Distance In Space Research Articles

Root Characteristics and Its Correlation with Yield of Some Maize (Zea mays L.) Genotypes in Bangladesh

The growth capacity and yield characteristics of crop plants are significantly influenced by their roots. To determine the influence of root characteristics and its correlation with yield of maize genotypes, an experiment was conducted at the experimental field of Department of Crop Botany and Tea Production Technology, Sylhet Agricultural University (SAU), Bangladesh during December 2014 to May 2015. The experimental materials were ZM 0001, ZM 0002, ZM 0003, ZM 0004, ZM 0005, ZM 0006, ZM 0007 and BARI Maize 6. Three replications and a Randomized Complete Block Design (RCBD) were used to set up the experiment. Necessary cultural practices were followed as and when require during the growing period. Data were recorded on number of roots plant-1, root length, root spreading until grain filling stage (90 days after germination) and dry matter accumulation of roots at 30 days interval until harvest. The results indicated that root number of maize genotypes increased from 30 to 90 DAG at a constant rate and in the grain filling stage and it was limited within 32.33 to 42.67. Root length was also increased from 30 to 90 DAG at a constant rate and in the grain filling stage it was limited within 25.33 to 31.1 cm. Root spreading was continued to increase from germination stage to 90 DAG and it was varied from 22 to 27.73 cm. Dry matter accumulation of roots increased gradually from 30 to 60 and 90 DAG up to harvest. In this study, root shoot ratio (RSR) and root weight ratio (RWR) had significant correlation with maize yield. From the root length and root spreading data, it is suggested that moderate tillage and a plant to plant distance spacing of 25-30 cm can be maintained for better yield of maize.

Artificial potential field-empowered dynamic holographic optical tweezers for particle-array assembly and transformation

Owing to the ability to parallel manipulate micro-objects, dynamic holographic optical tweezers (HOTs) are widely used for assembly and patterning of particles or cells. However, for simultaneous control of large-scale targets, potential collisions could lead to defects in the formed patterns. Herein we introduce the artificial potential field (APF) to develop dynamic HOTs that enable collision-avoidance micro-manipulation. By eliminating collision risks among particles, this method can maximize the degree of parallelism in multi-particle transport, and it permits the implementation of the Hungarian algorithm for matching the particles with their target sites in a minimal pathway. In proof-of-concept experiments, we employ APF-empowered dynamic HOTs to achieve direct assembly of a defect-free 8 × 8 array of microbeads, which starts from random initial positions. We further demonstrate successive flexible transformations of a 7 × 7 microbead array, by regulating its tilt angle and inter-particle spacing distances with a minimalist path. We anticipate that the proposed method will become a versatile tool to open up new possibilities for parallel optical micromanipulation tasks in a variety of fields.

Acoustic and Kinematic Predictors of Intelligibility and Articulatory Precision in Parkinson's Disease.

This study investigated relationships within and between perceptual, acoustic, and kinematic measures in speakers with and without dysarthria due to Parkinson's disease (PD) across different clarity conditions. Additionally, the study assessed the predictive capabilities of selected acoustic and kinematic measures for intelligibility and articulatory precision ratings. Forty participants, comprising 22 with PD and 18 controls, read three phrases aloud using conversational, less clear, and more clear speaking conditions. Acoustic measures and their theoretical kinematic parallel measures (i.e., acoustic and kinematic distance and vowel space area [VSA]; second formant frequency [F2] slope and kinematic speed) were obtained from the diphthong /aɪ/ and selected vowels in the sentences. A total of 368 listeners from crowdsourcing provided ratings for intelligibility and articulatory precision. The research questions were examined using correlations and linear mixed-effects models. Intelligibility and articulatory precision ratings were highly correlated across all speakers. Acoustic and kinematic distance, as well as F2 slope and kinematic speed, showed moderately positive correlations. In contrast, acoustic and kinematic VSA exhibited no correlation. Among all measures, acoustic VSA and kinematic distance were robust predictors of both intelligibility and articulatory precision ratings, but they were stronger predictors of articulatory precision. The findings highlight the importance of measurement selection when examining cross-domain relationships. Additionally, they support the use of behavioral modifications aimed at eliciting larger articulatory gestures to improve intelligibility in individuals with dysarthria due to PD. https://doi.org/10.23641/asha.27011281.

