Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Co-axial Parallel Ring Type Ultrasonic Motor

Ultrasonic motors have been attracting considerable attention in the last decades. Different types of ultrasonic motors have been constructed and manufactured. The objective of this paper is to propose a novel co-axial parallel ring type ultrasonic motor with double stators and double rotors for high output torque and electromagnetic compatibility application. Firstly, the configuration of the novel ultrasonic motor is presented. Several methods are employed to ensure the electromagnetic compatibility. Then, modeling studies focused on performance estimation and analyses of the novel motor are examined. Afterwards, operational performances of the novel motor are examined and compared with that of conventional ring type ultrasonic motor with single stator and single rotor. The results indicate that performances of the novel ultrasonic motor have been improved significantly compared with the conventional ultrasonic motor, which indicates promising prospect of the novel ultrasonic motor.
New method for weighted low-rank approximation of complex-valued matrices and its application for the design of 2-D digital filters

The design of two-dimensional (2-D) digital filters can be accomplished using the singular-value decomposition (SVD) method proposed by the authors in the past. The method in its present form treats all the elements of the sampled frequency-response matrix uniformly. Although the method works very well, in certain applications improved designs can be achieved by preconditioning the frequency-response matrix in order to emphasize important parts and deemphasize unimportant parts of the matrix. The preconditioning can be achieved through the use of an optimal weighted low-rank approximation (WLRA). Current methods for WLRA provide only local solutions. In this paper, we propose a method that can be used to perform WLRA which is globally optimal for complex-valued matrices. The usefulness of the proposed method is demonstrated by applying it to the design of 2-D digital filters.
Principal Transcriptional Programs Regulating Plant Amino Acid Metabolism in Response to Abiotic Stresses1[W][OA]

Using a bioinformatics analysis of public Arabidopsis (Arabidopsis thaliana) microarray data, we propose here a novel regulatory program, combining transcriptional and posttranslational controls, which participate in modulating fluxes of amino acid metabolism in response to abiotic stresses. The program includes the following two components: (1) the terminal enzyme of the module, responsible for the first catabolic step of the amino acid, whose level is stimulated or repressed in response to stress cues, just-in-time when the cues arrive, principally via transcriptional regulation of its gene; and (2) the initiator enzyme of the module, whose activity is principally modulated via posttranslational allosteric feedback inhibition in response to changes in the level of the amino acid, just-in-case when it occurs in response to alteration in its catabolism or sequestration into different intracellular compartments. Our proposed regulatory program is based on bioinformatics dissection of the response of all biosynthetic and catabolic genes of seven different pathways, involved in the metabolism of 11 amino acids, to eight different abiotic stresses, as judged from modulations of their mRNA levels. Our results imply that the transcription of the catabolic genes is principally more sensitive than that of the biosynthetic genes to fluctuations in stress-associated signals. Notably, the only exception to this program is the metabolic pathway of Pro, an amino acid that distinctively accumulates to significantly high levels under abiotic stresses. Examples of the biological significance of our proposed regulatory program are discussed.
A Conceptual Framework for Software Change Effort Estimation during Ongoing Software Development

Change effort estimation (CEE) is the process of predicting the work and the hours needed when there is a software change request. Software changes that are not correctly addressed, not complete and not consistent with other artefacts will introduce delay to the project and exceed the original budget. Requirement changes during software development phase are delicate to handle due to the fact that the software artefacts are still undergoing development. Any change would affect the components under development. Software Project Manager (SPM) needs evidence and justifications to decide whether to accept or not a change request. This paper aims to investigate a suitable effort estimation approach that can be applied to requirement changes during an ongoing software development. A conceptual model of the influential effort estimation methods is proposed. It is hoped that the evidence and results from the proposed model is able to convince the client and the developers involved to accept the SPM’s decision.
The Approximation of Some Invertible Operators Using Newton ’ s Method in Banach Spaces

Under the hypothesis that the derivative of an operator satisfies Lipschitz conditions, it is known that Newton’s method is convergent. These conditions ensure from Banach theorem of inversability for operators that in balls of a namely radius, these are inversable. The aim of this article is to emphasize an algoritm of approximation for some invertible types of operators using Newton’s method. Mathematics Subject Classification: 65H10, 47H15, 49R20
Limits to sustained energy intake XII: is the poor relation between resting metabolic rate and reproductive performance because resting metabolism is not a repeatable trait?

