Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning basis skills by autonomous segmentation of humanoid motion trajectories

Manipulation tasks are characterized by continuous motion trajectories containing a set of key phases. In this paper, we propose a probabilistic method to autonomously segment the motion trajectories for estimating the key phases embedded in such a task. The autonomous segmentation process relies on principal component analysis to adaptively project into one of the low-dimensional subspaces, in which a Gaussian mixture model is learned based on Bayesian information criterion and expectation-maximization algorithms. The basis skills are estimated by a set of Gaussians approximating quasi-linear key phases, and those times spent calculated from the segmentation points between two consecutive Gaussians representing the local changes of dynamics and directions of the trajectories. The basis skills are then used to build novel motion trajectories with possible motion alternatives and optional parts. After sequentially reorganizing the basis skills, a Gaussian mixture regression process is used to retrieve smooth motion trajectories. Two experiments are presented to demonstrate the capability of the autonomous segmentation approach.
Integrating Information Systems Using Normalized Systems Theory: Four Case Studies

New technical and business opportunities lead to the adoption of new information systems. Integrating these new systems with the existing application landscape poses many challenges, especially when legacy systems are involved. These systems may rely on completely different architectures or assumptions regarding functionality. Normalized Systems Theory addresses this issue by stating that information systems should behave as stable systems. It identifies the main obstacle to achieving stability, so-called combinatorial effects, and proposes four design theorems to avoid these combinatorial effects. Based on these theorems, a set of exemplary software elements are created which can be used to generate applications. In this paper, we demonstrate the real-world usage of these software elements in legacy integration projects by describing four case studies. From a theoretical perspective, these cases validate the theorybased approach of Normalized Systems Theory. From a practical perspective, these cases demonstrate how adoption of Normalized Systems software could be approached: first, by integrating existing systems, and second, by building future applications adhering to the theory.
Robust Boundary DetectionWith Adaptive Grouping

This paper presents a perceptual grouping algorithm that performs boundary extraction on natural images. Our grouping method maintains and updates a model of the appearance of the image regions on either side of a growing contour. This model is used to change grouping behaviour at run-time, so that, in addition to following the traditional Gestalt grouping principles of proximity and good continuation, the grouping procedure favours the path that best separates two visually distinct parts of the image. The resulting algorithm is computationally efficient and robust to clutter and texture. We present experimental results on natural images from the Berkeley Segmentation Database and compare our results to those obtained with three alternate grouping methods.
Wide‐angle triangulation array study of simultaneous primary microseism sources

Persistent low frequency noise between 10 and 200 mHz due to storm systems is commonly observed as microseisms on seismic records from land and ocean bottom detectors. We report on an analysis of 20-second microseisms recorded simultaneously on two land-based long-period arrays (the Alaskan Long Period Array and the Large Aperture Seismic Array) during November 1973. Azimuths of approach are determined by applying frequency wave-number analysis and beam-forming techniques to coherent bandpass-filtered samples of the microseismic noise field recorded by the arrays. Microseismic source azimuths exhibit sufficient stability over periods of one hour to permit determination of reliable source locations by triangulation with the two arrays. Locations for two microseism noise sources associated with two separate Atlantic and Pacific pelagic storms were found simultaneously with these methods. In both cases, the microseismic noise source appears to be associated with nearshore processes. Although the gross spectral character of the microseisms displays the commonly observed primary- and double-frequency microseism peaks, slight spectral differences are apparent for the two noise sources.
An Efficient GPU Implementation for Large Scale Individual-Based Simulation of Collective Behavior

In this work we describe a GPU implementation for an individual-based model for fish schooling. In this model each fish aligns its position and orientation with an appropriate average of its neighbors’ positions and orientations. This carries a very high computational cost in the so-called nearest neighbors search. By leveraging the GPU processing power and the new programming model called CUDA we implement an efficient framework which permits to simulate the collective motion of high-density individual groups. In particular we present as a case study a simulation of motion of millions of fishes. We describe our implementation and present extensive experiments which demonstrate the effectiveness of our GPU implementation.
Analytical expression for the relative dispersion of the cloud droplet size distribution

