Repetitive Patterns Research Articles

Pattern-Making and Textile Technologies across Asia

Abstract To consider textiles along the trade routes that traverse Asia is to consider materials, technologies, images and ideas: fibres and filaments, dyestuffs, and the technologies of felt-making, weaving, embroidery, carpet-weaving and block-printing. Pattern-making is affected by all of these factors. And the trajectories of designs, repeated to form patterns, bring us to confront changes in meaning over time and space, relating textiles to the history of ideas. Within the breadth of this vast complexity of cultural exchange on multiple levels, this paper offers a brief exploration of two vexing problems. The first concerns origins and cultural diffusion of a warp-resist patterning technique (ikat). The second concerns the origin, development and transmission of drawloom weaving, resulting in the production of compound textiles with repeat patterns from selvedge to selvedge. These overarching questions relate aspects of pattern-making integral to two textile technologies with a view towards stimulating future research.

AUTISM DIAGNOSIS

This document results from a theoretical study, the objective of which was to discuss the importance of conducting high-quality diagnoses of Autism Spectrum Disorder (ASD) and to compare how this screening process is conducted through the Unified Health System (SUS) and specialized private clinics. The research was conducted through a literature review and case study analysis to assess the waiting time, cost, diagnostic quality, and follow-up care after the screening process had been completed. Autism is a neurodevelopmental condition characterized by significant deficits in communication, selective eating, and social interaction, as well as repetitive patterns of behaviors, activities, and/or interests.

Façade Design Pattern Optimization Workflow Through Visual Spatial Frequency Analysis and Structural Safety Assessment

As the demand for highly efficient yet aesthetically pleasing, complex building envelope structures is rising worldwide, computational analysis and generative design tools are becoming ever so relevant. Previous methods for achieving a natural distribution of structural or shading elements in non-uniform façades are mostly based either on computer-generated pseudo-randomness or a literal biomorphic approach where a naturally occurring pattern is directly projected on the façade surface. As an alternative, this research introduces a novel technique for optimisation that utilises a two-dimensional Power Spectrum Analysis, suitable for numerically assessing the alignment of designed geometry with natural patterns. By integrating this optimisation method into the design process, the façade pattern generation can be automated and optimal design can be selected by evaluating multiple design solutions. Instead of using repetitive geometrical patterns or generated pseudo-randomness, patterns objectively similar to those occurring in nature can be created without directly copying natural structures. The distribution of the structural and shading elements controls the way natural light permeates the building and, considering the data gathered from images of natural scenes, this method can be used to design structures not only with optimal structural and energy performance but also with visual and psychological occupant comfort in mind.

A memory access number constraint-based string prediction technique for high throughput SCC implemented in AVS3

String prediction (SP) is a highly efficient screen content coding (SCC) tool that has been adopted in international and Chinese video coding standards. SP exhibits a highly flexible and efficient ability to predict repetitive matching patterns. However, SP also suffers from low throughput of decoded display output pixels per memory access, which is synchronized with the decoder clock, due to the high number of memory accesses required to decode an SP coding unit for display. Even in state-of-the-art (SOTA) SP, the worst-case scenario involves two memory accesses for decoding each 4-pixel basic string unit across two memory access units, resulting in a throughput as low as two pixels per memory access (PPMA). To solve this problem, we are the first to propose a technique called memory access number constraint-based string prediction (MANC-SP) to achieve high throughput in SCC. First, a novel MANC-SP framework is proposed, a well-designed memory access number constraint rule is established on the basis of statistical data, and a constrained RDO-based string searching method is presented. Compared with the existing SOTA SP, the experimental results demonstrate that MANC-SP can improve the throughput from 2 to 2.67 PPMA, achieving a throughput improvement of 33.33% while maintaining a negligible impact on coding efficiency and complexity.

