial autocorrelation, selectivity and representativity issues, and possible anticipation effects. To illustrate the importance of methodological choices on estimation results, the framework is applied to the case of the implementation of a bus rapid transit (BRT) system in Québec City, a medium-size Canadian city, as a specific case study.

Dynamic Modeling and Optimization Analysis of Rigid–Flexible Coupling Manipulator Based on Assumed Mode Method

Lightweight robotic arms are one of the main technologies to improve the working performance of robotic arms in the future. Focusing on the spatial vibrations issue brought about by the light-weighting of a space robotic arm in this paper, a rigid–flexible coupling dynamics model of a space robotic arm system was established based on the assumed mode method and Lagrange method. Based on the lightweight flexible robotic arm structure, a comparative analysis of the first four mode functions was conducted under different fixed constraints and physical properties to determine the mode order that matches the simulation analysis of this robotic arm, thus, further simplifying the rigid–flexible coupling dynamics equations of the system. The overall rigid model and simplified dynamic model of the robotic arm system were solved by using MATLAB, resulting in a motion trajectory of the flexible arm end in space. The three-dimensional model was validated and simulated using virtual prototype technology under the same joint inputs as the model in MATLAB. The simulation results demonstrated that the trajectory of the end of the flexible arm was basically the same between simplified dynamics model simulation and virtual prototype simulation, and the maximum deviation of the end trajectories of the flexible connecting rods [Formula: see text] and [Formula: see text] was less than 18[Formula: see text]mm and 58[Formula: see text]mm, respectively. Meanwhile, the trajectory trend of the end of the flexible arm in the two aforementioned models was the same as the simulation results of the ideal model (overall rigid model). The above conclusions can verify the correctness of the mathematical model of dynamics obtained from the calculations in this paper. In addition, the research data showed that the maximum vibration deviation of the flexible arm was stabilized within a certain value range under different joint inputs, and this research also provided theoretical support for the late vibration suppression control of the spatial rigid–flexible coupled robotic arm.

Advancing Hyperspectral Image Analysis with CTNet: An Approach with the Fusion of Spatial and Spectral Features.

Hyperspectral image classification remains challenging despite its potential due to the high dimensionality of the data and its limited spatial resolution. To address the limited data samples and less spatial resolution issues, this research paper presents a two-scale module-based CTNet (convolutional transformer network) for the enhancement of spatial and spectral features. In the first module, a virtual RGB image is created from the HSI dataset to improve the spatial features using a pre-trained ResNeXt model trained on natural images, whereas in the second module, PCA (principal component analysis) is applied to reduce the dimensions of the HSI data. After that, spectral features are improved using an EAVT (enhanced attention-based vision transformer). The EAVT contained a multiscale enhanced attention mechanism to capture the long-range correlation of the spectral features. Furthermore, a joint module with the fusion of spatial and spectral features is designed to generate an enhanced feature vector. Through comprehensive experiments, we demonstrate the performance and superiority of the proposed approach over state-of-the-art methods. We obtained AA (average accuracy) values of 97.87%, 97.46%, 98.25%, and 84.46% on the PU, PUC, SV, and Houston13 datasets, respectively.

Relatedness and regional economic complexity: Good news for some, bad news for others

PurposeThis article aims to evaluate the entry and exit of companies from local productive structures, with a specific focus on the sectoral complexity of these activities and the complexity of these portfolios. The study focuses on empirically demonstrating the thesis that related economic diversification exacerbates the development gap between more and less complex regions.Design/methodology/approachThe article uses indicators formulated by the economic complexity approach. They allow a relevant descriptive analysis of the economic diversification process in Brazilian micro-regions and provide the foundation for the econometric tests conducted. Through three distinct estimation strategies (OLS, logit, probit), the influence of complexity and relatedness on the entry and exit events of firms from local portfolios is tested.FindingsIn all estimated models, the stronger relationship between an activity and a portfolio significantly increases its probability of entering the productive structure and, at the same time, acts as a significant factor in preventing its exit. Furthermore, the results reveal that the complexity of a sector reduces the probability of its specialization in less complex regions while increasing it in more complex regions. On the other hand, sectoral complexity significantly increases the probability of a sector leaving less complex local structures but has no significant effect in highly complex regions.Research limitations/implicationsDue to the data used, the indicators are calculated considering only formal job numbers. Additionally, the tests do not detect the influence of spatial issues. These limitations should be addressed by future research.Practical implicationsThe article characterizes a prevailing process of uneven development among Brazilian regions and brings relevant implications, primarily for policymakers. Specifically, for less complex regions, policies should focus on creating opportunities to improve their diversification capabilities in complex sectors that are not too distant from their portfolios.Originality/valueThe article makes an original contribution by proposing an evaluation of regional diversification in Brazil with a focus on complexity, introducing a more detailed differentiation of regions based on their complexity levels and examining the impact of sectoral complexity on diversification patterns within each group.

