Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonlinear speed observer for high-performance induction motor control

In this paper, we consider the problem of estimating the angular velocity of an induction motor using encoder measurements. Two methods are compared. In the first method, the speed is found by calculating the backward difference of the position measurement and low-pass filtering the result. In the second method, the velocity is estimated using a nonlinear observer constructed using the known dynamic model of the induction motor. The performance of the two methods is evaluated in the context of their use for velocity feedback in a high-performance field-oriented control law. Experimental results demonstrate that the speed observer leads to a smoother operation of the motor in closed-loop. With the estimator based on differentiation, either the delay imposed by the low-pass filter is too large to maintain high bandwidth feedback, or the fluctuations in the estimated speed are so large that much more energy ends up being dissipated to achieve the same control task. >
Software-cooperative power-efficient heterogeneous multi-core for media processing

A heterogeneous multi-core processor (HMCP) architecture, which integrates general purpose processors (CPU) and accelerators (ACC) to achieve high-performance as well as low-power consumption with the support of a parallelizing compiler, was developed. The evaluation was performed using an MP3 audio encoder on a simulator that accurately models the HMCP. It showed that 16-frame encoding on the HMCP with four CPUs and four ACCs yielded 24.5-fold speed-up of performance against sequential execution on one CPU. Furthermore, power saving by the compiler reduced energy consumption of the encoding to 0.17 J, namely, by 28.4%.
A Gang of Bandits

Multi-armed bandit problems formalize the exploration-exploitation trade-offs arising in several industrially relevant applications, such as online advertisement and, more generally, recommendation systems. In many cases, however, these applications have a strong social component, whose integration in the bandit algorithm could lead to a dramatic performance increase. For instance, content may be served to a group of users by taking advantage of an underlying network of social relationships among them. In this paper, we introduce novel algorithmic approaches to the solution of such networked bandit problems. More specifically, we design and analyze a global recommendation strategy which allocates a bandit algorithm to each network node (user) and allows it to "share" signals (contexts and payoffs) with the neghboring nodes. We then derive two more scalable variants of this strategy based on different ways of clustering the graph nodes. We experimentally compare the algorithm and its variants to state-of-the-art methods for contextual bandits that do not use the relational information. Our experiments, carried out on synthetic and real-world datasets, show a consistent increase in prediction performance obtained by exploiting the network structure.
Object-based Saliency as a Predictor of Attention in Visual Tasks

The top-down guidance of visual attention is an important factor allowing humans to effectively process incoming visual information. Our understanding of the processes governing attention is not complete, with growing evidence for attention selection based on cognitive relevance. In this paper, we investigate whether models for salient object detection from computer vision can be used to predict attentional shifts in visual tasks. Our results show that the object-based interpretation of saliency provided by these models is a substantially better predictor of fixation locations than traditional pixel-based saliency.
Roles for Sphingolipid Biosynthesis in Mediation of Specific Programs of the Heat Stress Response Determined through Gene Expression Profiling*

Previous studies have demonstrated roles for de novo production of sphingolipids in Saccharomyces cerevisiae in the regulation of the transient cell cycle arrest and nutrient permease degradation associated with the heat stress response, suggesting multiple functions for yeast sphingolipids in this response. We, therefore, sought to determine the generalized involvement of sphingolipids in the heat stress response by using microarray hybridization of RNA isolated from heat-stressed cultures of the mutant strain lcb1–100, which is unable to produce sphingolipids in response to heat. Approximately 70 genes showed differential regulation during the first 15 min of heat stress in the lcb1–100 strain compared with the wild type strain, indicating a requirement for de novo sphingolipid biosynthesis for proper regulation of these genes during heat stress. Grouping these genes into functional categories revealed several pathways, including some in which sphingolipids were previously suspected to play a role, such as stress response pathways and cell cycle regulation. Hierarchical clustering analysis revealed sphingolipid involvement in regulation of tRNA synthesis and metabolic genes and transporters. Additionally, the microarray results demonstrated novel sphingolipid involvement in transcriptional regulation of pathways of translation and cell wall organization and biogenesis. Our results demonstrate a broad-reaching effect of sphingolipids in the yeast heat stress response and suggest that the mechanism of sphingolipid involvement in several cellular pathways occurs via sphingolipid-mediated regulation of message levels.
MULTIPLE DICTIONARY FOR SPARSE MODELING

Much of the progress made in image processing in the past decades can be attributed to better modeling of image content, and a wise deployment of these models in relevant applications. In this paper, we review the role of this recent model in image processing, its rationale, and models related to it. As it turns out, the field of image processing is one of the main beneficiaries from the recent progress made in the theory and practice of sparse and redundant representations. Sparse coding is a key principle that underlies wavelet representation of images. Sparse representation based classification has led to interesting image recognition results, while the dictionary used for sparse coding plays a key role in it. In general, the choice of a proper dictionary can be done using one of two ways: i) building asparsifying dictionary based on a mathematical model of the data, or ii) learning a dictionary to perform best on a training set.
A coalition formation mechanism based on inter-agent trust relationships

