Distance In Space Research Articles

Influence of Flexor Pronator Muscle Contraction on Medial Elbow Joint Space Distance in High School Baseball Players: A Cross-Sectional Study.

The contraction of the flexor pronator muscles (FPMs) plays an important role in stabilizing the elbow joint in baseball players. However, the influence of different types of contractions on the medial joint space (MJS) in high school baseball players is not well understood. This study aimed to elucidate the effects of individual or combined contractions of the FPMs, specifically the flexor carpi ulnaris (FCU), flexor digitorum superficialis (FDS), pronator teres (PT), palmaris longus, and flexor carpi radialis, on the MJS in high school baseball players. We hypothesized that contractions, particularly of the FDS, PT, and FCR, would lead to a narrowing of the MJS. The study included 36 high school baseball players who executed nine different contraction tasks related to the FPMs (including a resting state) in a randomized order. The MJS was measured using ultrasound equipment and compared with the resting state. The Friedman test, as a repeated-measures one-way ANOVA, was performed, followed by Steel's test for multiple comparisons. All analyses were conducted using EZR software, with a significance level set at 5%. The repeated-measures one-way ANOVA and the Friedman test revealed a significant difference among the nine contraction tasks (p < 0.001). Using Steel's test, a significant reduction in the MJS (mean ± SD) was observed compared with the resting state (4.8 ± 1.2 mm), particularly in contraction tasks involving the PT (4.0 ± 1.0 mm, p = 0.017), FDS and PT (4.0 ± 1.1 mm, p = 0.007), and FCU, FDS, and PT (4.0 ± 1.1 mm, p = 0.008). Incorporating the PT into contraction tasks significantly reduced the MJS, emphasizing the important role of the PT in elbow joint stability. More work is required to see if the results of this study can be used to develop injury prevention and rehabilitation strategies.

Examination Of The Relationship Between Body Mass Index And The Skin-Epidural Space Distance Measured By Ultrasound In The Lumbar Region

The aim of the study; to investigate whether there is a relationship between body mass index (BMI), waist circumference, and abdominal subcutaneous adipose tissue and the skin-epidural space distance measured by ultrasonography.

A heterotic Kähler gravity and the distance conjecture

Deformations of the heterotic superpotential give rise to a topological holomorphic theory with similarities to both Kodaira-Spencer gravity and holomorphic Chern-Simons theory. Although the action is cubic, it is only quadratic in the complex structure deformations (the Beltrami differential). Treated separately, for large fluxes, or alternatively at large distances in the background complex structure moduli space, these fields can be integrated out to obtain a new field theory in the remaining fields, which describe the complexified hermitian and gauge degrees of freedom. We investigate properties of this new holomorphic theory, and in particular connections to the swampland distance conjecture in the context of heterotic string theory. In the process, we define a new type of symplectic cohomology theory, where the background complex structure Beltrami differential plays the role of the symplectic form.

Drill Pattern Optimisation for Large Complex Blasts to Improve Fragmentation and Dig Efficiency

Abstract At large-scale open-pit metallic mines, drill-and-blast designs can reach over 1,000 drill holes per blast. A critical input to the design of a blast is the location of sensitive zones where ground vibration, air overpressure or flyrock needs to be constrained. The other critical input is the hardness profile of the ground. Often, the hardness across such large blasts varies significantly from soft to extra hard. Traditional approaches for pattern design use constant distance (burden and spacing) between the production drill holes and vary the explosive product strength and amount in each hole to account for variation in hardness and to adhere to blast constraints. Although this approach is operationally easier to execute, it is challenging to meet fragmentation and diggability objectives. To better address these objectives, this work provides a nonlinear mathematical model for optimising drill hole locations in conjunction with explosive amounts. The model optimises the design using a three-stage methodology. In the first stage, a novel heuristic method is used to perform local optimisation to determine the number of holes. In the second stage, the precise hole locations are determined, and in the third stage the energy intensity in each hole is optimised. In a study of 10 blasts from a Pilbara iron ore mine, for the dig efficiency objective, results indicate that variable designs achieve $$\sim $$ ∼ 2% better dig efficiency, with $$\sim $$ ∼ 11% fewer holes. For the fragmentation objective, variable designs achieve $$\sim $$ ∼ 9% better adherence to the target mean particle size, with $$\sim $$ ∼ 5% less standard deviation and $$\sim $$ ∼ 13% fewer holes.

