Miracle-dz/UniFAR-FTUs huggingface dataset:
An angle super-resolution approach of sparse acoustic vector array based on compressed sensing

In order to improve the Direction of Arrival (DOA) estimation performance of Acoustic Vector Sensor (AVS), an angle super-resolution approach based on Compressed Sensing (CS) is proposed. First, the CS theory is introduced into this field by exploiting the sparsity of target scene. Then, a joint sparse model along with Singular Value Decomposition (SVD) is utilized to accumulate signal power and reduce dimension. Finally, RMFOCUSS is utilized as a performance guaranteed recovery algorithms with available practicability for estimating targets angle. Compared with traditional methods, the proposed approach achieves better angle resolution in coping with both incoherent and coherent signals, also mitigates the high sidelobe problem caused by sparse array effectively.
Price Leadership on the World Crude Oil Market

The paper investigates the role of Saudi Arabia in the dynamic behavior of world crude oil prices over recent decades. The analysis tests the hypothesis that Saudi Arabian crude oil prices lead crude oil prices on the world market. If Saudi Arabian crude oil price has led the prices of other countries on the world crude oil market, there would be a long- run equilibrium relationship between each country's crude oil price and Saudi Arabian price. Comparable geographic data were assembled for six OPEC (Iran, Indonesia, Libya, Nigeria, Saudi Arabia and Venezuela) and six non-OPEC (Canada, China, Mexico, Norway, United Kingdom and United States) countries, covering the period 1970 through 2007. Three widely used econometric techniques (dynamic correlation analysis, cointegration analysis and VAR analysis) are employed. The results support a long-run equilibrium relationship between Saudi Arabian crude oil price and prices in other OPEC and non-OPEC countries.
A system for accurate characterization of wireless sensor networks with power states and energy harvesting system efficiency

Wireless sensor network (WSN) nodes have to cope with severe power supply constraints. Energy harvesting system (EHS) technology is used for prolonging network lifetime. Robust operation of such systems heavily relies on accurate models of EHS efficiency and node power dissipation for calculating sustainable operation modes. A node's energy balance can be described with a power state model (PSM). While for battery operated WSNs PSM measurement errors and battery effects have to be considered, this paper widens the point of view to EHS properties. We analyze varying PSMs at runtime, EHS efficiency and measurement error's impacts on duty cycled WSNs. We show a measurement system setup and results from profiling a PSM for Mica2 nodes with an EHS. We explain important considerations for such systems with showing the variance of a node's energy consumption depending on its supply and we profile EHS efficiency for deducing an energy storage level operating point. The results contribute to problems in the field of low power WSNs and especially EHS supported ones. Robustness of duty cycled WSNs heavily depends on measurement error bounds and is impacted by EHS efficiency. The reader is provided with a methodology for measuring and modeling robust WSNs.
Open-Source Geographic Information Systems Software: Myths and Realities

The development of open-source software has received substantial attention recently. Following the successful examples of projects such as Linux, Apache, and Perl there has been substantial interest by policy makers and researchers on the dynamics of the production of open-source software (Benkler, 2003). A topic of particular interest is the adoption of open-source software systems in developing nations, as a means of reducing licensing costs and of promoting indigenous technological development by having access to the source code of these systems. A recent survey on intellectual property rights and international development commissioned by the government of the United Kingdom underpins such policies with an explicit recommendation.
Energetics of syntrophic fatty acid oxidation