INNOVATIVE FOOTWEAR DESIGN FOR AUTISTIC INDIVIDUALS: MERGING AESTHETICS AND SENSORY NEEDS

The integration of repetitive visual patterns and geometric shapes in footwear design for autistic individuals presents an innovative approach that transcends mere aesthetics. This strategy aims to address the sensory and emotional needs of users, highlighting the importance of visual stimuli in promoting focus and mental organization—key elements for those facing sensory challenges. Research indicates that emphasizing symmetry and repetition in design can create visually pleasing footwear while also facilitating better concentration. Various studies suggest that the perceptual abilities and visual processing strategies of autistic individuals can be harnessed to foster richer and more effective learning experiences, aiding in the development of essential social and cognitive skills. Furthermore, the selection of comfortable materials and the consideration of ergonomic design are crucial to ensure that the shoes are not only visually appealing but also functional and comfortable for everyday wear. By focusing on these aspects, footwear can serve as more than just a fashion statement; it can become a tool for enhancing the quality of life for autistic individuals. The thoughtful combination of art, comfort, and sensory experience in shoe design promotes inclusion and celebrates the uniqueness of each individual. This approach fosters a deep connection between the user and the product, ultimately contributing to a more supportive and understanding environment for those on the autism spectrum.

O LÚDICO COMO PROPOSTA ESTRATÉGICA PARA O ENSINO, APRENDIZAGEM E DESENVOLVIMENTO DE ESTUDANTES AUTISTAS

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by atypical development, behavioral manifestations, deficits in communication and social interaction, repetitive and stereotyped behavior patterns, and may include a restricted repertoire of interests and activities. It is crucial that schools are concerned with the quality of education, which requires the collective commitment of educators and students, aiming at the integral formation of citizenship through the effective construction of knowledge. In order to better understand autism within the context of regular schools and education for autistic individuals, we chose to conduct a bibliographical research, discussing the theoretical foundations relevant to the study. Upon concluding the research, we observed that the use of play as a pedagogical method can be highly effective with autistic students, providing an interesting and fun approach to learning acquisition. We recognize that autistic students have special educational needs that must be met by teachers in order to promote their development and ensure that they follow the teaching-learning process.

Exploring Repetitive Integer Patterns in the Complex Roots of Homogeneous Polynomials

Exploring Repetitive Integer Patterns in the Complex Roots of Homogeneous Polynomials

Identification of Mirror Repeats in Viral Genomes Using FPCB Analysis

The majority of living domains consist of DNA as genetic material with the minor exception of viruses. The uniquenature of every species determines by its unique pattern of genome or gene products. The genomic features become an evidentexample of evolutionary study also. Different types of repeat patterns are observed in genomes of living domains including humanbeings whose two third portion of the genome is repetitive. Among the varied type of repeat sequences Mirror Repeats (MR) playcrucial roles at the genetic level in every species. The major focus of our research is on identification & to check the distributionof mirror repeats in some selected infectious viruses of three different domains (Animal, Plant & Human). For this, we employeda bioinformatics-based approach refer as FASTA PARALLEL COMPLEMENT BLAST (FPCB) to identify unique mirror repeat (MR)sequences. The identified repeats vary in their length as well as found to be distributed throughout the selected viral genomes.The maximum no of MR were reported in the case of Dengue virus (229) & minimum is in the case of TMV (97). In the remainingselected viruses - HCV, HPV, HTLV-1, PVY, Rabies virus 178, 156, 175, 203 & 204 MR sequences were reported. These sequencescan be utilized in many ways like in molecular diagnosis, drug delivery target as well as evolutionary study, etc. The present researchalso helps in the development of novel tools of bioinformatics to study mirror repeats and their functional perspective in thecontext of their occurrence in all domains.

Exploring the functions of lexical bundles in undergraduate opinion paragraphs for pedagogical use

Abstract Corpus-based studies of lexical bundles have opened new avenues for language teaching research. The fact that naturally occurring language consists of patterns of lexical repetition and multi-word units has given rise to the question of chunkiness in learner language. This study was designed to examine lexical bundles and their functions in a small, specialized learner corpus of opinion paragraphs written by Saudi English as a Foreign Language (EFL) students at the University of Jeddah. The study takes a frequency-driven approach to identify common lexical bundles. A learner corpus of 237 writing tasks produced by Saudi undergraduate students from 11 different sections is compiled and explored. The primary aim was to identify high-frequency five-word lexical bundles and explore their functions in the learner corpus, as well as investigate any distributional differences in bundle use across the various student sections. The findings revealed that learners utilized lexical bundles primarily to serve four key functions: expressing stance, supporting a point, introducing an item, and making recommendations. Notably, variations were observed in the distribution of these functional categories among the different student groups. The study concludes by outlining some pedagogical applications for educators and language practitioners, highlighting the value of learner corpus-informed approaches to enhancing learners’ awareness and mastery of lexical patterning in academic writing. By better understanding the role of formulaic language in learner production, instructors can tailor their teaching to more effectively support students’ linguistic development.

