Fundamental Objects Research Articles

The Remedial Values of Adaptive Ball Types for Children with Autism Spectrum Disorders

Previous studies in the area of motor impairments in children with autism spectrum disorders (ASDs) have warranted an urgent need to review interventions that support fundamental movement skills (FMS). This paper intends to investigate the effectiveness of adaptive ball types used within Physical Education (PE) on the object control proficiency (a subgroup of FMS), in children with ASDs. Following pilot work, 12 children (aged 14.70 ± 2.70) performed four object control tasks (throwing, catching, kicking and soccer style dribbling), using three different ball types (the Developmental Ball, an underweight ball and a control ball). A repeated measures ANOVA was run to statically analyse performance scores. The ANOVA indicated that the type of ball used (f(2,22) 22.798, p<0.001), activity undertaken (f(3,33)= 12.377, p<0.01) and the interaction between the two (f(6,66)=-70.163, p<0.01) ultimately, had a significant effect on motor proficiency. Moreover, the Developmental Ball proved to be consistently beneficial across the object control skills, with post hoc t-tests showing strong significance against the underweight ball in kicking (t(11)=-3,031, p<0. 033) and soccer style dribbling (t(11)=-8.603, p<0.016). This paper concludes Skogstad’s creation to be an invaluable blueprint for the development of fundamental object control skills, in children with ASDs.

Two-loop five-point integrals: light, heavy and large-spin correlators

We evaluated all two-loop conformal integrals appearing in five-point correlation functions of protected operators of N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} = 4 Super Yang-Mills in several kinematical regimes. Starting from the correlation function of the lightest operators of the theory, we were able to extract structure constants of up to two spinning operators for small and large values of spin and the tensor structure label (polarization). We conjectured an universal all-loop behaviour for the large-spin, small-polarization structure constants and comment on the subtleties of analytically continuing it from finite to large spin. We also consider correlation functions of heavier operators that get factorized in the more fundamental object called decagon. We fixed this object at two loops in general kinematics and studied its physical properties under OPE and null limits.

Characterising transformations between quantum objects, 'completeness' of quantum properties, and transformations without a fixed causal order

Many fundamental and key objects in quantum mechanics are linear mappings between particular affine/linear spaces. This structure includes basic quantum elements such as states, measurements, channels, instruments, non-signalling channels and channels with memory, and also higher-order operations such as superchannels, quantum combs, n-time processes, testers, and process matrices which may not respect a definite causal order. Deducing and characterising their structural properties in terms of linear and semidefinite constraints is not only of foundational relevance, but plays an important role in enabling the numerical optimisation over sets of quantum objects and allowing simpler connections between different concepts and objects. Here, we provide a general framework to deduce these properties in a direct and easy to use way. While primarily guided by practical quantum mechanical considerations, we also extend our analysis to mappings between general linear/affine spaces and derive their properties, opening the possibility for analysing sets which are not explicitly forbidden by quantum theory, but are still not much explored. Together, these results yield versatile and readily applicable tools for all tasks that require the characterisation of linear transformations, in quantum mechanics and beyond. As an application of our methods, we discuss how the existence of indefinite causality naturally emerges in higher-order quantum transformations and provide a simple strategy for the characterisation of mappings that have to preserve properties in a 'complete' sense, i.e., when acting non-trivially only on parts of an input space.

Intuitional Content or Avoiding the Myth of the Given – A Dilemma for McDowell

ABSTRACT McDowell’s “Avoiding the Myth of the Given” (2008, 2009) attempts to reconcile two claims: 1) what we most fundamentally experience is a fundamental level of invariable simple objects and their sensible properties; experience of these objects and properties is the ultimate ground of our knowledge of the world; 2) experience is through-and-through conceptually structured. This leads McDowell to endorsing the incoherent notion of intuitional content – necessary and thus irrevisable basic empirical conceptually structured contents or empirical categories. The notion requires the necessity and irrevisability of purely formal concepts and the on-going responsiveness to experience of empirical concepts. This reveals a dilemma: If the fundamental objects of experience are invariable then they cannot have empirically conceptual form; for revisability is a mark of the empirically conceptual. But purely formal concepts cannot give us the fundamental empirical structure of the world. The dilemma forces us to choose between claiming that the fundamental objects of experience are invariable and claiming that they are conceptually formed. I conclude by briefly describing how Kant successfully faces the challenge of accounting for the most fundamental invariable level of objects of experience without yielding to the myth of the given.