Fatty acids are key intermediates in methanogenic degradation of organic matter in sediments as well as in anaerobic reactors. Conversion of butyrate or propionate to acetate, (CO2), and hydrogen is endergonic under standard conditions, and becomes possible only at low hydrogen concentrations (10 4--10-5 bar). A model of energy sharing between fermenting and methanogenic bacteria attributes a maximum amount of about 20 kJ per mol reaction to each partner in this syntrophic cooperation system. This amount corresponds to synthesis of only a fraction (one-third) of an ATP to be synthesized per reaction. Recent studies on the biochemistry of syntrophic fatty acid-oxidizing bacteria have revealed that hydrogen release from butyrate by these bacteria is inhibited by a protonophore or the ATPase inhibitor DCCD (N,N'-dicyclohexyl carbodiimide), indicating that a reversed electron transport step is involved in butyrate or propionate oxidation. Hydrogenase, butyryl-CoA dehydrogenase, and succinate dehydrogenase acitivities were found to be partially associated with the cytoplasmic membrane fraction. Also glycolic acid is degraded to methane and CO 2 by a defined syntrophic coculture. Here the most difficult step for hydrogen release is the glycolate dehydrogenase reaction (E~=-92 mV). Glycolate dehydrogenase, hydrogenase, and ATPase were found to be membrane-bound enzymes. Membrane vesicles produced hydrogen from glycolate only in the presence of ATP; protonophores and DCCD inhibited this hydrogen release. This system provides a suitable model to study reversed electron transport in interspecies hydrogen transfer between fermenting and methanogenic bacteria in methanogenic biomass degradation.
A PI3-Kinase–Mediated Negative Feedback Regulates Neuronal Excitability

Use-dependent downregulation of neuronal activity (negative feedback) can act as a homeostatic mechanism to maintain neuronal activity at a particular specified value. Disruption of this negative feedback might lead to neurological pathologies, such as epilepsy, but the precise mechanisms by which this feedback can occur remain incompletely understood. At one glutamatergic synapse, the Drosophila neuromuscular junction, a mutation in the group II metabotropic glutamate receptor gene (DmGluRA) increased motor neuron excitability by disrupting an autocrine, glutamate-mediated negative feedback. We show that DmGluRA mutations increase neuronal excitability by preventing PI3 kinase (PI3K) activation and consequently hyperactivating the transcription factor Foxo. Furthermore, glutamate application increases levels of phospho-Akt, a product of PI3K signaling, within motor nerve terminals in a DmGluRA-dependent manner. Finally, we show that PI3K increases both axon diameter and synapse number via the Tor/S6 kinase pathway, but not Foxo. In humans, PI3K and group II mGluRs are implicated in epilepsy, neurofibromatosis, autism, schizophrenia, and other neurological disorders; however, neither the link between group II mGluRs and PI3K, nor the role of PI3K-dependent regulation of Foxo in the control of neuronal excitability, had been previously reported. Our work suggests that some of the deficits in these neurological disorders might result from disruption of glutamate-mediated homeostasis of neuronal excitability.
Topic Modeling with Sentiment Clues and Relaxed Labeling Schema

This paper proposes a method to extract sentiment topics from a text collection. The method utilizes sentiment clues and a relaxed labeling schema to extract sentiment topics. Experiments with a quantitative and a qualitative evaluations was done to confirm the performance of the method. The quantitative evaluation with a polarity classification marked the accuracy of 0.701 in tweets and 0.691 in newswire texts. These performances are comparable to support vector machine baselines. The qualitative evaluation of polarity topic extraction showed an overall accuracy of 0.729, and a higher accuracy of 0.889 for positive topic extraction. The result indicates the efficacy of our method in extracting sentiment topics.
Motion planning of mobile robot considering velocity-dependent cost and time

Unmanned autonomous vehicles are desired to navigate in unstructured environment considering not only obstacle avoidance but also avoidance of unpreferred vibrations and impacts. Such unpreferred motion properties often depend on nature of terrain and velocity of vehicle, which have not been considered sufficiently. This paper presents an unmanned-vehicle's motion optimization method based on such velocity-dependent cost of traversing uneven terrains. The proposed method consists of two parts, prediction of velocity-dependent cost based on visual observation and planning using RASMO reflecting the predicted cost. Simulation and experiments were conducted to verify the proposed method.
Congruences for numerical data of an embedded resolution

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A Statistical Study of De-Embedding Applied to Eye Diagram Analysis

