Shape Coding Research Articles

Beyond the Rhetoric of Revanchism Towards the Metropolitan Core: An Analysis of Symbolic Representations of Milan From Its Peripheries

Socio-political research has shown that in metropolitan peripheries, populist parties have gained significant support. This is because these parties capitalise on a widespread feeling of exclusion, leading to a revanchist social representation of affluent metropolitan centres. This article contributes to the debate on metropolitan dynamics by exploring the social representations of the centre–periphery relationship, showing how symbolic representations play a role in shaping codes of action and revanchism alone is insufficient to understand the core–periphery relationship. Four suburbs with similar socioeconomic characteristics in the functional urban area of Milan were selected. Milan is the most important Italian metropolis, and it has a relevant socio-political fracture. Semi-structured interviews were carried out to analyse the cultural meanings of living on the periphery among local leaders. The metropolitan centre is perceived as necessary, evoking ‘efficient’ representations; however, these peripheral contexts are meaningful places of belonging. This article shows that an analysis of the dynamics at work at the metropolitan level should consider peripheral contexts.

The Effectiveness of Individualized Morphosyntactic Target Identification and Explicit Intervention Using the SHAPE CODING System for Children With Developmental Language Disorder and the Impact of Within-Session Dosage.

We investigated the effectiveness of a highly individualized morphosyntactic intervention using the SHAPE CODING™ system delivered at different dosages. Eight children with developmental language disorder aged 8;0-10;10 (years;months) received 10 hr of explicit individualized intervention for morphosyntax delivered in 30-min individual sessions once per week for 20 weeks. Following at least four baseline probe tests, two grammatical targets per session received explicit instruction until they reached criterion (90%), when the next target was introduced. To control for session length and teaching episode density, either both targets received 20 teaching episodes per session or one target received 10 teaching episodes and the other 30. Maintenance testing of completed targets was also carried out. Scores on probe tests post-intervention were significantly higher than during the baseline phase (d = 1.6) with no change during the baseline or maintenance phases. However, progress during the intervention phase was highly significant. One participant showed significantly faster progress with intervention, while one (with the lowest attention score) made little progress. When considering progress relative to cumulative intervention sessions, progress was faster with 30 teaching episodes per session and slower with 10. However, when cumulative teaching episodes were used as the predictor, all three within-session dosages showed very similar rates of progress, with the odds of a correct response increasing by 3.9% for each teaching episode. The targets that were achieved required an average of 40-60 teaching episodes. With the exception of one participant, the individualized intervention was highly effective and efficient. Thus, the individualized target identification process and intervention method merit further research in a larger group of children. The cumulative number of teaching episodes per target provided across sessions appeared to be key. Thus, clinicians should aim for high teaching episode rates, particularly if the number of sessions is constrained. Otherwise, intervention scheduling can be flexible. https://doi.org/10.23641/asha.25996168.

Collaborative Tooth Motion Diffusion Model in Digital Orthodontics

Tooth motion generation is an essential task in digital orthodontic treatment for precise and quick dental healthcare, which aims to generate the whole intermediate tooth motion process given the initial pathological and target ideal tooth alignments. Most prior works for multi-agent motion planning problems usually result in complex solutions. Moreover, the occlusal relationship between upper and lower teeth is often overlooked. In this paper, we propose a collaborative tooth motion diffusion model. The critical insight is to remodel the problem as a diffusion process. In this sense, we model the whole tooth motion distribution with a diffusion model and transform the planning problem into a sampling process from this distribution. We design a tooth latent representation to provide accurate conditional guides consisting of two key components: the tooth frame represents the position and posture, and the tooth latent shape code represents the geometric morphology. Subsequently, we present a collaborative diffusion model to learn the multi-tooth motion distribution based on inter-tooth and occlusal constraints, which are implemented by graph structure and new loss functions, respectively. Extensive qualitative and quantitative experiments demonstrate the superiority of our framework in the application of orthodontics compared with state-of-the-art methods.

Line Shape Code Comparison of the Effect of Periodic Fields on Hydrogen Lines

Spectral line shapes code in plasmas (SLSPs) code comparison workshops have been organized in the last decade with the aim of comparing the spectra obtained with independently developed analytical and numerical models. Here, we consider the simultaneous effect of a plasma microfield and a periodic electric field on the hydrogen lines Lyman-α, Lyman-β, Balmer-α, and Balmer-β for plasma conditions where the Stark effect usually dominates line broadening.

Enhanced architecture and implementation of spectrum shaping codes.