Variation in thermal courtship activity curves across individuals exceeds variation across populations and sexes.

The dynamics of mating interactions can vary in response to a wide variety of environmental factors. Here, we investigate the potential for individuals to vary consistently in the environmental conditions under which they actively engage in courtship. Specifically, we quantify variation in how courtship activity changes with environmental temperature across levels of biological organization in Enchenopa binotata treehoppers. Male E. binotata produce vibrational courtship signals and receptive females respond with their own sex-specific vibrational courtship signal. We tested each individual twice for the production of courtship signals across a range of ecologically-relevant temperatures (18 - 36 °C). Then, we measured repeatability and variability in the resulting thermal courtship activity curves, including the temperature of peak activity and tolerance to thermal extremes. We also looked at patterns of variation across populations and sexes. We found minimal variation across populations, but significant variation across individuals. Specifically, we found prevalent repeatability in how thermally generalized or specialized individuals are. However, repeatability was limited to females only. We also found higher variability in female traits than in male traits, although patterns of variability did not always predict patterns of repeatability. These results suggest that thermal variation could alter the dynamics of mate competition, and that-due to potentially different selective optima for males and females-the sexes may respond to changes in temperature in different ways. Specifically, females show a higher potential to adapt but males show a higher potential to be more robust to changes in temperature due to overall higher courtship activity across temperatures.

High Prevalence and Impact of Shoulder Pain Among Gym Instructors: A Study on Work-Related Musculoskeletal Disorders

INTRODUCTION :- Gym instructors within the fitness industry play a pivotal role in guiding individuals towards achieving a range of health and fitness goals. In addition to muscular and skeletal health, gym instructors are instrumental in boosting the immune system. Even though they help in maintaining the body gym trainers have a limited knowledge of mechanism of injury, neglecting and repetitive movements of the joint leads to worsening of injury and increase in the pain. Musculoskeletal pain can stem from various sources, including uncommon or repetitive activities that strain muscles, tendons, and ligaments. Additionally, it may result from sudden, jerky movements, falls, fractures, or underlying musculoskeletal conditions. The result of repetitive activities that strain the muscles, tendons and sprain the ligaments. Insufficient recovery time, rapid pace work, repetitive motion patterns, heavy weight lifting, forceful manual exertions, mechanical pressure concentrations or whole body vibrations can lead to development of other musculoskeletal disorders. The impact of a musculoskeletal condition on an individual's quality of life is substantial, extending beyond mere physical discomfort. Such conditions not only affect personal well-being but also impose a considerable financial strain, manifested through compensation payments and lost wages. Instances of sick leave, absenteeism, and even job abandonment contribute to diminished job efficiency,further exacerbating the socioeconomic repercussions of these disorders. METHODOLOGY :- A total of 147 participants were selected on the basis of inclusion and exclusion criteria. A consent form was filled by them and the study and questionnaire was explained to them.Self-made Questionnaire was explained to each gym instructors according to language understood by that person as well as google forms were also made available for their convenience.Each gym instructor completed a self administered questionnaire which included information regarding complaints of current shoulder pain. The total data was collected and was statistically analyzed. CONCLUSION :- The Prevalence of shoulder pain in gym instructors is high (78%). The presence of shoulder pain causes a gym instructors to avoid certain activities due to pain which causes a hindrance in their work related activities.

