Spatial Limitations Research Articles

Advancements in Nanomaterial Dispersion and Stability and Thermophysical Properties of Nano-Enhanced Phase Change Materials for Biomedical Applications.

Phase change materials (PCMs) are materials that exhibit thermal response characteristics, allowing them to be utilized in the biological field for precise and controllable temperature regulation. Due to considerations of biosafety and the spatial limitations within human tissue, the amount of PCMs used in medical applications is relatively small. Therefore, researchers often augment PCMs with various materials to enhance their performance and increase their practical value. The dispersion of nanoparticles to modify the thermophysical properties of PCMs has emerged as a mature concept. This paper aims to elucidate the role of nanomaterials in addressing deficiencies and enhancing the performance of PCMs. Specifically, it discusses the dispersion methods and stabilization mechanisms of nanoparticles within PCMs, as well as their effects on thermophysical properties such as thermal conductivity, latent heat, and specific heat capacity. Furthermore, it explores how various nano-additives contribute to improved thermal conductivity and the mechanisms underlying enhanced latent heat and specific heat. Additionally, the potential applications of PCMs in biomedical fields are proposed. Finally, this paper provides a comprehensive analysis and offers suggestions for future research to maximize the utilization of nanomaterials in enhancing the thermophysical properties of PCMs for biomedical applications.

Enzyme induced polymer degradation as a pathway to create microbial habitats for biomanufacturing intensification

Polymer hydrogels are instrumental in cell immobilization for biomanufacturing, yet traditional hydrogel bioreactors often compromise cell viability, function, and mass transfer. This results in uncontrolled microbial proliferation and significant cell leakage, thereby impeding the continuous production of high-value products. To address these challenges, we introduce an innovative liquid microcavity technique employing a blend of Gelatin-methacryloyl (Gel-MA) and Pluronic F127diacrylate (F127-DA) for precision bioprinting, followed by selective enzymatic digestion of gelatin to create microbial habitats. Through tailoring of the hydrogel’s pore structure and integration of diverse networks, our approach facilitates controlled nutrient transfer, efficient waste removal, and stable mechanical support, all while maintaining a leak-free suspension culture of microorganisms. We validated the effectiveness of our method by fabricating yeast-infused Three-dimensional (3D) lattice constructs, successfully achieving continuous fermentation of glucose into ethanol in a flow reactor with minimal efficiency reduction (≥90 % yield) over five cycles. This research not only confronts the spatial limitations inherent in hydrogel-based systems but also demonstrates a foundational potential for revolutionary change in biomanufacturing practices.

Corporeal and Spatial Engagements in Emma Donoghue’s 'Room'

Garnered critical acclaim after its publication in 2010, Emma Donoghue’s renowned novel Room delves into the lives of a woman and her son who are held captive in a confined space for several years. The room where they are imprisoned functions as a coded space in which Ma and Jack are subjected to the disciplinary power of Old Nick. The restrictive space that offers no opportunities and living there according to Old Nick’s oppressive regulations lay the basis for analysing the characters’ experiences in the work using Foucault’s viewpoints. In this respect, the exercise of Foucauldian strategies by Old Nick causes them to lose their autonomy and to damage their self. The restrictive heterotopia and the disciplinary gaze turn them into docile bodies that become mere platforms to be dominated. Even after their breaking free, the traces of the spatial limitation follow them psychologically because transitioning to different spaces further challenges their sense of identity and self-integrity. Jack struggles to adapt to the outside world, which showcases the antinomy of the private and public. In this respect, the room leaves a lasting impact on their bodies, stigmatizing them and becoming a source of trauma that needs to be addressed for their new life. The interplay between the spatial codes of the room and their bodies is complex, with each representing and transforming the other. Therefore, this study examines the complex dynamics between physical and spatial interactions that lead to traumatic consequences through the lens of Foucault’s thoughts, by revealing and examining the dimensions of the challenging conditions that trauma victims experience in order to step into the healing process.