Windbreak Effectiveness of Single and Double-Arranged Shelterbelts: A Parametric Study Using Large Eddy Simulation

Shelterbelts provide essential protection against wind erosion and soil degradation, as well as protection for fruit-bearing plants and crops from strong winds. Enhancing their sheltering capabilities requires optimizing their pattern and orientation, as well as defining their height and desired canopy shape, according to the desired performance. In this work, Large Eddy Simulation is employed to investigate the flow field and windbreak effectiveness of single and double-arranged shelterbelts characterized by different geometry and resistance to the air passage for neutral atmospheric condition. In particular, the canopy of the shelterbelts is modeled as an isotropic porous medium immersed in atmospheric boundary layer flow using the Darcy–Forchheimer model. Results show that a shelterbelt with a rectangular-shaped cross-section and a large canopy height results in the most significant reduction in mean wind speed and TKE, thus providing a large wind-protection region. As the spacing distance of double-arranged shelterbelts increases, the protection zones formed by both shelterbelts are reduced. The systematic comparisons of flow patterns, drag force coefficients, and windbreak effectiveness indicators of a series of single and double-arranged shelterbelts are essential for optimizing the design and management of shelterbelts.

Neuronal parts list and wiring diagram for a visual system

A catalogue of neuronal cell types has often been called a ‘parts list’ of the brain1, and regarded as a prerequisite for understanding brain function2,3. In the optic lobe of Drosophila, rules of connectivity between cell types have already proven to be essential for understanding fly vision4,5. Here we analyse the fly connectome to complete the list of cell types intrinsic to the optic lobe, as well as the rules governing their connectivity. Most new cell types contain 10 to 100 cells, and integrate information over medium distances in the visual field. Some existing type families (Tm, Li, and LPi)6–10 at least double in number of types. A new serpentine medulla (Sm) interneuron family contains more types than any other. Three families of cross-neuropil types are revealed. The consistency of types is demonstrated by analysing the distances in high-dimensional feature space, and is further validated by algorithms that select small subsets of discriminative features. We use connectivity to hypothesize about the functional roles of cell types in motion, object and colour vision. Connectivity with ‘boundary types’ that straddle the optic lobe and central brain is also quantified. We showcase the advantages of connectomic cell typing: complete and unbiased sampling, a rich array of features based on connectivity and reduction of the connectome to a substantially simpler wiring diagram of cell types, with immediate relevance for brain function and development.

Agency at a distance: learning causal connections

AbstractIn a series of papers, we have argued that causal cognition has coevolved with the use of various tools. Animals use tools, but only as extensions of their own bodies, while humans use tools that act at a distance in space and time. This means that we must learn new types of causal mappings between causes and effects. The aim of this article is to account for what is required for such learning of causal relations. Following a proposal by Grush and Springle, we argue that learning of inverse mappings from effects to causes is central. Learning such mappings also involves constraints based on monotonicity, continuity and convexity. In order for causal thinking to extend beyond space and time, mental simulations are required that predict the effects of actions. More advanced forms of causal reasoning involve more complicated forms of simulations.