PhysiCell Studio: a graphical tool to make agent-based modeling more accessible.

Defining a multicellular model can be challenging. There may be hundreds of parameters that specify the attributes and behaviors of objects. In the best case, the model will be defined using some format specification - a markup language - that will provide easy model sharing (and a minimal step toward reproducibility). PhysiCell is an open-source, physics-based multicellular simulation framework with an active and growing user community. It uses XML to define a model and, traditionally, users needed to manually edit the XML to modify the model. PhysiCell Studio is a tool to make this task easier. It provides a GUI that allows editing the XML model definition, including the creation and deletion of fundamental objects: cell types and substrates in the microenvironment. It also lets users build their model by defining initial conditions and biological rules, run simulations, and view results interactively. PhysiCell Studio has evolved over multiple workshops and academic courses in recent years, which has led to many improvements. There is both a desktop and cloud version. Its design and development has benefited from an active undergraduate and graduate research program. Like PhysiCell, the Studio is open-source software and contributions from the community are encouraged.

Hierarchy of curvatures in exceptional geometry

Despite remarkable success in describing supergravity reductions and backgrounds, generalized geometry and exceptional field theory are still lacking a fundamental object of differential geometry, the Riemann tensor. We show that to construct it, a hierarchy of connections is required. They complement the spin connection with higher representations known from the tensor hierarchy. This approach allows to define generalized homogeneous spaces which underlie generalized U-duality, admit consistent truncations and provide a huge class of new flux backgrounds with nontrivial structure groups. Published by the American Physical Society 2024

Fast, parallel, and cache-friendly suffix array construction

PurposeString indexes such as the suffix array (sa) and the closely related longest common prefix (lcp) array are fundamental objects in bioinformatics and have a wide variety of applications. Despite their importance in practice, few scalable parallel algorithms for constructing these are known, and the existing algorithms can be highly non-trivial to implement and parallelize.MethodsIn this paper we present caps-sa, a simple and scalable parallel algorithm for constructing these string indexes inspired by samplesort and utilizing an LCP-informed mergesort. Due to its design, caps-sa has excellent memory-locality and thus incurs fewer cache misses and achieves strong performance on modern multicore systems with deep cache hierarchies.ResultsWe show that despite its simple design, caps-sa outperforms existing state-of-the-art parallel sa and lcp-array construction algorithms on modern hardware. Finally, motivated by applications in modern aligners where the query strings have bounded lengths, we introduce the notion of a bounded-context sa and show that caps-sa can easily be extended to exploit this structure to obtain further speedups. We make our code publicly available at https://github.com/jamshed/CaPS-SA.

Feynman Diagrams beyond Physics: From Biology to Economy

Feynman diagrams represent one of the most powerful and fascinating tools developed in theoretical physics in the last century. Introduced within the framework of quantum electrodynamics as a suitable method for computing the amplitude of a physical process, they rapidly became a fundamental mathematical object in quantum field theory. However, their abstract nature seems to suggest a wider usage, which actually exceeds the physical context. Indeed, as mathematical objects, they could simply be considered graphs that depict not only physical quantities but also biological or economic entities. We survey the analytical and algebraic properties of such diagrams to understand their utility in several areas of science, eventually providing some examples of recent applications.