We study long-term coalitions of customer and vendor software agents based on trust relationships among the agents. We propose a coalition formation mechanism designed at microscopic (agent) level and analyzed at both microscopic and macroscopic (system) levels. The evaluation compares agent strategies (individual vs. social) and analyzes the system behavior under different circumstances. The advantages of the mechanism are that it is simple, scales up well and does not require communication between the agents. It reduces the dynamic of the system and is beneficial for the individual agents (ensures higher individual gain).
Effects of total glucosides of peony on immunological hepatic fibrosis in rats.

AIM To study the effects of total glucosides of peony (TGP) on immunological hepatic fibrosis induced by human albumin in rats. METHODS Sixty adult male Sprague-Dawley rats were randomly divided into: Normal group, model group, TGP (60 and 120 mg/kg) treatment groups and colchicines (0.1 mg/kg) treatment group. On the day before the rats were killed, those in TGP or colchicine groups received TGP or colchicine as above from the first day of tail vein injection of human albumin. The rats in normal and model groups were only administered with the same volume of vehicle. At the end of the 16th wk, rats in each group were killed. Blood and tissue specimens were taken. Levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), nitric oxide (NO), content of malondialdehyde (MDA), activity of superoxide dismutase (SOD) and glutathione peroxidase (GSH-px), were measured by biochemical methods. Serum procollagen type III (PC III) and laminin (LN) were determined by radioimmunoassay. Liver collagen level was determined by measuring hydroxyproline content in fresh liver samples. Hepatic tissue sections were stained with hematoxylin-eosin and examined under a light microscope. RESULTS Histological results showed that TGP improved the human albumin-induced alterations in the liver structure, alleviated lobular necrosis and significantly lowered collagen content. The antifibrotic effect of TGP was also confirmed by decreased serum content of LN and PCIII in TGP-treated group. Moreover, the treatment with TGP effectively reduced the hydroxyproline content in liver homogenates. However, the level of ALT and AST increased in fibrotic rat but had no significance compared with normal control, whereas the ratio of A/G decreased without significance. TGP had no effect on level of ALT, AST and the ratio of A/G. Furthermore, TGP treatment significantly blocked the increase in MDA and NO, associated with a partial elevation in liver total antioxidant capacity including SOD and GSH-px. CONCLUSION TGP has beneficial effects on hepatic fibrosis in rats by inhibition of collagen synthesis and decreasing oxidative stress.
The effects of categorical and linguistic adaptation on binocular rivalry initial dominance

Binocular rivalry (BR) is a phenomenon in which visual perception alternates between two different monocular stimuli. There has been a long debate regarding its nature, with a special emphasis on whether low- or high-level mechanisms are involved. Prior adaptation to one of the two monocular stimuli is known to affect initial dominance in the subsequent dichoptic presentation. In the present work, we have used three different types of adaptation in order to investigate how each one affects initial dominance during BR. In the first adaptation type, adapting to a stimulus identical to the one used during rivalry has led to its consequent suppression, verifying previous findings. The binocular presentation which we have used excludes the possibility of eye-adaptation, suggesting that it is the specific stimulus that the brain adapts to. In the second adaptation type, we find suppression effects following adaptation to stimuli belonging to the same category (face or house) but are different from the specific ones used in the following BR presentation. In the final adaptation type, in which the words “face” or “house” are used as adaptors, no statistically significant effect was found. These results suggest that perceptual selection can be directly influenced by the prior presentation of visual stimuli different to the ones used during BR, and thus support a higher-level, cognitive influence on the latter.
Enhancing Observability in Distribution Grids Using Smart Meter Data

Due to limited instrumentation, distribution grids are currently challenged by observability issues. On the other hand, smart meter data are communicated to utility operators from nodes with renewable generation and elastic demand. This paper employs grid data from metered buses toward inferring the underlying grid state. System nodes are partitioned into buses with time-varying injections that are assumed metered, and buses with relatively stationary conventional loads that are non-metered. Exploiting the variability at metered buses and the stationarity of conventional loads, the novel idea here is to solve the non-linear power flow (PF) equations jointly over consecutive time instants. By putting forth a coupled formulation of the PF problem (CPF), grid states can be recovered by metering fewer buses. An intuitive and easily verifiable rule pertaining to the locations of (non-)metered buses on the physical grid is shown to be a necessary and sufficient criterion for local observability in radial networks. To account for noisy smart meter readings, a coupled power system state estimation (CPSSE) problem is further devised. Both CPF and CPSSE tasks are tackled via augmented semi-definite program relaxations. The observability criterion along with the CPF and CPSSE solvers are numerically corroborated using randomly generated and actual solar and load data on the IEEE 34-bus benchmark feeder.
Imaging Atherosclerosis