The development of extremely large male genitalia under spatial limitation.

Extensive research in evolutionary biology has focused on the exaggeration of sexual traits; however, the developmental basis of exaggerated sexual traits has only been determined in a few cases. The evolution of exaggerated sexual traits may involve the relaxation of constraints or developmental processes mitigating constraints. Ground beetles in the subgenus Ohomopterus (genus Carabus) have species-specific genitalia that show coevolutionary divergence between the sexes. Here, we examined the morphogenesis of the remarkably enlarged male and female genitalia of Carabus uenoi by X-ray microcomputed tomography. The morphogenetic processes generating the male and female genitalia at the pupal stage were qualitatively similar to those in closely related species with standard genital sizes. Higher growth rates contributed to the exaggeration of both the male and female genital parts of C. uenoi, possibly related to a gene network commonly upregulated in both sexes. Additionally, the length of the copulatory piece (CP), the enlarged male genital part stored in the aedeagus (AD), reached close to that of the AD at the later developmental stages and thereafter decelerated to grow in parallel with the AD, suggesting a structural constraint on the CP by the outer AD. Then, unlike related species, the lengths of the CP and AD increased at eclosion, suggesting a mechanism leading to further elongation of the male genitalia. These observations suggest that a developmental process allows continuous growth of the male genitalia even under the spatial limitation. These results revealed the spatio-temporal dynamics of the development of exaggerated genital structures under structural constraints.

Single-fed Ku/Ka dual-band aperture shared planar antenna array for satellite communication

This paper presents a single-fed Ku/Ka dual-band aperture-shared planar antenna array designed for satellite communication. The need to enhance data transmission speeds has driven the exploration of higher frequency bands, such as the Ku-band and Ka-band. Researchers have been investigating the design of multiband antennas to achieve space miniaturization and cost-effectiveness in these higher frequency bands. However, previous works faced challenges, including spatial efficiency limitations, complex radiator structures, band isolation issues, and increased complexity in the feeding network. To address the abovementioned challenges, this paper proposes a single-fed Ku/Ka dual-band shared-aperture planar antenna array. By combining a patch antenna for the Ku-band and a cavity antenna for the Ka-band, a simple and single-fed network is realized. The proposed antenna element is further extended to a linear array antenna and a sequentially rotated array antenna. The implemented sequentially rotated array antenna exhibited a measured impedance bandwidth of 17.4–19.7 GHz (12.4%) and 27.0–29.0 GHz (7.1%). Moreover, the proposed sequentially rotated array antenna demonstrated measured peak gains of 13.7 dBi for right-hand circular polarization in the Ku-band receiver and a measured peak gain of 15.6 dBi for left-hand circular polarization in the Ka-band transmitter, making it highly suitable for satellite communication.

Data Clustering Utilization Technologies Using Medians of Current Values for Improving Arc Sensing in Unstructured Environments.

In the shipbuilding industry, welding automation using welding robots often relies on arc-sensing techniques due to spatial limitations. However, the reliability of the feedback current value, core sensing data, is reduced when welding target workpieces have significant curvature or gaps between curved workpieces due to the control of short-circuit transition, leading to seam tracking failure and subsequent damage to the workpieces. To address these problems, this study proposes a new algorithm, MBSC (median-based spatial clustering), based on the DBSCAN (density-based spatial clustering of applications with noise) clustering algorithm. By performing clustering based on the median value of data in each weaving area and considering the characteristics of the feedback current data, the proposed technique utilizes detected outliers to enhance seam tracking accuracy and responsiveness in unstructured and challenging welding environments. The effectiveness of the proposed technique was verified through actual welding experiments in a yard environment.