SUMMARY Many studies have investigated the consequences of individual variation in resting metabolic rate at thermoneutrality (RMRt) on reproductive performance. Despite strong theoretical reasons for expecting such an association, results have generally been disappointing. A fundamental assumption of these studies is that RMRt is a repeatable trait. We examined repeatability of RMRt in female MF1 mice over short (15 days apart; N=238) and long intervals (110 days apart; N=33). In the long-term experiment, after the first RMRt measurement, females were separated in two groups: the first was kept virgin (N=16); the second was allowed to breed (N=17) and measured 15 days after they had weaned their pups. We also examined the association between RMRt and reproduction. We used Pearson's correlation (r) and intraclass correlation coefficients (ρ) to estimate repeatability. There was a strong effect of body mass on RMRt for all measurements. Over the short interval, repeatability was significant for body mass (r=0.86; ρ=0.86), RMRt (r=0.68; ρ=0.68,) and residual-RMRt (r=0.58; ρ=0.58). Over long intervals, repeatability of residual-RMRt was high in virgin females (r=0.59; ρ=0.60), but not in the breeders (r=0.38; ρ=0.39); body mass was repeatable only for non-breeders measured by r (r=0.55). There was no significant correlation between RMRt or residual-RMRt and litter size or litter mass. In conclusion, RMRt and residual-RMRt are highly repeatable traits in virgin MF1 female mice. The lack of association between non-reproductive RMRt and reproductive performance in MF1 mice does not come about because of its poor repeatability.
The Block Diagonal Infinite Hidden Markov Model

The Infinite Hidden Markov Model (IHMM) extends hidden Markov models to have a countably infinite number of hidden states (Beal et al., 2002; Teh et al., 2006). We present a generalization of this framework that introduces nearly block-diagonal structure in the transitions between the hidden states, where blocks correspond to “subbehaviors” exhibited by data sequences. In identifying such structure, the model classifies, or partitions, sequence data according to these sub-behaviors in an unsupervised way. We present an application of this model to artificial data, a video gesture classification task, and a musical theme labeling task, and show that components of the model can also be applied to graph segmentation.
Toward Ubiquitous Communication Platform for Emergency Medical Care

Interaction between emergency medical technicians (EMTs) and doctors is essential in emergency medical care. Doctors require diverse information related to a patient to provide efficient aid. In 2005, we started the Ikoma119 project and have developed a ubiquitous communication platform for emergency medical care called Mobile ER. Our platform, which is based on wireless internet technology, has such desirable properties as low-cost, location-independent service, and ease of service introduction. We provide an overview of our platform and describe the services that we have developed. We also discuss the remaining issues to realize our platform's actual operation.
A statistical significance test for person authentication

Keywords: learning Reference EPFL-CONF-83049 URL: http://publications.idiap. ch/downloads/reports/2004/bengio_2004_odyssey_stats. pdf Related documents: http://publications.idiap. ch/index.php/publications/showcite/bengio:2003:idiap-03-83 Record created on 2006-03-10, modified on 2017-05-10
The host galaxies of X-ray selected Active Galactic Nuclei to z= 2.5: Structure, star-formation and their relationships from CANDELS and Herschel/PACS ⋆

We study the relationship between the structure and star formation rate (SFR) of X-ray selected low and moderate luminosity active galactic nuclei (AGNs) in the two Chandra Deep Fields, using Hubble Space Telescope imaging from the Cosmic Assembly Near Infrared Extragalactic Legacy Survey (CANDELS) and deep far-infrared maps from the PEP+GOODS-Herschel survey. We derive detailed distributions of structural parameters and FIR luminosities from carefully constructed control samples of galaxies, which we then compare to those of the AGNs. At z ~ 1, AGNs show slightly diskier light profiles than massive inactive (non-AGN) galaxies, as well as modestly higher levels of gross galaxy disturbance (as measured by visual signatures of interactions and clumpy structure). In contrast, at z ~ 2, AGNs show similar levels of galaxy disturbance as inactive galaxies, but display a red central light enhancement, which may arise from a more pronounced bulge in AGN hosts or extinguished nuclear light. We undertake a number of tests of both these alternatives, but our results do not strongly favor one interpretation over the other. The mean SFR and its distribution among AGNs and inactive galaxies are similar at z> 1.5. At z 1.5.
Iris Image Segmentation based on Industrial Vision Tools

In the last few years biometric data acquisition and processing systems for person identity verification and / or identification started to be increasingly used. This is done both in military applications for person identification in military operations and war theatres, but also in civilian applications for personal identity verification, accounting systems, etc. Depending on the organization policy, such systems must be secured and customized, for application enhancement, and to fulfil the organization requirements. Such systems which allow customization and enhancement are not available for source code modification and feature enhancement. This paper presents a software image processing development environment IPDE based on vision tools, which is able to run vision projects but also allow the user to develop stand alone applications in a short amount of time, applications which are based on customized vision tools. The IPDE is used to exemplify the process of creating an iris recognition application where a set of vision tools were used in order develop a customized iris image segmentation routine. The paper is structured on three chapters presenting the IPDE architecture, the vision tools, the application development stages, and ends with some experimental data and conclusions.
Integral Histogram Image Computing For Parallel Hardware Architecture