An efficient heuristic for geometric analysis of cell deformations.

Sickle cell disease causes erythrocytes to become sickle-shaped, affecting their movement in the bloodstream and reducing oxygen delivery. It has a high global prevalence and places a significant burden on healthcare systems, especially in resource-limited regions. Automated classification of sickle cells in blood images is crucial, allowing the specialist to reduce the effort required and avoid errors when quantifying the deformed cells and assessing the severity of a crisis. Recent studies have proposed various erythrocyte representation and classification methods (Jennifer et al., 2023 [1]). Since classification depends solely on cell shape, a suitable approach models erythrocytes as closed planar curves in shape space (Epifanio et al., 2020). This approach employs elastic distances between shapes, which are invariant under rotations, translations, scaling, and reparameterizations, ensuring consistent distance measurements regardless of the curves' position, starting point, or traversal speed. While previous methods exploiting shape space distances had achieved high accuracy, we refined the model by considering the geometric characteristics of healthy and sickled erythrocytes. Our method proposes (1) to employ a fixed parameterization based on the major axis of each cell to compute distances and (2) to align each cell with two templates using this parameterization before computing distances. Aligning shapes to templates before distance computation, a concept successfully applied in areas such as molecular dynamics (Richmond et al., 2004 [2]), and using a fixed parameterization, instead of minimizing distances across all possible parameterizations, simplifies calculations. This strategy achieves 96.03% accuracy rate in both supervised classification and unsupervised clustering. Our method ensures efficient erythrocyte classification, maintaining or improving accuracy over shape space models while significantly reducing computational costs.

Low-Complexity 2D DOA Estimation via L-Shaped Array for Underwater Hexapod Robot

This paper takes underwater hexapod robot target grasping in an extremely shallow water environment as the research goal and carries out the research on a high-precision and low-complexity method of target positioning. We address the above problem of estimating the two-dimensional (2D) directions of arrival (DOAs) of targets, using an L-shaped ultrasonic array. Based on the above considerations, low-complexity 2D multiple signal classification (MUSIC) based on sparse signal recovery (SSR) is proposed to enhance the super-resolution capability and DOA estimation accuracy. In the first step, subspace dimension is determined based on space distance. Then, a mixed-norm method is exploited to construct the projection subspace and new noise subspace. Finally, the orthogonality between the noise and signal subspaces is used to estimate DOAs. Via a numerical simulations analysis, we illustrate that the proposed technique can enhance the accuracy of DOA estimation while also being robust against coherent sources and limited snapshots.

MDTR: a knowledge-guided interpretable representation for quantifying liver toxicity at transcriptomic level