Fragments of harmony amid apparent chaos: A closer look at the X-ray quasi-periodic eruptions of the galaxy RX J1301.9+2747

Quasi-periodic eruptions (QPEs) are an extreme X-ray variability phenomenon associated with low-mass ($M_ BH < 10^7 M_ odot $) supermassive black holes (SMBHs). First discovered in the nucleus of the galaxy GSN 069, they have been so far securely detected in five other galaxies, including RX J1301.9+2747. When detected, the out-of-QPE emission (quiescence) is consistent with the high-energy tail of thermal emission from an accretion disk. In this article we present the X-ray properties of RX J1301.9+2747, both in quiescence and during QPEs, and complement this information with radio observations. We analyze X-ray data taken during five XMM-Newton observations between 2000 and 2022. The last three observations were taken in coordination with radio observations with the Karl G. Jansky Very Large Array. We also made use of EXOSAT, ROSAT, and Chandra archival observations taken between 1983 and 2009. XMM-Newton detected 34 QPEs of which eight have significantly lower amplitudes than the others. No correlated radio/X-ray variability was observed during QPEs. In terms of timing properties, the QPEs in RX J1301.9+2747 do not exhibit the striking regularity observed in the discovery source GSN 069. In fact there is no clear repetition pattern between QPEs: the average time separation between their peaks is about four hours, but it can be as short as one, and as long as six hours. The QPE spectral properties of RX J1301.9+2747 as a function of energy are, however, very similar to those of GSN 069 and of other QPE sources. During their evolution, X-ray QPEs follow a hysteresis pattern in the temperature-luminosity plane, with a hotter rise than decay. The quiescent emission of RX J1301.9+2747 is more complex than that of GSN 069, as it requires a soft X-ray excess-like component in addition to the thermal emission from the accretion disk. Its long-term X-ray quiescent flux variations are of a low amplitude and not strictly monotonic, with a general decay over the course of $ years. We discuss our observational results in terms of some of the ideas and models that have been proposed so far for the physical origin of QPEs.

Machine Learning-Based Investigation of Atomic Packing Effects: Chemical Pressures at the Extremes of Intermetallic Complexity.

Intermetallic phases represent a domain of emergent behavior, in which atoms with packing and electronic preferences can combine into complex geometrical arrangements whose long-range order involves repeat patterns containing thousands of atoms or is incompatible with a 3D unit cell. The formation of such arrangements points to unexplained driving forces within these systems that, if understood, could be harnessed in the design of new metallic materials. DFT-chemical pressure (CP) analysis has emerged as an approach to visualize how atomic packing tensions within simpler crystal structures can drive this complexity and create potential functionality. However, the applications of this method have hitherto been limited in scope by its dependence on resource-intensive electronic structure calculations. In this Article, we develop machine learning (ML)-based implementation of the CP approach, drawing on the collection of DFT-CP schemes in the Intermetallic Reactivity Database. We illustrate the method with comparisons of ML-CP and DFT-CP schemes for a series of examples, before demonstrating its application with an exploration of one of the quintessential instances of complexity in intermetallic chemistry, Mg2Al3, whose high-temperature unit cell is a 2.8 nm cube containing 1227 atoms. An analysis of its ML-CP-derived interatomic pressures traces the origins of the structure to simple matching rules for the assembly of Frank-Kasper polyhedra. The ML-CP model can be immediately employed on other intermetallic systems, through either its web interface or a command-line version, with just a crystallographic information file.

Les violences conjugales dans les couples appartenant aux « minorités sexuelles » : quelles causes traumatologiques ?

IntroductionMost prevention and awareness-raising programs are heteronormative and do not take into account the presence of violence in sexual minority couples. MethodThe aim of this study is to review the literature on domestic violence in sexual minority couples in relation to any traumatic experiences that may be causes and/or consequences. ResultsA link between childhood trauma, stress or a combination of the two in the perpetration of domestic violence in sexual minorities is highlighted just like the recent creation of typologies in these couples. DiscussionSuffering from significant methodological biases, nevertheless, these studies, which are all too rare, deserve to highlight phenomena that should be better appreciated. Although domestic violence in minority couples appears to be similar to violence in heterosexual couples, two-way violence is more prevalent. This bidirectional violence could largely be the result of a cyclical process of violence from childhood to adulthood, moving from intrafamilial trauma in childhood to societal stress related to sexual orientation in adolescence and finally to mutual violence within the couple in adulthood. ConclusionThe origins of the perpetration of domestic violence in a sexual minority couple appear to be linked to: the consequences, particularly psychological, of stress related to sexual minorities, which mediate the subsequent violence; the cycle of violence with the internalisation of an appropriate violent relationship model, thus representing a generational transmission and a pattern of repetition; the presence of bidirectional violence, also involving defence and reaction behaviours, accentuated by traumatic experiences or stress related to minorities.