An analytical expression that relates the relative dispersion (ratio of standard deviation to mean radius) of the cloud droplet size distribution to CCN spectra and updraft velocity is derived from adiabatic growth theory of cloud droplets. Coupled with the Twomey expression for droplet concentration, the analytical expression is used to examine the relationship of relative dispersion to droplet concentration under different combinations of CCN spectra and updraft velocities. These analytical results compare favorably with the corresponding simulations of an adiabatic parcel model. The analytical expression theoretically demonstrates that an increase in aerosol loading (CCN concentration) leads to concurrent increases in the droplet concentration and relative dispersion whereas a larger updraft velocity leads to a higher droplet concentration but a smaller relative dispersion.
Phylogenetic analyses place the Australian monotypic Revwattsia in Dryopteris (Dryopteridaceae)

Abstract Revwattsia fragilis (Watts) D.L. Jones (Dryopteridaceae), originally described as a Polystichum Roth by the pioneer Australian botanist Reverend W.W. Watts in 1914, is a rare epiphytic fern endemic to northeastern Queensland, Australia. Known from only a few populations, it is restricted to tropical rainforests in the Atherton Tablelands. We used the cpDNA markers psbA-trnH, rbcL, rbcL-accD, rps4-trnS, trnG-trnR, trnL-trnF, and trnP-petG to infer the relationships of Revwattsia fragilis within Dryopteridaceae. Based on our molecular analysis, we were able to reject Watts’s 1914 hypothesis of a close relationship to Polystichum. Its closest allies are a suite of Asian Dryopteris Adans. species including Dryopteris labordei, Dryopteris gymnosora, Dryopteris erythrosora and Dryopteris cystolepidota; maintaining Revwattsia renders Dryopteris paraphyletic. The epiphytic habit and distinctive long-creeping rhizome of Revwattsia appear to be autapomorphies and do not warrant its generic status. In the course of our investigation we confirmed that polyphyly of Dryopteris is also sustained by the inclusion of Acrorumohra (H.Itô) H. Itô, Acrophorus C.Presl, Arachniodes Blume, Diacalpe Blume, Dryopsis Holttum & P.J.Edwards, and Peranema D.Don. The epithet fragilis is occupied in Dryopteris, therefore we provide the name Dryopteris wattsii nom. nov. to accommodate Revwattsia fragilis in Dryopteris.
Temporal difference learning waveform selection

The largest difference between cognitive radar and other adaptive radar is the adaptivity of transmitter in cognitive radar. How to optimally decide or select the radar waveform for next transmission based on the observation of past radar returns is one of the important issues. In this paper, with the stochastic dynamic programming model of waveform selection, we use the method of temporal difference learning to solve this problem and realize the adaptivity of waveform selection. The simulation results show that the uncertainty of state estimation using temporal difference learning is less than that using fixed waveform.
Graph Based Models for Unsupervised High Dimensional Data Clustering and Network Analysis

