Miracle-dz/UniFAR-FTUs huggingface dataset:
Powered walking based on the passive dynamic principles: A virtual slope walking approach

The presented work is motivated to implement the principles of passive dynamic walking (PDW) on the powered bipeds. The Virtual Slope Walking (VSW), as one PWD control approach, is chosen to be mathematically analyzed and realized to achieve fast dynamic walking. Our method of formulating the fixed point of the limit cycle gait is presented, and the walking pattern generation is designed in the polar coordinate for the better consistency with the model. The algorithms are implemented on a planar robot Stepper-2D, which achieved the walking speed from 0.69m/s upto 1.03m/s. The self-stabilized walking has the best robustness at the speed of 0.81m/s, where the robot was able to walk on the level ground, step over random obstacles smaller than 4% of the leg length, and step over a big obstacle of 7.2% of the leg length.
An algorithm for distributed cooperative precoder selection in a cellular network

The performance in the downlink of a reuse 1:1 cellular wireless system is severely degraded due to the interference originating from adjacent cell sites. Even the spectral efficiency gains due to MIMO vanish for cell-edge users who are interference limited. Cooperative MIMO, which involves coordination amongst base stations serving adjacent cell-sites, is a promising technique to address the co-channel interference problem. In this paper, we study cooperation in the downlink of an interference channel. The basestations cooperate amongst themselves to arrive separately at precoding strategies which improve the signal-to-interference-and-noise ratio of the cell-edge users and hence the throughput. We propose a distributed algorithm that independently determines the precoder which mitigates the interference to the neighboring cell edge users without compromising on the in-cell performance. This algorithm requires only modest levels of on-air-feedback and information exchange among the basestations on the backhaul networks.
Fast Algorithms for Constant Approximation k-Means Clustering

In this paper we study the k-means clustering problem. It is well-known that the general version of this problem is NP -hard. Numerous approximation algorithms have been proposed for this problem. In this paper, we propose three constant approximation algorithms for k-means clustering. The first algorithm runs in time O(( k )nd), where k is the number of clusters, n is the size of input points, and d is dimension of attributes. The second algorithm runs in time O(kn log n). This is the first algorithm for k-means clustering that runs in time polynomial in n, k and d simultaneously. The run time of the third algorithm ( O(k log kd) ) is independent of n. Though an algorithm whose run time is independent of n is known for the k-median problem, ours is the first such algorithm for the k-means problem.
Organotin Compound Derived from 3-Hydroxy-2-formylpyridine Semicarbazone: Synthesis, Crystal Structure, and Antiproliferative Activity

The novel diphenyltin(IV) compound [Ph2(HyFoSc)Sn] (2), where H2HyFoSc (1) is 3-hydroxy-2-formylpyridine semicarbazone, was prepared and characterized by vibrational and NMR (1H, 13C) spectroscopy. The structure of [Ph2(HyFoSc)Sn] was confirmed by single-crystal X-ray crystallography. The doubly deprotonated ligand is coordinated to the tin atom through the enolic-oxygen, the azomethine-nitrogen, and phenolic-oxygen, and so acts as an anionic tridentate ligand with the ONO donors. Two carbon atoms complete the fivefold coordination at the tin(IV) center. Intermolecular hydrogen bonding, C–H → π, and π → π interactions combine to stabilize the crystal structure. Compounds 1 and 2 have been evaluated for antiproliferative activity in vitro against the cells of three human tumor cell lines: MCF-7 (human breast cancer cell line), T24 (bladder cancer cell line), A549 (nonsmall cell lung carcinoma), and a mouse fibroblast L-929 cancer cell line.
Spatial patterns of tree species distribution in New Guinea primary and secondary lowland rain forest

Questions How do spatial patterns of tree distribution and species co-occurrence differ between primary and secondary tropical rain forests? What signatures of ecological processes might be discerned by comparing the spatial patterns of trees between primary and secondary forest plots? Location Tropical rain forest vegetation, lowlands of Papua New Guinea. Methods All trees over 5 cm DBH were surveyed in two non-replicated 1-ha plots situated in primary and secondary forest. Grid location, DBH, height and species identity were recorded for all surveyed trees. Analysis of the spatial pattern and the autocorrelation of tree sizes and identities were used to assess the structure of the forest found within the plots. Functions combining Ripley's K and the individual species–area relationship were applied to study the spatial distribution of trees and species diversity. Results The spatial distribution of common species, and all stems collectively, was aggregated in the secondary forest plot but not different from random in the primary forest plot. Diameter and height were also strongly spatially auto-correlated in the secondary forest plot but not in the primary forest plot. Conspecific aggregations were more common in the secondary forest plot. Finally, the secondary forest plot was characterized by the presence of diversity-repelling species and lower diversity than the primary forest plot, where diversity-accumulating species were present. Conclusions We attribute the weaker autocorrelation of tree size in the primary forest to the development of size hierarchies throughout the course of stand aging. The conspecific aggregation and low local diversity within the secondary forest plot are likely caused by dispersal limitation during a brief period of establishment after disturbance. The higher local diversity of the primary forest can be explained by the reduction of species aggregation through increased mortality of conspecifics. This is caused by strong intraspecific competition, supporting the spatial segregation hypothesis (interspecific spatial segregation).
A platform as-a-service for hybrid cloud/fog environments

