Coordination Sequences Research Articles

FASTDLO: Fast Deformable Linear Objects Instance Segmentation

In this paper, an approach for fast and accurate segmentation of Deformable Linear Objects (DLOs) named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FASTDLO</i> is presented. A deep convolutional neural network is employed for background segmentation, generating a binary mask that isolates DLOs in the image. Thereafter, the obtained mask is processed with a skeletonization algorithm and the intersections between different DLOs are solved with a similarity-based network. Apart from the usual pixel-wise color-mapped image, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FASTDLO</i> also describes each DLO instance with a sequence of 2D coordinates, enabling the possibility of modeling the DLO instances with splines curves, for example. Synthetically generated data are exploited for the training of the data-driven methods, avoiding expensive collection and annotations of real data. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FASTDLO</i> is experimentally compared against both a DLO-specific approach and general-purpose deep learning instance segmentation models, achieving better overall performances and a processing rate higher than 20 FPS.

Structural and Electronic Effects on Phosphine Chalcogenide Stabilized Silicon Centers in Four-Membered Heterocyclic Cations.

Understanding the interplay of structural and electronic parameters in the stabilization of Lewis acidic silicon centers is crucial for stereochemical questions and applications in bond activation and catalytic transformations. Phosphine chalcogenide functionalized (Ch = O, S, and Se) hydrosilanes having tert-butyl and 2,4,6-trimethoxyphenyl (TMP) substituents on the silicon atom were synthesized, and the ring-closing reactions to afford the heterocyclic four-membered CPChSi cations were investigated. Synthetic access was only achieved for the sulfur- and selenium-based cations. A thorough study by means of single-crystal X-ray structure determination, NMR spectroscopic data, and density functional theory (DFT) calculations provided insight into important electronic and structural parameters affecting the stability of the intramolecularly stabilized cations. Detailed structural considerations were made on the contributions to the ring strain (angular strain and steric repulsion). Thermochemical investigations showed that the substituents on the silicon and phosphorus atoms play an important role for the stability of the cationic heterocycles. In the absence of large steric repulsions through bulky substituents (methyl groups on silicon and tert-butyl groups on phosphorus), an intrinsic stability sequence of the intramolecular Ch-Si coordination depending on the chalcogen atom in the direction Se ≤ S < O can be observed. However, the order is reversed (O < S < Se) in the case of strong repulsions between sterically demanding substituents (tert-butyl groups on both silicon and phosphorus atoms). Natural bond orbital (NBO) analysis supported the explanations for the observed deshielding trends in 31P NMR spectroscopy and revealed that the O-Si bond is more ionic in nature compared to the S-Si and Se-Si bonds, with the latter exhibiting higher covalent character due to a more efficient charge transfer through a σ-type nCh → pSi interaction.

Quantitative Evaluation of Environmental Loading Products and Thermal Expansion Effect for Correcting GNSS Vertical Coordinate Time Series in Taiwan

We explored the driving factors of nonlinear signals in vertical coordinate sequences of stations in a Taiwan global navigation satellite system (GNSS) network, including atmospheric loading (ATML), hydrological loading (HYDL), and non-tidal ocean loading (NTOL) effects. At the same time, we used the finite element analysis software MIDAS to quantify the vertical displacements of different types of monuments due to the thermal expansion effect, including deep drilled braced (DDB) and short drilled braced (SDB). By quantitatively comparing the correction results of GNSS time series with different single mass loading models, we found that there was little difference in the correction of different environmental loading products. We compared different combinations of each loading product to correct the GNSS time series, and finally selected the best combination suitable for Taiwan GNSS network, that is, ATML (GFZ_ECMWF IB) + HYDL (IMLS_MERRA2) + NTOL (IMLS_MPIOM06). We found that the spatial and temporal models of ATML and NTOL are very similar, with non-tidal atmospheric loading and non-tidal ocean loading working together, a pattern that may be related to tropical cyclones. Both models also showed good correction effect on GNSS stations in the western plain of Taiwan, but with limited correction effect in the eastern part of Taiwan. This may be due to the influence of the subtropical monsoon climate in Taiwan and the barrier of the central mountain range, resulting in obvious differences between eastern and western Taiwan. The hydrological loading was found to act in the opposite way to the thermal expansion effect in the temporal domain, indicating that some displacements in hydrological loading may cancel out displacements caused by the thermal expansion effect. This aspect of displacement is not included in the hydrological loading model but should be considered when accurately estimating the temporal and spatial variation of water storage capacity in Taiwan using GNSS observed displacements.

