Miracle-dz/UniFAR-FTUs huggingface dataset:
Waveforms of Terahertz Radiation Emitted from Superconducting Dipole Antenna

We have observed the ultrashort electromagnetic pulse radiation from a current-biased bow-tie structure of YBa2Cu3O7-delta thin film dipole antenna on MgO using 100 fs, 750 nm laser pulses. With the electro-optic detection, we obtained the THz pulses with 1.0 ps full width at half maximum, containing frequency components up to 1.0 THz. The THz peak amplitude dependence shows the saturation and a nonlinear behavior with a higher excitation pumping power and with the applied bias currents. The saturation on the dependence with the excitation powers exhibits the bolometric heating in nature. However, the nonlinear characterization of the THz radiation from the superconductive thin film antenna revealed that the inadequacy of pure supercarrier approximation on a two-fluid model. The ultrashort transient response and the deviation from the classical theory are discussed in relation to the quasiparticle dynamics of the nonequilibrium mechanism.
Reasoning About Compositions of Concerns

In this paper we propose a framework for defining and reasoning about compositions of concerns, based on multivalued logics. Rather than providing a small set of built-in composition operations, our framework provides a mechanism for constructing arbitrary types of composition. Our multi-valued logic model checker, chek allows us to reason about the properties of compositions of concerns.
A verification theorem for hybrid optimal control problem

A class of the hybrid optimal control problem is formulated and a hybrid dynamic programming principle (DPP) is presented which constitutes a generalization of the celebrated dynamic programming principle of Richard Bellman [1]. It is shown that similarly to the case of continuous dynamic programming, which leads to the well known Hamilton-Jacobi-Bellman (HJB) functional partial differential equation, the hybrid dynamic programming principle (HDPP) leads to a hybrid HJB equation.
Curiosities of REPINs and RAYTs

Repetitive extragenic palindromic (REP) sequences are a ubiquitous feature of bacterial genomes. Recent work shows that REPs are remnants of a larger mobile genetic element termed a REPIN. REPINs consists of two REP sequences in inverted orientation separated by a spacer region and are thought to be non-autonomous mobile genetic elements that exploit the transposase encoded by REP-Associated tYrosine Transposases (RAYTs). Complimentarity between the two ends of the REPIN suggests that the element forms hairpin structures in single stranded DNA or RNA. In addition to REPINs, other more complex arrangements of REPs have been identified in bacterial genomes, including the genome of the model organism Pseudomonas fluorescens SBW25. Here, we summarize existing knowledge and present new data concerning REPIN diversity. We also consider factors affecting the evolution of REPIN diversity, the ease with which REPINs might be co-opted by host genomes and the consequences of REPIN activity for the structure of bacterial genomes.
Unified speech and audio coding scheme for high quality at low bitrates

Traditionally, speech coding and audio coding were separate worlds. Based on different technical approaches and different assumptions about the source signal, neither of the two coding schemes could efficiently represent both speech and music at low bitrates. This paper presents a unified speech and audio codec, which efficiently combines techniques from both worlds. This results in a codec that exhibits consistently high quality for speech, music and mixed audio content. The paper gives an overview of the codec architecture and presents results of formal listening tests comparing this new codec with HE-AAC(v2) and AMR-WB+. This new codec forms the basis of the reference model in the ongoing MPEG standardization activity for Unified Speech and Audio Coding.
A two-level hybrid evolutionary algorithm for modeling one-dimensional dynamic systems by higher-order ODE models

This paper presents a new algorithm for modeling one-dimensional (1-D) dynamic systems by higher-order ordinary differential equation (HODE) models instead of the ARMA models as used in traditional time series analysis. A two-level hybrid evolutionary modeling algorithm (THEMA) is used to approach the modeling problem of HODE's for dynamic systems. The main idea of this modeling algorithm is to embed a genetic algorithm (GA) into genetic programming (GP), where GP is employed to optimize the structure of a model (the upper level), while a GA is employed to optimize the parameters of the model (the lower level). In the GA, we use a novel crossover operator based on a nonconvex linear combination of multiple parents which works efficiently and quickly in parameter optimization tasks. Two practical examples of time series are used to demonstrate the THEMA's effectiveness and advantages.
Journal of Graph Algorithms and Applications Generalizing Geometric Graphs

Network visualization is essential for understanding the data obtained from huge real-world networks such as flight-networks, the AS-network or social networks. Although we can compute layouts for these networks reasonably fast, even the most recent display media are not capable of displaying these layouts in an adequate way. Moreover, the human viewer may be overwhelmed by the displayed level of detail. The increasing amount of data therefore requires techniques aiming at a sensible reduction of the visual complexity of huge layouts. We consider the problem of computing a generalization of a given layout reducing the complexity of the drawing to an amount that can be displayed without clutter and handled by a human viewer. We take a first step at formulating graph generalization within a mathematical model and we consider the resulting problems from an algorithmic point of view. We show that these problems are NP-hard in general, and provide efficient approximation algorithms as well as efficient and effective heuristics. We also showcase some sample generalizations.
Artificially intelligent accompaniment using Hidden Markov Models to model musical structure