Mathematical formulations for the multi-period alternative fuel refueling station location problem with routing under decision-dependent flow dynamics

The refueling station location problem with routing considers vehicles’ ranges and drivers’ preferences about their routes to improve the alternative fuel station infrastructure. Comprehensive planning is necessary for developing a mature infrastructure to overcome budgetary constraints and spatial limitations. Hence, adopting a multi-period planning approach becomes crucial when taking into account the evolving demand for alternative fuel vehicles over time. The evolution of demand can be dependent on exogenous and endogenous factors. Although it is typical to account for exogenous demand growth in multi-period planning, a few studies also take into account an endogenous factor which is the refueling opportunity of drivers on their paths. In this study, in addition to the refueling opportunities, we consider the proximity of each individual station to the flow-based demands. We draw attention to the significance of considering the effects of individual station locations on demand evolution, as these strategic locations can play an important role in reducing the drivers’ range anxiety and increasing their acceptance of the technology. Hence, we introduce a multi-period alternative fuel refueling station location problem with routing under different vehicle flow evolution dynamics that employ various weights for the factors where the natural growth rate is exogenous and the decisions of station locations and flow coverage are endogenous to the problem. We propose three mixed integer linear programming formulations for different evolution dynamics. We carry out computational experiments on the real road networks of Belgium, California, and Turkey and present our findings on the performances of the proposed mathematical models and the gains that can be obtained by considering multi-period planning and incorporating the effects of decisions into the vehicle flow evolution.

Exploring the Complexity of Mauli: An Analysis of Solidarity, Speech Community, Religion, and Gender in Marathi Address Term Usage

This paper delves into the intricate semantic nuances and sociopragmatic functions inherent in the Marathi address term “mauli” in the context of a colossal religious gathering. Through morphosyntactic analysis, it uncovers the term’s grammatical gender and its generic usage to encompass feminine and motherly attributes, embracing inclusiveness and generosity. Drawing from primary data collected during the Asadhi pilgrimage of 2023 through semi-structured interviews and participant observations, supplemented by secondary sources such as albums and songs, the study quantitatively and qualitatively examines the frequency and contextual use of “mauli”. Findings reveal its multifaceted sociopragmatic functions, including identity establishment, solidarity marking, politeness expression, and religiosity demonstration. However, its efficacy is constrained by temporal and spatial limitations, potentially hindering broader societal benefits. This exploration sheds light on the complex interplay between linguistic expressions, social dynamics, and religious practices within the Marathi cultural milieu.

DeepWaterFraction: A globally applicable, self-training deep learning approach for percent surface water area estimation from Landsat mission imagery

Surface water area estimation is essential for understanding global environmental dynamics, yet it presents significant challenges, particularly when dealing with small water bodies like ponds and narrow width rivers. Surface water areas for these small bodies are often inaccurately represented by existing methods due to the spatial resolution limitations in commonly used remote sensing images. This study introduces DeepWaterFraction (DWF), a deep learning approach, to estimate percent surface water area from Landsat mission imagery. DWF is trained with a self-training method, which creates training data by upscaling remote sensing images and water map labels to a lower resolution, enabling the creation of a large-scale, global coverage training dataset. DWF demonstrates superior accuracy in estimating areas for small water bodies compared to several existing methods for surface water area estimation, with a pixel-wise root mean squared error of 14.3 %. Specifically, it reduces error rates by 54.3 % for water bodies with a minimum area of 0.001 km2 and by 22.6 % for those with a minimum area of 0.01 km2. DWF’s application in global river discharge inversion is also explored, showcasing its capability to capture width variations in narrow rivers (<90 m) better than existing methods, and its robustness across environments including wetland, tree covers, and urban areas. Even for wider rivers (>150 m), DWF’s performance remains superior, as its ability to accurately quantify mixed water pixel areas effectively reflects discharge variations when the variation area is small. We find that self-training is an effective strategy for generating extensive global training datasets for water mapping, with a high upscaling factor being critical for ensuring label accuracy. This study presents a step forward in the accurate global mapping of water resources.