UAV-Supported Route Planning for UGVs in Semi-Deterministic Agricultural Environments

Automated agricultural operations must be planned and organized to reduce risk and failure potential while optimizing productivity and efficiency. However, the diversity of natural outdoor environments and the varied data types and volumes required to represent an agricultural setting comprise critical challenges for the deployment of fully automated agricultural operations. In this regard, this study develops an integrated system for enabling an unmanned aerial vehicle (UAV) supported route planning system for unmanned ground vehicles (UGVs) in the semi-structured environment of orchards. The research focus is on the underpinning planning system components (i.e., world representation or map generation or perception and path planning). In particular, the system comprises a digital platform that receives as input a geotagged depiction of an orchard, which is obtained by a UAV. The pre-processed data define the agri-field’s tracks that are transformed into a grid-based map capturing accessible areas. The grid map is then used to generate a topological path planning solution. Subsequently, the solution is translated into a sequence of coordinates that define the calculated optimal path for the UGV to traverse. The applicability of the developed system was validated in routing scenarios in a walnuts’ orchard using a UGV. The contribution of the proposed system entails noise reduction techniques for the accurate representation of a semi-deterministic agricultural environment for enabling accuracy in the route planning of utilized automated machinery.

Internal Similarity Network for Rejoining Oracle Bone Fragment Images

Rejoining oracle bone fragments plays an import role in studying the history and culture of the Shang dynasty by its characters. However, current computer vision technology has a low accuracy in judging whether the texture of oracle bone fragment image pairs can be put back together. When rejoining fragment images, the coordinate sequence and texture features of edge pixels from original and target fragment images form a continuous symmetrical structure, so we put forward an internal similarity network (ISN) to rejoin the fragment image automatically. Firstly, an edge equidistant matching (EEM) algorithm was given to search similar coordinate sequences of edge segment pairs on the fragment image contours and to locally match the edge coordinate sequence of an oracle bone fragment image. Then, a target mask-based method was designed in order to put two images into a whole and to cut a local region image by the local matching edge. Next, we calculated a convolution feature gradient map (CFGM) of the local region image texture, and an internal similarity pooling (ISP) layer was proposed to compute the internal similarity of the convolution feature gradient map. Finally, ISN was contributed in order to evaluate a similarity score of a local region image texture and to determine whether two fragment images are a coherent whole. The experiments show that the correct judgement probability of ISN is higher than 90% in actual rejoining work and that our method searched 37 pairs of correctly rejoined oracle bone fragment images that have not been discovered by archaeologists.

An End-to-End Classifier Based on CNN for In-Air Handwritten-Chinese-Character Recognition

A convolutional neural network (CNN) has been successfully applied to in-air handwritten-Chinese-character recognition (IAHCCR). However, the existing models based on CNN for IAHCCR need to convert the coordinate sequence of a character into images. This conversion process increases training and classifying time, and leads to the loss of information. In order to solve this problem, we propose an end-to-end classifier based on CNN for IAHCCR in this paper, which, to knowledge, is novel for online handwritten-Chinese-character recognition (OLHCCR). Specifically, our model based on CNN directly takes the original coordinate sequence of an in-air handwritten-Chinese-character as input, and the output of the full connection layer is pooled by global average pooling to form a fixed-size feature vector, which is sent to softmax for classification. Our model can not only directly process coordinate sequences such as the models based on recurrent neural network (RNN), but can also obtain the global structure information of characters. We conducted experiments on two datasets, IAHCC-UCAS2016 and SCUT-COUCH2009. The experimental results show a comparison with existing CNN models based on image processing or RNN-based methods; our method does not require data augmentation techniques nor an ensemble of multiple trained models, and only uses a more compact structure to obtain higher recognition accuracy.

