Spatial Definition Research Articles

Built environment – the secret recipe for mental health healing and recovery: a literature review

PurposeIn the context of urbanization, mental health disorders are becoming an increasing presence that cannot be ignored. It has been discovered that the built environment can influence mental health; however, the relationship between the two is complex, and previous studies lack a general overview of the two. Consequently, this study examines built environment and mental health through a literature review to provide a comprehensive overview and recommendations for psychological health planning in relation to the built environment.Design/methodology/approachThis literature review includes bibliometric analysis and narrative synthesis. Additionally, meta-analysis has been employed to scrutinize the relationship between built environment elements and mental health effects.FindingsThe bibliometric analysis reveals that “health equity” and “healthy aging” have prompted a new wave of research in this field, with the meso- and micro-environment becoming the main focus. Based on the keywords, a narrative synthesis is conducted to identify the influence mechanism, the spatial definition of built environment provides the foundation for the identification of impact elements, the influence of built environment on mental health is realized both directly and indirectly, and diverse methods of data acquisition and analysis offer the basis for exploration and research.Originality/valueUltimately, six optimization strategies and four modular planning recommendations are proposed to improve built environment practices to mitigate mental health problems, strengthen public psychological resilience and help achieve the sustainable development goal of health and well-being.

Spatially defined microenvironment for engineering organoids.

In the intricately defined spatial microenvironment, a single fertilized egg remarkably develops into a conserved and well-organized multicellular organism. This observation leads us to hypothesize that stem cells or other seed cell types have the potential to construct fully structured and functional tissues or organs, provided the spatial cues are appropriately configured. Current organoid technology, however, largely depends on spontaneous growth and self-organization, lacking systematic guided intervention. As a result, the structures replicated in vitro often emerge in a disordered and sparse manner during growth phases. Although existing organoids have made significant contributions in many aspects, such as advancing our understanding of development and pathogenesis, aiding personalized drug selection, as well as expediting drug development, their potential in creating large-scale implantable tissue or organ constructs, and constructing multicomponent microphysiological systems, together with functioning at metabolic levels remains underutilized. Recent discoveries have demonstrated that the spatial definition of growth factors not only induces directional growth and migration of organoids but also leads to the formation of assembloids with multiple regional identities. This opens new avenues for the innovative engineering of higher-order organoids. Concurrently, the spatial organization of other microenvironmental cues, such as physical stresses, mechanical loads, and material composition, has been minimally explored. This review delves into the burgeoning field of organoid engineering with a focus on potential spatial microenvironmental control. It offers insight into the molecular principles, expected outcomes, and potential applications, envisioning a future perspective in this domain.

Towards Sustainable and Sufficient City Region Food Systems: Reflections from the Case Study of Turin, Italy

The City Region Food System (CRFS) approach has emerged in recent years as a framework for shaping urban food governance and policies that overcome the methodological cityism of approaches limited to urban territories defined by administrative boundaries. This article critically analyses the concept referring to the case study of the metropolitan city of Turin, Italy, as part of action research contributing to ongoing efforts to establish food policies. The discussion focuses on three dimensions: (1) the spatial definition of the city region; (2) the relation between the support of short and the re-assessment of long supply chains, with reference to a relational understanding of space; (3) the tensions between the CRFS as an analytical concept and a transformative framework. Results suggest that there is no linear path to define the spatial limits for a CRFS analysis and that a pragmatic approach can best serve policies; that long supply chains should not be ignored but integrated into local food policies; that there are contradictions in the transformative dimension of the CRFS literature when investigating the underlying sustainable development framework from a growth-critical perspective; and that separating the analytical more clearly from the normative dimension could make the discussion more productive.