Advances in atherosclerosis imaging technology and research have provided a range of diagnostic tools to characterize high-risk plaque in vivo; however, these important vascular imaging methods additionally promise great scientific and translational applications beyond this quest. When combined with conventional anatomic- and hemodynamic-based assessments of disease severity, cross-sectional multimodal imaging incorporating molecular probes and other novel noninvasive techniques can add detailed interrogation of plaque composition, activity, and overall disease burden. In the catheterization laboratory, intravascular imaging provides unparalleled access to the world beneath the plaque surface, allowing tissue characterization and measurement of cap thickness with micrometer spatial resolution. Atherosclerosis imaging captures key data that reveal snapshots into underlying biology, which can test our understanding of fundamental research questions and shape our approach toward patient management. Imaging can also be used to quantify response to therapeutic interventions and ultimately help predict cardiovascular risk. Although there are undeniable barriers to clinical translation, many of these hold-ups might soon be surpassed by rapidly evolving innovations to improve image acquisition, coregistration, motion correction, and reduce radiation exposure. This article provides a comprehensive review of current and experimental atherosclerosis imaging methods and their uses in research and potential for translation to the clinic.
miRNA Expression in Control and FSHD Fetal Human Muscle Biopsies

Background Facioscapulohumeral muscular dystrophy (FSHD) is an autosomal-dominant disorder and is one of the most common forms of muscular dystrophy. We have recently shown that some hallmarks of FSHD are already expressed in fetal FSHD biopsies, thus opening a new field of investigation for mechanisms leading to FSHD. As microRNAs (miRNAs) play an important role in myogenesis and muscle disorders, in this study we compared miRNAs expression levels during normal and FSHD muscle development. Methods Muscle biopsies were obtained from quadriceps of both healthy control and FSHD1 fetuses with ages ranging from 14 to 33 weeks of development. miRNA expression profiles were analyzed using TaqMan Human MicroRNA Arrays. Results During human skeletal muscle development, in control muscle biopsies we observed changes for 4 miRNAs potentially involved in secondary muscle fiber formation and 5 miRNAs potentially involved in fiber maturation. When we compared the miRNA profiles obtained from control and FSHD biopsies, we did not observe any differences in the muscle specific miRNAs. However, we identified 8 miRNAs exclusively expressed in FSHD1 samples (miR-330, miR-331-5p, miR-34a, miR-380-3p, miR-516b, miR-582-5p, miR-517* and miR-625) which could represent new biomarkers for this disease. Their putative targets are mainly involved in muscle development and morphogenesis. Interestingly, these FSHD1 specific miRNAs do not target the genes previously described to be involved in FSHD. Conclusions This work provides new candidate mechanisms potentially involved in the onset of FSHD pathology. Whether these FSHD specific miRNAs cause deregulations during fetal development, or protect against the appearance of the FSHD phenotype until the second decade of life still needs to be investigated.
Relativistic dynamics of electrons in intense laser fields.

Following a brief review of the analytic solution for the relativistic motion of a single electron in a pulse of very strong plane-wave radiation, numerical simulations are presented that probe the effects of space-charge forces and spatial inhomogeneity of the radiation upon the one-electron dynamics. The nonlinearities introduced by relativistic effects can lead to irregular dynamics. For pulses with a smoothly varying temporal envelope the behavior of electrons that are ionized during the pulse can be very different from that of ambient electrons. The calculations support the use of short-pulsed lasers to produce high-energy electrons and incoherent x rays, but reveal possible difficulties in the formation of cold overionized plasmas suitable for recombination lasers.
Improving the design of interoperable platform through a structured case study description approach: Application to a nuclear crisis

In this article, we briefly describe a crisis management case that has been chosen (in the European funded project PLAY) to test the federated-open-trusted platform for event-driven interaction between services. A description of such complex use case in natural language is obviously limited and should be completed with a formal description methodology to gather the necessary knowledge. Considering our technical requirements we suggest to combine the S-Cube approach with the model driven architecture approach to propose a complete and structured case study description framework. Then this article presents a nuclear crisis case modeled according to these guidelines.
Integrating Diagnostic B-Mode Ultrasonography Into CT-Based Radiation Treatment Planning