Handling Turn Transitions in Australian Tactile Signed Conversations

ABSTRACT This article explores how deafblind Australian Sign Language (Auslan) users, who communicate through an alternative range of modalities including tactile (hands) and kinetic (body movement) inputs, manage turn transitions. Studies of deafblind communication have typically employed a signal-based approach. In contrast, this article applies broader Conversational Analysis (CA) frameworks, which have been developed based on interlocutors who primarily rely on auditory-vocal and visual resources but have been productively applied to a range of languages, participants, and settings. Through fine-grained analyses of a single case study, this article examines how tactile Auslan signers orient to the relevance of turn transitions at possible completion points. The research illuminates the mechanics of how tactile Auslan signers negotiate turns and advances our understanding of both the analytical potentials of CA and the ways particular deafblind Auslan signers coordinate sequences, actions, and multimodalities in their interactional choreography. Data are in tactile Auslan.

On the growth of the wallpaper groups.

Coordination sequences (also called growth functions) appear in various areas of chemistry and crystallography, such as ice crystals and zeolites, and various areas of mathematics, such as lattice theory and geometric group theory. Cannon's method of cone types is modified for finding the coordination sequence of the Cayley graph of a group. This method is then applied to compute the growth functions and the growth series of the Cayley graphs of the wallpaper groups (the 2D crystallographic groups). The paper has several tables and colored figures summarizing and illustrating the results.

Video-Based 3D pose estimation for residential roofing

ABSTRACT Residential roofers are often exposed to awkward postures and motions in a prolonged time, which may not only reduce their body stability and increase fall potential, but also increase the risk of musculoskeletal disorders (MSDs). To assess their risks of fatal and musculoskeletal injuries, it is crucial to capture 3D body poses of workers during roofing tasks. In this paper, we proposed a novel two-stage motion estimation approach based on a convolution neural network to estimate residential roofer’s body poses using three-view video data. Our approach includes two stages: (1) use of an offline multi-view model to estimate the 3D pose in a single frame; (2) use of a multi-frame model to apply temporal convolutions to refine the multi-view outputs. The performance of the approach was evaluated by comparing our estimation with the gold-standard marker-based 3D human pose during one of the common residential roofing tasks – shingle installation. The evaluation results show that the proposed multi-frame model can effectively improve the accuracy of the coordinate sequence. Moreover, these results prove that the proposed video-based motion estimation approach can efficiently and accurately locate 3D body joints and pave the way for future onsite motion analysis during roofing activities.

A Shape Reconstruction and Measurement Method for Spherical Hedges Using Binocular Vision.

The center coordinate and radius of the spherical hedges are the basic phenotypic features for automatic pruning. A binocular vision-based shape reconstruction and measurement system for front-end vision information gaining are built in this paper. Parallel binocular cameras are used as the detectors. The 2D coordinate sequence of target spherical hedges is obtained by region segmentation and object extraction process. Then, a stereo correcting algorithm is conducted to keep two cameras to be parallel. Also, an improved semi-global block matching (SGBM) algorithm is studied to get a disparity map. According to the disparity map and parallel structure of the binocular vision system, the 3D point cloud of the target is obtained. Based on this, the center coordinate and radius of the spherical hedges can be measured. Laboratory and outdoor tests on shape reconstruction and measurement are conducted. In the detection range of 2,000–2,600 mm, laboratory test shows that the average error and average relative error of standard spherical hedges radius are 1.58 mm and 0.53%, respectively; the average location deviation of the center coordinate of spherical hedges is 15.92 mm. The outdoor test shows that the average error and average relative error of spherical hedges radius by the proposed system are 4.02 mm and 0.44%, respectively; the average location deviation of the center coordinate of spherical hedges is 18.29 mm. This study provides important technical support for phenotypic feature detection in the study of automatic trimming.