Spectral shaping codes are modulation codes widely used in communication and data storage systems. This research enhances the algorithms employed in constructing spectral shaping codes for hardware implementation. We present a parallel scrambling calculation with a time complexity of O(1). Second, in the minimum accumulated signal power (MASP) module, the sine-cosine accumulation needs to be determined by remainder with time complexity O(n2). We offer reduced MASP computations for short bit-width data, ROM storage, and addition pipelines. It can remove the remainder operation, reducing accumulated complexity to O(1). In addition, we present a search algorithm to generate segmented lines to replace the square operations in the MASP module. By employing the search algorithm and shift operations, we can reduce the complexity of the square from O(n2) to O(1). The implementation results reveal that the original and proposed MASPs yield nearly identical spectrum nulls. The encoder-decoder of the spectral shaping codes with proposed approaches consumes just 6% of the hardware resources when carried out with a Spartan6 XC6SLX25.

Neural-ABC: Neural Parametric Models for Articulated Body With Clothes.

In this paper, we introduce Neural-ABC, a novel parametric model based on neural implicit functions that can represent clothed human bodies with disentangled latent spaces for identity, clothing, shape, and pose. Traditional mesh-based representations struggle to represent articulated bodies with clothes due to the diversity of human body shapes and clothing styles, as well as the complexity of poses. Our proposed model provides a unified framework for parametric modeling, which can represent the identity, clothing, shape and pose of the clothed human body. Our proposed approach utilizes the power of neural implicit functions as the underlying representation and integrates well-designed structures to meet the necessary requirements. Specifically, we represent the underlying body as a signed distance function and clothing as an unsigned distance function, and they can be uniformly represented as unsigned distance fields. Different types of clothing do not require predefined topological structures or classifications, and can follow changes in the underlying body to fit the body. Additionally, we construct poses using a controllable articulated structure. The model is trained on both open and newly constructed datasets, and our decoupling strategy is carefully designed to ensure optimal performance. Our model excels at disentangling clothing and identity in different shape and poses while preserving the style of the clothing. We demonstrate that Neural-ABC fits new observations of different types of clothing. Compared to other state-of-the-art parametric models, Neural-ABC demonstrates powerful advantages in the reconstruction of clothed human bodies, as evidenced by fitting raw scans, depth maps and images. We show that the attributes of the fitted results can be further edited by adjusting their identities, clothing, shape and pose codes. The dataset and trained parametric model will be available at https://ustc3dv.github.io/NeuralABC/.

Optimization of lap splice positions for near-zero rebar cutting waste in diaphragm walls using special-length-priority algorithms

ABSTRACT Construction processes often result in rebar waste when cutting stock length rebar to required length, incurring significant costs and contributing to CO2 emissions. While prior research has explored rebar waste reduction through cutting pattern optimization, the potential gain from adjusting lap splice positions has been neglected. This study focuses on enhancing waste reduction by optimizing lap splice positions, particularly focusing on utilizing special length rebar to achieve a cutting waste rate below 1%. Our approach employs a three-step heuristic algorithm: (1) optimizing lap splice positions for alignment with special length rebar; (2) generating cutting patterns based on special length rebar; (3) creating cutting patterns for remaining rebars using stock length rebar. Applying this algorithm to a diaphragm wall at an interchange station adhering to the British Standard shape codes yielded remarkable results. The cutting waste decreased by 3,000.22 tons, the CO2 emissions reduced by 10,398.77 tons, and the cost savings totaled USD 3,480,108. Consequently, the cutting waste rate reached an impressive 0.77%. By adopting the principles outlined in this paper, construction practices can significantly reduce waste, promote sustainability, and mitigate financial losses associated with rebar waste.

Applications of Neural Networks to Metallic Flexor Geometry Optimization of Flat Wipers

<div>In recent years, demands of flat wipers have rapidly increased in the vehicle industry due to their simpler structure compared to the conventional wipers. Procedures for evaluating the appropriate metallic flexor geometry, which is one of the major components of the flat wiper, were proposed in the authors’ previous study. However, the computational cost of the aforementioned procedures seems to be unaffordable to the industry. The discrete Winkler model regarding the flexor as the Euler–Bernoulli beam is established as the mathematical model in this study to simulate a flexor compressed against a surface at various wiping angles. The deflection of the beam is solved using a finite difference method, and the calculated contact pressure distributions agree fairly with those based on the corresponding finite element model. Flexor designs are paired with various windshield surfaces to accumulate a sufficiently large simulation database based on the mathematical model. An artificial neural network (ANN) approach is developed to predict contact pressure distributions of the flexor much faster than the mathematical model. Geometry of the curved surface is represented by a shape code obtained via a principal component analysis (PCA) and used in the ANN model. The ANN algorithm is also applied to efficiently evaluate the wiping patterns according to the simulated contact pressure distributions. These patterns are then classified by using a convolutional neural network (CNN) to identify several suitable flexor designs for the specific windshield. The flat wiper suggested by the current procedures is experimentally validated to justify its qualified wiping performances.</div>