We describe a stable method for calibrating digital waveforms and eye diagrams by use of the measurement system response function and its regularized inverse. The function describing the system response includes the response of the oscilloscope and any associated cables and test fixtures. We demonstrate the effectiveness of the method by performing a statistical analysis of the calculated eye height and eye width obtained from a controlled experiment consisting of multiple cable lengths, bit rates, and oscilloscope samplers. We also demonstrate our approach by measuring the transmission through a test device consisting of a short length of cable, a ball-grid array socket, and complicated circuit board.
Wavelet-based parallel MRI regularization using bivariate sparsity promoting priors

Parallel magnetic resonance imaging (pMRI) relying on multiple receiver coils has emerged as a powerful 3D imaging technique for reducing scanning time or increasing spatial or temporal resolution. The acquired k-space is subsampled, and full field of view (FoV) images are then reconstructed from the acquired aliased data by applying methods such as the SENSE algorithm. However, reconstructed images using SENSE may suffer from several kinds of artifacts mainly because of noise and inaccurate sensitivity profiles. In this paper, we propose a regularized SENSE reconstruction method in which the regularization takes place in the wavelet transform domain. More precisely, a Bayesian strategy is adopted by introducing a bivariate prior to model the complex-valued signal. Experiments on synthetic data and real T1-weighted MRI images at 1.5 Tesla magnetic field show that the proposed method provides improved reconstruction.
Increased detection performance in airport security screening using the x - ray ort as pre - employm

An injection-molded cast aluminum base shell, open at the bottom and having individual openings at the top through which respectively protrude a part of the ignition transformer and a part of the transistorized circuit unit, in each case for external connections, consolidates enough of the circuit components to provide an assembly that can be mounted in an accessible portion of the motor compartment of a vehicle on the vehicle body structure to facilitate comprehensive maintenance attention.
Cannabinoids Enhance NMDA-Elicited Ca2+ Signals in Cerebellar Granule Neurons in Culture

A physiological role for cannabinoids in the CNS is indicated by the presence of endogenous cannabinoids and cannabinoid receptors. However, the cellular mechanisms of cannabinoid actions in the CNS have yet to be fully defined. In the current study, we identified a novel action of cannabinoids to enhance intracellular Ca2+responses in CNS neurons. Acute application of the cannabinoid receptor agonists R(+)-methanandamide, R(+)-WIN, and HU-210 (1–50 nm) dose-dependently enhanced the peak amplitude of the Ca2+ response elicited by stimulation of the NMDA subtype of glutamate receptors (NMDARs) in cerebellar granule neurons. The cannabinoid effect was blocked by the cannabinoid receptor antagonist SR141716A and the Gi/Go protein inhibitor pertussis toxin but was not mimicked by the inactive cannabinoid analogS(−)-WIN, indicating the involvement of cannabinoid receptors. In current-clamp studies neither R(+)-WIN norR(+)-methanandamide altered the membrane response to NMDA or passive membrane properties of granule neurons, suggesting that NMDARs are not the primary sites of cannabinoid action. Additional Ca2+ imaging studies showed that cannabinoid enhancement of the Ca2+ signal to NMDA did not involve N-, P-, or L-type Ca2+ channels but was dependent on Ca2+ release from intracellular stores. Moreover, the phospholipase C inhibitor U-73122 and the inositol 1,4,5-trisphosphate (IP3) receptor antagonist xestospongin C blocked the cannabinoid effect, suggesting that the cannabinoid enhancement of NMDA-evoked Ca2+ signals results from enhanced release from IP3-sensitive Ca2+ stores. These data suggest that the CNS cannabinoid system could serve a critical modulatory role in CNS neurons through the regulation of intracellular Ca2+signaling.
Investigating Children's Play Preferences and Safety in New Zealand Playgrounds