Evaluation of text-to-gesture generation model using convolutional neural network

Conversational gestures have a crucial role in realizing natural interactions with virtual agents and robots. Data-driven approaches, such as deep learning and machine learning, are promising in constructing the gesture generation model, which automatically provides the gesture motion for speech or spoken texts. This study experimentally analyzes a deep learning-based gesture generation model from spoken text using a convolutional neural network. The proposed model takes a sequence of spoken words as the input and outputs a sequence of 2D joint coordinates representing the conversational gesture motion. We prepare a dataset consisting of gesture motions and spoken texts by adding text information to an existing dataset and train the models using specific speaker’s data. The quality of the generated gestures is compared with those from an existing speech-to-gesture generation model through a user perceptual study. The subjective evaluation shows that the model performance is comparable or superior to those by the existing speech-to-gesture generation model. In addition, we investigate the importance of data cleansing and loss function selection in the text-to-gesture generation model. We further examine the model transferability between speakers. The experimental results demonstrate successful model transferability of the proposed model. Finally, we show that the text-to-gesture generation model can produce good quality gestures even when using a transformer architecture.

Multi-scale coal and gangue dual-energy X-ray image concave point detection and segmentation algorithm

The premise of identifying, locating, and sorting coal and gangue using photoelectric sorting technology is that independent image targets should be obtained. In this study, concave point detection and segmentation algorithm are proposed to segment overlapping particles. First, the edge coordinate sequence is obtained for the overlapping part of the concave defect area of the adhesion target and the binary image of the adhesion target. Subsequently, the initial linear equation passing through the beginning and ending points of the sequence is built. The traversal sequence updates the new linear equation parallel to the initial linear equation, and the positional relationship between the front and back points of the search point and the linear equation is determined. The concave point detection is transformed into the positional relationship between pixels and linear equations. Lastly, the segmentation line segmentation image is generated based on concave points, and the segmentation accuracy reaches 93.15%.

Coordination sequences of periodic structures are rational via automata theory.

The conjecture of Grosse-Kunstleve et al. [(1996), Acta Cryst. A52, 879-889], that coordination sequences of periodic structures in n-dimensional Euclidean space are rational, is proved. This has been recently proven by Nakamura et al. [(2021), Acta Cryst. A77, 138-148]; however, the proof presented here is a straightforward application of classic techniques from automata theory.

Application Progress of Transcranial Direct Current Stimulation Combined with Limb Therapy in Rehabilitation of Lower Limbs after Stroke

Motor dysfunction of lower extremities is one of the most common and urgent problems to be solved in patients with stroke. Even if early and standardized rehabilitation therapy, there are still many patients who cannot restore their walking function or have serious abnormal gait after 6 months of onset. It has a great impact on their daily activities and self-care ability, and brings a heavy economic burden to the society and family financial situation. Rehabilitation interventions for motor dysfunction of lower extremities include central intervention techniques and peripheral intervention techniques. Central intervention technology stimulates the brain, such as neuroregulation and scalp acupuncture, while peripheral intervention technology stimulates limbs, such as functional electrical stimulation (FES) and robot-assisted gait training (RAGT). Although the two technologies have different stimulation targets, the same purpose, previous studies found that the treatment effect was better when combined application of effective central intervention technology with peripheral intervention technology. It is called brain-limb coordinated regulation therapy technology, which can be divided into brain-upper-limb coordinated therapy mode and brain-lower-limb coordinated therapy mode according to different coordinated parts. The technology can be divided into synchronous brain-limb coordination therapy mode and asynchronous brain-limb coordination therapy mode according to the different coordination sequence. The asynchronous mode can be further divided into the mode of stimulating the brain first and then the limbs, and the mode of stimulating the limbs first and then the brain. At present, this technique is widely used in clinical research. Transcranial direct current stimulation (tDCS) is widely used in combination with lower limb rehabilitation therapy because of its advantages such as high safety, easy to carry equipment and long delayed effect time. However, the therapeutic effect of this kind of synergistic therapy is quite different, due to the different lower limb rehabilitation techniques and different sequence involved in the synergistic therapy. This article reviews the application progress of tDCS with different treatment parameters combined with different lower limb rehabilitation techniques and different cooperative treatment sequence in stroke, and discusses the factors which affect the effect of cooperative treatment and the possible effective cooperative treatment mode, in order to provide new ideas for the treatment of lower limb dysfunction after stroke.