Influence of strong directional sources in ambient seismic imaging using traffic-induced noise

Continuously moving seismic sources, such as vehicles and train cars, play a crucial role as passive sources for nondestructive exploration in urban areas. Seismic interferometry is commonly used in field data acquisition and processing using linear arrays. However, the simultaneous recording of high-energy noise, excited by buildings and factories, cannot be overlooked. We simulate moving-source seismic records with strong noises using orthogonal arrays. When strong noise originates from specific angles, the energy-phase velocity curves of arrays in different directions significantly diverge. We determine that an L-shaped array, formed by orthogonal arrays, can effectively mitigate this effect, yielding more consistent results. Nonetheless, spatial constraints often preclude the deployment of L-shaped arrays. To mitigate this issue, we develop a new parallel observation system. Field tests conducted on a main road validate that the new array is comparable with the L-shaped array in terms of dispersion extraction. Similar to synthetic data, the phase velocity extracted from the linear array field data is found to be unreliable. Drilling data align well with the inversion results of the parallel observation system. Given the challenges of urban traffic-induced signal acquisition, deploying multiazimuth arrays to minimize noise impact is essential. Considering the spatial limitations, the convenient parallel observation system emerges as a good choice.

Gel-assisted mass spectrometry imaging enables sub-micrometer spatial lipidomics

A technique capable of label-free detection, mass spectrometry imaging (MSI) is a powerful tool for spatial investigation of native biomolecules in intact specimens. However, MSI has often been precluded from single-cell applications due to the spatial resolution limit set forth by the physical and instrumental constraints of the method. By taking advantage of the reversible interaction between the analytes and a superabsorbent hydrogel, we have developed a sample preparation and imaging workflow named Gel-Assisted Mass Spectrometry Imaging (GAMSI) to overcome the spatial resolution limits of modern mass spectrometers. With GAMSI, we show that the spatial resolution of MALDI-MSI can be enhanced ~3-6-fold to the sub-micrometer level without changing the existing mass spectrometry hardware or analysis pipeline. This approach will vastly enhance the accessibility of MSI-based spatial analysis at the cellular scale.

A SIR epidemic model on a refining spatial grid II-central limit theorem

A SIR epidemic model on a refining spatial grid II-central limit theorem

Computational Fluid Dynamics Simulation of High-Resolution Spatial Distribution of Sensible Heat Fluxes in Building-Congested Area

Urban areas consist of various land cover types, with a high proportion of artificial surfaces among them. This leads to unfavorable thermal environments in urban areas. Continuous research on the thermal environment, specifically on the sensible heat flux (Qh), has been conducted. However, previous research has faced temporal, spatial, and resolution limitations when it comes to detailed analysis of sensible heat flux in urban areas. Therefore, in this study, a computational fluid dynamics (CFD) model combined with the LDAPS and the VUCM was developed to simulate Qh at one-hour intervals over a 1-month period in an urban area with various land cover types. Model validation was performed by comparing it with measurements, confirming the suitability of the model for simulating Qh. The land cover was categorized into five types: building, road, bare land, grassland, and tree areas. Qh exhibited distinct patterns depending on the land cover type. When averaging the Qh distribution over the target period, buildings, roads, and bare land areas showed a predominance of upward Qh values, while grassland and tree areas displayed dominant downward Qh values. Additionally, even within the same land cover types, slight Qh variations were identified based on their surroundings. The averaged Qh value for building areas was the highest at 36.79 W m−2, while that for tree areas was −3.04 W m−2. Moreover, during the target period, the time-averaged Qh showed that building, road, and bare land areas peaked at 14 LST, while grassland and tree areas exhibited very low Qh values. Notably, buildings reached a maximum Qh of 103.30 W m−2 but dropped to a minimum of 1.14 W m−2 at 5 LST.

