Miracle-dz/UniFAR-FTUs huggingface dataset:
Segmentation method of human manipulation task based on measurement of force imposed by a human hand on a grasped object

This paper proposes a segmentation method of human manipulation task based on measurement of contact force imposed by a human hand on a grasped object. We define an index measure for segmenting a human manipulation task into primitives. The indices are calculated from the set of the contact forces measured at all the contact points during a manipulation task. Then, we apply the EM algorithm to the set of the indices in order to segment the manipulation task into primitives. These primitives are mapped onto the robotic hand to impose appropriate contact forces on a grasped object. In the experiments, manipulation tasks performed in daily human life have been successfully segmented.
Teachers' and Leaders' Perceptions of an Induction Program's Influence on Teacher Retention in a Title I School with a High Population of English Language Learners

Issues related to teacher attrition and retention have plagued our educational systems for decades; particularly in urban schools serving low income, low achieving, and culturally and linguistically diverse students. A review of the literature revealed that urban schools are often staffed with novice teachers (teachers with less than three years’ experience) who feel unprepared to meet the language acquisition and pedagogical needs of culturally and linguistically diverse students. In recent years, teacher induction programs have been implemented to circumvent attrition in hopes of retaining novice teachers. These programs often pair novice teachers with veteran teachers. This qualitative study investigated teachers’ and leaders’ perceptions of the effectiveness of their induction program's influence in retaining teachers. The theoretical framework of organizational climate and culture structured this study. The concepts of school climate and culture were used to investigate the interconnected experiences that participants had with the organizational practices in place at the school site. This study was conducted in a Title I school with a high enrollment of English Language Learners (ELLs) in a large urban school district, considered to be high performing by its district’s internal ranking system. The ten participants included the principal, assistant principal, three novice teachers, two veteran teachers, and three mentors. The major components of the comprehensive induction program included (a) administrative support, (b) mentoring, and (c) collaborative support from colleagues. The data were collected from individual interviews with the 10 participants, documents and artifacts from the induction program, and observational field notes recorded during on-site visits to the school. The key themes that emerged after the triangulation of the data were (a) instructional leadership practices, (b) a collaborative school climate and culture, and (c) a comprehensive induction program. The findings aligned with current and historical research that a collaborative school climate and culture, instructional leadership practices, and a comprehensive induction program increase teacher retention. INDEX WORDS: Novice teachers, Retention, Induction programs, Organizational climate and culture, School climate and culture, Instructional leadership, Culturally linguistic and diverse populations TEACHERS’ AND LEADERS’ PERCEPTION OF AN INDUCTION PROGRAM’S INFLUENCE ON TEACHER RETENTION IN A TITLE I SCHOOL WITH A HIGH POPULATION OF ENGLISH LANGUAGE LEARNERS
Quantifying Dynamic Changes in Plantar Pressure Gradient in Diabetics with Peripheral Neuropathy

Diabetic foot ulcers remain one of the most serious complications of diabetes. Peak plantar pressure (PPP) and peak pressure gradient (PPG) during walking have been shown to be associated with the development of diabetic foot ulcers. To gain further insight into the mechanical etiology of diabetic foot ulcers, examination of the pressure gradient angle (PGA) has been recently proposed. The PGA quantifies directional variation or orientation of the pressure gradient during walking and provides a measure of whether pressure gradient patterns are concentrated or dispersed along the plantar surface. We hypothesized that diabetics at risk of foot ulceration would have smaller PGA in key plantar regions, suggesting less movement of the pressure gradient over time. A total of 27 participants were studied, including 19 diabetics with peripheral neuropathy and 8 non-diabetic control subjects. A foot pressure measurement system was used to measure plantar pressures during walking. PPP, PPG, and PGA were calculated for four foot regions – first toe (T1), first metatarsal head (M1), second metatarsal head (M2), and heel (HL). Consistent with prior studies, PPP and PPG were significantly larger in the diabetic group compared with non-diabetic controls in the T1 and M1 regions, but not M2 or HL. For example, PPP was 165% (P = 0.02) and PPG was 214% (P < 0.001) larger in T1. PGA was found to be significantly smaller in the diabetic group in T1 (46%, P = 0.04), suggesting a more concentrated pressure gradient pattern under the toe. The proposed PGA may improve our understanding of the role of pressure gradient on the risk of diabetic foot ulcers.
The Evalita 2011 Parsing Task: the constituency track