Abstract:Debate on the issue of safety standards in playgrounds centers on the tradeoff between allowing children to manage their own risk, and protecting them from harm. The behavior of children was monitored on 56 playgrounds during the summer on the North Island of New Zealand. The most-commonly featured play items were swings, slides and climbing apparatus. Swinging was the most popular play activity for all children, followed by spinning (roundabouts, spinning tops), and climbing. Accident events were rare, with a risk of minor injury of 0.1 per child per hour. Failure to provide shade contributed to the under-use of slides, which were frequently hot to the touch. Older children still use playgrounds, although older girls seem poorly served by the emphasis on skate parks and sporting activities. The needs of children to experience risk and challenge should be balanced against safety when designing playgrounds.
Highly specific and quantitative gene expression profiling based on DNA computing

DNA chips and microarrays have been used to simultaneously analyze the expression profiling of many genes [1, 2]. In the analysis, the two-color method [3] is generally employed to determine the relative expression levels between two samples. However, not only the relative expression levels between target genes in a sample but also the absolute expression level of each target gene in a sample cannot be determined accurately with conventional DNA chips and microarrays combined with the two-color method. This hinders extensive and quantitative analysis of gene expression profiling data using bioinformatics. Here, we introduce a gene expression profiling method based on DNA computing, which enable us to know the absolute amount of target gene transcripts.
Structural insight into the catalytic mechanism of gluconate 5‐dehydrogenase from Streptococcus suis: Crystal structures of the substrate‐free and quaternary complex enzymes

Gluconate 5‐dehydrogenase (Ga5DH) is an NADP(H)‐dependent enzyme that catalyzes a reversible oxidoreduction reaction between D‐gluconate and 5‐keto‐D‐gluconate, thereby regulating the flux of this important carbon and energy source in bacteria. Despite the considerable amount of physiological and biochemical knowledge of Ga5DH, there is little physical or structural information available for this enzyme. To this end, we herein report the crystal structures of Ga5DH from pathogenic Streptococcus suis serotype 2 in both substrate‐free and liganded (NADP+/D‐gluconate/metal ion) quaternary complex forms at 2.0 Å resolution. Structural analysis reveals that Ga5DH adopts a protein fold similar to that found in members of the short chain dehydrogenase/reductase (SDR) family, while the enzyme itself represents a previously uncharacterized member of this family. In solution, Ga5DH exists as a tetramer that comprised four identical ∼29 kDa subunits. The catalytic site of Ga5DH shows considerable architectural similarity to that found in other enzymes of the SDR family, but the S. suis protein contains an additional residue (Arg104) that plays an important role in the binding and orientation of substrate. The quaternary complex structure provides the first clear crystallographic evidence for the role of a catalytically important serine residue and also reveals an amino acid tetrad RSYK that differs from the SYK triad found in the majority of SDR enzymes. Detailed analysis of the crystal structures reveals important contributions of Ca2+ ions to active site formation and of specific residues at the C‐termini of subunits to tetramer assembly. Because Ga5DH is a potential target for therapy, our findings provide insight not only of catalytic mechanism, but also suggest a target of structure‐based drug design.
Energy-Aware Dynamic Resource Allocation on Hadoop YARN Cluster

The web big data applications are executed on Hadoop cluster in the cloud datacenter, which requires large amounts of energy. And the energy costs take a considerable fraction of the data center's overall costs. Therefore, the reduction of the energy consumption in the cloud datacenter becomes a critical issue. In this paper, we propose energy-aware dynamic node management technology for online MapReduce jobs by powering on/off nodes in Hadoop cluster to reduce energy consumption while meet user's Service Level Agreements (SLA). Under the dynamic node management policy, the time-varying workload is predicted by extracting the MapReduce job history information continuously. And then, the energy-aware dynamic node management with deadline-driven is used to keep the proper number of nodes for MapReduce tasks based on the average execution time of containers and predictive workloads. Finally, the nodes which have been kept in idle state for threshold duration are turned off to reduce energy costs. We perform extensive simulations on a Yarn Scheduler Load Simulator (SLS) to exploit the energy consumption, the violations on SLA and execution time for each big data application in a period of time. The experimental results demonstrate that our proposed policy to achieve energy savings over comparable four policies with respect to meeting SLA.
The n-Component KP Hierarchy and Representation Theory