Three is the magic number: Distance measurement of NGC 3147 using SN 2021hpr and its siblings

Context. The nearby spiral galaxy NGC 3147 hosted three Type Ia supernovae (SNe Ia) in the past decades that have been the subjects of intense follow-up observations. Simultaneous analysis of their data provides a unique opportunity for testing different methods of light curve fitting and distance estimation. Aims. The detailed optical follow-up of SN 2021hpr allows us to revise the previous distance estimations to NGC 3147 and compare the widely used light curve fitting algorithms to each other. After the combination of the available and newly published data of SN 2021hpr, its physical properties can also be estimated with higher accuracy. Methods. We present and analyse new BV griz and Swift photometry of SN 2021hpr to constrain its general physical properties. Together with its siblings, SNe 1997bq and 2008fv, we cross-compared the individual distance estimates of these three SNe given by the Spectral Adaptive Lightcurve Template (SALT) code, and we also checked their consistency with the results from the Multi-Color Light Curve Shape (MLCS) code. The early spectral series of SN 2021hpr was also fit with the radiative spectral code TARDIS to verify the explosion properties and constrain the chemical distribution of the outer ejecta. Results. After combining the distance estimates for the three SNe, the mean distance to their host galaxy, NGC 3127, is 42.5 ± 1.0 Mpc, which matches with the distance inferred by the most up-to-date light curve fitters, SALT3 and BayeSN. We confirm that SN 2021hpr is a Branch-normal Type Ia SN that ejected ~1.12 ± 0.28 M⊙ from its progenitor white dwarf and synthesized ~0.44 ± 0.14 M⊙ of radioactive 56Ni.

Object detection and tracking on UAV RGB videos for early extraction of grape phenotypic traits

Grapevine phenotyping is the process of determining the physical properties (e.g., size, shape, and number) of grape bunches and berries. Grapevine phenotyping information provides valuable characteristics to monitor the sanitary status of the vine. Knowing the number and dimensions of bunches and berries at an early stage of development provides relevant information to the winegrowers about the yield to be harvested. However, the process of counting and measuring is usually done manually, which is laborious and time-consuming. Previous studies have attempted to implement bunch detection on red bunches in vineyards with leaf removal and surveys have been done using ground vehicles and handled cameras. However, Unmanned Aerial Vehicles (UAV) mounted with RGB cameras, along with computer vision techniques offer a cheap, robust, and timesaving alternative. Therefore, Multi-object tracking and segmentation (MOTS) is utilized in this study to determine the traits of individual white grape bunches and berries from RGB videos obtained from a UAV acquired over a commercial vineyard with a high density of leaves. To achieve this goal two datasets with labelled images and phenotyping measurements were created and made available in a public repository. PointTrack algorithm was used for detecting and tracking the grape bunches, and two instance segmentation algorithms - YOLACT and Spatial Embeddings - have been compared for finding the most suitable approach to detect berries. It was found that the detection performs adequately for cluster detection with a MODSA of 93.85. For tracking, the results were not sufficient when trained with 679 frames.This study provides an automated pipeline for the extraction of several grape phenotyping traits described by the International Organization of Vine and Wine (OIV) descriptors. The selected OIV descriptors are the bunch length, width, and shape (codes 202, 203, and 208, respectively) and the berry length, width, and shape (codes 220, 221, and 223, respectively). Lastly, the comparison regarding the number of detected berries per bunch indicated that Spatial Embeddings assessed berry counting more accurately (79.5%) than YOLACT (44.6%).

Rethinking Rotation Invariance with Point Cloud Registration

Recent investigations on rotation invariance for 3D point clouds have been devoted to devising rotation-invariant feature descriptors or learning canonical spaces where objects are semantically aligned. Examinations of learning frameworks for invariance have seldom been looked into. In this work, we review rotation invariance (RI) in terms of point cloud registration (PCR) and propose an effective framework for rotation invariance learning via three sequential stages, namely rotation-invariant shape encoding, aligned feature integration, and deep feature registration. We first encode shape descriptors constructed with respect to reference frames defined over different scales, e.g., local patches and global topology, to generate rotation-invariant latent shape codes. Within the integration stage, we propose an Aligned Integration Transformer (AIT) to produce a discriminative feature representation by integrating point-wise self- and cross-relations established within the shape codes. Meanwhile, we adopt rigid transformations between reference frames to align the shape codes for feature consistency across different scales. Finally, the deep integrated feature is registered to both rotation-invariant shape codes to maximize their feature similarities, such that rotation invariance of the integrated feature is preserved and shared semantic information is implicitly extracted from shape codes. Experimental results on 3D shape classification, part segmentation, and retrieval tasks prove the feasibility of our framework. Our project page is released at: https://rotation3d.github.io/.

