Spatial Shape Research Articles

Unravelling the object-based nature of visual working memory: insight from pointers.

Visual working memory (VWM) plays a crucial role in temporarily storing and processing visual information, but the nature of stored representations and their interaction with new inputs has long been unclear. The pointer system refers to how VWM links new sensory inputs to stored information using specific cues. This study aimed to investigate whether the pointer system is based on spatial, feature-based, or object-based cues by employing the repetition benefit effect, where memory performance improves with repeated memory items. Across three experiments, we manipulated spatial positions, shapes, and colors as pointer cues to determine how these features affect VWM consolidation and updating. The results showed that while spatial location serves as a strong pointer cue, shape and color features can also effectively reestablish object correspondence in VWM. These findings support the view that the pointer system in VWM is flexible and object-based, utilizing various feature cues to maintain memory continuity. This study provides new insights into how VWM connects new inputs with stored information through the pointer system.

Varying size and shape of spatial units

When an analysis over a specific geographic area is performed, the way that area is divided into regions can affect the outcome of the analysis. Results obtained based on different geographic units can be conflicting. This issue is known as the Modifiable Areal Unit Problem (MAUP). The objective of this paper is to understand the extent to which the regional setting influences the results of an analysis with spatially aggregated variables, with a focus on agglomeration effects, in the case of Germany. Relying on a sample of manufacturing firms over 7 years we estimate a fixed effects model to explain the firm-specific total factor productivity in dependence of region-based agglomeration variables. We simulate 1000 regional settings of Germany on three scales and overtake thereby some characteristics of the administrative units, which are used as the baseline. We infer that the spatial scale and shape matter in the case of Germany.

Structural damage detection for spatial frame structures with semi-rigid joints using multiple set wireless measurements

Damage detection of a complex spatial frame structure with semi-rigid joints is a challenging task. Most existing damage detection methods consider the joint as rigid and the nonuniform cross section of the member is not considered. This assumption results to a large error in the structural damage identification. A novel generic element is proposed for the nonuniform cross-section member with semi-rigid joints at both ends in this study. The finite element model of spatial structures with semi-rigid joints is established using the proposed element. The modal strain energy-based damage index is defined and its sensitivity to the member and joint damage has been investigated using numerical and experimental study. An 8-m long bridge model with the bolted connection at joints is built in the laboratory. Dynamic responses of the bridge under random excitations are monitored using 13 wireless tri-axis accelerometers. The spatial mode shapes of the bridge are extracted using the reference-based stochastic subspace identification from multiple set wireless measurements. The numerical model is validated using experimental results. Dynamic responses of the bridge with different damage scenarios have been simulated using the validated model and the corresponding damage indices are obtained. The results show that the proposed method is reliable and accurate to analyze dynamic behavior of the spatial structure with semi-rigid joints, and structural damage can be identified accurately using the modal strain energy-based damage index.

Comparison of indicators to evaluate the performance of climate models

AbstractThe evaluation of climate models is a crucial step in climate studies. It consists of quantifying the resemblance of model outputs to reference data to identify models with superior capacity to replicate specific climate variables. Clearly, the choice of the evaluation indicator significantly impacts the results, underscoring the importance of selecting an indicator that properly captures the characteristics of a “good model”. This study examines the behaviour of six indicators, considering spatial correlation, distribution mean, variance and shape. Monthly data for precipitation, temperature and teleconnection patterns in Central America were utilized in the analysis. A new multicomponent measure was selected based on these criteria to assess the performance of 32 CMIP6 models in reproducing the annual seasonal cycle of these variables. The top six models were determined using multicriteria methods. It was found that even the best model reproduces one derived climatic variable poorly in this region. The proposed measure and selection method can contribute to enhancing the accuracy of climatological research based on climate models.

Examining the Effects of Environment, Geography, and Elevation on Patterns of DNA Methylation Across Populations of Two Widespread Bumble Bee Species.