It is the aim of the present article to give all formulations of the n-component KP hierarchy and clarify connections between them. The generalization to the n-component KP hierarchy is important because it contains many of the most popular systems of soliton equations, like the Davey–Stewartson system (for n=2), the two-dimensional Toda lattice (for n=2), the n-wave system (for n⩾3) and the Darboux–Egoroff system. It also allows us to construct natural generalizations to the Davey–Stewartson and Toda lattice systems. Of course, the inclusion of all these systems in the n-component KP hierarchy allows us to construct their solutions by making use of vertex operators.
Does an iPad Change the Experience? A Look at Mother-Child Book Reading Interactions

Does an iPad Change the Experience? A Look at Mother-Child Book Reading Interactions Kathryn L. MacKay Education Inquiry, Measurement, and Evaluation, BYU Doctorate of Philosophy Researchers have long argued the importance of shared book reading and its potential impact on future reading growth. With the increasing popularity of e-books and the introduction of interactive iPad books, more and more parents are sharing books with their children in digital format. This may have a direct impact on the nature of the interactions that occur during young children’s early book sharing experiences. This multiple-case study examined the nature of the interactions between six mother-child dyads as they read a story on an iPad compared with the interactions that happened during a traditional book reading. A coding system was developed to categorize behaviors during the reading sessions. The categories included (a) meaning talk, (b) text and print talk, (c) technology talk, and (d) the nature of the affective climate. The results of this study indicate that mother-child traditional read-alouds and digital iPad read-alouds are different experiences. During digital readings there was an increase in the number of vocabulary-related (a subcategory of meaning) interactions but a decrease in the number of interactions related to text and print. The results also showed that as the dyad shared a digital storybook, they engaged in many interactions about the technological elements of the iPad texts, which may be important to the development of digital literacies in young children. The findings also indicate that a child is more engaged with digital texts than with traditional texts, which is important because engagement is an essential component in literacy development. However, sometimes the child’s increased engagement with the digital texts resulted in both members of the dyad being less sensitive to the other. Digital storybook reading is a relatively new experience for many parents and thus, they may not know how to interact with their children in ways that promote the development of traditional and digital literacies.
Skin-Aware Stylization of Video Portraits

This paper presents a new non-photorealistic/stroke-based rendering (NPR/SBR) framework for the stylization of videos featuring head shots of people, such as home videos, movies, and camera mobile phone clips. Spatiotemporal skin and edge detection are used to locate and emphasize the semantic content in the stylization process. The SBR portion of the algorithm features novel techniques for motion expression with elliptical brush strokes, brush stroke anchor point distribution, spatio-temporal color-sampling, and brush stroke animation with regard to state-of-the-art issues such as object occlusion and uncovering in the source video. A wide user-accessible parameter space and finishing touches such as cartoon-like edge decoration and other quirky effects empowers a variety of artistic outputs. The resulting stylized sequences are fun and interesting with regard to compression, summarization, motion visualization, story-boarding and art. Both the semantic content, and underlying video motion is highlighted and summarized on every frame of the stylized output sequence.
Labeled directed graphs and FSA as classifiers of strings

The classical concept of a finite state automaton (FSA) has long been used in computer science to classify formal languages regarded as sets of strings. This paper surveys and unifies recent results on strings recognized by FSA defined by labeled directed graphs, and highlights several interesting open questions. In particular, one of our open questions deals with a new method of applying a related construction to classification
DOES A ROTTEN APPLE SPOIL THE REST ? CRIME AND SOCIAL INTERACTION IN ARGENTINA

Violence shows strong disparities between regions and time. The most obvious explanation for such disparities is that both economic and social conditions change over regions and time. However, it is found that less than 50% of the variance of crime is explained by economic and deterrence variables. One of the possible explanations for such puzzle may be the existence of social interaction across agents. If such interaction exists then it can be argued that it plays a role in explaining higher variance in crime rates unexplained by urban/economic characteristics. Using a database for 390 counties in Argentina we find evidence of social interaction for robberies, but such interaction is negligible for more serious crimes (homicide and rape).