The demand for analyzing patterns and structures of data is growing dramatically in recent years. The study of network structure is pervasive in sociology, biology, computer science, and many other disciplines. My research focuses on network and high-dimensional data analysis, using graph based models and tools from sparse optimization. The specific question about networks we are studying is clustering : partitioning a network into cohesive groups. Depending on the contexts, these tightly connected groups can be social units, functional modules, or components of an image. My work consists of both theoretical analysis and numerical simulation. We first analyze some social network and image datasets using a quality function called modularity , which is a popular model for clustering in network science. Then we further study the modularity function from a novel perspective: with my collaborators we reformulate modularity optimization as a minimization problem of an energy functional that consists of a total variation term and an L2 balance term. By employing numerical techniques from image processing and L1 compressive sensing, such as the Merriman-Bence-Osher (MBO) scheme, we develop a variational algorithm for the minimization problem. Along a similar line of research, we work on a multi-class segmentation problem using the piecewise constant Mumford-Shah model in a graph setting. We propose an efficient algorithm for the graph version of Mumford-Shah model using the MBO scheme. Theoretical analysis is developed and a Lyapunov functional is proven to decrease as the algorithm proceeds. Furthermore, to reduce the computational cost for large datasets, we incorporate the Nystrom extension method to efficiently approximates eigenvectors of the graph Laplacian based on a small portion of the weight matrix. Finally, we implement the proposed method on the problem of chemical plume detection in hyper-spectral video data. These graph based clustering algorithms we proposed improve the time efficiency significantly for large scale datasets. In the last chapter, we also propose an incremental reseeding strategy for clustering, which is an easy-to-implement and highly parallelizable algorithm for multiway graph partitioning. We demonstrate experimentally that this algorithm achieves state-of-the-art performance in terms of cluster purity on standard benchmark datasets. Moreover, the algorithm runs an order of magnitude faster than the other algorithms.
N‐methyl‐N‐nitrosourea induces retinal degeneration in the rat via the inhibition of NF‐κB activation

Retinitis pigmentosa (RP) is a group of inherited neurodegenerative diseases characterized by the loss of photoreceptor cells through apoptosis. N‐methyl‐N‐nitrosourea (MNU) is an alkylating toxicant that induces photoreceptor cell death resembling hereditary RP. This study aimed to investigate the role of nuclear factor κB (NF‐κB) in MNU‐induced photoreceptor degeneration. Adult rats received a single intraperitoneal injection of MNU (60 mg/kg bodyweight). Hematoxylin and eosin staining demonstrated progressive outer nuclear layer (ONL) loss after MNU treatment. Transmission electron microscopy revealed nuclear pyknosis, chromatin margination in the photoreceptors, increased secondary lysosomes, and lobulated retinal‐pigmented epithelial cells in MNU‐treated rats. Numerous photoreceptor cells in the ONL showed positive TUNEL staining and apoptosis rate peaked at 24 hours. Enhanced depth imaging spectral‐domain optical coherence tomography showed ONL thinning and decreased choroid thickness. Electroretinograms showed decreased A wave amplitude that predominated in scotopic conditions. Western blot analysis showed that nuclear IκBα level increased, whereas nuclear NF‐κB p65 decreased significantly in the retinas of MNU‐treated rats. These findings indicate that MNU leads to selective photoreceptor degradation, and this is associated with the inhibition of NF‐κB activation.
Trends in marriage and time spent single in sub-Saharan Africa: a comparative analysis of six population-based cohort studies and nine Demographic and Health Surveys

Objectives: To describe trends in age at first sex (AFS), age at first marriage (AFM) and time spent single between events and to compare age-specific trends in marital status in six cohort studies. Methods: Cohort data from Uganda, Tanzania, South Africa, Zimbabwe and Malawi and Demographic and Health Survey (DHS) data from Uganda, Tanzania and Zimbabwe were analysed. Life table methods were used to calculate median AFS, AFM and time spent single. In each study, two surveys were chosen to compare marital status by age and identify changes over time. Results: Median AFM was much higher in South Africa than in the other sites. Between the other populations there were considerable differences in median AFS and AFM (AFS 17–19 years for men and 16–19 years for women, AFM 21–24 years and 18–19 years, respectively, for the 1970–9 birth cohort). In all surveys, men reported a longer time spent single than women (median 4–7 years for men and 0–2 years for women). Median years spent single for women has increased, apart from in Manicaland. For men in Rakai it has decreased slightly over time but increased in Kisesa and Masaka. The DHS data showed similar trends to those in the cohort data. The age-specific proportion of married individuals has changed little over time. Conclusions: Median AFS, AFM and time spent single vary considerably among these populations. These three measures are underlying determinants of sexual risk and HIV infection, and they may partially explain the variation in HIV prevalence levels between these populations.
Highly Nonrigid Object Tracking via Patch-Based Dynamic Appearance Modeling