Visual place recognition for aerial imagery: A survey

Aerial imagery and its direct application to visual localization is an essential problem for many Robotics and Computer Vision tasks. While Global Navigation Satellite Systems (GNSS) are the standard default solution for solving the aerial localization problem, it is subject to a number of limitations, such as, signal instability or solution unreliability that make this option not so desirable. Consequently, visual geolocalization is emerging as a viable alternative. However, adapting Visual Place Recognition (VPR) task to aerial imagery presents significant challenges, including weather variations and repetitive patterns. Current VPR reviews largely neglect the specific context of aerial data. This paper introduces a methodology tailored for evaluating VPR techniques specifically in the domain of aerial imagery, providing a comprehensive assessment of various methods and their performance. However, we not only compare various VPR methods, but also demonstrate the importance of selecting appropriate zoom and overlap levels when constructing map tiles to achieve maximum efficiency of VPR algorithms in the case of aerial imagery. The code is available on our GitHub repository — https://github.com/prime-slam/aero-vloc.

Radar gait recognition using Dual-branch Swin Transformer with Asymmetric Attention Fusion

Video-based gait recognition suffers from potential privacy issues and performance degradation due to dim environments, partial occlusions, or camera view changes. Radar has recently become increasingly popular and overcome various challenges presented by vision sensors. To capture tiny differences in radar gait signatures of different people, a dual-branch Swin Transformer is proposed, where one branch captures the time variations of the radar micro-Doppler signature and the other captures the repetitive frequency patterns in the spectrogram. Unlike natural images where objects can be translated, rotated, or scaled, the spatial coordinates of spectrograms and CVDs have unique physical meanings, and there is no affine transformation for radar targets in these synthetic images. The patch splitting mechanism in Vision Transformer makes it ideal to extract discriminant information from patches, and learn the attentive information across patches, as each patch carries some unique physical properties of radar targets. Swin Transformer consists of a set of cascaded Swin blocks to extract semantic features from shallow to deep representations, further improving the classification performance. Lastly, to highlight the branch with larger discriminant power, an Asymmetric Attention Fusion is proposed to optimally fuse the discriminant features from the two branches. To enrich the research on radar gait recognition, a large-scale NTU-RGR dataset is constructed, containing 45,768 radar frames of 98 subjects. The proposed method is evaluated on the NTU-RGR dataset and the MMRGait-1.0 database. It consistently and significantly outperforms all the compared methods on both datasets. The codes are available at:https://github.com/wentaoheunnc/NTU-RGR.

Diagnosis of Autism in Children Based on their Gait Pattern and Movement Signs Using the Kinect Sensor

Abstract Background: Autism spectrum disorders are a type of developmental disorder that primarily disrupt social interactions and communications. Autism has no treatment, but early diagnosis of it is crucial to reduce these effects. The incidence of autism is represented in repetitive patterns of children’s motion. When walking, these children tighten their muscles and cannot control and maintain their body position. Autism is not only a mental health disorder but also a movement disorder. Method: This study aims to identify autistic children based on data recorded from their gait patterns using a Kinect sensor. The database used in this study comprises walking information, such as joint positions and angles between joints, of 50 autistic and 50 healthy children. Two groups of features were extracted from the Kinect data in this study. The first one was statistical features of joints’ position and angles between joints. The second group was the features based on medical knowledge about autistic children’s behaviors. Then, extracted features were evaluated through statistical tests, and optimal features were selected. Finally, these selected features were classified by naïve Bayes, support vector machine, k-nearest neighbors, and ensemble classifier. Results: The highest classification accuracy for medical knowledge-based features was 87% with 86% sensitivity and 88% specificity using an ensemble classifier; for statistical features, 84% of accuracy was obtained with 86% sensitivity and 82% specificity using naïve Bayes. Conclusion: The dimension of the resulted feature vector based on autistic children’s medical knowledge was 16, with an accuracy of 87%, showing the superiority of these features compared to 42 statistical features.