IntroductionDrug-induced liver injury (DILI) has been investigated at the patient level. Analysis of gene perturbation at the cellular level can help better characterize biological mechanisms of hepatotoxicity. Despite accumulating drug-induced transcriptome data such as LINCS, analyzing such transcriptome data upon drug treatment is a challenging task because the perturbation of expression is dose and time dependent. In addition, the mechanisms of drug toxicity are known only as literature information, not in a computable form.MethodsTo address these challenges, we propose a Multi-Dimensional Transcriptomic Ruler (MDTR) that quantifies the degree of DILI at the transcriptome level. To translate transcriptome data to toxicity-related mechanisms, MDTR incorporates KEGG pathways as representatives of mechanisms, mapping transcriptome data to biological pathways and subsequently aggregating them for each of the five hepatotoxicity mechanisms. Given that a single mechanism involves multiple pathways, MDTR measures pathway-level perturbation by constructing a radial basis kernel-based toxicity space and measuring the Mahalanobis distance in the transcriptomic kernel space. Representing each mechanism as a dimension, MDTR is visualized in a radar chart, enabling an effective visual presentation of hepatotoxicity at transcriptomic level.Results and DiscussionIn experiments with the LINCS dataset, we show that MDTR outperforms existing methods for measuring the distance of transcriptome data when describing for dose-dependent drug perturbations. In addition, MDTR shows interpretability at the level of DILI mechanisms in terms of the distance, i.e., in a metric space. Furthermore, we provided a user-friendly and freely accessible website (http://biohealth.snu.ac.kr/software/MDTR), enabling users to easily measure DILI in drug-induced transcriptome data.

A High-Speed Rail-Facilitated Evolution of the City-Network Structure in Less-Developed Regions: Evidence from Jiangxi Province, China

The role of high-speed rail (HSR) in facilitating the spatial restructuring of regional and urban networks has long interested scholars and policymakers. This study explored HSR-facilitated city-network evolution in less-developed regions through the example of Jiangxi Province, China. Applying social network analysis methods, the study calculated indicators of network association strength, density, centrality, and cohesive subgroups using HSR passenger flow data from Jiangxi’s counties and cities for the years of 2009, 2014, 2019, and 2024. The quadratic assignment procedure (QAP) method was utilized to measure the factors that influence of HSR passenger flow network in Jiangxi Province. Research on the spatial network structure of HSR passenger flow and its influencing factors to promote the sustainable development of less-developed regions via HSR construction was explored. The main findings are as follows: Jiangxi’s city-network structure experienced a substantial increase from 2009 to 2024 in network properties, including the degree of association, network density, and the centrality of cities. The structure of the subgroups remained relatively stable, with a few exceptions. Cities in different subgroups form close and strong connections with each other resulting from HSR. HSR has effectively shortened the time and space distances and enhanced the spatial links between cities. Five factors, including population size, geographic distance, spatial proximity, economic development, and administrative hierarchy, demonstrated significant impacts on the HSR passenger flow network in Jiangxi Province. As HSR services continue to expand throughout the less-developed regions, optimizing HSR’s network effects should focus on strengthening the driving role of central HSR cities, promoting cross-regional coordination, and integrating HSR fully with other transportation modes.

Measuring Distances in High Dimensional Spaces Why Average Group Vector Comparisons Exhibit Bias, And What to Do about it

Abstract Analysts often seek to compare representations in high-dimensional space, e.g., embedding vectors of the same word across groups. We show that the distance measures calculated in such cases can exhibit considerable statistical bias, that stems from uncertainty in the estimation of the elements of those vectors. This problem applies to Euclidean distance, cosine similarity, and other similar measures. After illustrating the severity of this problem for text-as-data applications, we provide and validate a bias correction for the squared Euclidean distance. This same correction also substantially reduces bias in ordinary Euclidean distance and cosine similarity estimates, but corrections for these measures are not quite unbiased and are (non-intuitively) bimodal when distances are close to zero. The estimators require obtaining the variance of the latent positions. We (will) implement the estimator in free software, and we offer recommendations for related work.

An Optimization Design of Energy Consumption for Aluminum Smelting Based on a Multi-Objective Artificial Vulture Algorithm