Hearing elliptic movements reveals the imprint of action on prototypical geometries

Within certain categories of geometric shapes, prototypical exemplars that best characterize the category have been evidenced. These geometric prototypes are classically identified through the visual and haptic perception or motor production and are usually characterized by their spatial dimension. However, whether prototypes can be recalled through the auditory channel has not been formally investigated. Here we address this question by using auditory cues issued from timbre-modulated friction sounds evoking human drawing elliptic movements. Since non-spatial auditory cues were previously found useful for discriminating distinct geometric shapes such as circles or ellipses, it is hypothesized that sound dynamics alone can evoke shapes such as an exemplary ellipse. Four experiments were conducted and altogether revealed that a common elliptic prototype emerges from auditory, visual, and motor modalities. This finding supports the hypothesis of a common coding of geometric shapes according to biological rules with a prominent role of sensory-motor contingencies in the emergence of such prototypical geometry.

Effect of collisions on motional Stark broadening of spectral lines

The shape of spectral lines in strongly magnetized plasmas is investigated theoretically in the framework of astrophysical research. Under certain conditions, the broadening of lines observed on white dwarf spectra is dominated by the so-called motional Stark effect, which occurs due to the Lorentz electric field v→×B→. If the plasma density is high enough, collisions between the emitter and perturbers change the atomic velocity v→ and the resulting motional Stark broadening is modified. We illustrate this modification through dedicated line shape calculations based on a stochastic model for the atomic velocity. A universal line shape formula, which is applicable to any isolated atomic line, is proposed for implementation in line shape codes.

Why Shape Coding? Asymptotic Analysis of the Entropy Rate for Digital Images.

This paper focuses on the ultimate limit theory of image compression. It proves that for an image source, there exists a coding method with shapes that can achieve the entropy rate under a certain condition where the shape-pixel ratio in the encoder/decoder is O(1/logt). Based on the new finding, an image coding framework with shapes is proposed and proved to be asymptotically optimal for stationary and ergodic processes. Moreover, the condition O(1/logt) of shape-pixel ratio in the encoder/decoder has been confirmed in the image database MNIST, which illustrates the soft compression with shape coding is a near-optimal scheme for lossless compression of images.

Arbitrary-Order and Multichannel Optical Vortices with Simultaneous Amplitude and Phase Modulation on Plasmonic Metasurfaces.

The highly localized and uneven spatial distribution of the subwavelength light field in metal metasurfaces provides a promising means for the generation of optical vortices (OVs) with arbitrary topological charges. In this paper, a simple and reliable way for generating multichannel OVs on gold nanoporous metasurfaces is reported. The instantaneous field of arbitrary-order OVs can be regulated and concentrated on the same focal surface by adapting photonic spin–orbit interaction (SOI) and geometric phase. The focal ring energy distribution of OVs along the conical propagation path is accurately calculated, and the double phase of units induced by spin rotation is confirmed. Based on the parameter optimization of the nanohole arrangement, the simultaneous amplitude and phase modulation of multichannel OVs has been realized. Furthermore, the average multichannel signal-to-noise ratio exceeds 15 dB, which meets the requirements of high resolution and low crosstalk. Our study obtains broadband and efficient OVs, which can contribute to improving the capacity storage and security of optical information and possess great application prospects in beam shaping, optical tweezers, and communication coding.

Morphokinematic modelling of the point-symmetric Cat’s Eye, NGC 6543: Ring-like remnants of a precessing jet

ABSTRACT The planetary nebula known as the Cat’s Eye Nebula (NGC 6543) has a complex, point-symmetric morphology that cannot be fully explained by the current theory of planetary nebula formation, the interacting stellar winds model. In order to reveal the 3D structure of the Cat’s Eye Nebula, we created a detailed 3D morphokinematic model of this nebula using a [N ii] image from the Hubble Space Telescope and five different position–velocity diagrams using the SHAPE code. This modelling approach has revealed point-symmetric partial rings, which were likely formed by a precessing jet.