The aim of Evalita Parsing Task is at defining and extending Italian state of the art parsing by encouraging the application of existing models and approaches. As in the Evalita’07 and ’09, the Task is organized around two tracks, i.e. Dependency Parsing and Constituency Parsing. In this paper, we describe only the Constituency Parsing track by presenting the data sets for development and testing, and reporting the results, which positively compare with those obtained for this same track held in the Evalita’07 and ’09.
Involvement of ryanodine-operated channels in tert-butylhydroperoxide-evoked Ca2+ mobilisation in pancreatic acinar cells

SUMMARY Reactive oxygen species and related oxidative damage have been implicated in the initiation of acute pancreatitis, a disease characterised in its earliest stages by disruption of intracellular Ca2+ homeostasis. The present study was carried out in order to establish the effect of the organic pro-oxidant, tert-butylhydroperoxide (tBHP), on the mobilisation of intracellular Ca2+ stores in isolated rat pancreatic acinar cells and the mechanisms underlying this effect. Cytosolic free Ca2+ concentrations ([Ca2+]c) were monitored using a digital microspectrofluorimetric system in fura-2 loaded cells. In the presence of normal extracellular Ca2+ concentrations ([Ca2+]o), perfusion of pancreatic acinar cells with 1 mmol l-1 tBHP caused a slow sustained increase in [Ca2+]c. This increase was also observed in a nominally Ca2+-free medium, indicating a release of Ca2+ from intracellular stores. Pretreatment of cells with tBHP abolished the typical Ca2+ response of both the physiological agonist CCK-8 (1 nmol l-1) and thapsigargin (TPS, 1 μmol l-1), an inhibitor of the SERCA pump, in the absence of extracellular Ca2+. Similar results were observed with carbonyl cyanide p-trifluoromethoxyphenylhydrazone (FCCP, 0.5 μmol l-1), a mitochondrial uncoupler. In addition, depletion of either agonist-sensitive Ca2+ pools by CCK-8 or TPS or mitochondrial Ca2+ pools by FCCP were unable to prevent the tBHP-induced Ca2+ release. By contrast, simultaneous administration of TPS and FCCP clearly abolished the tBHP-induced Ca2+ release. These results show that tBHP releases Ca2+ from agonist-sensitive intracellular stores and from mitochondria. On the other hand, simultaneous application of FCCP and of 2-aminoethoxydiphenylborane (2-APB), a blocker of IP3-mediated Ca2+release, was unable to suppress the increase in [Ca2+]c induced by tBHP, while the application of 50 μmol l-1 of ryanodine (which is able to block the ryanodine channels) inhibits tBHP-evoked Ca2+ mobilisation. These findings indicate that tBHP releases Ca2+ from non-mitochondrial Ca2+ pools through ryanodine channels.
Particle filtering for multitarget detection and tracking

This paper presents a particle filter approach to recursively estimating the joint multitarget probability density (JMPD) for the purposes of simultaneous multitarget detection and tracking. The JMPD is a conditional probability density that characterizes uncertainty in both target state and target number given the measurements. Estimation of the JMPD presents a formidable computational challenge due to the high dimensionality of the state space needed to explicitly model the correlations between target states and between target states and target number. We address this challenge with an importance density that is measurement directed and which adaptively factorizes the problem into a set of smaller sub-problems when possible. We demonstrate the algorithm on a set of real targets whose motion is taken from a set of military battle exercises
Phenex: Ontological Annotation of Phenotypic Diversity