Comparison of Climatology of Precipitation Diurnal Cycle in Kalimantan Deduced from Rain Gauge and IMERG Data

Abstract The diurnal cycle is repetitive pattern of changes in weather factors on land and oceans due to the Earth rotation. Kalimantan Island as the largest island in the Maritime Islands region has a complex rainfall pattern that is influenced by local factors and global circulation. The research was conducted to find out the climatological comparison of the diurnal cycle of rain in Kalimantan based on rain gauge data and Integrated Multi-SatellitE Retrievals for GPM Version 07 (IMERG V07) data for the period 2016 - 2022. Data validation using rain gauge data to validate and calibrate IMERG satellite data, improving the accuracy and reliability of satellite rainfall estimates. The diurnal cycle is evaluated through a Precipitation Amount (PA), Precipitation Frequency (PF), and Precipitation Intensity (PI) every hour. The results show that the maximum rainfall occurs in the afternoon and evening along the coast, and in the middle of the night and morning on the Kalimantan plains. Kalimantan has high rainfall intensity values at short rainfall durations, i.e. rain lasting less than 3 hours. This is expected to improve the quality of hydrometeorological disaster mitigation in Kalimantan.

THE BENEFITS OF NON-BIOLOGICAL THERAPY IN CHILDREN WITH AUTISM SPECTRUM DISORDER (ASD)

Introduction – Autism Spectrum Disorders (ASD) are a group of neurodevelopmental disorders characterized by three main problems, namely the presence of communication disorders, impaired reciprocal social interaction with the surrounding environment, and restricted, repetitive, and stereotyped behavior patterns in the first 3 years of age. In Indonesia, there were around 112,000 ASD sufferers in 2012, while in 2015 it was estimated that 1 in 250 children had ASD, or around 134,000 people. Methods – The author used the literature review method by collecting the results of several kinds of literature on ASD, and non-biological therapy and their benefits in ASD children. The literature on non-biological therapy and its benefits in ASD children is limited to 2011-2021. Results – Autism is a lifelong disorder, so it is important to recognize it as early as possible, and parents need to understand the problem. It's important to remember that the cause of autism is unknown, and no single drug has been found that can cure ASD, but some therapies can suppress ASD symptoms that can help ASD lead a more productive life by reducing symptoms and improving skills. Discuss – There is no definitive therapy that can cure ASD, but therapy is aimed at improving ASD symptoms. Non-biological therapy which includes behavioral therapy (such as TEACCH or ABA) is currently used as first-line therapy for ASD. Conclusion – Symptoms that appear in ASD children vary widely, therefore the therapy given is individual and depends on the circumstances and symptoms that appear. There are many types of non-biological therapies for ASD, such as ABA, TEACCH, PECS, Caregiver-mediated Intervention, Parent-mediated Communication, SIT, and AIT. These therapies have been shown to have benefits in improving ASD symptoms such as communication skills, social interaction, and behavior, where each therapy has different benefits in each type. These therapies are given to everyone as needed. Keywords: non-biological, children, autism.

Key Synaptic Pathology in Autism Spectrum Disorder: Genetic Mechanisms and Recent Advances.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social interactions and verbal communication, accompanied by symptoms of restricted and repetitive patterns of behavior or interest. Over the past 30 years, the morbidity of ASD has increased in most areas of the world. Although the pathogenesis of ASD is not fully understood, it has been associated with over 1000 genes or genomic loci, indicating the importance and complexity of the genetic mechanisms involved. This review focuses on the synaptic pathology of ASD and particularly on genetic variants involved in synaptic structure and functions. These include SHANK, NLGN, NRXN, FMR1, and MECP2 as well as other potentially novel genes such as CHD8, CHD2, and SYNGAP1 that could be core elements in ASD pathogenesis. Here, we summarize several pathological pathways supporting the hypothesis that synaptic pathology caused by genetic mutations may be the pathogenic basis for ASD.