The application of synthetic wollastonite in digital light processing 3D printing

The application of synthetic wollastonite in digital light processing 3D printing

Computer Vision for Substrate Detection in High‐Throughput Biomaterial Screens Using Bright‐Field Microscopy

High‐throughput screening (HTS) can be used when ab initio information is unavailable for rational design of new materials, generating data on properties such as chemistry and topography that control cell behavior. Biomaterial screens are typically fabricated as microarrays or “chips,” seeded with the cell type of interest, then phenotyped using immunocytochemistry and high‐content imaging, generating vast quantities of image data. Typically, analysis is only performed on fluorescent cell images as it is relatively simple to automate through intensity thresholding of cellular features. Automated analysis of bright‐field images is rarely performed as it presents an automation challenge as segmentation thresholds that work in all images cannot be defined. This limits the biological insight as cell response cannot be correlated to specifics of the biomaterial feature (e.g., shape, size) as these features are not visible on fluorescence images. Computer Vision aims to digitize tasks humans do by sight, such as identify objects by their shape. Herein, two case studies demonstrate how open‐source approaches, (region‐based convolutional neural network and algorithmic [OpenCV]), can be integrated into cell‐biomaterial HTS analysis to automate bright‐field segmentation across thousands of images, allowing rapid, spatial definition of biomaterial features during cell analysis for the first time.

Brain state dynamics differ between eyes open and eyes closed rest.

The human brain exhibits spatio-temporally complex activity even in the absence of external stimuli, cycling through recurring patterns of activity known as brain states. Thus far, brain state analysis has primarily been restricted to unimodal neuroimaging data sets, resulting in a limited definition of state and a poor understanding of the spatial and temporal relationships between states identified from different modalities. Here, we applied hidden Markov model (HMM) to concurrent electroencephalography-functional magnetic resonance imaging (EEG-fMRI) eyes open (EO) and eyes closed (EC) resting-state data, training models on the EEG and fMRI data separately, and evaluated the models' ability to distinguish dynamics between the two rest conditions. Additionally, we employed a general linear model approach to identify the BOLD correlates of the EEG-defined states to investigate whether the fMRI data could be used to improve the spatial definition of the EEG states. Finally, we performed a sliding window-based analysis on the state time courses to identify slower changes in the temporal dynamics, and then correlated these time courses across modalities. We found that both models could identify expected changes during EC rest compared to EO rest, with the fMRI model identifying changes in the activity and functional connectivity of visual and attention resting-state networks, while the EEG model correctly identified the canonical increase in alpha upon eye closure. In addition, by using the fMRI data, it was possible to infer the spatial properties of the EEG states, resulting in BOLD correlation maps resembling canonical alpha-BOLD correlations. Finally, the sliding window analysis revealed unique fractional occupancy dynamics for states from both models, with a selection of states showing strong temporal correlations across modalities. Overall, this study highlights the efficacy of using HMMs for brain state analysis, confirms that multimodal data can be used to provide more in-depth definitions of state and demonstrates that states defined across different modalities show similar temporal dynamics.

Full waveform inversion of ocean bottom seismometer data from the oceanic Pacific Plate of the Japan trench

SUMMARY The geometrical and seismic structure of the Pacific oceanic Plate of the Japan Trench is essential for the understanding of earthquake activity in the area. Ocean Bottom Seismometer (OBS) data can be used, via ray-based tomography, to obtain estimates of properties such as crust thickness and structure, hydration and depth to the Moho boundary. The spatial resolution of these properties can be substantially improved by using the full waveform inversion (FWI) method. Most OBS data in this area are acquired with a sparse receiver spacing of 5–6 km, whereas FWI is assumed to work best with denser (1–2 km) receiver spacing. We show that FWI can be adapted to sparsely sampled data with better resolution than traveltime tomography. Using a 500 km long OBS longitudinal profile from the Japan Trench we obtain a detailed velocity structure of the crust, a better definition of the Moho boundary, a well-defined low-velocity layer in the lower crust and a clear spatial definition of areas with velocity inversions.

Local and quantitative measurement of mechanical properties by electrical-nanoindentation in situ SEM: Application to a multi-phase AgCuPd alloy

Local and quantitative measurement of mechanical properties by electrical-nanoindentation in situ SEM: Application to a multi-phase AgCuPd alloy

Development and Fabrication of Microdosimeter Arrays Based on Single‐Crystal Diamond Schottky Diodes