Understanding the myriad avenues through which spatial and environmental factors shape evolution is a major focus in biological research. From a molecular perspective, much work has been focused on genomic sequence variation; however, recently there has been increased interest in how epigenetic variation may be shaped by different variables across the landscape. DNA methylation has been of particular interest given that it is dynamic and can alter gene expression, potentially offering a path for a rapid response to environmental change. We utilized whole genome enzymatic methyl sequencing to evaluate the distribution of CpG methylation across the genome and to analyze patterns of spatial and environmental association in the methylomes of two broadly distributed montane bumble bees (Bombus vancouverensis Cresson and Bombus vosnesenskii Radoszkowski) across elevational gradients in the western US. Methylation patterns in both species are similar at the genomic scale with ∼1% of CpGs being methylated and most methylation being found in exons. At the landscape scale, neither species exhibited strong spatial or population structuring in patterns of methylation, although some weak relationships between methylation and distance or environmental variables were detected. Differential methylation analysis suggests a stronger environment association in B. vancouverensis given the larger number of differentially methylated CpG's compared to B. vosnesenskii. We also observed only a handful of genes with both differentially methylated CpGs and previously detected environmentally associated outlier SNPs. Overall results reveal a weak but present pattern in variation in methylation over the landscape in both species.

Implementasi Augmented Reality untuk Pengenalan Bangun Ruang

Solid Geometry is a part of mathematics learning that has various forms and types. The diversity of spatial shapes has area and volume formulas so that you can know the number of sides and area of each spatial shape. By utilizing Augmented Reality technology to introduce spatial structures, it makes it interesting to study. The aim of this research is to create an AR application for solid geometry in an Android-based 3D model so that it can facilitate learning in a fun way. This AR application was created using Vuforia, Unity and a marker to be able to call up the space that has been created. From this research, it is hoped that the interim results can help the learning and teaching process on spatial building materials. Application research results that can be used for the learning stage.

CosineTR: A dual-branch transformer-based network for semantic line detection

Semantic line is a straight line based representation designed to well capture the spatial layout or structural shape of the scene in an image that is valuable as a high-level visual property. In this paper, we propose an efficient end-to-end trainable semantic line detection model named Complementary semantic line TRansformer (CosineTR), which is designed according to an old proverb “two heads are better than one”. CosineTR adopts a dual-branch framework to detect semantic lines with a coarse to fine strategy. These two branches are built based on well-designed attention modules to capture multi-scale line semantic features locally and globally, and are equipped with heatmap prediction head and parameter regression head respectively to perform semantic line detection from two different perspectives. In addition, we introduce bilateral region attention and Gaussian prior cross-attention modules to reinforce semantic contexts extracted by the two branches, and couple them to form complementary feature representations by leveraging a feature interaction method. Extensive experiments demonstrate that our approach is effective and achieves competitive semantic line detection performance on multiple datasets.

Predicting traffic intensity in the urban area of Madrid: Integrating route network topology into a machine-learning model

In addition to temporal effects, spatial effects must be considered in models of traffic intensity. Temporal effects (temporal autocorrelation) and spatial proximity shape observed traffic intensity, with repetitive patterns of peak and trough hours on weekdays and simultaneous peaks in traffic intensity picked up by traffic sensors along roadways of similar capacity. In this article we explore the ability of a neural network (NN) model to replicate both patterns, with the explicit inclusion of the route network’s characteristics. Combining information on optimal routes between different origins and destinations in the Madrid metropolitan area with the localization of traffic sensors, we estimate the route use intensities that mimic the observed traffic patterns as those that can most accurately reproduce the traffic-intensity values recorded by the sensors throughout the urban area. We conclude that this modeling approach can in fact mimic the distribution of the main origins and destinations of displacements in the metropolitan area of Madrid, reproducing the spatial and temporal patterns observed in traffic intensity. In addition, we conduct an analysis of anomalies to test an eventual application of the proposed method to determine the effects on the traffic system of critical events, such as the implementation of the Madrid Central Low Emission Zone.