This paper presents methods and a clinical procedure for integrating B-mode ultrasound images tagged with position information with a planning computed tomography (CT) scan for radiotherapy. A workflow is described that allows the integration of these modalities into the clinic. A surface mapping approach provides a preregistration of the ultrasound image borders onto the patient's skin. Successively, a set of individual ultrasound images from a freehand sweep is chosen by the physician. These images are automatically registered with the planning CT scan using novel intensity-based methods. We put a particular focus on deriving an appropriate similarity measure based on the physical properties and artifacts of ultrasound. A combination of a weighted mutual information term, edge correlation, clamping to the skin surface, and occlusion detection is able to assess the alignment of structures in ultrasound images and information reconstructed from the CT data. We demonstrate the practicality of our methods on five patients with head and neck tumors and cervical lymph node metastases and provide a detailed report on the conducted experiments, including the setup, calibration, acquisition, and verification of our algorithms. The mean target registration error on nine data sets is 3.9 mm. Thus, the additional information about intranodal architecture and fulfillment of malignancy criteria derived from a high-resolution ultrasonography of lymph nodes can be localized and visualized in the CT scan coordinate space and is made available for further radiation treatment planning.
3D-DART: a DNA structure modelling server

There is a growing interest in structural studies of DNA by both experimental and computational approaches. Often, 3D-structural models of DNA are required, for instance, to serve as templates for homology modeling, as starting structures for macro-molecular docking or as scaffold for NMR structure calculations. The conformational adaptability of DNA when binding to a protein is often an important factor and at the same time a limitation in such studies. As a response to the demand for 3D-structural models reflecting the intrinsic plasticity of DNA we present the 3D-DART server (3DNA-Driven DNA Analysis and Rebuilding Tool). The server provides an easy interface to a powerful collection of tools for the generation of DNA-structural models in custom conformations. The computational engine beyond the server makes use of the 3DNA software suite together with a collection of home-written python scripts. The server is freely available at http://haddock.chem.uu.nl/dna without any login requirement.
Suggestion of probabilistic reward-independent knowledge for dynamic environment in reinforcement learning

Recently, reinforcement learning attracts attention as the learning technique that is often used on actual robot. As one of problems of reinforcement learning, it is difficult for reinforcement learning to cope with changing purpose, because reinforcement learning depend on reward. Until now, we suggested that we learned to use information does not depend on reward for solving the problem. This information is environmental transition. We defined this information as “Reward-Independent Knowledge (RIK)”. A robot gets RIK and predicts route from initial state to purpose state by using RIK. Reinforcement learning can cope with changing purpose by using RIK. However, it is difficult for RIK to cope with dynamic environment, because RIK is one to one correspondence between state-action pair and next state. Therefore, we suggest that RIK has multiple next state and probability of each possible next state. In this paper, we perform an experiment by simulation. We show that suggested knowledge copes with changing purpose and dynamic environment. In this experiment, we adopt a maze problem which a goal change and changing structure of maze. By this, we will show that suggested knowledge can cope with changing purpose and dynamic environment.
Evaluation of routing schemes in opportunistic networks considering energy consumption

Opportunistic networks are challenged wireless networks where most of the time contacts are intermittent and link performance is typically highly variable. In this kind of environment, an end-to-end path between the source and the destination may only exist for a brief period and may change quickly. Long propagation and variable queuing delays might be introduced and conventional routing protocols for mobile ad hoc networks are inappropriate to deliver messages between nodes. Different routing protocols for opportunistic networks have been proposed in the literature. In most cases, authors evaluate the performance of their protocols considering metrics like delivery ratio and delivery latency, disregarding the importance of energy consumption constraint. In this work we compare the performance of the Epidemic, Spray and Wait, PROPHET, MaxProp and Bubble Rap routing protocols considering energy consumption. We evaluate how the energy consumption impacts the routing performance and how the different forwarding algorithms for opportunistic networks influence the energy usage in the mobile nodes.
X‐ray powder diffraction of polymer/layered silicate nanocomposites: Model and practice

X-ray powder diffraction in reflection (Bragg-Brentano parafocusing geometry) is extensively used to characterize the structure of polymer/layered silicate nanocomposites (PLSNs). The large basal spacings (d 001 > 2.0 nm) necessitates the collection of data at scattering angles (2θ) of less than 10°. The calculation of an ideal scattering profile for PLSNs provides an avenue to ascertain the influence of experimental parameters and the arrangement, organization, concentration, and composition of constituents on the experimentally observed pattern. This enables better experimental technique, more complete utilization of the scattering data, insight into inconsistencies between scattering and microscopy, and minimization of incorrect interpretation or overinterpretation of data. Because of the strong θ dependence of theoretical and experimental factors at low values of 2θ, careful sample preparation and data evaluation are necessary and should be complemented by microscopic observations, especially for PLSNs with low volume fractions of organically-modified layered silicates (OLS) that are suspected of having exfoliated morphologies. X-ray powder diffraction in reflection alone is insufficient to completely characterize and ascribe PLSN morphology.