Building Krylov complexity from circuit complexity

Krylov complexity has emerged as a probe of operator growth in a wide range of nonequilibrium quantum dynamics. However, a fundamental issue remains in such studies: the definition of the distance between basis states in Krylov space is ambiguous. Here we show that Krylov complexity can be rigorously established from circuit complexity when dynamical symmetries exist. Whereas circuit complexity characterizes the geodesic distance in a multidimensional operator space, Krylov complexity measures the height of the final operator in a particular direction. The geometric representation of circuit complexity thus unambiguously designates the distance between basis states in Krylov space. This geometric approach also applies to time-dependent Liouvillian superoperators, where a single Krylov complexity is no longer sufficient. Multiple Krylov complexity may be exploited jointly to fully describe operator dynamics. Published by the American Physical Society 2024

The influence of the rotor spacing distance and rotating speed ratio on the power production of dual rotor wind turbines using a modified two-way interaction blade element momentum method

The present study aims to develop an accurate and fast improved blade element method (BEM) with two-way rotor-rotor interaction model which can account for two-way rotor-rotor interaction and the influence of rotor spacing while most previous BEM models for co-axis dual rotor wind turbines (DRWT) ignore the rear to front rotor interaction effect. A modified BEM model distinct from computationally intensive Computation Fluids Dynamics (CFD) model, is proposed for DRWTs. Validation of the present model is conducted by comparing it with experimental data from referenced literature for both co- and counter-rotating configuration. In our case study, for both co- and counter-rotating configurations, the power coefficient (CP) maps exhibit a double-hump shape instead of a single peak on the power output -λ curve observed in a single rotor wind turbine system. This characteristic may lead the DRWT to a local CPmax condition rather than the global CPmax while pursing the optimum operational condition. Although the counter-rotating DRWT can achieve a higher CPmax for most rotor spacing ratio (S/R) cases, it exhibits inferior power output than the single rotor for the S/R = 0.1 case. The present model can serve as a rapid and accurate model for configuring and control strategy evaluating DRWTs.

Performance improvement strategies of boron-doped lithium-rich layered oxide cathode materials for wide temperature condition

Herein, the boron-doped Li-rich materials are prepared by rapid nucleation-assisted solvothermal and high-temperature method. In this work, the effects of boron doping on crystal structure and cycling performances of as-prepared materials were investigated. The material characterization results show that the introduction of B reduces the TM valence, enlarges the (003) space distance, and modulates the local crystal structure, which may change the electrochemical performance of as-prepared samples. Li1.2Ni0.24Co0.08Mn0.48B0.02O2 (LLNCMBO-2) showed an increase in discharge capacity of 36.5 mAh g−1 at 0.1 C compared to the pristine sample. The LLNCMBO-2 exhibit high capacity retention of 85.50 % after 200 cycles with a voltage decay of only 254.9 mV. Additionally, the results of wide temperature testing show that the electrochemical performance of boron-doped samples improved evidently.

Computational Analysis of a Novel Iterative Scheme with an Application

The computational study of fixed-point problems in distance spaces is an active and important research area. The purpose of this paper is to construct a new iterative scheme in the setting of Banach space for approximating solutions of fixed-point problems. We first prove the strong convergence of the scheme for a general class of contractions under some appropriate assumptions on the domain and a parameter involved in our scheme. We then study the qualitative aspects of our scheme, such as the stability and order of convergence for the scheme. Some nonlinear problems are then considered and solved numerically by our new iterative scheme. The numerical simulations and graphical visualizations prove the high accuracy and stability of the new fixed-point scheme. Eventually, we solve a 2D nonlinear Volterra Integral Equation (VIE) via the application of our main outcome. Our results improve many related results in fixed-point iteration theory.

Multi-scale locality preserving projection for partial multi-view incomplete multi-label learning

Amidst advancements in feature extraction techniques, research on multi-view multi-label classifications has attracted widespread interest in recent years. However, real-world scenarios often pose a challenge where the completeness of multiple views and labels cannot be ensured. At present, only a handful of techniques have attempted to address the complex issue of partial multi-view incomplete multi-label classification, and the majority of these approaches overlook the significance of manifold structures between instances. To tackle these challenges, we propose a novel partial multi-view incomplete multi-label learning model, termed MSLPP. Differing from existing studies, MSLPP emphasizes retaining the effective inherent structure of data during the feature extraction process, thereby facilitating a richer semantic information extraction. Specifically, MSLPP captures and integrates four types of information: the distance and similarity information in the original feature space, and the distance and similarity information in the extracted feature space. Further, by adopting the graph embedding technique, it simultaneously preserves the intrinsic structure with multi-scale information through a constraint term. Moreover, taking into account the negative impact of the missing views on the model and the possible impact of missing views on the data inherent structure, we further propose a shielding strategy for missing views, which not only eliminates the negative effects of missing views on the model but also more accurately captures the inherent data structure. The experimental results on five widely recognized datasets indicate that the model performs better than many excellent methods.