How to find optimal quantum states for optical micromanipulation and metrology in complex scattering problems: tutorial

The interaction of quantum light with matter is of great importance to a wide range of scientific disciplines, ranging from optomechanics to high-precision measurements. A central issue we discuss here, is how to make optimal use of both the spatial and the quantum degrees of freedom of light for characterizing and manipulating arbitrary observable parameters in a linear scattering system into which suitably engineered light fields are injected. Here, we discuss a comprehensive framework based on a quantum operator that can be assembled solely from the scattering matrix of a system and its dependence on the corresponding local parameter, making this operator experimentally measurable from the far field using only classical light. From this, the effect of quantum light in the near field, i.e., in the vicinity of the target object, can be inferred. Based on this framework, it is straightforward to formulate optimal protocols on how to jointly design both the spatial shape and the quantum characteristics of light for micromanipulation as well as for parameter estimation in arbitrarily complex media. Also, the forces of the quantum vacuum naturally emerge from this formalism. The aim of our tutorial is to bring different perspectives into alignment and thereby build a bridge between the different communities of wave control, quantum optics, micromanipulation, quantum metrology, and vacuum physics.

MPeat2D – a fully coupled mechanical–ecohydrological model of peatland development in two dimensions

Abstract. Higher-dimensional models of peatland development are required to analyse the influence of spatial heterogeneity and complex feedback mechanisms on peatland behaviour. However, the current models exclude the mechanical process that leads to uncertainties in simulating the spatial variability in the water table position, vegetation composition, and peat physical properties. Here, we propose MPeat2D, a peatland development model in two dimensions, which considers mechanical, ecological, and hydrological processes together with the essential feedback from spatial interactions. MPeat2D employs poroelasticity theory that couples fluid flow and solid deformation to model the influence of peat volume changes on peatland ecology and hydrology. To validate the poroelasticity formulation, the comparisons between numerical and analytical solutions of Mandel's problems for two-dimensional test cases are conducted. The application of MPeat2D is illustrated by simulating peatland growth over 5000 years above a flat and impermeable substrate with free-draining boundaries at the edges, using constant and variable climate. In both climatic scenarios, MPeat2D produces lateral variability in the water table depth, which results in the variation in the vegetation composition. Furthermore, the drop in the water table at the margin increases the compaction effect, leading to a higher value of bulk density and a lower value of active porosity and hydraulic conductivity. These spatial variations obtained from MPeat2D are consistent with the field observations, suggesting plausible outputs from the proposed model. By comparing the results of MPeat2D to a one-dimensional model and a two-dimensional model without the mechanical process, we argue that mechanical–ecohydrological feedbacks are important for analysing spatial heterogeneity, shape, carbon accumulation, and resilience of peatlands.

Liquid microlens compound structure for enhanced sub-micron resolution imaging and accelerated reconfigurable deformation manipulation

The optical observation of sub-micron structures encounters significant challenges due to the inadequate spatial shape matching of optical devices and the limitations imposed by diffraction. These factors result in suboptimal imaging resolution and the introduction of defocus distortion. One approach to mitigating these limitations involves utilizing a liquid microlens (LML) assisted microscope, which offers real-time and localized control capabilities. However, the dynamic tuning of LML is subject to volatility and instability, adversely affecting sub-micron resolution imaging. To address this issue, a contour-following coating inspired by the natural cornea is applied to the droplet's surface, resulting in the formation of liquid microlens compound structures (LMLCS). Firstly, photoresist microholes are fabricated on the optical disc. Then, liquid self-assembly technology is used to fill glycerol in the microholes. At last, a conformal spreading method of UV-curable adhesive precursor film is developed to ensure the combination of the microlens bilayer structure. Through the application of optical information transmission theory, finite difference time domain (FDTD) method, and the principle of Abbe microscopic imaging, the imaging magnification process and sub-micron resolution characteristic of the LMLCS are revealed. Remarkably, the obtained focal width at half maximum (FWHM) of 1.54 μm is smaller than the theoretical value, enabling reconfigurable sub-micron resolution observation and 1.63 times imaging magnification of 226 nm grating lines under the optical microscope. Compared with unencapsulated LML, this compound structure exhibits better sub-micron resolution capability, greater imaging magnification, and faster adaptive dynamic response characteristics. Consequently, the LMLCS introduces exciting prospects for exploring optical sub-micron measurement and sensing devices with exceptional performance.