Background Phenotypic differences among species have long been systematically itemized and described by biologists in the process of investigating phylogenetic relationships and trait evolution. Traditionally, these descriptions have been expressed in natural language within the context of individual journal publications or monographs. As such, this rich store of phenotype data has been largely unavailable for statistical and computational comparisons across studies or integration with other biological knowledge. Methodology/Principal Findings Here we describe Phenex, a platform-independent desktop application designed to facilitate efficient and consistent annotation of phenotypic similarities and differences using Entity-Quality syntax, drawing on terms from community ontologies for anatomical entities, phenotypic qualities, and taxonomic names. Phenex can be configured to load only those ontologies pertinent to a taxonomic group of interest. The graphical user interface was optimized for evolutionary biologists accustomed to working with lists of taxa, characters, character states, and character-by-taxon matrices. Conclusions/Significance Annotation of phenotypic data using ontologies and globally unique taxonomic identifiers will allow biologists to integrate phenotypic data from different organisms and studies, leveraging decades of work in systematics and comparative morphology.
POS tagging of Chinese Buddhist texts using Recurrent Neural Networks

Chinese POS tagging, as one of the most important problems in the NLP community, has been investigated in the past decades. This project, for the first time in the literature, tests different neural network models on a Chinese Buddhist contexts, which are the representative for the Medieval Chinese. Our results demonstrate the capacity of neural network models, and the results are than the popular trigram HMM model in the literature. Differences between the Buddhist texts and modern Chinese data are also revealed by the experiments. Lastly, we also propose several interesting topics for future research.
An Optimal Algorithm for Checking Regularity

We present a deterministic algorithm ${\cal A}$ that, in O(m2) time, verifies whether a given m by m bipartite graph G is regular, in the sense of Szemeredi [Regular partitions of graphs, in Problemes Combinatoires et Theorie des Graphes (Orsay, 1976), Colloques Internationaux CNRS 260, CNRS, Paris, 1978, pp. 399--401]. In the case in which G is not regular enough, our algorithm outputs a witness to this irregularity. Algorithm ${\cal A}$ may be used as a subroutine in an algorithm that finds an $\varepsilon$-regular partition of a given n-vertex graph $\Gamma$ in time O(n2). This time complexity is optimal, up to a constant factor, and improves upon the bound O(M(n)), proved by Alon et al. [The algorithmic aspects of the regularity lemma, J. Algorithms, 16 (1994), pp. 80--109], where M(n)=O(n2.376) is the time required to square a 0--1 matrix over the integers. Our approach is elementary, except that it makes use of linear-sized expanders to accomplish a suitable form of deterministic sampling.
Simultaneous energy and information cooperation in MIMO cooperative cognitive radio systems

This paper considers energy and information cooperation between a single-antenna primary user (PU) pair and a multiple-antennae secondary user (SU) pair in a cognitive radio system. The secondary transmitter (ST) harvests energy from the primary signal and gains opportunity to transmit its own signal in return for helping relay the primary transmitter's (PT) traffic. A time-divided power splitting scheme is proposed to enable the energy and information cooperation with the objective of maximizing the throughput of the SU pair under the energy constraint of the ST and the received signal-to-inference plus noise ratio (SINR) constraint of the primary receiver (PR). Simulation results demonstrate the influence of the time division proportion and the power splitting parameter on the throughput of the SU pair and the PU pair.
The Effect of Fixed Speed Enforcement Cameras on Accidents in France : Two Complementary Approaches