The interest in microdosimetry is growing thanks to the advancement in microdosimetric technologies, improving detector performance and reliability. Herein, the fabrication and characterization of a novel diamond‐based microdosimeter are proposed. The microdosimeter consists of an array of single‐crystal diamond Schottky diodes about 1.5 μm thick connected in parallel. The detector prototypes are characterized using the ion beam‐induced charge technique, employing a 6 MeV carbon ions microbeam. Despite a good overall response, the first prototypes are affected by the “bridge effect”: a charge collection beneath the metallic bridges connecting the sensitive volumes (SVs), which alters the energy deposition spectrum. To mitigate the bridge effect, different technological solutions are explored: the selective growth of intrinsic diamond layers and the use of an insulating material such as photoresist. These second prototypes reveal a good SV spatial definition without any charge collection from the bridges and a good response homogeneity within the SVs ranging between 3% and 5% full‐width‐half‐maximum among the different prototypes. While the cell‐like thickness and lateral dimensions of SVs make the diamond microdosimeter array ideal for radiobiological applications, its array configuration can make it highly versatile to perform under different fluence rate conditions in particle therapy.

Population Change and Residential Segregation in Italian Small Areas, 2011–2021: An Analysis With New Spatial Units

This article explores spatial patterns of demographic change and residential segregation in Italy over the past decade, a topic which has not been studied in detail in the literature. Population ageing and migration are unfolding rapidly in a number of European countries, generating tensions and challenges at local level. Aggregate regional or national statistics can conceal significant variations at local level, which are of considerable interest and relevance. This is particularly the case in Italy, where spatial heterogeneity and regional disparities are marked. The analysis presented in this paper uses a new source of data derived from large public archives, which permits comparisons to be made at local level with the 2011 census of population. In this way, it is possible to map out and to analyse demographic trends at a fine level of spatial definition. In order to exploit the potential of these data, the authors use a new set of spatial units which were derived by applying automatic rezoning procedures. These output areas are well suited to the study of the age structure of local populations, population change, and migration in a uniform way across the entire national territory, as the empirical results confirm.

Isogeometric topology optimization of structures using the overweight approach

In this paper, a 2D isogeometric formulation of the material distribution for structural topology optimization considering minimum weight and local stress constraints using the overweight approach is proposed. The aim of this isogeometric formulation is to provide solutions with high spatial definition using a lower number of design variables in comparison with the formulations previously developed to define the material layout. Despite of this, an important number of local stress constraints has to be considered in the solution of the problem. For this purpose, an Overweight Constraint is used to consider all of them. The structural analysis is performed by means of the Isogeometric Analysis (IGA) and the distribution of material is modeled by means of quadratic B-splines. Moreover, the optimization is addressed by means of the Sequential Linear Programming algorithm (SLP) that is driven by the information provided by a full first-order sensitivity analysis extension of the IGA formulation. Finally, the proposed formulation is tested by means of some benchmark problems, and the results show that the isogeometric formulation provides solutions with high spatial definition. A comparison with a Finite Element Method (FEM) topology optimization formulation is included.

Intersection movements delay modelling based on crowd-sensed global positioning system trajectory data

Developing accurate large-scale transportation models, used to guide policy adoption and evaluate infrastructure alternatives or changes in sociodemographic conditions, is data and resource intensive. This research proposes a novel method for modeling intersection movement delay using crowd-sensed Global Positioning System (GPS) data. This is achieved by providing a general definition of turning movements and extracting travel times thought GPS trajectory data analysis. Additionally, a straightforward method is proposed to integrate the observed delays per movement type into volume-delay functions. The spatial definition provided for turning movements captured distinct speed profiles per turn type. The significant differences in mean speeds for different turn types highlights the importance of integrating turn penalty functions based on real observations and underscore the importance of crowd-sensed GPS data. A simple technique is also proposed to integrate the proposed method into the volume-delay functions used in large scale transport models.

Wide-field mid-infrared hyperspectral imaging beyond video rate

Mid-infrared hyperspectral imaging has become an indispensable tool to spatially resolve chemical information in a wide variety of samples. However, acquiring three-dimensional data cubes is typically time-consuming due to the limited speed of raster scanning or wavelength tuning, which impedes real-time visualization with high spatial definition across broad spectral bands. Here, we devise and implement a high-speed, wide-field mid-infrared hyperspectral imaging system relying on broadband parametric upconversion of high-brightness supercontinuum illumination at the Fourier plane. The upconverted replica is spectrally decomposed by a rapid acousto-optic tunable filter, which records high-definition monochromatic images at a frame rate of 10 kHz based on a megapixel silicon camera. Consequently, the hyperspectral imager allows us to acquire 100 spectral bands over 2600-4085 cm−1 in 10 ms, corresponding to a refreshing rate of 100 Hz. Moreover, the angular dependence of phase matching in the image upconversion is leveraged to realize snapshot operation with spatial multiplexing for multiple spectral channels, which may further boost the spectral imaging rate. The high acquisition rate, wide-field operation, and broadband spectral coverage could open new possibilities for high-throughput characterization of transient processes in material and life sciences.