Pervasive impacts of railway edge effects on edaphic parameters and vegetation distribution patterns

Addressing the ecological impacts of transport corridors while planning any transport network is paramount for a better of understanding ecological processes, biodiversity distribution, and ecosystem resilience. Here, we evaluated the impacts of railway edges on edaphic parameters, plant diversity, and composition in the northwestern Himalaya as a function of perpendicular distance from the railway track. In 2014 and 2017, we sampled vegetation plots across 31 sites distributed along 119 km of the Kashmir railway to test the effect of railway tracks on edaphic and vegetative parameters in short-term periods. T-shaped plots were laid comprising four sub-plots, one parallel to the track and the other three perpendiculars to it. We adopted the Mountain Invasion Research Network road survey methodology for data collection. We found (i) an increasing trend in all soil parameters (electrical conductivity, salinity, organic carbon, available nitrogen, and available phosphorus), except pH, as the distance from the railway track increased; (ii) significant railway edge effects on the importance value index of plant growth forms, life span, nativity and taxonomic group across space (distance of plots from the track) and time (2014–2017); and (iii) a significant spatiotemporal railway edge effects on plant species composition. Our results are pioneering in showing that railway tracks crossing through different ecosystems alter the edaphic conditions, resulting in direct and indirect edge effects on key abiotic and biotic factors, which in turn impact the vegetation of the surrounding natural habitats on both sides of the railway track. Our study contributes toward a better understanding of the role of anthropogenic edges like railways on edaphic parameters and vegetation distribution.

A novel asymmetric extension of power XLindley distribution: properties, inference and applications to engineering data

It is impossible to overstate the importance of using trigonometric functions appropriately in distribution theory. The main contribution of the research is to construct a flexible trigonometric extension of the power XLindley distribution. More specifically, we build an innovative two-parameter lifetime distribution known as the sine power XLindley distribution (SPXLD) using characteristics from the sine-generated family of distributions. As the main motivational fact, it provides an attractive alternative to the power Lindley, power XLindley, weighted Lindley, and extended power Lindley distributions; it may be better able to model lifetime phenomena presenting data of leptokurtic and platkurtic nature. In contrast to the increasing, decreasing, and reversed-j-shaped hazard rate function, the density exhibits asymmetric shapes with varying peakedness levels. Several significant characteristics are illustrated, including moments, the quantile function, the probability density function in series representation, the stress-strength reliability, and incomplete moments. To analyze the behavior of the suggested distribution, sixteen estimation techniques are applied, such as the maximum likelihood, percentiles, some methods of minimum distances, some methods based on minimum and maximum spacing distances, and the Kolmogorov method. After that, an extensive simulation study and the examination of two survival real datasets are used to show the viability, usefulness, and adaptability of the SPXLD. Relevant goodness of fit criteria demonstrates that the SPXLD fits several current distributions.

The phase space distance between collider events

How can one fully harness the power of physics encoded in relativistic N-body phase space? Topologically, phase space is isomorphic to the product space of a simplex and a hypersphere and can be equipped with explicit coordinates and a Riemannian metric. This natural structure that scaffolds the space on which all collider physics events live opens up new directions for machine learning applications and implementation. Here we present a detailed construction of the phase space manifold and its differential line element, identifying particle ordering prescriptions that ensure that the metric satisfies necessary properties. We apply the phase space metric to several binary classification tasks, including discrimination of high-multiplicity resonance decays or boosted hadronic decays of electroweak bosons from QCD processes, and demonstrate powerful performance on simulated data. Our work demonstrates the many benefits of promoting phase space from merely a background on which calculations take place to being geometrically entwined with a theory’s dynamics.