In this article, we want to assess the effect on road accidents of the campaign of speed enforcement cameras (SEC) installation launched in 2003 in France. We use two complementary approaches. The first one relies on two explicit structural models of the number of road accidents in a town and includes a town-specific fixed effect in a non-linear framework. As we use aggregated data at the town level, the cameras do not uniformly affect the accidents, depending on the town size. To estimate these structural models, we use a innovative Gauss-Seidel strategy recently introduced by [Guimaraes and Portugal, 2009]. The second approach relies on a non-parametrical methodology and directly identifies the impact of cameras using a matching procedure between towns equipped with cameras at different but close dates. These two methods are complementary. The first one aims to estimate precise impacts and the second one aims to solve potential issues of endogeneity and risks of misspecification. We show that the impact of cameras is strong in the first months after the installation, but decreases afterwards. The two methods give the same magnitudes for the impact of fixed cameras over time. To our knowledge, this result is rarely put into evidence by the international literature, which focuses mostly on short-term outcomes. These results suggest that the multiplication of fixed speed cameras is probably not effective enough to enhance the accidents’decrease. Public authorities should turn now to try new tools as mobile cameras or speed displaying devices, as many other European countries.
Contributions of white matter connectivity and BOLD modulation to cognitive aging: A lifespan structure-function association study

The ability to flexibly modulate brain activation to increasing cognitive challenge decreases with aging. This age-related decrease in dynamic range of function of regional gray matter may be, in part, due to age-related degradation of regional white matter tracts. Here, a lifespan sample of 171 healthy adults (aged 20-94) underwent MRI scanning including diffusion-weighted imaging (for tractography) and functional imaging (a digit n-back task). We utilized structural equation modeling to test the hypothesis that age-related decrements in white matter microstructure are associated with altered BOLD modulation, and both in turn, are associated with scanner-task accuracy and executive function performance. Specified structural equation model evidenced good fit, demonstrating that increased age negatively affects n-back task accuracy and executive function performance in part due to both degraded white matter tract microstructure and reduced task-difficulty related BOLD modulation. We further demonstrated that poorer white matter microstructure integrity was associated with weakened BOLD modulation, particularly in regions showing positive modulation effects, as opposed to negative modulation effects. This structure-function association study provides further evidence that structural connectivity influences functional activation, and the two mechanisms in tandem are predictive of cognitive performance, both during the task, and for cognition measured outside the scanner environment.
Pure gauge configurations and solutions to fermionic superstring field theory equations of motion

Recent results on solutions to the equation of motion of the cubic fermionic string field theory and an equivalence of nonpolynomial and cubic string field theory are discussed. To have the possibility of dealing with both GSO(+) and GSO(−) sectors in the uniform way, a matrix formulation for the NS fermionic SFT is used. In constructions of analytical solutions to open-string field theories truncated pure gauge configurations parametrized by wedge states play an essential role. The matrix form of this parametrization for NS fermionic SFT is presented. Using the cubic open superstring field theory as an example we demonstrate explicitly that for the large parameter of the perturbation expansion these truncated pure gauge configurations give divergent contributions to the equations of motion on the subspace of the wedge states. The perturbation expansion is corrected by adding extra terms that are just those necessary for the equation of motion contracted with the solution itself to be satisfied.
A Prediction based Energy-Efficient Tracking Method in Sensor Networks

Energy is one of the most critical constraints for sensor network applications of tracking. Object tracking is an important feature of the ubiquitous society and also a killer application of wireless sensor networks. Object Tracking Sensor Network is mainly used to track certain objects in a monitored area and to report their location to the application's users. On the other hand, Object Tracking Sensor Network is familiar for their energy consumption when compared with other WSN applications. Based on the fact that the actions of the tracked objects are sometimes knowable, we propose a Prediction-based Energy Efficient tracking technique using sequential patterns deliberate to achieve considerable reductions in the energy degenerate by the Object Tracking Sensor Networks while maintaining tolerable missing rate levels. The intended method can not only decrease the missing-rate by predict future movements of moving objects, but can also reduce the energy consumption by sinking the number of nodes that join in tracking i.e., the majority of the sensor nodes stay in sleep mode and minimizing the communication disbursement. Index Terms- Object tracking, wireless sensor networks (WSNs), prediction based energy efficient technique, object tracking sensor network (OTSN).
Pitch-Scaled Spectrum Based Excitation Model for Hidden Markov Model-based Speech Synthesis