MendNet: Restoration of Fractured Shapes Using Learned Occupancy Functions

AbstractWe provide a novel approach to perform fully automated generation of restorations for fractured shapes using learned implicit shape representations in the form of occupancy functions. Our approach lays the groundwork to perform automated object repair via additive manufacturing. Existing approaches for restoration of fractured shapes either require prior knowledge of object structure such as symmetries between the restoration and the fractured object, or predict restorations as voxel outputs that are impractical for repair at current resolutions. By leveraging learned occupancy functions for restoration prediction, our approach overcomes the curse of dimensionality with voxel approaches, while providing plausible restorations. Given a fractured shape, we fit a function to occupancy samples from the shape to infer a latent code. We apply a learned transformation to the fractured shape code to predict a corresponding code for restoration generation. To ensure physical validity and well‐constrained shape estimation, we contribute a loss that models feasible occupancy values for fractured shapes, restorations, and complete shapes obtained by joining fractured and restoration shapes. Our work overcomes deficiencies of shape completion approaches adapted for repair, and enables consumer‐driven object repair and cultural heritage object restoration. We share our code and a synthetic dataset of fractured meshes from 8 ShapeNet classes at: https://github.com/Terascale‐All‐sensing‐Research‐Studio/MendNet.

Comprehensive folding variations for protein folding.

The revelation of protein folding is a challenging subject in both discovery and description. Except for acquirement of accurate 3D structure in protein stable state, another big hurdle is how to discover structural flexibility for protein innate character. Even if a huge number of flexible conformations are known, difficulty is how to represent these conformations. A novel approach, protein structure fingerprint, has been developed to expose the comprehensive local folding variations, and then construct folding conformations for entire protein. The backbone of five amino acid residues was identified as a universal folden, and then a set of Protein Folding Shape Code (PFSC) was derived for completely covering folding space in alphabetic description. Sequentially, a database was created to collect all possible folding shapes of local folding variations for all permutation of five amino acids. Successively, Protein Folding Variation Matrix (PFVM) assembled all possible local folding variations along sequence for a protein, which possesses several prominent features. First, it showed the fluctuation with certain folding patterns along sequence which revealed how the protein folding was related the order of amino acids in sequence. Second, all folding variations for an entire protein can be simultaneously apprehended at a glance within PFVM. Third, all conformations can be determined by local folding variations from PFVM, so total number of conformations is no longer ambiguous for any protein. Finally, the most possible folding conformation and its 3D structure can be acquired according PFVM for protein structure prediction. Therefore, the protein structure fingerprint approach provides a significant means for investigation of protein folding problem.

A Low-Complexity Probabilistic Amplitude Shaping With Short Linear Block Codes

We propose a new probabilistic amplitude shaping (PAS) scheme based on short linear block codes. In the proposed system, the capacity-approaching signal distribution is generated in the process of decoding linear block codes for a given information bit sequence. We associate the design problem of shaping codes with the classical covering problem, suggesting the use of good covering codes for shaping. From simulation results, it is demonstrated that by selecting <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">perfect</i> binary codes as our shaping codes, the proposed scheme offers a shaping gain of around 0.3–1.0 dB. By comparing with the enumerative sphere shaping (ESS) of the same block length, we verify that the proposed scheme achieves significantly lower storage complexity and computational complexity at the receiver even with comparable block error rate performance.

A large chromosomal inversion shapes gene expression in seaweed flies (Coelopa frigida).

Inversions often underlie complex adaptive traits, but the genic targets inside them are largely unknown. Gene expression profiling provides a powerful way to link inversions with their phenotypic consequences. We examined the effects of the Cf‐Inv(1) inversion in the seaweed fly Coelopa frigida on gene expression variation across sexes and life stages. Our analyses revealed that Cf‐Inv(1) shapes global expression patterns, most likely via linked variation, but the extent of this effect is variable, with much stronger effects in adults than larvae. Furthermore, within adults, both common as well as sex‐specific patterns were found. The vast majority of these differentially expressed genes mapped to Cf‐Inv(1). However, genes that were differentially expressed in a single context (i.e., in males, females, or larvae) were more likely to be located outside of Cf‐Inv(1). By combining our findings with genomic scans for environmentally associated SNPs, we were able to pinpoint candidate variants in the inversion that may underlie mechanistic pathways that determine phenotypes. Together the results of this study, combined with previous findings, support the notion that the polymorphic Cf‐Inv(1) inversion in this species is a major factor shaping both coding and regulatory variation resulting in highly complex adaptive effects.