Two-fold degeneracy of a class of rational Painlev\'e V solutions

We present a construction of a class of rational solutions of the Painlev\'e V equation that exhibit a two-fold degeneracy, meaning that there exist two distinct solutions that share identical parameters. The fundamental object of our study is the orbit of translation operators of $A^{(1)}_{3}$ affine Weyl group acting on the underlying seed solution that only allows action of some symmetry operations. By linking points on this orbit to rational solutions, we establish conditions for such degeneracy to occur after involving in the construction additional B\"acklund transformations that are inexpressible as translation operators. This approach enables us to derive explicit expressions for these degenerate solutions. An advantage of this formalism is that it easily allows generalization to higher Painlev\'e systems associated with dressing chains of even period $N>4$.

Solving Particle–Antiparticle and Cosmological Constant Problems

We solve the particle-antiparticle and cosmological constant problems proceeding from quantum theory, which postulates that: various states of the system under consideration are elements of a Hilbert space H with a positive definite metric; each physical quantity is defined by a self-adjoint operator in H; symmetry at the quantum level is defined by a representation of a real Lie algebra A in H such that the representation operator of any basis element of A is self-adjoint. These conditions guarantee the probabilistic interpretation of quantum theory. We explain that in the approaches to solving these problems that are described in the literature, not all of these conditions have been met. We argue that fundamental objects in particle theory are not elementary particles and antiparticles but objects described by irreducible representations (IRs) of the de Sitter (dS) algebra. One might ask why, then, experimental data give the impression that particles and antiparticles are fundamental and there are conserved additive quantum numbers (electric charge, baryon quantum number and others). The reason is that, at the present stage of the universe, the contraction parameter R from the dS to the Poincare algebra is very large and, in the formal limit R→∞, one IR of the dS algebra splits into two IRs of the Poincare algebra corresponding to a particle and its antiparticle with the same masses. The problem of why the quantities (c,ℏ,R) are as are does not arise because they are contraction parameters for transitions from more general Lie algebras to less general ones. Then the baryon asymmetry of the universe problem does not arise. At the present stage of the universe, the phenomenon of cosmological acceleration (PCA) is described without uncertainties as an inevitable kinematical consequence of quantum theory in semiclassical approximation. In particular, it is not necessary to involve dark energy the physical meaning of which is a mystery. In our approach, background space and its geometry are not used and R has nothing to do with the radius of dS space. In semiclassical approximation, the results for the PCA are the same as in General Relativity if Λ=3/R2, i.e., Λ>0 and there is no freedom for choosing the value of Λ.

Vehicle detection and tracking in intelligent transportation systems based deep learning

This research paper focuses on the advancements and optimizations made to fundamental object detection algorithms in vehicle detection. The study explores integrating and reusing CNN (Convolutional Neural Networks) models with other techniques to enhance performance. Three main models, namely Faster R-CNN (Faster Region-based Convolutional Neural Network), Improved SSD (Single Shot Multibox Detector), and YOLOv4 (You Only Look Once v4), are analyzed, showcasing their incremental improvements in accuracy and overall detection performance. However, the increased computational complexity and time demands are trade-offs. The study also presents EnsembleNet, a model combining Faster R-CNN and YOLOv5, which achieves higher average precision values. Another approach involves fusing edge features with CNN models, resulting in faster and more accurate vehicle recognition. The paper predicts future deep learning trends, emphasizing the need for improved hardware capabilities to handle complex models. Integrating deep learning with sensor fusion and edge computing holds promise for intelligent transportation systems.

A Survey on Open-Vocabulary Detection and Segmentation: Past, Present, and Future.

As the most fundamental scene understanding tasks, object detection and segmentation have made tremendous progress in deep learning era. Due to the expensive manual labeling cost, the annotated categories in existing datasets are often small-scale and pre-defined, i.e., state-of-the-art fully-supervised detectors and segmentors fail to generalize beyond the closed vocabulary. To resolve this limitation, in the last few years, the community has witnessed an increasing attention toward Open-Vocabulary Detection (OVD) and Segmentation (OVS). By "open-vocabulary", we mean that the models can classify objects beyond pre-defined categories. In this survey, we provide a comprehensive review on recent developments of OVD and OVS. A taxonomy is first developed to organize different tasks and methodologies. We find that the permission and usage of weak supervision signals can well discriminate different methodologies, including: visual-semantic space mapping, novel visual feature synthesis, region-aware training, pseudo-labeling, knowledge distillation, and transfer learning. The proposed taxonomy is universal across different tasks, covering object detection, semantic/instance/panoptic segmentation, 3D and video understanding. The main design principles, key challenges, development routes, methodology strengths, and weaknesses are thoroughly analyzed. In addition, we benchmark each task along with the vital components of each method in appendixand updated online at awesome-ovd-ovs. Finally, several promising directions are provided and discussed to stimulate future research.