A novel framework for low-contrast and random multi-scale blade casting defect detection by an adaptive global dynamic detection transformer

The radiographic inspection plays a crucial role in ensuring the casting quality for improving the service life under harsh environments. However, due to the low-contrast between the defects and the image background, the random spatial position distribution, random shapes and aspect ratios of the defects, the development of an accurate defect automatic detection system is still challenging. To address these issues, this paper proposes a novel framework for low-contrast and random multi-scale casting defect detection, which is referred to as adaptive global dynamic detection transformer (AGD-DETR). A novel defect-aware data augmentation method is first proposed to adaptively highlight the feature of the low-contrast defect boundary. A multi-attentional pyramid feature refinement (MPFR) module is then established to refine and fuse the multi-scale defect features of random sizes. Afterwards, a novel global dynamic receptive fusion-transformer (GDRF-Transformer) detection scheme is designed to perform the global perception and feature dynamic extraction of complex internal casting defects. It includes 4D-anchor query and cross-layer box update strategy, query rectification by prior information of defect aspect ratio, and global adaptive-feed forward network (GA-FFN). A dataset comprising turbine blade casting defect radiographic (TBCDR) images, is used to demonstrate the high efficiency of the proposed AGD-DETR. The obtained results show that the proposed method can accurately capture the spatial position distributions and complex defect shapes. Furthermore, it outperforms existing state-of-the-art defect detection methods.

Controlled swelling-induced shape change of soft gel filled structures

Gels are polymers that can imbibe large amounts of solvent and generate large volumetric deformations in a process commonly termed swelling. The swelling-induced deformations can be harnessed to produce pressure against surrounding elastic elements, and therefore lead to spatial shape changes without the need for an external energy source. In the present paper, we consider a thin cylindrical elastic tube that encapsulates a gel and deforms in response to the swelling-induced forces. It is expected that by controlling the spatial stiffness distribution of the tube, the deformed swelling-induced shape can be programmed. We exploit this simple idea to obtain controlled shape change driven by the large volumetric expansion of gels. To this end, we train a machine learning algorithm through many FE simulations that enable solving the inverse problem: for any prescribed swelling-induced target shape, the algorithm provides the spatial stiffness distribution of the thin tube. The results confirm that precise controlled shape change is achievable by exploiting the large swelling-induced volumetric deformations in an autonomous manner (i.e. without the need for any external energy source). This work paves the way for new perspectives in the design of shape-change systems based on the simple yet proper elastic distribution of confining structures.

Ethnomathematics Study: Geometrical Concept in Kudus Market Snacks

Most students consider mathematics difficult, because it is abstract. To respond to this, teachers can use ethnomathematics in learning mathematics so that mathematics is easy to understand. One of the ethnomathematics objects that can be used is market snacks. Market snacks are traditional foods that are often sold in crowded places such as markets. This study aims to analyze the geometrical concepts that exist in various forms of market snacks in Kudus. This research uses a type of qualitative research with an ethnographic approach. Data collection used semi-structural interviews with 3 market snack sellers, literature studies, and documentation. The results of the study found that there are geometric concepts in market snacks. Triangular, rectangular, and circular shapes are found, while for spatial shapes, rectangular pyramids, blocks, spheres, triangular prisms, and tubes are found. The research results can be used as an alternative source of learning mathematics, especially in geometry material.