A novel tracking algorithm is proposed for targets with drastically changing geometric appearances over time. To track such objects, we develop a local patch-based appearance model and provide an efficient online updating scheme that adaptively changes the topology between patches. In the online update process, the robustness of each patch is determined by analyzing the likelihood landscape of the patch. Based on this robustness measure, the proposed method selects the best feature for each patch and modifies the patch by moving, deleting, or newly adding it over time. Moreover, a rough object segmentation result is integrated into the proposed appearance model to further enhance it. The proposed framework easily obtains segmentation results because the local patches in the model serve as good seeds for the semi-supervised segmentation task. To solve the complexity problem attributable to the large number of patches, the Basin Hopping (BH) sampling method is introduced into the tracking framework. The BH sampling method significantly reduces computational complexity with the help of a deterministic local optimizer. Thus, the proposed appearance model could utilize a sufficient number of patches. The experimental results show that the present approach could track objects with drastically changing geometric appearance accurately and robustly.
Role of the Indian Ocean in the ENSO–Indian Summer Monsoon Teleconnection in the NCEP Climate Forecast System

AbstractThe observed negative correlation between El Nino–Southern Oscillation (ENSO) and the Indian summer monsoon is not simulated by the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) coupled model. The correlation is partially restored in the simulations where the Indian Ocean (IO) sea surface temperature (SST) is prescribed with the daily mean or climatology. Comparison among the simulations suggests that ENSO-induced SST anomalies form a strong dipole pattern oriented along the zonal direction in the IO in the coupled model, preventing the ENSO signals from reaching the Indian monsoon region. In the model, the dipole develops early in the monsoon season and extends to the central equatorial IO while it is formed at the end of the season in observations. The dipole modifies low-level winds and surface pressure, and grows in a positive feedback loop involving winds, surface pressure, and SST. Examination of the mean state in the model reveals that the thermocline is.
A Zero Velocity Detection Algorithm Using Inertial Sensors for Pedestrian Navigation Systems

In pedestrian navigation systems, the position of a pedestrian is computed using an inertial navigation algorithm. In the algorithm, the zero velocity updating plays an important role, where zero velocity intervals are detected and the velocity error is reset. To use the zero velocity updating, it is necessary to detect zero velocity intervals reliably. A new zero detection algorithm is proposed in the paper, where only one gyroscope value is used. A Markov model is constructed using segmentation of gyroscope outputs instead of using gyroscope outputs directly, which makes the zero velocity detection more reliable.
Discouraged Workers? Job Search Outcomes of Older Workers

Many have suggested we adopt policies that explicitly encourage the elderly to work. Behind this suggestion is the assumption that if an older person desires a job, one will be found; however, little is known about the extent to which this is true, and in the Health and Retirement Study, many more respondents say they expect to work after retirement than actually undertake work. This raises an important question: To what extent can the elderly readily find suitable jobs? In the context of a theoretical job search model, we examine the decision to search for a job and the probability of transitioning to employment using a large sample of non-workers from the Health and Retirement Study. The effects of both supply-side factors (individual characteristics) and demand-side factors (local labor market conditions) are estimated. We find employment transition rates are relatively low for older searchers: only half of older searchers successfully attain jobs. We examine various explanations for this result, including variation in search intensity, reservation wages, and the possibility of intervening health shocks. We conclude that about 13% of older job searchers becomes a discouraged worker in the sense of being willing to work at the prevailing wage, but unable to find a job.
Development of vocal tract length normalized phonetic engine for Gujarati and Marathi languages