Fog computing brings cloud close to end-users and data sources by enabling computation and storage at the edges of the network. An application can have some of its components running in a “distant” cloud and interacting with the other components running in the fog, closer to end-users and data sources such as wireless sensors. Low latency is the main benefit. Applications spanning cloud and fog, such as Internet of Things (IoT) applications, are still provisioned manually nowadays. This paper proposes an architecture for a Platform as-a-Service (PaaS) to automate applications provisioning in a hybrid cloud/fog environment. Cloud Foundry is used as the basis for its implementation. As a use case, the proposed PaaS was employed to provision a simple component-based IoT application that detects fire and dispatches robots to fight the fire. A prototype is built and measurements are made.
Subword unit based speech recognition in car environments

This paper presents results of speaker-independent speech recognition experiments concerning acoustic front-ends, models and their structures in car environments. The database comprises 350 speakers in 6 different cars. We investigate whole-word models, context-independent phoneme models and context-dependent within-word phoneme models. We studied task-dependent (same vocabulary context in training and test) phoneme models and present first results on task-independent (broad context in training, i.e. phonetically rich material) scenarios. The latter allows flexible vocabulary definition for applications with dynamically changing command words or new applications avoiding an expensive data collection. Acoustic preprocessing is carried out with mel-cepstrum combined with spectral subtraction and SNR normalization. The task-dependent word error rates are well below 3% for both whole-word and phoneme models. The task-independent scenarios have to be worked on further.
Design, Fabrication and Temperature Sensitivity Testing of a Miniature Piezoelectric-Based Sensor for Current Measurements

Grid capacity, reliability, and efficient distribution of power have been major challenges for traditional power grids in the past few years. Reliable and efficient distribution within these power grids will continue to depend on the development of lighter and more efficient sensing units with lower costs in order to measure current and detect failures across the grid. The objective of this paper is to present the development of a miniature piezoelectric-based sensor for AC current measurements in single conductors, which are used in power transmission lines. Additionally presented in this paper are the thermal testing results for the sensor to assess its robustness for various operating temperatures.
Effect of cooperative and selection relaying schemes on multiuser diversity in downlink cellular systems with relays

In this paper, we investigate the effect of cooperative and selection relaying schemes on multiuser diversity in downlink cellular systems with fixed relay stations (RSs). Each mobile station (MS) is either directly connected to a base station (BS) and/or connected to a relay station. We first derive closed-form solutions or upper-bound of the ergodic and outage capacities of four different downlink data relaying schemes: A direct scheme, a relay scheme, a selection scheme, and a cooperative scheme. The selection scheme selects the best access link between the BS and an MS. For all schemes, the capacity of the BS-RS link is assumed to be always larger than that of RS-MS link. Half-duplex channel use and repetition based relaying schemes are assumed for relaying operations. We also analyze the system capacity in a multiuser diversity environment in which a maximum signal-to-noise ratio (SNR) scheduler is used at a base station. The result shows that the selection scheme outperforms the other three schemes in terms of link ergodic capacity, link outage capacity, and system ergodic capacity. Furthermore, our results show that cooperative and selection diversity techniques limit the performance gain that could have been achieved by the multiuser diversity technique.
Automatic Speech Emotion Recognition using Support Vector Machine

Automatic Speech Emotion Recognition (SER) is a current research topic in the field of Human Computer Interaction (HCI) with wide range of applications. The purpose of speech emotion recognition system is to automatically classify speaker's utterances into five emotional states such as disgust, boredom, sadness, neutral, and happiness. The speech samples are from Berlin emotional database and the features extracted from these utterances are energy, pitch, linear prediction cepstrum coefficients (LPCC), Mel Frequency cepstrum coefficients (MFCC), Linear Prediction coefficients and Mel cepstrum coefficients (LPCMCC). The Support Vector Machine (SVM) is used as a classifier to classify different emotional states. The system gives 66.02% classification accuracy for only using energy and pitch features, 70.7% for only using LPCMCC features, and 82.5% for using both of them.
An output match design method for high efficiency and broadband class-J PA