Image fusion research based on the Haar-like multi-scale analysis

In view of the serious color and definition distortion in the process of the traditional image fusion, this study proposes a Haar-like multi-scale analysis model, in which Haar wavelet has been modified and used for the medical image fusion to obtain even better results. Firstly, when the improved Haar wavelet basis function is translated, inner product and down-sampled with each band of the original image, the band is decomposed into four sub-images containing one low-frequency subdomain and three high-frequency subdomains. Secondly, the different fusion rules are applied in the low-frequency domain and the high-frequency domains to get the low-frequency sub-image and the high-frequency sub-images in each band. The four new sub-frequency domains are inverse-decomposed to reconstruct each new band. The study configures and synthesizes these new bands to produce a fusion image. Lastly, the two groups of the medical images are used for experimental simulation. The Experimental results are analyzed and compared with those of other fusion methods. It can be found the fusion method proposed in the study obtain the superior effects in the spatial definition and the color depth feature, especially in color criteria such as OP, SpD, CR and SSIM, comparing with the other methods.

Adaptive Laboratory Evolution of Probiotics toward Oxidative Stress Using a Microfluidic-Based Platform.

Adaptive laboratory evolution (ALE) can be used to make bacteria less susceptible to oxidative stress. An alternative to large batch scale ALE cultures is to use microfluidic platforms, which are often more economical and more efficient. Microfluidic ALE platforms have shown promise, but many have suffered from subpar cell passaging mechanisms and poor spatial definition. A new approach is presented using a microfluidic Evolution on a Chip (EVoc) design which progressively drives microbial cells from areas of lower H2O2 concentration to areas of higher concentration. Prolonged exposure, up to 72h, revealed the survival of adaptive strains of Lacticaseibacillus rhamnosus GG, a beneficial probiotic often included in food products. After performing ALE on this microfluidic platform, the bacteria persisted under high H2O2 concentrations in repeated trials. After two progressive exposures, the ability of L. rhamnosus to grow in the presence of H2O2 increased from 1mm H2O2 after a lag time of 31h to 1mm after 21h, 2mm after 28h, and 3mm after 42h. The adaptive strains have different morphology, and gene expression compared to wild type, and genome sequencing revealed a potentially meaningful single nucleotide mutation in the protein omega-amidase.

Dynamic visual noise has limited influence on the habitat selection and behavioural activity of crustaceans and cephalopods

AbstractEnvironments contain various forms of noise that can interfere with the ability of animal sensory systems to perceive information. One ubiquitous type of visual noise in shallow aquatic habitats is caustic flicker (or caustics), consisting of dynamically moving light patterns caused by the refraction of light when passing through the water's rippling surface. While some teleost fish avoid environments with caustic noise (where their prey can be more difficult to detect), it remains untested whether caustics affect the habitat selection of invertebrates. In the present study, we ask whether three invertebrate species, the shore crab Carcinus maenas, the brown shrimp Crangon crangon, and the common cuttlefish Sepia officinalis, prefer or avoid associating with environments with caustic noise, and whether caustics affect their behavioural activity and habitat exploration. To do this, we exposed the three species in binary choice experiments to different simulated caustic noise levels varying in their temporal (speed) and spatial (definition) components. Neither of the three tested invertebrate species spent more or less time in environments with higher caustic noise levels. While we also found no evidence that caustics affected the behavioural activity and exploration of Ca. maenas and S. officinalis, the brown shrimp Cr. crangon reduced its activity with increasing spatial caustic noise. However, all obtained effect sizes in this study were small, suggesting that caustic noise only minimally affects invertebrate behaviour. Overall, our results show that, unlike in teleost fish, caustics have limited influence on the habitat selection, exploration, and activity of crustaceans and cephalopods.