The speech generated by hidden Markov model (HMM)-based speech synthesis systems (HTS) suffers from a ‘buzzing’ sound, which is due to an oversimplified vocoding technique. This paper proposes a new excitation model that uses a pitch-scaled spectrum for the parametric representation of speech in HTS. A residual signal produced using inversing filtering retains the detailed harmonic structure of speech that is not part of the linear prediction (LP) spectrum. By using pitchscaled spectrums, we can compensate the LP spectrum using the detailed harmonic structure of the residual signal. This spectrum can be compressed using a periodic excitation parameter so that it can used to train HTS. We define an aperiodic measure as the harmonicsto-noise ratio, and calculate a voicing-cut off frequency to fit the aperiodic measure to a sigmoid function. We combine the LP coefficient, pitch-scaled spectrum, and sigmoid function to create a new parametric representation of speech. Listening tests were carried out to evaluate the effectiveness of the proposed technique. This vocoder received a mean opinion score of 4.0 in analysis-synthesis experiments, before dimensionality reduction. By integrating this vocoder into HTS, we improved the sound of the synthesized speech compared with the pulse train excitation model, and demonstrated an even better result than
A Simple Ocean Data Assimilation Analysis of the Global Upper Ocean 1950–95. Part I: Methodology

Abstract The authors describe a 46-year global retrospective analysis of upper-ocean temperature, salinity, and currents. The analysis is an application of the Simple Ocean Data Assimilation (SODA) package. SODA uses an ocean model based on Geophysical Fluid Dynamics Laboratory MOM2 physics. Assimilated data includes temperature and salinity profiles from the World Ocean Atlas-94 (MBT, XBT, CTD, and station data), as well as additional hydrography, sea surface temperature, and altimeter sea level. After reviewing the basic methodology the authors present experiments to examine the impact of trends in the wind field and model forecast bias (referred to in the engineering literature as “colored noise”). The authors believe these to be the major sources of error in the retrospective analysis. With detrended winds the analysis shows a pattern of warming in the subtropics and cooling in the Tropics and at high latitudes. Model forecast bias results partly from errors in surface forcing and partly from limitati.
An Exploration Framework to Identify and Track Movement of Cloud Systems

We describe a framework to explore and visualize the movement of cloud systems. Using techniques from computational topology and computer vision, our framework allows the user to study this movement at various scales in space and time. Such movements could have large temporal and spatial scales such as the Madden Julian Oscillation (MJO), which has a spatial scale ranging from 1000 km to 10000 km and time of oscillation of around 40 days. Embedded within these larger scale oscillations are a hierarchy of cloud clusters which could have smaller spatial and temporal scales such as the Nakazawa cloud clusters. These smaller cloud clusters, while being part of the equatorial MJO, sometimes move at speeds different from the larger scale and in a direction opposite to that of the MJO envelope. Hitherto, one could only speculate about such movements by selectively analysing data and a priori knowledge of such systems. Our framework automatically delineates such cloud clusters and does not depend on the prior experience of the user to define cloud clusters. Analysis using our framework also shows that most tropical systems such as cyclones also contain multi-scale interactions between clouds and cloud systems. We show the effectiveness of our framework to track organized cloud system during one such rainfall event which happened at Mumbai, India in July 2005 and for cyclone Aila which occurred in Bay of Bengal during May 2009.
A Quantitative Examination of Crime: Reported Incidents at Land-Grant Higher Education Institutions versus Reported Societal Incidents

This study investigates differences in reported criminality between land-grant higher education institutions and society for the period encompassing 2001-2010. Using analysis of variance (ANOVA) and a stratification of reported incidents of campus crime (per the Clery Act) versus societal crime, statistically significant outcomes were observed for the crime categories of cumulative crime, robbery, sex crimes, assault crimes, burglary, and motor vehicle theft. Within the contexts of campus safety and campus security, the outcomes of this study reiterate the uniqueness of campus criminality among land-grant higher education settings.