The theory of class-J power amplifiers is reviewed. Based on the theory, a new output match method is proposed. Instead of the restricted impedance condition, we design the different fundamental and 2nd harmonic output impedances based on the variation tendency of termination impedance according to the different frequencies. Therefore, the PA can work efficiently in the band. A 10W GaN transistor device (CGH40010) is applied in the simulation. And the results show this method can enhance the PAE over 60% across a bandwidth of 1.6-2.5 GHz.
Robocentric mapping and localization in modified spherical coordinates with bearing measurements

In this paper, a new approach to robotic mapping is presented that uses modified spherical coordinates in a robot-centered reference frame and a bearing-only measurement model. The algorithm provided in this paper permits robust delay-free state initialization and is computationally more efficient than the current standard in bearing-only (delay-free initialized) simultaneous localization and mapping (SLAM). Importantly, we provide a detailed nonlinear observability analysis which shows the system is generally observable. We also analyze the error convergence of the filter using stochastic stability analysis. We provide an explicit bound on the asymptotic mean state estimation error. A comparison of the performance of this filter is also made against a standard world-centric SLAM algorithm in a simulated environment.
Against Liver Stages of Murine Malaria T Cell Responses + the Magnitude of CD8 Early Self-Regulatory Mechanisms Control

Following immunization with Plasmodium yoelii sporozoites, the CD8 (cid:1) T cell population speciﬁc for the SYVPSAEQI epitope expressed in sporozoite and liver stages of this malaria parasite revealed the existence of a short term Ag presentation process that translated into a single clonal burst. Further expansion of this CD8 (cid:1) T cell population in conditions of sustained Ag exposure and additional supply of naive cells was inhibited by regulatory mechanisms that were developed as early as 24–48 h after priming. Studies using mouse models for Plasmodium or inﬂuenza virus infections revealed that this mechanism is Ag speciﬁc and is mediated by activated CD8 (cid:1) T cells that inhibit the priming of naive cells. This interference of the priming of naive cells appeared to result from limited access to Ag-presenting dendritic cells, which become disabled or are eliminated after contact with activated cells. Thus, concomitantly with the development of their effector antimicrobial capacity, CD8 (cid:1) T cells also acquire a self-regu-latory role that is likely to represent one of the earliest mechanisms induced in the course of an immune response and that limits the magnitude of the early expansion of CD8 (cid:1) T lymphocytes reactive to microorganisms. The Journal of Immunology, 2003, 171: 964–970.
Numerical stability of fast trigonometric transforms: a worst case study

This paper presents some new results on numerical stability for various fast trigonometric transforms. In a worst case study, we consider the numerical stability of the classical fast Fourier transform (FFT) with respect to different precomputation methods for the involved twiddle factors and show the strong influence of precomputation errors on the numerical stability of the FFT. The examinations are extended to fast algorithms for the computation of discrete cosine and sine transforms and to efficient computations of discrete Fourier transforms for nonequispaced data. Numerical tests confirm the theoretical estimates of numerical stability. ∗ Contact author: Manfred Tasche, Mailing address: Department of Mathematics,University of Rostock,D – 18051 Rostock, Germany, Tel. 0049 / 381 – 498 – 1549, Fax 0049 / 381 – 498 – 1520, e–mail: manfred.tasche@mathematik.uni-rostock.de
Inference and Characterization of Multi-Attribute Networks with Application to Computational Biology

Our work is motivated by and illustrated with application of association networks in computational biology, specifically in the context of gene/protein regulatory networks. Association networks represent systems of interacting elements, where a link between two different elements indicates a sufficient level of similarity between element attributes. While in reality relational ties between elements can be expected to be based on similarity across multiple attributes, the vast majority of work to date on association networks involves ties defined with respect to only a single attribute. We propose an approach for the inference of multi-attribute association networks from measurements on continuous attribute variables, using canonical correlation and a hypothesis-testing strategy. Within this context, we then study the impact of partial information on multi-attribute network inference and characterization, when only a subset of attributes is available. We consider in detail the case of two attributes, wherein we examine through a combination of analytical and numerical techniques the implications of the choice and number of node attributes on the ability to detect network links and, more generally, to estimate higher-level network summary statistics, such as node degree, clustering coefficients, and measures of centrality. Illustration and applications throughout the paper are developed using gene and protein expression measurements on human cancer cell lines from the NCI-60 database.
Modeling valuations for EuroQol health states.