Multi-typology and multi-scale maps of the in-use building material stock in China

China's rapid urban expansion and population migration have led to a substantial increase in building material stocks (MS). Understanding these stocks is crucial for effective planning and managing the built environment. This study analyzed in-use building MS in China from 2000 to 2020 at different spatial scales and resolutions and employed typological data as a bridge addressing information gaps in non-residential buildings and the spatial scale discontinuity issue in MS analysis. At the macro scale, MS in China increased from 70 gigatons (Gt) in 2000 to 133 Gt in 2020. Non-residential and non-urban MS played substantial roles, constituting 41.8 % and 47.9 % in 2020, respectively. In highly urbanized regions, the proportion of residential building MS decreased due to the prevalence of more functional buildings. Some southern provinces had MS from rural areas even exceeding 50 %, emphasizing the importance of considering rural areas in construction resource management. At a high-resolution scale using GIS data, differences emerged between the analysis and statistical data. These differences, especially in estimating residential and commercial building MS, may be attributed to the mixed-use of building types in Chinese cities or unclear delineations of land use types. We advocate for further research to explore these variations, establishing consistent MS methods across different spatial scales and providing decision-makers with effective data support and analytical tools.

Enhancing the worship experience: a quantitative approach to the Şehzade and Süleymaniye discussion

Süleyman I and Mimar Sinan stand as influential figures of the Ottoman Empire, leaving an indelible mark on Istanbul's cultural and architectural landscape. Built by Sinan for Süleyman the Magnificent, Şehzade Mehmed and Süleymaniye Mosques in particular have been subjects of debate. Şehzade is described by many scholars as a peak in sixteenth century Ottoman architecture, whilst Süleymaniye, built shortly after, is viewed as an architectural regression. This article investigates the transition from the symmetrical quatrefoil scheme of Şehzade to Süleymaniye’s basilica-like design with quantitative methods, based on certain design principles. Spatial perception, visibility, and daylight analyses were conducted on models and plan drawings based on 3D point cloud data obtained from terrestrial laser scanning. Spatial perception analyses suggest that Sinan intended to influence users’ perception with the formation of the superstructure. Resulting visibility levels of certain focal points in the sanctum area prove how they were pivotal in the design process. Finally, daylight analyses results indicate how daylight was also a significant design criterion for Sinan. Ultimately, the study demonstrates that Süleymaniye’s floor plan is an improved design addressing the spatial issues that exist in Şehzade, highlighting Mimar Sinan’s effort to enhance the worship experience.

PFAS: exploration of neurotoxicity and environmental impact.

Per- and polyfluoroalkyl substances (PFAS) are widespread contaminants stemming from various industrial and consumer products, posing a grave threat to both human health and ecosystems. PFAS contamination arises from multiple sources, including industrial effluents, packaging, and product manufacturing, accumulating in plants and impacting the food chain. Elevated PFAS levels in water bodies pose significant risks to human consumption. This review focuses on PFAS-induced neurological effects, highlighting disrupted dopamine signalling and structural neuron changes in humans. Animal studies reveal apoptosis and hippocampus dysfunction, resulting in memory loss and spatial learning issues. The review introduces the BKMR model, a machine learning technique, to decipher intricate PFAS-neurotoxicity relationships. Epidemiological data underscores the vulnerability of young brains to PFAS exposure, necessitating further research. Stricter regulations, industry monitoring, and responsible waste management are crucial steps to reduce PFAS exposure.

Gender-Specific Fine Motor Skill Learning Is Impaired by Myelin-Targeted Neurofibromatosis Type 1 Gene Mutation.

Neurofibromatosis type 1 (NF1) is caused by mutations in the NF1 gene. The clinical presentation of NF1 includes diverse neurological issues in pediatric and adult patients, ranging from learning disabilities, motor skill issues, and attention deficit disorder, to increased risk of depression and dementia. Preclinical research suggests that abnormal neuronal signaling mediates spatial learning and attention issues in NF1; however, drugs that improve phenotypes in models show inconclusive results in clinical trials, highlighting the need for a better understanding of NF1 pathophysiology and broader therapeutic options. Most NF1 patients show abnormalities in their brain white matter (WM) and myelin, and links with NF1 neuropathophysiology have been suggested; however, no current data can clearly support or refute this idea. We reported that myelin-targeted Nf1 mutation impacts oligodendrocyte signaling, myelin ultrastructure, WM connectivity, and sensory-motor behaviors in mice; however, any impact on learning and memory remains unknown. Here, we adapted a voluntary running test-the complex wheel (CW; a wheel with unevenly spaced rungs)-to delineate fine motor skill learning curves following induction of an Nf1 mutation in pre-existing myelinating cells (pNf1 mice). We found that pNf1 mutant females experience delayed or impaired learning in the CW, while proper learning in pNf1 males is predominantly disrupted; these phenotypes add complexity to the gender-dependent learning differences in the mouse strain used. No broad differences in memory of acquired CW skills were detected in any gender, but gene-dose effects were observed at the studied time points. Finally, nitric oxide signaling regulation differentially impacted learning in wild type (WT)/pNf1, male/female mice. Our results provide evidence for fine motor skill learning issues upon induction of an Nf1 mutation in mature myelinating cells. Together with previous connectivity, cellular, and molecular analyses, these results diversify the potential treatments for neurological issues in NF1.