In the process of regenerative aluminum smelting, the temperature of the furnace needs to be maintained between 700 and 850 by adjusting the setting parameters of the smelting furnace. The setting parameters are usually adjusted by manual work, and inaccuracies in manual operation can lead to wasted energy as well as unstable temperatures. Energy consumption and temperature stability are two conflicting objectives, which are difficult to find optimal parameters for the aluminum smelting process. In this paper, an improved multi-objective artificial vulture algorithm (IMOAVOA) is developed to solve a multi-objective problem of energy consumption and temperature deviations in the regenerative aluminum smelting process. The dynamic switching–elimination mechanism based on crowding distance is proposed to maintain the archive, which enhances the diversity of solutions by dynamically switching the operation space for deleting redundant solutions in the archive and dynamically deleting the solution with the smallest crowding distance in the operation space. The multi-directional leader selection mechanism is developed to select better leaders. To improve the convergence of the algorithm, the bounce strategy is introduced in the IMOAVOA. The effectiveness of the proposed algorithm is verified by UF1-UF10, kursawe, Viennet2, Viennet3, ZDT1-ZDT6, DTLZ4, and DTLZ6 test functions with several multi-objective algorithms. The experimental results indicate that IMOAVOA outperforms the original algorithm and three other multi-objective algorithms in terms of the algorithm convergence, the Pareto front coverage, and the solution diversity. Finally, the proposed algorithm is tested in an application case of regenerative aluminum smelting process. The results show that the optimal parameters for the aluminum smelting process using the proposed algorithm can reduce the consumption while meeting the objective of furnace temperature.

Continuous goal representations: Distance in representational space affects goal switching.

Theorists across all fields of psychology consider goals crucial for human action control. Still, the question of how precisely goals are represented in the cognitive system is rarely addressed. Here, we explore the idea that goals are represented as distributed patterns of activation that coexist within continuous mental spaces. In doing so, we discuss and extend popular models of cognitive control and goal-directed behavior, which implicitly convey an image of goals as discrete representational units. To differentiate empirically between discrete and continuous formats of goal representation, we employed a set-shifting paradigm in which participants switched between color goals that varied systematically in their distance in representational space. Across three experiments, we found that previous goals biased behavior during goal switches and that the extent of this bias decreased gradually with the previous goal's distance in color space from color information in the current trial. These graded effects of goal distance on performance are difficult to reconcile with the assumption that goals are discrete representational entities. Instead, they suggest that goals are represented as distributed, partly overlapping patterns of activation within continuous mental spaces. Moreover, the monotonous effects of distance in representational space on performance observed across all conditions in all experiments imply that the spreading of goal activation in representational space follows a monotonous (e.g., bell-shaped) distribution and not a nonmonotonous (e.g., Mexican-hat shaped) one. Our findings ask for a stronger consideration of the continuity of goal representations in models and investigations of goal-directed behavior.

The Complexity of Human Space: Multi-layered Networks and the Relativity of Distance

Abstract This article characterizes the human space as reflecting the architecture of interdependencies within it, which may generate alternative identifications of external boundaries and internal divisions. After introducing how human actors and activities are arranged according to relative positions belonging to different dimensions and leading to multi-layered networks, the article illustrates the multi-dimensionality and multi-layeredness of the human space by considering the production space as a network of interdependencies in which division of labour and the mutual fitting of activities take place along plural dimensions (here identified with tasks and productive functions, capacities, and materials-in-process) and give rise to hierarchical patterns of interdependence along each dimension. The article shows that it is possible to visualize relative positions in different ways depending on the actors’ or the analyst’s point of view, which may draw attention to a particular dimension of interdependence rather than others. Such open-endedness leads to the relativity of distance. At the same time, the actors’ (or the analyst’s) point of view, by fixing the focus of attention on specific dimensions and layers, may lead to closure, in the sense that relative distances become associated with the dimension and layer of interdependence that are central to a given context. The article goes on to propose a theoretical framework to study distance and proximity in the human space, and applies it to the problem of how to identify possible definitions of collective interest in a space of interdependent actors.

Changes in interpersonal distance modulate social attention engagement: Evidence from EEG alpha band suppression.