Integral histogram image can gather speed the computing process of feature algorithm in computer vision, butex habits high working out complexity and incompetent memory access. In this paper, we propose a configurable parallel architecture to improve the computing efficiency of integral histogram. The design in the several integral objects is well supported for an integral histogram image such as image intensity, image gradient, and local binary pattern. Meanwhile, this architecture utilizes the proposed strip-based memory partitioning mechanism to rapidly process the integral histogram in a pipeline fashion with maximum parallelism. The improvement problem of the integrated histogram memory caused by storing the histogram data and the configurable data correlation memory compression mechanism effectively solves the problem. It completely reduces the data redundancy in the integral histograms and stores a lot of memory resources. The proposed architecture of this paper analyzes the logic size, area and power consumption with Xilinx 14.2.
Temporal Difference Learning in Continuous Time and Space

A continuous-time, continuous-state version of the temporal difference (TD) algorithm is derived in order to facilitate the application of reinforcement learning to real-world control tasks and neurobiological modeling. An optimal nonlinear feedback control law was also derived using the derivatives of the value function. The performance of the algorithms was tested in a task of swinging up a pendulum with limited torque. Both the "critic" that specifies the paths to the upright position and the "actor" that works as a nonlinear feedback controller were successfully implemented by radial basis function (RBF) networks.
CACE: Exploiting Behavioral Interactions for Improved Activity Recognition in Multi-inhabitant Smart Homes

We propose CACE (Constraints And Correlations mining Engine) which investigates the challenges of improving the recognition of complex daily activities in multi-inhabitant smart homes, by better exploiting the spatiotemporal relationships across the activities of different individuals. We first propose and develop a loosely-coupled Hierarchical Dynamic Bayesian Network (HDBN), which both (a) captures the hierarchical inference of complex (macro-activity) contexts from lower-layer microactivity context (postural and improved oral gestural context), and (b) embeds the various types of behavioral correlations and constraints (at both micro-and macro-activity contexts) across the individuals. While this model is rich in terms of accuracy, it is computationally prohibitive, due to the explosive increase in the number of jointly-defined states. To tackle this challenge, we employ data mining to learn behaviorally-driven context correlations in the form of association rules, we then use such rules to prune the state space dramatically. To evaluate our framework, we build a customized smart home system and collected naturalistic multi-inhabitant smart home activities data. The system performance is illustrated with results from real-time system deployment experiences in a smart home environment reveals a radical (max 16 fold) reduction in the computational overhead compared to traditional hybrid classification approaches, as well as an improved activity recognition accuracy of max 95%.
Metabolism and Pharmacokinetics of Morinidazole in Humans : Identification of Diastereoisomeric Morpholine N-Glucuronides Catalyzed by UDP Glucuronosyltransferase 1 A 9

Morinidazole [R,S-1-(2-methyl-5-nitro-1H-imidazol-1-yl)-3-morpholinopropan-2-ol] is a new 5-nitroimidazole class antimicrobial agent. The present study aimed to determine the metabolism and pharmacokinetics of morinidazole in humans and to identify the enzymes responsible for the formation of the major metabolites. Plasma and urine samples were collected before and after an intravenous drip infusion of 500 mg of racemic morinidazole. Ultraperformance liquid chromatography/quadrupole time-of-flight mass spectrometry revealed 10 metabolites. Morinidazole glucuronidation, followed by renal excretion, was the major elimination pathway, accounting for 35% of the dose. The metabolic pathway displayed regioselectivities and stereoselectivities. Unexpectedly, the nitrogen atom of the morpholine ring, rather than the aliphatic hydroxyl group at the side chain, was glucuronidated to form S-morinidazole glucuronide (M8-1) and R-enantiomer glucuronide (M8-2). The plasma exposure of M8-2 was 6-fold higher than that of M8-1, accounting for 22.9 and 3.96% of the parent drug exposure, respectively. Investigation of morinidazole glucuronidation using human liver microsomes (HLMs) and 12 recombinant UDP glucuronosyltransferases (UGTs) indicated that this biotransformation was mainly catalyzed by UGT1A9. A kinetic study showed that N -glucuronidation of racemic morinidazole in both HLMs and in UGT1A9 obeyed a typical Michaelis-Menten plot. The Km values for M8-1 and M8-2 formation by HLMs were similar (11.3 and 15.1 mM), but the Vmax values were significantly different (111 and 1660 pmol min 1 mg protein ). Overall, after an intravenous administration, morinidazole and its metabolites were eliminated in humans primarily via renal excretion. The major metabolites were two diastereoisomeric N -glucuronides, and UGT1A9 played an important role in N -glucuronidation.
Complications in using automated methods to increase clinical trial accrual