A novel static mixer for blending hydrogen into natural gas pipelines

A novel static mixer is designed specifically to blend hydrogen into natural gas pipelines, and its effectiveness is validated by numerical simulation method. Firstly, the structural model of the proposed static mixer model for hydrogen-methane blending is introduced, and the evaluation indicators are defined. Secondly, the computational fluid dynamic model for the mixing process is established based on the Large Eddy Simulation(LES) method, and the accuracy of the numerical results is validated against the experimental data of a benchmark gas mixing model. Subsequently, using LES, effects structural parameters (angle and height of trapezoidal baffle, number of mixing elements, and spacing and installation distance of mixing elements) and flow parameters (main flow velocity and hydrogen blending ratio) on the mixing homogeneity and pressure drop of the static mixer are investigated systematically to explore the optimal design and operational conditions. The numerical results showed that the static mixer can significantly improve the mixing efficiency of hydrogen and natural gas with acceptable pressure loss. In the range of flow conditions concerned, a best performance of mixing could be obtained by installing the mixer at a distance of 3D (D is the diameter of the natural gas pipeline) downstream the blending point, setting the spacing between mixing elements as 1D and employing four mixing elements. Finally, the underlying physics of mass transportation are analyzed based on the vortex structures generated by the mixer.

COMPARISON OF FREEWAY SPACE DISTANCE OF WILLIS METHOD WITH DIGITAL PHOTO ANALYSIS METHOD IN BANJAR TRIBE

Background: The face's vertical dimension or vertical height is the distance between two anatomical points, namely the points on the maxilla and mandible. In measuring the vertical dimension, vertical dimensions of rest (DVR) and vertical dimensions of occlusion (DVO) must be measured. The difference between the vertical dimension of rest (DVR) and the vertical dimension of occlusion (DVO) is called the freeway space (FWS) or interocclusal distance. Freeway space is a key requirement for optimal comfort and function of a partial or complete denture. Each individual's freeway space distance is the movement of muscle function, which can be measured by direct methods such as the Willis method using calipers and the digital photo analysis method using computer software. Two measurement methods can be used to measure freeway space distance direct and indirect. Purpose: To analyze the difference between freeway space distance measured by the Willis method and by digital photo analysis of Adobe Photoshop and Corel Draw graphic design software in the Banjar tribe (a review of students at the Faculty of Dentistry, Universitas Lambung Mangkurat Banjarmasin). Methods: This study is a quantitative study with an analytic observational method and a cross-sectional approach. This study was conducted by collecting data simultaneously at one time by comparing three different methods on the same sample without being given any treatment. Results: One Way ANOVA test is 0.296 (P>0.05) which means there is no significant difference. Conclusion: There is no significant difference between the results of measuring freeway space distance using the Willis method with a digital caliper and digital photo analysis with Adobe Photoshop and Corel Draw software.

Woody plant communities in different land management types and implications on mountain biodiversity conservation in central Ethiopia

The prominence of mountains as social-ecological systems and the need for sustainable mountain development have increasingly been recognized in global agendas and international conventions. This study aims to investigate woody plant diversity, composition, and population structure in two different land management types: lands managed by the Wanchi Ecotourism Association (WETA) and non-WETA members at the slopes of Wanchi Mountain. Trees and shrubs with diameter at breast height (DBH) ≥ 5 cm were recorded from 20 m by 20 m plots and those with DBH<5 cm were counted within sub-plots of 10 m by 10 m. Tree seedlings were recorded from five 3 m by 3 m sub-sub-plots. The quasi-Poisson generalized linear model with a log-link function was used to analyze the richness of woody species and their association with environmental variables. Non-metric multidimensional scaling with Bray-Curtis distance in two-dimensional space was employed for the woody species composition. Tree species population structure was analyzed using tree diameter distribution classes. The study identified 104 woody plants belonging to 82 genera and 52 families. Woody species richness in WETA-managed lands is significantly (P=0.009) greater than that of non-WETA-managed lands. The study found that woody species richness significantly declined with increasing anthropogenic disturbance (P<0.001) and slope (P<0.001) in both WETA and non-WETA-managed land. Woody species richness also showed negative associations with aspect. The tree species in both the land management types revealed nearly similar population structures. The study highlighted the importance of sustainable land management practices such as ecotourism in areas of significant natural endowments like that of the Wanchi Mountain. Such practices can guide more sustainable mountain biodiversity conservation while realizing appropriate local livelihood improvement strategies.