Interpersonal space is regulated carefully and updated dynamically during social interactions to maintain comfort. We investigated the naturalistic processing of interpersonal distance in real time and space using a powerful implicit neurophysiological measure of attentional engagement. In a sample of 37 young adults recruited at a UK university, we found greater EEG alpha band suppression when a person occupies or moves into near personal space than for a person occupying or moving into public space. In the dynamic condition only, the differences attenuated over the course of the experiment, and were sensitive to individual differences in social anxiety. These data show, for the first time, neurophysiological correlates of interpersonal distance coding in a naturalistic setting. Critically, while veridical distance is important for attentional response to the presence of a person in one's space, the behavioural relevance of their movement through public and personal space takes primacy.

Exploring Order–Disorder Transitions Using a Two-State Master Equation

In this study, we explore the order–disorder transition in the dynamics of a straightforward master equation that describes the evolution of a probability distribution between two states, p1 and p2 (with p1+p2=1). We focus on (1) the behavior of entropy S, (2) the distance D from the uniform distribution (p1=p2=1/2), and (3) the free energy F. To facilitate understanding, we introduce two price-ratios: ηS=dS/dtdF/dt and ηD=dD/dtdF/dt. They respectively define the energetic costs of modifying (1) S and (2) D. Our findings indicate that both energy costs diverge to plus and minus infinity as the system approaches the uniform distribution, marking a critical transition point where the master equation temporarily loses its physical meaning. Following this divergence, the system stabilizes itself into a new well-behaved regime, reaching finite values that signify a new steady state. This two-regime behavior showcases the intricate dynamics of simple probabilistic systems and offers valuable insights into the relationships between entropy, distance in probability space, and free energy within the framework of statistical mechanics, making it a useful case study that highlights the underlying principles of the system’s evolution and equilibrium. Our discussion revolves about the order–disorder contrast that is important in various scientific disciplines, including physics, chemistry, and material science, and even in broader contexts like philosophy and social sciences.

Predictive Model for Deformation of Adjacent Pipelines Caused by Tunnel Boring in Twin-Lane Tunnels in Soft Ground Layers

To create a discretized prediction model for the deformation of an adjacent pipeline, the pipeline structure is discretized, the differential equations governing the longitudinal deformation of the pipeline are inferred, and the displacement expressions and the solution methods of the virtual nodes of each unit are provided after discretization. This approach is based on the Pasternak foundation beam theory. It aims to address the issue of the difficulty in predicting the deformation of the adjacent pipeline caused by shield tunneling in a saturated soft ground layer in the Yangtze River Delta. The deformation pattern of the surrounding soil is determined and confirmed through additional numerical simulation, and the discretized prediction model is contrasted with the conventional Winkler foundation beam model and the Pasternak foundation beam model. The findings demonstrate that the discrete prediction model is simpler to solve and more accurately describes the deformation characteristics of the adjacent pipeline as well as the deformation distribution law. The calculated deformation characteristics primarily appear as the adjacent pipeline’s deformation due to the double tunnel boring exhibiting a “mono-peak shape” with a large middle and small ends, which is consistent with the actual situation. The two main factors influencing the pipeline deformation are the shield tunneling distance and pipeline spacing; the former has a negative correlation with the pipeline deformation, while the latter has a positive correlation. This work can offer a straightforward deformation prediction technique for shield tunneling in the Yangtze River Delta’s saturated soft ground next to existing pipelines.

Niche comparisons reveal significant divergence despite narrow endemism in Leavenworthia, a genus of rare plants.