An intuitive construction of modular flow

The theory of modular flow has proved extremely useful for applying thermodynamic reasoning to out-of-equilibrium states in quantum field theory. However, the standard proofs of the fundamental theorems of modular flow use machinery from Fourier analysis on Banach spaces, and as such are not especially transparent to an audience of physicists. In this article, I present a construction of modular flow that differs from existing treatments. The main pedagogical contribution is that I start with thermal physics via the KMS condition, and derive the modular operator as the only operator that could generate a thermal time-evolution map, rather than starting with the modular operator as the fundamental object of the theory. The main technical contribution is a new proof of the fundamental theorem stating that modular flow is a symmetry. The new proof circumvents the delicate issues of Fourier analysis that appear in previous treatments, but is still mathematically rigorous.

Laplace transformations and sine-Gordon type integrable PDE

It is well known that the Laplace cascade method is an effective tool for constructing solutions to linear equations of hyperbolic type, as well as nonlinear equations of the Liouville type. The connection between the Laplace method and soliton equations of hyperbolic type remains less studied. The article shows that the Laplace cascade also has important applications in the theory of hyperbolic equations of the soliton type. Laplace’s method provides a simple way to construct such fundamental objects related to integrability theory as the recursion operator, the Lax pair and Dubrovin-type equations, allowing one to find algebro-geometric solutions. As an application of this approach, previously unknown recursion operators and Lax pairs are found for two nonlinear integrable equations of the sine-Gordon type.

Thauma: Pain or Wonder? Considerations Starting from Emanuele Severino and Martin Heidegger

The topic of evil, variously understood, constitutes a fundamental object of questioning and problematicity, so much so that the Italian philosopher Emanuele Severino believes that the thauma from which philosophical research traditionally begins means precisely “anguished pain”, caused, in the last resort, from the becoming of entities. This article intends, first of all, to evaluate the argumentative cogency of the Severinian interpretation in reference to this/of this question and then, move on to analyze some of the writings in which Martin Heidegger deals with the same theme/subject: even the German philosopher has in fact provided interesting considerations that can be profitably used to grasp the most appropriate way of understanding this concept. The question that arises, in fact, is not purely terminological, but involves the same intonation that characterizes the philosophical question and the starting point from which it originates.
 From the comparison between the two philosophers, in addition to some interpretative limits that seem to be found in both, some significant convergences will emerge, at least in relation to the role that emotions play within the philosophical investigation.

Topological Inference of the Conley Index

AbstractThe Conley index of an isolated invariant set is a fundamental object in the study of dynamical systems. Here we consider smooth functions on closed submanifolds of Euclidean space and describe a framework for inferring the Conley index of any compact, connected isolated critical set of such a function with high confidence from a sufficiently large finite point sample. The main construction of this paper is a specific index pair which is local to the critical set in question. We establish that these index pairs have positive reach and hence admit a sampling theory for robust homology inference. This allows us to estimate the Conley index, and as a direct consequence, we are also able to estimate the Morse index of any critical point of a Morse function using finitely many local evaluations.