Strategic planning in Russian regions: Spatial development issues

Strategies for the socio-economic development of Russian regions must necessarily include sections devoted to spatial aspects, which in some cases, however, fail to reach their goals due to crude methodological recommendations aimed at effective problem-solving within the regional strategy. The paper discusses the theoretical and methodological fundamentals of sections on spatial development included in the socio-economic development strategies of the RF subjects (using the case of the Ural Federal District (UrFO)). The study rests on the theories of strategic management, as well as regional and municipal management. The research data are obtained from regulatory documents and strategies for the socio-economic development of the UrFO subjects. Qualitative analysis methods were used. We reveal the structural specificity, goals, indicators and measures covered in the sections on spatial development. Despite the existence of the methodological recommendations, each RF subject tends to establish the structure of the ‘spatial’ section based on regional priorities and characteristics. The article reports on the most successful practices of spatial planning in terms of agglomerations and clusters, placement of industrial and social facilities, infrastructure, including the functional zoning of territory, identification of the promising areas of the region’s existing and emerging economic centers’ specialization, etc. Based on the research findings, we recommend to more actively use zoning by the level of socio-economic development, pinpoint promising growth points relating them to the current strategic projects, and develop target indicators more accurately considering the dynamics of population settlement, location of production and infrastructure development.

Study on the Spatial Characteristic and Issue for Spatial Planning in the Quasi-DID

Study on the Spatial Characteristic and Issue for Spatial Planning in the Quasi-DID

Cooperative Scheduling for Directional Wireless Charging With Spatial Occupation

Wireless Power Transfer (WPT) technology has been developed rapidly in recent years. The cooperative charging model and corresponding scheduling methods have been proposed to save the charging cost in paid charging service. However, the state-of-the-art methods ignore the spatial occupation issue of rechargeable devices. Moreover, the cooperative charging scheduling in directional wireless charging has not been studied yet. This paper studies the cooperative scheduling for directional wireless charging with spatial occupation. We formulate the Cooperative Charging Scheduling with Spatial occupation (CCSS) problem of Mobile Rechargeable Sensor Devices (MRSDs) for optimizing the total cost of whole charging system. We first investigate the properties of optimal arrangement of MRSDs in charging group and calculate the tight intervals of charging angles of MRSDs. We show that it is sufficient to bound the error by conducting angle discretization for only two MRSDs in each charging group. Then, a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$(\ln n+1)(1+\varepsilon )$</tex-math></inline-formula> -approximation algorithm of the CCSS problem is proposed based on greedy approach, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$n$</tex-math></inline-formula> is the number of MRSDs, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\varepsilon$</tex-math></inline-formula> is the discretization error. The results of extensive simulations and field experiments demonstrate that our algorithm can reduce at most 42.5% total cost comparing with the benchmark algorithms.

Understanding fire regimes: A biogeographical perspective.

Fire regimes are often considered to be either driven by climate, fuel load or human activities. A significant proportion of fires across various ecosystems occur via large fire events. Recently, suggestions have been made that fires are becoming more severe and frequent as a consequence of current climate change. Although there are many factors influencing fire events, scientists have not found a suitable framework that can provide for understanding fires at the macroscale level. This review article proposes a new conceptual framework to better understand fire regimes. The proposed framework relies on a biogeographical perspective of fire regimes that include characteristics that have been underestimated in previous frameworks and to mitigate time as well as spatial scale issues at the macrolevel.

Research on the sustainable development of scenic-dependent rural spaces: A Case Study of Heping Village

Scenic-dependent rural areas, as a distinct category of rural spaces, are a significant element that cannot be overlooked in China's current efforts towards sustainable rural development. This study focuses on the spatial issues encountered during the development of scenic-dependent rural areas, taking Heping Village as a case study. It emphasizes the needs of the users and employs Space Syntax to analyze spatial patterns at three levels: points, lines, and areas. By adjusting the spatial sustainable layout, accessibility, and complexity, a model for sustainable rural spatial development is proposed, characterized by "one village, two cores, three axes, four zones, and multiple points." The aim of this model is to reconstruct the inadequacies of spatial arrangement within the village and promote the sustainable development of scenic-dependent rural areas through a symbiotic approach.