Phonetic engine (PE) is a system that converts speech sound units into symbols without any higher-level information (such as semantic or linguistic details). This paper presents the development of PE in two Indian languages, viz., Gujarati and Marathi. To investigate the performance of PE, speech recorded in three different modes, viz., read, spontaneous and lecture is considered. Database consists of a large number of speakers in each mode for these languages. In order to reduce the effects of speaker differences in the databases, Vocal Tract Length Normalization (VTLN) using Lee-Rose method is incorporated. Here, performances of PEs are tested using state-of-the-art Mel frequency cepstral coefficients (MFCC) and vocal tract length normalized features. Hidden Markov model (HMM)-based approach is used for modeling the phonetic units. On an average, improvement of 3.12 % and 1.32 % is achieved using vocal tract length normalized PE over MFCCs for Gujarati and Marathi, respectively.
Feature versus model based noise robustness

Over the years, the focus in noise robust speech recognition has shifted from noise robust features to model based techniques such as parallel model combination and uncertainty decoding. In this paper, we contrast prime examples of both approaches in the context of large vocabulary recognition systems such as used for automatic audio indexing and transcription. We look at the approximations the techniques require to keep the computational load reasonable, the resulting computational cost, and the accuracy measured on the Aurora4 benchmark. The results show that a well designed feature based scheme is capable of providing recognition accuracies at least as good as the model based approaches at a substantially lower computational cost.
Clinical Applications of Electrical Stimulation After Spinal Cord Injury

Abstract Summary: During the last one-half century, electrical stimulation has become dinically significant for improving health and restoring useful function afterspinal cord injury. Short-term stimulation can be provided by electrodes on the skin or percutaneous fine wires, but implanted systems are preferable for long-term use. Electrical stimulation of intact lower motor neurons can exercise paralyzed musdes and reverse wasting; improve strength, endurance, and cardiovascular fitness; and may reduce the progression of osteoporosis. Other potential therapeutic uses being investigated indude reduction of spasticity, prevention of deep vein thrombosis, and improvement of tissue health. Pacing of intact phrenic nerves in high tetraplegia can produce effective respiration without mechanical ventilation, allowing improved speech, increased mobility, and increased sense of well-being. lmprovement of cough has also been demonstrated. Stimulation of intact sacral ne.rves can produce effective micturition and reduce urinary tract infection; it can also improve bowel function and erection. lt is usually combined with posterior sacral rhizotomy to improve continence and bladder capacity, and the combination has been shown to reduce costs of care. Electroejaculation can now produce semen in most men with spinal cord injury. Significant achievements have also been made in restoring limb function . Useful hand grasp can be provided in CS and C6 tetraplegia, reducing dependence on adapted equipment and assistants. Standing, assistance with transfers, and walking for short distances can be provided to selected persons with paraplegia, improving their access to objects, places, and opportunities that are inaccessible from a wheelchair. This review summarizes the current state of therapeutic and neuroprosthetic applications of electrical stimulation afterspinal cord injury and identifies some future directions of research and dinical and commercial development.
A geometric nonlinear observer for simultaneous localisation and mapping

The Simultaneous Localisation and Mapping (SLAM) problem involves estimating the pose of a robot relative to landmarks observed in the environment while at the same time estimating the location of those landmarks in the environment. This paper introduces a framework in which the landmarks and robot pose can be modelled in a single geometric structure, that of a homogeneous space obtained as the quotient of a novel Lie-group that we term the SLAMn(3) group. Using this formulation we apply techniques from observer design for symmetric systems to derive a novel observer for the SLAM problem posed in continuous-time.
Why do cells have multiple error‐prone DNA polymerases?

Recent years have witnessed the emergence of a plethora of so‐called novel DNA polymerases in both eukaryotic and prokaryotic cells. Many of these DNA polymerases are characterized by poor replicational fidelity and low processivity, and are devoid of 3′ → 5′ exonuclease activity. This article describes the discovery of these error‐prone polymerases and what is known about their biological function. Environ. Mol. Mutagen. 38:105–110, 2001. © 2001 Wiley‐Liss, Inc.