Asteroid pairs: Survey of the inner main belt

Context. An asteroid pair forms when an asteroid splits into two unbound fragments because of collision, rotational fission, or binary system decay. The two components of the asteroid pair share similar physical properties and their orbits converge when integrated into the past. Currently, 268 asteroid pairs are known, and new pairs are discovered alongside the continuous discovery of new asteroids. Aims. We conducted a survey in the inner asteroid belt to find new asteroid pairs, estimated their age, and classified their physical properties. As presently no M-type asteroid pairs are known, we also conducted a specialized survey of them. Methods. We preselected asteroid pair candidates based on their distances in the five-dimensional space of osculating orbital elements. We created multiple clones within the uncertainties of their orbital elements and conducted their backtrack integration into the past. We searched for convergence of their clones at close spatial points with small relative velocities, the distribution of which determines the pair formation age. Results. We find 40 new asteroid pairs, thus increasing the total number of known pairs by 15%. One of the newly discovered pairs, 469759 - 2016 QZ 123, with an age of 2.6−0.2+0.7 kyr is now the third-youngest known asteroid pair. We studied the influence of the mutual gravitation of pair components on the process of their evolution and successfully observed the gravitational catching of the two pair members in the past. As a byproduct of pair search, we find eight asteroids connected in a cluster with an age of 76−25+15 kyr that belongs to the Phocaea family and incorporates one previously known asteroid pair. We confirm the convergence of ten asteroid pairs discovered in our previous research and improve their age estimates. We observed a deficiency of M-type asteroid pairs, and therefore conducted a dedicated search for M-type pairs, but found none.

Approximation for probability of coverage in softly inhibitive cellular networks

AbstractThe Strauss point process is a very popular model for describing the random cellular networks, yet several key statistical properties such as intensity, empty space function, and probability generating functional have remained elusive. This article addresses these issues by first leveraging the Poisson saddle point method to approximate the distance‐conditioned intensity for Strauss point processes. Subsequently, the author derives an analytically tractable expression for the distribution of empty space distance based on a conditional thinning mechanism. Additionally, the author establishes an upper bound for the probability generating functional in Strauss point processes, which is crucial for evaluating the Laplace transform of cumulative interference in relevant cellular networks. These findings facilitate the systematic derivation of spatially averaged probability of coverage, and the accuracy of analytic results is validated through simulations.

The Importance and Role of Tyres on Road Vehicles: Their influence on Breaking Distance

It is considered that tyres play the primary role in terms of road safety on dry, wet, snowy or icy roads. This is due to their importance, as they are the element of support, of contact, of the car with the road (the track). This scientific paper presents concrete research carried out by the author with a view to implementing theoretical and practical concepts, in which the technical aspects of tyres fitted to road vehicles are presented. In this way, those interested can find out how tyres and wheel rims are labelled and marked; specific data are presented on summer and winter tyres; the phenomenon of of the aquaplaning of car wheels is defined, presented and explained; the forces and moments acting during braking are presented and defined; the braking distance (space) and the two second rule in road traffic are presented and explained. The paper concludes with a case study presenting the contribution of road car transmissions to braking distance reduction and an original research on braking distance, carried out using the second order active factorial experiment method, in which two cars of different classes (a Lamborghini Huracane Technica and a Dacia Logan), equipped with different tyre categories, were used. Finally, results and conclusions are presented.