This paper describes the issues involved in improving accruals for clinical trials using a web-based system. We installed a custom web-based expert system at the H. Lee Moffitt Cancer Center and Research Institute to help physicians screen patients for phase II clinical trials. The system allows physicians to screen a patient for multiple trials simultaneously. Experiments have shown that adaptation of the system into a clinical environment and the success of the system are related to the amount of time physicians are willing to spend entering data. We also found significant regulatory issues (HIPAA) that make implementation challenging.
The problem of small and large matrices in parallel Matrix Multiplication

In this paper we discuss the case in which, using the generalized Cannon's algorithm, it is possible to reduce communications in matrix multiplication. We then apply reduction of communications to the case in which we have to multiply large matrices, in particular rectangular matrices. Two strategies are proposed to solve the problem of multiplying two large squared matrices. For the case in which we have to deal with small matrices, some methods are proposed to use the entire number of processors.
Genetic immunization with adeno-associated virus vectors expressing herpes simplex virus type 2 glycoproteins B and D

Intramuscular injection of mice with an adeno-associated virus (AAV) vector expressing herpes simplex virus type 2 glycoprotein B led to the generation of both gB-specific major histocompatibility complex class I-restricted cytotoxic T lymphocytes and anti-gB antibody. AAV-mediated immunization was more potent than plasmid DNA or protein in generating antibody responses.
An efficient copyright protection scheme for digital images using biometrics and watermarking

The drastic advancement of digital technologies has demanded the owners to pay immense attention in securing their digital contents. Of late, watermarking has been utilized by researchers for the security of digital documents. However the embedded watermark data can be easily hacked by the hackers and thus result as a threat to protection of digital content. The proposed method is an efficient scheme for protecting the copyrights of digital images with the aid of both biometrics and digital watermarking. Our scheme utilizes the fingerprint biometric feature of the proprietor to produce the watermark. The minutiae points are obtained from the fingerprint and the co-ordinates of the minutiae points are shuffled. Later, a vector is formed from the shuffled coordinates of minutiae points and is eventually utilized as watermark. The embedding and extraction of watermark is carried out in the DCT-SVD domain. If any ownership disputes arise on the image, the watermark is extracted from the watermarked image and evaluated against the vector constructed from the shuffled co-ordinates of minutiae points which are obtained from the fingerprint of the person asserting ownership. If they go with each other, the claiming person is considered to be the rightful owner of the image. Therefore the biometric feature employed in our scheme establishes that the information is extremely safe. In addition it is not essential to carry the information; it is not possible for the hackers to hack it as well.
Optimistic Planning in Markov Decision Processes Using a Generative Model

We consider the problem of online planning in a Markov decision process with discounted rewards for any given initial state. We consider the PAC sample complexity problem of computing, with probability 1 - δ, an ∊-optimal action using the smallest possible number of calls to the generative model (which provides reward and next-state samples). We design an algorithm, called StOP (for Stochastic-Optimistic Planning), based on the "optimism in the face of uncertainty" principle. StOP can be used in the general setting, requires only a generative model, and enjoys a complexity bound that only depends on the local structure of the MDP.
Psychopathology in Patients with ICDs over Time: Results of a Prospective Study

Introduction: The effects of implantable cardioverter defibrillators (ICDs) and ICD shocks on psychological state have previously been studied. However, it is still unclear how health‐related quality‐of‐life changes over time using standardized assessments. We sought to characterize the effects of ICDs and ICD shocks on psychological outcomes.
Face-space Action Recognition by Face-Object Interactions

Action recognition in still images has seen major improvement in recent years due to advances in human pose estimation, object recognition and stronger feature representations. However, there are still many cases in which performance remains far from that of humans. In this paper, we approach the problem by learning explicitly, and then integrating three components of transitive actions: (1) the human body part relevant to the action (2) the object being acted upon and (3) the specific form of interaction between the person and the object. The process uses class-specific features and relations not used in the past for action recognition and which use inherently two cycles in the process unlike most standard approaches. We focus on face-related actions (FRA), a subset of actions that includes several currently challenging categories. We present an average relative improvement of 52% over state-of-the art. We also make a new benchmark publicly available.
Multivariate analysis of Web content changes

News websites are expected to deliver in a timely manner the latest stories as well as their latest developments. Thereby, tools, such as, search engines, need to cope with these rapid and frequent content changes by adjusting their crawling activities accordingly. In this paper we explore and model the properties and temporal behavior of the content changes of three major news websites. The dynamics of the changes is characterized by large fluctuations and significant differences from day to day and from hour to hour. However, a certain degree of similarity in the overall patterns of each website exists. In particular, the application of multivariate analysis techniques allows us to identify groups of days with similar change patterns, thus allowing for the customization of the crawling policies adopted by search engines.