Enhancing paracellular and transcellular permeability using nanotechnological approaches for the treatment of brain and retinal diseases.

Paracellular permeability across epithelial and endothelial cells is, in large part, regulated by apical intercellular junctions also referred to as tight junctions (TJs). These junctions contribute to the spatial definition of different tissue compartments within organisms, separating them from the outside world as well as from inner compartments, with their primary physiological role of maintaining tissue homeostasis. TJs restrict the free, passive diffusion of ions and hydrophilic small molecules through paracellular clefts and are important for appropriate cell polarization and transporter protein localisation, supporting the controlled transcellular diffusion of smaller and larger hydrophilic as well as hydrophobic substances. This traditional diffusion barrier concept of TJs has been challenged lately, owing to a better understanding of the components that are associated with TJs. It is now well-established that mutations in TJ proteins are associated with a range of human diseases and that a change in the membrane fluidity of neighbouring cells can open possibilities for therapeutics to cross intercellular junctions. Nanotechnological approaches, exploiting ultrasound or hyperosmotic agents and permeation enhancers, are the paradigm for achieving enhanced paracellular diffusion. The other widely used transport route of drugs is via transcellular transport, allowing the passage of a variety of pro-drugs and nanoparticle-encapsulated drugs via different mechanisms based on receptors and others. For a long time, there was an expectation that lipidic nanocarriers and polymeric nanostructures could revolutionize the field for the delivery of RNA and protein-based therapeutics across different biological barriers equipped with TJs (e.g., blood-brain barrier (BBB), retina-blood barrier (RBB), corneal TJs, etc.). However, only a limited increase in therapeutic efficiency has been reported for most systems until now. The purpose of this review is to explore the reasons behind the current failures and to examine the emergence of synthetic and cell-derived nanomaterials and nanotechnological approaches as potential game-changers in enhancing drug delivery to target locations both at and across TJs using innovative concepts. Specifically, we will focus on recent advancements in various nanotechnological strategies enabling the bypassing or temporally opening of TJs to the brain and to the retina, and discuss their advantages and limitations.

Spatiotemporal Variograms as Neighborhood Definers

Spatial neighborhood definitions are a consistent source of disagreement among geographic scholars. This research will focus on the implementation and evaluation of spatiotemporal variograms (STVs) as a source of spatial neighborhood definition. STVs show the similarity, measured by semivariance, of spatial events to each other when separated by time and space. Over both time and space, there should exist distances over which pairs of points become “independent” of one another. We seek seeks to answer two questions in relation to STVs and their use as neighborhood definitions: (1) What data and process adjustments are necessary to implement STVs to provide neighborhood search definitions in time and space, and (2) Given that there are many ways to define a neighborhood, STVs may provide a comprehensive method that uses the data themselves to inform the size and scope of neighborhoods, with the added advantage to evaluating both spatial and temporal axes at once. We demonstrate a well‐defined neighborhood that accounts for temporal variation as well as spatial and will be a needed addition as the tools incorporating simultaneous spatial and temporal neighborhoods are implemented.

“It should be treated in a better way” – Perceived topovacancy in the participative urban planning

“It should be treated in a better way” – Perceived topovacancy in the participative urban planning

Online Waypoint Path Refinement for Mobile Robots Using Spatial Definition and Classification Based on Collision Probability

A novel online path refinement method is suggested for mobile robots, which refines the given path including several waypoints using sensor data with low computational load. The method periodically plans a waypoint path from the current robot position to a certain waypoint on the given waypoint path. While the robot moves along the given path, the path is continuously refined to avoid collisions and local minima which can be caused by unmapped obstacles which are not represented on the map but sensed by sensors. Also if a shortcut is detected while the robot is moving, the shortcut replaces the existing waypoint path. This Online Waypoint Path Refinement (OWPR) method is very practical in terms of computation time and memory size, since it is performed regardless of the size of the workspace. To validate the actual performances of OWPR method, various simulations and experiments were conducted. As a result of simulation and experiment, the maximum execution time of the OWPR algorithm was less than 10 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ms</i> , and the generated waypoint path shortened the overall travel distance without collision and falling to the local minima.