Beyond sense-specific processing: decoding texture in the brain from touch and sonified movement

Texture, a fundamental object attribute, is perceived through multisensory information including touch and auditory cues. Coherent perceptions may rely on shared texture representations across different senses in the brain. To test this hypothesis, we delivered haptic textures coupled with a sound synthesizer to generate real-time textural sounds. Participants completed roughness estimation tasks with haptic, auditory, or bimodal cues in an MRI scanner. Somatosensory, auditory, and visual cortices were all activated during haptic and auditory exploration, challenging the traditional view that primary sensory cortices are sense-specific. Furthermore, audio-tactile integration was found in secondary somatosensory (S2) and primary auditory cortices. Multivariate analyses revealed shared spatial activity patterns in primary motor and somatosensory cortices, for discriminating texture across both modalities. This study indicates that primary areas and S2 have a versatile representation of multisensory textures, which has significant implications for how the brain processes multisensory cues to interact more efficiently with our environment.

A Taylor resolution over complete intersections

The Taylor resolution is a fundamental object in the study of free resolutions over the polynomial ring, due to its explicit formula, cellular/combinatorial structure, and applicability to any and all monomial ideals. This paper generalizes the Taylor resolution to complete intersection rings via the Eisenbud–Shamash construction.

Monitoring and Quality Evaluation Method of English Teaching in Machine Manufacturing Based on Machine Learning and Internet of Things

INTRODUCTION: With the continuous development of society, education is getting more and more attention, and all stages of education, such as elementary school, middle school, high school, Etc., are the fundamental objects of attention, while English in the university, as a critical foreign language, is also given considerable attention. Among the various majors in the university, different majors pay different attention to English, among which in the mechanical engineering major, the importance of English is still relatively front and centre, which is helpful for the improvement of students' mechanical engineering level. However, in the current teaching, there are still a series of problems in the English teaching of mechanical majors, which have certain obstacles to improving students' English level. OBJECTIVES: To give university English teachers more feedback and opinions through a reasonable and perfect teaching monitoring and quality evaluation method; combining their English reading teaching with relevant rules and regulations can better promote the educational quality level of university English and help students improve their English more reasonably. METHODS: To study and analyze the monitoring and quality evaluation of English teaching in mechanical majors to get the relevant optimization suggestions of teaching mode, and to solve the correlation problem based on multiple linear regression through the calculation of SPSS software, to analyze the final impact mechanism of each item on the quality of teaching. RESULTS: The results of the sample survey indicate that, firstly, five factors, namely, research direction, disciplinary ladder, scientific research, talent cultivation and management, will have a significant impact on the monitoring and quality evaluation of English teaching in the mechanical program. Secondly, further research on the influence mechanism suggests that the monitoring and quality evaluation of English language teaching in mechanical majors needs some improvement, affecting the English language proficiency of students in this field. CONCLUSION: After summarizing several factors that impact the evaluation of the quality of English teaching, it is clear that such English classroom teaching has a positive effect on the training of mechanical students.

The study on the characteristics of carbon pressure agglomeration and the dynamic evolution of heterogeneity in China from a regional perspective.

Provinces (cities and districts) with identifiable boundaries are under intense pressure to reduce emissions as a fundamental unit and research object of carbon peaking and carbon-neutrality goals. Due to the significant variability of regional development, achieving equilibrium between carbon emissions and carbon absorption is challenging, contributing to the difficulty of developing carbon emission reduction and relevant green strategic initiatives in China. Therefore, this paper explored the spatial effect of carbon balance with carbon pressure as the starting point. First, this paper defined the "carbon pressure index" (CPI) of 30 provinces (cities and districts) in China from 2000 to 2019. Second, this paper validated the CPI agglomeration evolutionary characteristics in global and local aspects based on the Moran's index. Third, this paper identified and decomposed the spatial heterogeneity of CPI using the kernel density estimation method and the Theil index, then extracted typical cities to analyze the specific causes. Finally, this paper classified the seven regions in China into four types according to a comprehensive analysis of CPI. The results indicated that China's ecological carbon cycle system was in a serious "carbon overload" state. Thirty provinces (cities and districts) showed significant spatial agglomeration characteristics. The spatial gap of CPI was gradually decreasing nationwide, and the intra-regional differences were the leading cause of CPI levels in China. This can provide policy basis for the improvement of China's balanced development system of regional carbon emission reduction.