Contrast-Reconstruction Representation Learning for Self-Supervised Skeleton-Based Action Recognition.

Skeleton-based action recognition is widely used in varied areas, e.g., surveillance and human-machine interaction. Existing models are mainly learned in a supervised manner, thus heavily depending on large-scale labeled data, which could be infeasible when labels are prohibitively expensive. In this paper, we propose a novel Contrast-Reconstruction Representation Learning network (CRRL) that simultaneously captures postures and motion dynamics for unsupervised skeleton-based action recognition. It consists of three parts: Sequence Reconstructor (SER), Contrastive Motion Learner (CML), and Information Fuser (INF). SER learns representation from skeleton coordinate sequence via reconstruction. However the learned representation tends to focus on trivial postural coordinates and be hesitant in motion learning. To enhance the learning of motions, CML performs contrastive learning between the representation learned from coordinate sequences and additional velocity sequences, respectively. Finally, in the INF module, we explore varied strategies to combine SER and CML, and propose to couple postures and motions via a knowledge-distillation based fusion strategy which transfers the motion learning from CML to SER. Experimental results on several benchmarks, i.e., NTU RGB+D 60/120, PKU-MMD, CMU, and NW-UCLA, demonstrate the promise of the our method by outperforming state-of-the-art approaches.

Compensatory action of the index and middle finger in the kinematic chain of a basketball shot

Purpose Performing effective actions requires the basketball player to balance factors such as motor variability, error minimalization and a complex sequence of coordination to determine the best action. Aim of study. The aim of the study was to differentiate the strength of the muscles of the index and middle fingers when performing a basketball shot. Methods Material and method. Study group enrolled 122 male college basketball league students. The study included psychophysiological tests to determine indices of individual and typological characteristics of higher nervous activity, proprioceptive sensitivity tests of the fingers of the leading hand, and field tests to assess participants' shooting skills. The touch-based finger pressure sensing system measured the different levels of pressure exerted by the participants' main index and middle finger during grasping. Results For both the middle and index finger, the highest correlation with shot efficiency was found for a 120 g load g (p &lt; 0,01 for 2PS; 2PS40 suc; FT; 3PSO and 3,5mS). Furthermore, high reproducibility of proprioceptive sensitivity of the index and middle finger of the leading hand was found in basketball players. Conclusions The research indicates that it is possible to organize compensatory behavior between joints on the basis of proprioception, with the last compensatory movements of the kinematic chain being performed by the fingers of the hand. The demonstrated high proprioceptive sensitivity of the index and middle finger of the leading hand in basketball players at a weekly interval may indicate ability to maintain high repeatability of movements controlled by these fingers.