For performing musicians, musical accompanists may not always be available during practice, or an available accompanist may not have the technical ability necessary. As a solution to this problem, many musicians practise with pre-recorded accompaniment. Such an accompaniment is fixed and does not interact with the musicians playing: the musician must adapt their performance to match the recording. To synchronise accompaniment with the soloist, it is preferable that an accompanist should be able to follow the musician through the score as they play, rather than the other way around. During performance, musicians may deviate from what is written in the score (either intentionally, by adding their own musical interpretation, or accidentally, by making performance errors). The accompanist should adjust their playing to follow the soloist. This work investigates how an artificial musician can follow a human musician through the performance of a piece (perform score following) using a Hidden Markov Model of the pieces musical structure. The computer musician is designed to interact with the human musician and provide accompaniment as a human accompanist would: musically and in real time. Having successfully implemented this representation, the performances of the resulting artificial accompanists has been evaluated both qualitatively, by human testers and quantitatively, by objective criteria based on that used at the Music Infomation Retrieval and EXchange Conference in 2006. The artificial accompanists can, in general, accompany human performers with a reasonable degree of accuracy. Testing has also raised an interesting reflection on the nature of co-operation between soloist and accompanist, and more generally on the role of the computer musician in ensemble performance.
Metabolic Network Discovery by Top-Down and Bottom-Up Approaches and Paths for Reconciliation

The primary focus in the network-centric analysis of cellular metabolism by systems biology approaches is to identify the active metabolic network for the condition of interest. Two major approaches are available for the discovery of the condition-specific metabolic networks. One approach starts from genome-scale metabolic networks, which cover all possible reactions known to occur in the related organism in a condition-independent manner, and applies methods such as the optimization-based Flux-Balance Analysis to elucidate the active network. The other approach starts from the condition-specific metabolome data, and processes the data with statistical or optimization-based methods to extract information content of the data such that the active network is inferred. These approaches, termed bottom-up and top-down, respectively, are currently employed independently. However, considering that both approaches have the same goal, they can both benefit from each other paving the way for the novel integrative analysis methods of metabolome data- and flux-analysis approaches in the post-genomic era. This study reviews the strengths of constraint-based analysis and network inference methods reported in the metabolic systems biology field; then elaborates on the potential paths to reconcile the two approaches to shed better light on how the metabolism functions.
Design and Development of an Adaptive Workflow-Enabled Spatial-Temporal Analytics Framework

Cloud computing is a suitable platform for execution of complex computational tasks and scientific simulations that are described in the form of workflows. Such applications are managed by Workflow Management System (WfMS). Because existing WfMSs are not able to autonomically provision resources to real-time applications and schedule them while supporting fault tolerance and data privacy, we present a highly-scalable workflow-enabled analytics system that manages inter-dependable analytics tasks adaptively with varying operational requirements on a common platform and enables visualization of multidimensional datasets of real world phenomena. In this paper, we present the architecture of such a WfMS and evaluate it in terms of performance for execution of workflows in Clouds. A real world application of climate-associated dengue fever prediction was evaluated on public, private, and hybrid Clouds and experienced effective speedup in all the environments.
A Predictive Traffic Controller for Sustainable Mobility Using Parameterized Control Policies

We present a freeway-traffic control strategy that continuously adapts traffic control measures to prevailing traffic conditions and features faster computation speed than conventional model-based predictive control (MPC). The control approach is based on the principles of state feedback control and MPC. Instead of computing the control input sequence, the proposed controller optimizes the parameters of control laws that parametrize the control input sequences. This way, the computational burden of the controller is substantially reduced. We demonstrate the proposed control approach on a calibrated model of part of the Dutch A12 freeway using variable speed limits and ramp-metering rate.
Neurological signs and results of magnetic resonance imaging in 40 cavalier King Charles spaniels with Chiari type 1-like malformations

In human beings a Chiari type 1 malformation is a developmental condition characterised by cerebellar herniation and syringohydromyelia. Abnormalities compatible with such a malformation were identified by magnetic resonance imaging in 39 cavalier King Charles spaniels with neurological signs and in one neurologically normal cavalier King Charles spaniel that was examined postmortem. The dogs with these abnormalities had a wide variety of neurological signs, but there was no apparent correlation between the neurological signs and the severity of cerebellar herniation, syringohydromyelia or hydrocephalus.
Shaping the future of prevention in social work: an analysis of the professional literature from 2000 through 2010.