Care and order in urban spaces: social workers and security guards

ABSTRACT Outreach work has been praised for its inclusionary potential and problematised for reproducing exclusion mechanisms. This study investigates these dynamics by exploring how spatial dimensions shape outreach work. Its point of departure is social workers employed in NGO-based initiatives in Norway. Focusing on the spatial context includes social workers’ relation to other actors who use and produce these urban spaces. In this case, the concern for and interaction with security guards is central to the social workers’ everyday work. While organised around different functions, both actors can be considered central in responding to marginalisation issues. Concerns in the literature on both outreach work and security guards’ policing include ways in which these care and order practices are engaged in mechanisms of social control and repression. The findings show how the two actors relate to each other, oppose and reproduce spatial ruling in complex ways. While their practices are shaped by spatial relations of power, dynamics of spatial in/exclusion are also constituted by embodied experiences of encounters with people subject to processes of marginalisation. As opposed to research focusing on social arrangements, this study contributes to understanding ways in which spatial dimensions of outreach work is significant.

DIVERSED ETHNOMATHEMATICS EXPLORATIONS OF BATAK CULTURES IN NORTH SUMATERA

The Batak ethnic group has cultural diversity and is rich in the values of each culture, both in the products and processes, and cultural philosophies. The Batak ethnicity is divided into several sub-ethnicities, including Toba Batak, Karo Batak, Mandailing Batak, and Simalungun Batak. The distinctive characteristics of each ethnicity can be used as material for research by researchers to explore the elements of that culture. In the field of mathematics, culture can also be used as an object of study. The research method used in the present study is the systematic literature review (SLR) which is aimed at identifying, studying, evaluating, and interpreting research results by the topics being studied so that it will answer the research questions that have been determined. The results can be seen that the Batak ethnic cultural components have mathematical concepts in them such as, among others, livelihood characters, traditional houses, traditional musical instruments, traditional foods, ulos cloth and ornaments. traditional dances, and traditional clothing. The mathematical concepts that are obtained from the exploration of Batak ethnic cultures include the concepts of lines, angles, congruence, spatial geometry, flat geometric shapes, spatial geometric shapes, geometric transformations, arithmetic sequences, and numbers. These diverse themes indicate that mathematics is our culture.

Mimicking nature to develop halide perovskite semiconductors from proteins and metal carbonates

Halide perovskite (HPs) nanostructures have recently gained extensive worldwide attentions because of their remarkable optoelectronic properties and fast developments. However, intrinsic instability against environmental factors—i.e., temperature, humidity, illumination, and oxygen—restricted their real-life applications. HPs are typically synthesized as colloids by employing organic solvents and ligands. Consequently, the precise control and tuning of complex 3D perovskite morphologies are challenging and have hardly been achieved by conventional fabrication methods. Here, we combine the benefits of self-assembly of biomolecules and an ion exchange reaction (IER) approach to customize HPs spatial shapes and composition. Initially, we apply a biomineralization approach, using biological templates (such as biopolymers, proteins, or protein assemblies), modulating the morphology of MCO3 (M = Ca2+, Ba2+) nano/microstructures. We then show that the morphology of the materials can be maintained throughout an IER process to form surface HPs with a wide variety of morphologies. The fabricated core–shell structures of metal carbonates and HPs introduce nano/microcomposites that can be sculpted into a wide diversity of 3D architectures suitable for various potential applications such as sensors, detectors, catalysis, etc. As a prototype, we fabricate disposable humidity sensors with an 11–95% detection range by casting the formed bio-templated nano/micro-composites on paper substrate.