Compensatory action of the index and middle finger in the kinematic chain of a basketball shot

Purpose Performing effective actions requires the basketball player to balance factors such as motor variability, error minimalization and a complex sequence of coordination to determine the best action. Aim of study. The aim of the study was to differentiate the strength of the muscles of the index and middle fingers when performing a basketball shot. Methods Material and method. Study group enrolled 122 male college basketball league students. The study included psychophysiological tests to determine indices of individual and typological characteristics of higher nervous activity, proprioceptive sensitivity tests of the fingers of the leading hand, and field tests to assess participants' shooting skills. The touch-based finger pressure sensing system measured the different levels of pressure exerted by the participants' main index and middle finger during grasping. Results For both the middle and index finger, the highest correlation with shot efficiency was found for a 120 g load g (p &lt; 0,01 for 2PS; 2PS40 suc; FT; 3PSO and 3,5mS). Furthermore, high reproducibility of proprioceptive sensitivity of the index and middle finger of the leading hand was found in basketball players. Conclusions The research indicates that it is possible to organize compensatory behavior between joints on the basis of proprioception, with the last compensatory movements of the kinematic chain being performed by the fingers of the hand. The demonstrated high proprioceptive sensitivity of the index and middle finger of the leading hand in basketball players at a weekly interval may indicate ability to maintain high repeatability of movements controlled by these fingers.

Exploring Project-Based Teaching for Engaging Students' Mathematical Learning

The declining interest of learners in mathematics in the learning process has resulted in poor achievement (Yeh et al., 2019). To get rid of these poor achievements, we explored project-based teaching in four topical areas (e.g., mathematical concepts of coordinate geometry, trigonometry, sequence, and series) in the school mathematics. This paper results from observing changes in engagement of learners in learning mathematics by motivating them through the project-based learning (PBL) guided by two theories – knowledge constitutive interests (Habermas, 1972), and collaborative and cooperative learning under the paradigms of interpretivism and criticalism. In this ethos, PBL is an “engaging and learner-directed approach that provides equal opportunities for students to explore their knowledge and understanding” (Thomas, 2000, p. 12). More specifically, we adopted the 'action research' method with the secondary level students (Grade IX) of one of the institutional schools in their classrooms. The information was collected by observing and recording the changes seen in consecutive seventeen days. The research landed that project-based learning is an appropriate pedagogy for engaged learning. The study revealed that the students were motivated while they got opportunities to interact in the projects. Moreover, the findings show that PBL is helpful to engage the learners through questioning, pair/group discussion, discovery learning, and concept mapping.

Norm form equations and linear divisibility sequences

Finding integer solutions to norm form equations is a classical Diophantine problem. Using the units of the associated coefficient ring, we can produce sequences of solutions to these equations. It is known that these solutions can be written as tuples of linear recurrence sequences. We show that for certain families of norm forms defined over quartic fields, there exist integrally equivalent forms making any one fixed coordinate sequence a linear divisibility sequence.

Development of bipedal walking in olive baboons, Papio anubis: A kinematic analysis.

Although extant nonhuman primates are not habitual bipeds, they are able to walk bipedally from an early age. In humans, children improve their walking skills through developmental processes and learning experience. In nonhuman primates, infants do not routinely experience bipedalism and their musculoskeletal system gradually specializes for other locomotor modes. The aim of this study is to explore the development of occasional bipedal walking in olive baboon and to test whether the postural adjustments change with age. We collected kinematics and spatiotemporal parameters of bipedal gait in an ontogenetic sample of 24 baboons. Data were collected at the primatology station of the CNRS (France) and a total of 47 bipedal strides were extracted for the present analysis. Adults and adolescents walk bipedally in the same way, and the average kinematic pattern is similar across the age-classes. Infants walk bipedally with longer duty factor, they present larger movement amplitude of the thigh and the amplitude of the knee joint decreases with speed. In contrast, older baboons increase the amplitude of the knee and ankle joints with speed. In a non-adapted biped, the postural adjustments of bipedal walking vary with age. In infant baboons, the balance requirements are likely to be higher and these are solved by adopting a "blocking strategy". In older baboons, the postural adjustments are focused on the lower limb and the movements increase with speed. These results may echo, in some respects, the developmental sequence of the intersegmental coordination described in the ontogeny of human locomotion.