Diversity of Popular Expressions in Arab Maghreb Drawings

The current research addresses the study of the diversity of popular expressions in the drawings of the Arab Maghreb which can be employed in formative formulations that are consistent with the concepts of modernity in art, as the heritage expressions was associated with the authentic civilizational concepts and with the myths and folkloric stories that have an active presence in the memory of the Arab consciousness. The current research included four sections, the first contained the theoretical framework of the research. It identified the research problem which was summarized in the following question: What is the diversity in the popular expressions in the Arab Maghreb? In addition to its inclusion of the importance of the research and the need for it, and the research objective represented by (identifying the popular expressions in the Arab Maghreb), and it also included the research limits, including the objective that was determined by studying the representations of popular expressions in drawings of the Arab Maghreb executed with acrylic, watercolor and oil paints within the time limits confined between (1955_2018) and the spatial limits in the countries of the Arab Maghreb (Morocco, Tunisia and Algeria), reaching the definition of the terms mentioned in the research. The study analyzed a sample of 4 models from the works of artists from each of the countries of the Arab. Th results showed that the Moroccan artist sought to enrich his artistic experience with subjects related to the local and folkloric richness in the diversity of popular expressions, as in all the sample models of the research. The research concluded with proposals, in which it was suggested to conduct a comparative study between popular symbols in the countries of the Maghreb and the Arab Gulf countries.

Exploring the Fundamental Spatial Limits of Magnetic All-Optical Switching.

All-optical switching (AOS) results in ultrafast and deterministic magnetization reversal upon single laser pulse excitation, potentially supporting faster and more energy-efficient data storage. To explore the fundamental limits of achievable bit densities in AOS, we have used soft X-ray transient grating spectroscopy to study the ultrafast magnetic response of a GdFe alloy after a spatially structured excitation with a periodicity of 17 nm. The ultrafast spatial evolution of the magnetization in combination with atomistic spin dynamics and microscopic temperature model calculations allows us to derive a detailed phase diagram of AOS as a function of both the absorbed energy density and the nanoscale excitation period. Our results suggest that the minimum size for AOS in GdFe alloys, induced by a nanoscale periodic excitation, is around 25 nm and that this limit is governed by ultrafast lateral electron diffusion and by the threshold for optical damage.

Examining the intersection of carceral space and well‐being: Correctional officers' perspectives on old and new prison design

AbstractIn the current study, we explored the prison design and infrastructural changes that Canadian correctional officers consider to be essential in the construction of a new provincial correctional institution intended to replace Her Majesty's Penitentiary (HMP) in the Canadian province of Newfoundland and Labrador. Analyzing 28 semi‐structured interviews conducted with correctional officers employed at HMP, we found the poor working conditions within HMP are, at least in part, related to the physical design of the prison, including inadequate lighting, poor air quality and temperature, high sound levels, and other spatial limitations. Building on the prison design literature, findings suggest that while prison design requires attention to physical security at the forefront, there are ways to improve the space, recognizing how an uncomfortable workplace and living conditions also pose a potential threat to the well‐being and safety of correctional officers and people who are incarcerated.

Monitoring Volcanic Plumes and Clouds Using Remote Sensing: A Systematic Review

Volcanic clouds pose significant threats to air traffic, human health, and economic activity, making early detection and monitoring crucial. Accurate determination of eruptive source parameters is crucial for forecasting and implementing preventive measures. This review article aims to identify the most common remote sensing methods for monitoring volcanic clouds. To achieve this, we conducted a systematic literature review of scientific articles indexed in the Web of Science database published between 2010 and 2022, using multiple query strings across all fields. The articles were reviewed based on research topics, remote sensing methods, practical applications, case studies, and outcomes using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Our study found that satellite-based remote sensing approaches are the most cost-efficient and accessible, allowing for the monitoring of volcanic clouds at various spatial scales. Brightness temperature difference is the most commonly used method for detecting volcanic clouds at a specified temperature threshold. Approaches that apply machine learning techniques help overcome the limitations of traditional methods. Despite the constraints imposed by spatial and temporal resolution and optical limitations of sensors, multiplatform approaches can overcome these limitations and improve accuracy. This study explores various techniques for monitoring volcanic clouds, identifies research gaps, and lays the foundation for future research.