Quantifying niche similarity among closely related species offers myriad insights into evolutionary history and ecology. In this study, our aim was to explore the interplay of geographic and niche space for rare, endemic plant species and determine if endemic habitats were environmentally similar or unique. We characterized the niche of all Leavenworthia species, a genus of rare plants endemic to rocky glades in the eastern United States, using WorldClim data, surface geology, elevation, and slope. We calculated the area of range overlap and estimated niche similarity between species in their total occupied niche space and the subset of niche space shared by both species. We used Linear Discriminant Analyses to determine which niche dimensions differed the most between species. We used niche dimensions with consistently high discriminatory power to perform a Random Forest classification analysis and Principal Component Analysis. Using a linear model, we related geographic distance to distance in niche space. Most species comparisons concluded that species' niches had diverged, with niche similarity increasing linearly with range overlap. Temperature variation, precipitation amount and seasonality, and surface geology were the most divergent niche dimensions among all species comparisons. Geographic distance explained 42% of the variation in niche space distance. Sites that were closer in niche space than expected were oriented east-west due to the strong correlation between latitude and PC1 scores. Despite being endemic to seemingly very similar habitat, niche similarity is low among Leavenworthia species. Low niche similarity, combined with low geographic overlap suggests that this lineage of rare plants potentially diversified in isolation but across a very small geographic area. The correlation between geographic space and niche space has received considerable attention, but our results suggest that geographic distance is a weak predictor of distance in niche space.

Structural performance enhancement of concrete beams with steel overlapped splices using nanoparticles

This paper presents research program towards cleaner building industry; through producing nano-enabled concrete, namely Carbon Nano Tubes (CNTs) Concrete (CNT-CRETE). Structural beam specimens are cast; hence, a series of three-point loading flexure tests is conducted to evaluate and compare the behavior of five groups of standard-size regular reinforced (RC) beams, compared with those using CNT-CRETE. Two previously recommended percentages of CNT are used (0.02% and 0.04% of cement weight). Three possible splice shapes are tested: direct contact splices, and two possible non-contact splices (spacing distances of 1.5 and 3.5 splice bar diameters). The splices with direct contact splices lead to the highest flexural load capacity. On the other hand, non-contact lap splices result in a more flexible section. CNT-CRETE beams exhibited considerable improvement in overall performance. Hence, using CNT-CRETE can lead to future reductions in splice lengths previously recommended by different codes for regular concrete. This will be an innovative addition to different codes. This step requires intensive future studies to cover different CNT types and configurations.

Stratified distance space improves the efficiency of sequential samplers for approximate Bayesian computation

Stratified distance space improves the efficiency of sequential samplers for approximate Bayesian computation

Study on the Effect of Multi-Row Pile Geometric Parameters on the Effective Isolation Zone

Ground vibration negatively affects both residents’ health and the operation of sensitive equipment, particularly in areas adjacent to transport infrastructure. Currently, multiple-row piles are commonly employed for vibration isolation; however, there is limited research on their vibration isolation zone (VIZ). This paper conducted field tests to examine the relationship between the geometric configuration of piles, such as pile length, spacing, row distance, arrangement, and number, and the VIZ. Using two-dimensional contours of the amplitude reduction ratio ( Ar), this paper defines the effective vibration isolation zone (EVIZ) as an area where Ar ≤0.45. The findings indicate that the EVIZ increases with longer pile lengths and more rows, but decreases with wider pile spacing and greater row distances. Moreover, diamond layouts are found to be more effective than rectangular layouts in expanding the EVIZ. Recommendations include maintaining a pile length to Rayleigh wavelength ratio between 0.58 and 0.87, and ensuring pile spacing and row distances are less than 0.12 and 0.11 times the Rayleigh wavelength. This research offers valuable insights for designing multiple-row pile systems.

On measuring distances in the quantum gravity landscape

In this note, we propose a generalized notion of distance between vacua in the theory of a scalar field ϕ with scalar potential V (ϕ) coupled to gravity. We propose the normalized tension of domain wall connecting different field values, with a varying normalization relative to a local energy scale, as the distance. We show this definition reproduces the usual moduli space distance for zero potential, as well as the d ∝ |log Λ| behavior with the vacuum energy Λ in the AdS case, previously proposed in the literature. In the case of large AdS we also obtain the expected exponent of mass versus distance in one particular case, when the mass of the light tower is m ~ Λ and there is a single extra dimension decompactifying. We also discuss the features and shortcomings of alternative but related proposals.