Eksplorasi Etnomatematika pada Permainan Tradisional Congklak di Kelurahan Srengseng Sawah

Ethnomathematics contributes greatly to the improvement of mathematics learning, because it relates to students' experiences in everyday life that touches the realm of local cultural arts so that students become more understanding of the mathematical concepts explained. This study aims to explore the concept of mathematics in the traditional game of congklak in Srengseng Sawah Village. This research is a qualitative research with an ethnographic approach. The data collection techniques used are observation, interview and documentation. The instruments in this study were researchers, observation guidelines, interview guidelines and documentation. Based on the research analysis and discussion of the history and philosophy of the traditional game of congklak, mathematical concepts in the game of congklak such as the concept of flat shapes, namely semicircles, circles, rectangles and spatial shapes, namely half a ball; the concept of transformation in this case reflection / mirroring; the concept of arithmetic calculation operations including addition, subtraction, multiplication and division. The game also has cultural and philosophical values.

Exploration of morphological coherence in open clusters with a “core-shell” structure

Context. The morphology of open clusters plays a major role in the study of their dynamic evolution. The study of their morphological coherence, namely, the three-dimensional (3D) difference between the inner and outer morphologies of open clusters, allows us to obtain a better understanding of the morphological evolution of open clusters. Aims. We aim to investigate the morphological coherence of 132 open clusters with up to 1 kpc from the Sun in the three-dimensional (3D) space within the heliocentric cartesian coordinate frame. The 132 open clusters have a 3D core-shell structure and conform to the ellipsoidal model, with all of them coming from a catalog of publicly available clusters in the literature. Methods. We employed the ellipsoid fitting method to delineate the 3D spatial structure of the sample clusters, while using the morphological dislocation (MD) defined in our previous work and the ellipticity ratio (ER) of the clusters’ inner and outer structures to characterize the morphological coherence of the sample clusters. Results. The results show an inverse correlation between the ER of the sample clusters and the number of their members, indicating that sample clusters with a much more elliptical external morphology than internal shape generally tend to host a large number of members. Meanwhile, a slight shrinking of the MD of the sample clusters with their members’ number may shed light on the significant role of the gravitational binding of the sample clusters in maintaining their morphological stability. Moreover, there are no correlations between the MD and ER of the sample clusters and their age. They are also not significantly correlated with the X-axis, the Y-axis, their orbital eccentricities, and the radial and vertical forces on them. However, the ER of the sample clusters displays some fluctuations in the distributions between it and the above covariates, implying that the morphologies of the sample clusters are sensitive to the external environment if sample effects are not taken into account. Finally, the analysis of the 3D spatial shapes of sample clusters with a small ER or a large ER demonstrates that the number of members lays an important foundation for forming a dense internal system for sample clusters. At the same time, the MD of the sample clusters can serve well as an indicator of their morphological stability, which is built upon a certain amount of member stars. Conclusions. We present a new insight into the morphological coherence of open clusters, attributed to the combination of their gravitational binding capacity and external environmental perturbations.

Optimization study of pruning strategy based on KNN trajectory similarity query

With the development of GPS positioning technology, a large amount of spatiotemporal trajectory data has been generated. Due to the complex structure of trajectory data, which has irregular spatial shapes and continuous temporal sequence attributes, querying massive trajectory data poses certain challenges. The pruning strategy of existing trajectory similarity query methods is not very effective. Even after pruning operations, there are still a large number of trajectories that need to undergo distance calculations to confirm whether they are similar trajectories. This paper proposes multiple local pruning optimization schemes, which maximally reduce the number of trajectories in the candidate set. Specifically, it starts with region pruning in the index space, eliminating index spaces with distances greater than the maximum similarity distance from the query trajectory. Then, it performs distance pruning between trajectories, removing trajectories that do not meet the distance conditions. Finally, it adds a termination condition: when the distance between the current index space and the query trajectory is greater than the maximum similarity distance and the number of trajectories in the result set is K, the loop is exited, and the query process ends. Tests on real datasets demonstrate that the KTSS method outperforms current algorithms of the same type.