The Sultan Mehmed the Conqueror Museum: The museumization of a cultural asset for an Ottoman conqueror

AbstractConversion to a museum is a common destiny of many cultural assets that cannot continue to serve their original functions. They are usually re‐functioned to provide public benefits in return for the expenditures made for their preservation. However, their architectural features may not always meet the expected results when functioning as a museum. The spatial limitations arising in such conversions are the main design gaps in the museumization projects. This article aims to address these gaps using a sample project of a museum on Sultan Mehmed the Conqueror converted from a medieval education structure.

Novel Learning of Bathymetry from Landsat 9 Imagery Using Machine Learning, Feature Extraction and Meta-Heuristic Optimization in a Shallow Turbid Lagoon

Bathymetry data is indispensable for a variety of aquatic field studies and benthic resource inventories. Determining water depth can be accomplished through an echo sounding system or remote estimation utilizing space-borne and air-borne data across diverse environments, such as lakes, rivers, seas, or lagoons. Despite being a common option for bathymetry mapping, the use of satellite imagery faces challenges due to the complex inherent optical properties of water bodies (e.g., turbid water), satellite spatial resolution limitations, and constraints in the performance of retrieval models. This study focuses on advancing the remote sensing based method by harnessing the non-linear learning capabilities of the machine learning (ML) model, employing advanced feature selection through a meta-heuristic algorithm, and using image extraction techniques (i.e., band ratio, gray scale morphological operation, and morphological multi-scale decomposition). Herein, we validate the predictive capabilities of six ML models: Random Forest (RF), Support Vector Machine (SVM), CatBoost (CB), Extreme Gradient Boost (XGB), Light Gradient Boosting Machine (LGBM), and KTBoost (KTB) models, both with and without the application of meta-heuristic optimization (i.e., Dragon Fly, Particle Swarm Optimization, and Grey Wolf Optimization), to accurately ascertain water depth. This is achieved using a diverse input dataset derived from multi-spectral Landsat 9 imagery captured on a cloud-free day (19 September 2023) in a shallow, turbid lagoon. Our findings indicate the superior performance of LGBM coupled with Particle Swamp Optimization (R2 = 0.908, RMSE = 0.31 m), affirming the consistency and reliability of the feature extraction and selection-based framework, while offering novel insights into the expansion of bathymetric mapping in complex aquatic environments.

An atomistic survey of shear coupling in asymmetric tilt grain boundaries and interpretation using the disconnections framework

Grain Boundaries (GB) play an important role in determining the behavior of polycrystalline materials. While the mechanisms of motion and associated shear response for symmetric tilt grain boundaries (STGBs) are well studied, the same is not true for asymmetric tilt grain boundaries (ATGBs) despite their greater prevalence in polycrystals. This study aims to investigate the shear response of a large collection of asymmetric tilt grain boundaries (ATGBs) using molecular dynamics (MD) simulations and interpret the data using a discrete disconnections model that works remarkably well for STGBs. MD simulations of shear-driven ATGBs show that the plastic shear (shear coupling factor) in the region swept by a GB exhibits a complex dependence on the inclination angle, and this dependence changes with the misorientation of the GB. In addition, the shear response was observed to be highly sensitive to the applied shear rate and temperature. Recognizing the spatial and temporal scale limitations of MD simulations, we extended the discrete disconnections mesoscale model of Khater et al. (2012) to calculate the nucleation barriers of disconnection modes and predict the effective shear coupling of an ATGB. We observed that the mesoscale model’s predictions of the shear coupling factor of ATGBs do not agree with those observed in MD simulations. Finally, we examine the hypotheses of our mesoscale model that contribute to disagreements between MD simulations and the mesoscale model and propose improvements to the mesoscale model for future work.