OBJECTIVES It has become increasingly common for preference-based measures of health-related quality of life to be used in the evaluation of different health-care interventions. For one such measure, The EuroQol, designed to be used for these purposes, it was necessary to derive a single index value for each of the 243 health states it generates. The problem was that it was virtually impossible to generate direct valuations for all of these states, and thus it was necessary to find a procedure that allows the valuations of all EuroQol states to be interpolated from direct valuations on a subset of these. METHODS In a recent study, direct valuations were elicited for 42 EuroQol health states (using the time trade-off method) from a representative sample of the UK population. This article reports on the methodology that was adopted to build up a "tariff" of EuroQol values from this data. RESULTS A parsimonious model that fits the data well was defined as one in which valuations were explained in terms of the level of severity associated with each dimension, an intercept associated with any move away from full health, and a term that picked up whether any dimension in the state was at its most severe level. CONCLUSIONS The model presented in this article appears to predict the values of the states for which there are direct observations and, thus, can be used to interpolate values for the states for which no direct observations exist.
New constraints on the gas age-ice age difference along the EPICA ice cores, 0-50 kyr

Abstract. Gas is trapped in polar ice sheets at ~50–120 m below the surface and is therefore younger than the surrounding ice. Firn densification models are used to evaluate this ice age-gas age difference (Δage) in the past. However, such models need to be validated by data, in particular for periods colder than present day on the East Antarctic plateau. Here we bring new constraints to test a firn densification model applied to the EPICA Dome C (EDC) site for the last 50 kyr, by linking the EDC ice core to the EPICA Dronning Maud Land (EDML) ice core, both in the ice phase (using volcanic horizons) and in the gas phase (using rapid methane variations). We also use the structured 10Be peak, occurring 41 kyr before present (BP) and due to the low geomagnetic field associated with the Laschamp event, to experimentally estimate the Δage during this event. Our results seem to reveal an overestimate of the Δage by the firn densification model during the last glacial period at EDC. Tests with different accumulation rates and temperature scenarios do not entirely resolve this discrepancy. Although the exact reasons for the Δage overestimate at the two EPICA sites remain unknown at this stage, we conclude that current densification model simulations have deficits under glacial climatic conditions. Whatever the cause of the Δage overestimate, our finding suggests that the phase relationship between CO2 and EDC temperature previously inferred for the start of the last deglaciation (lag of CO2 by 800±600 yr) seems to be overestimated.
A general purpose Hyper – Heuristic based on Ant colony optimization

In the plan of the CHESC2001 competition [1], an hy per heuristic has been designed based on the Ant Colony Optimization method (from now ACO). According to the competition goals, the algorithm w as developed with the intention to produce an independent model of the problem doma in and the particular instance to be solved. This means that the hyper-heuristic is a bstr cted from the features of each heuristic previously known; therefore, the work is based exclusively on the behavior observed during the problem resolution. These types of hyper-heuristics are known as heuristic selection and online learning [2]. The model presented in this document was implemente d for Hyflex framework [3] provided for the participatants in the competition.
Can Cognitive-Behavioral Therapy Be Optimized With Parent Psychoeducation? A Randomized Effectiveness Trial of Adolescents With Major Depression in Puerto Rico.

This is a longitudinal randomized control trial on the impact of adding a parent psychoeducation intervention (TEPSI) as part of cognitive-behavioral therapy (CBT) for adolescents with Major Depressive Disorder (MDD) in a Puerto Rican sample. We tested the efficacy of adding 8 group sessions of TEPSI to 12 sessions of individual CBT on reducing depressive symptoms, MDD diagnosis, and improving family functioning. Participants (n = 121) were randomized to individual CBT with or without TEPSI. No main group effects were found for most patient domains including depression symptoms, as well as presence of adolescent's MDD diagnosis at posttreatment. Results did show a main effect of CBT over time for depression symptoms, suicide ideation, family criticism, and the presence of MDD diagnosis decreasing from pre- to postintervention. A year post treatment, almost 70% of adolescents in both conditions (CBT and CBT + TEPSI) remained in remission. A main effect was obtained for treatment in the adolescent's perception of familism and family emotional involvement. The primary hypothesis that family psychoeducation would optimize CBT for depression in adolescents was not supported. Both conditions yielded similar clinical end points. The culturally adapted CBT was found effective with Latino/a adolescents showing clinically significant improvements from pretreatment to posttreatment and remained stable at a 1-year follow-up. Regarding family outcomes, adolescents in CBT + TEPSI remained stable from pretreatment to posttreatment on family emotional involvement, while adolescents in CBT-alone showed an increase. The implication of these findings is discussed.
Robust Phase Retrieval via ADMM with Outliers

An outlier-resistance phase retrieval algorithm based on alternating direction method of multipliers (ADMM) is devised in this letter. Instead of the widely used least squares criterion that is only optimal for Gaussian noise environment, we adopt the least absolute deviation criterion to enhance the robustness against outliers. Considering both intensity- and amplitude-based observation models, the framework of ADMM is developed to solve the resulting non-differentiable optimization problems. It is demonstrated that the core subproblem of ADMM is the proximity operator of the L1-norm, which can be computed efficiently by soft-thresholding in each iteration. Simulation results are provided to validate the accuracy and efficiency of the proposed approach compared to the existing schemes.