In light of the Patient Protection and Affordable Care Act's goals of better patient care, cost control, and improved population outcomes, prevention has emerged as an important component of health reform. Social work, with its extensive involvement in the health system and deep roots in public health, can benefit from a better understanding of its role in prevention. This study builds on the Social Work Interest in Prevention Study (SWIPS), which evaluated extent, type, and levels of prevention content in nine social work journals from 2000 to 2005. The goal of the expanded study, the SWIPS-Expansion, was to assess whether interest in prevention increased over the years in which health reform was enacted. Of the 3,745 articles reviewed, 9.0 percent (n = 336) met the criteria for "prevention articles. " Between 2000 and 2010, prevention articles rose from 4.1 percent to 14.3 percent of all articles. A secondary analysis focused on topics within social work prevention, with violence, aging, and disease as primary focal areas. The findings suggest that although prevention interest appears to be growing, it remains a minority focus in the profession's journals. A national conversation on prevention can help expand the profession's role in health reform at this critical time.
Analysis and prototyping of multicellular ac-dc converter for future dc distribution system

A multicellular ac-dc converter is proposed to realize highly efficient dc distribution system in data centers. The proposed converter consists of the singe-phase full-bridge ac-dc cell converters using ultralow loss GaN (Gallium Nitride) transistors and the non-regulated highly efficient isolated dc-dc cell converters. These cell converters are connected in ISOP (Input Series and Output Parallel)-IPOS (Input Parallel and Output Series) to interface various voltage classes in the distribution system. The analysis of the multicellular converter is conducted based on the state-space averaging method, and the control strategy of the ac-dc cell converter is derived from the analysis for the stable operation, taking the behavior of the non-regulated dc-dc cell converter into account. A small-scale prototype is also developed and the potential to achieve the total efficiency over 96% (98% in the ac-dc conversion stage and 98% in the dc-dc conversion stage) was verified. The proposed multicellular ac-dc converter achieves the energy saving not only in the ICT (Information and Communication Technology) distribution system but also in the power grids which have different voltage classes. The proposed topology enables the widespread use of standardized power electronics converters and contributes to realizing highly electrified low-carbon society.
A self-interference cancelling front-end for in-band full-duplex wireless and its phase noise performance

This paper describes a frequency-agile RF front-end in 65nm CMOS targeting short-range full-duplex wireless communication. Complementing previous work on a self-interference cancelling receiver, this work describes the co-integrated transmitter and reports the phase noise advantages of using correlated clock resources to clock all up- and downconverters present in the system. The hardware is capable of frequency-agile operation from 0.15 to 3.5GHz carrier frequency. Measurements at 2.5 GHz indicate that the RX noise floor is only 1 dB degraded by phase noise when operated from a commercial PLL with ~ -38 dBc phase noise.
The Industrial Organisation of the Dance Industry in the Netherlands: A Transaction Cost Perspective on Hybrid Forms of Organisation

The organization of Electronic Dance Music (EDM) events has become a major export product in the Netherlands. In order to respond quickly to the new trends and needs, innovative forms of cooperation between producers are to be set up for the organization of exciting new events. A case study on how these EDM events are actually organised in the Netherlands shows that the best way to do it is through hybrid forms of organisation, which combine horizontal forms of organisation through the market and vertical forms through the hierarchy. As EDM events are characterised by much asset specificity, the perspective of transaction cost economics indicates why this industry relies on hybrid forms of organisation. Trust between the collaborating partners, intrinsic motivation to be professional in the design and creation of new, ground-breaking music sensations and an extensiv e use of social media play a key role in lowering the transaction costs in the dance industry.
Association between meat consumption and carotid intima-media thickness in Korean adults with metabolic syndrome.

OBJECTIVES The effect of meat consumption on cardiometabolic risk has been continuously studied, but their associations are not conclusive. The aim of this study is to examine the association between the consumption of meat or red meat and carotid intima-media thickness (IMT) in healthy Korean adults. METHODS This study evaluated 2374 community-dwelling adults (933 men and 1441 women) who were free of cardiovascular disease or cancer, living in a rural area in Korea. Total meat and red meat intakes were assessed with a validated 103 item-food frequency questionnaire. Carotid IMT was evaluated ultrasonographically, IMTmax was defined as the highest value among IMT of bilateral common carotid arteries. RESULTS After adjustment for potential confounding factors, the mean IMTmax tended to increase in higher meat consumption groups in both men and women with metabolic syndrome (p for trend= 0.027 and 0.049, respectively), but not in participants without metabolic syndrome. Frequent meat consumption (≥5 servings/week) was significantly associated with higher IMTmax in men with metabolic syndrome (by 0.08 mm, p=0.015). Whereas, the association was not significant in women (by 0.05 mm, p=0.115). Similar but attenuated findings were shown with red meat intake. CONCLUSIONS Our findings suggest that a higher meat consumption may be associated with a higher carotid IMT in Korean adults with metabolic syndrome. The frequent meat consumption (≥5 servings/week), compared with the others, was associated with a higher carotid IMTmax only in men with metabolic syndrome. Further research is required to explore optimal meat consumption in people with specific medical conditions.
Transfer function analysis for clinical evaluation of dynamic cerebral autoregulation—a comparison between spontaneous and respiratory-induced oscillations

Oscillations of arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) can be used for non-invasive assessment of cerebral autoregulation using transfer function analysis. Either spontaneous oscillations (SPO) around 0.1 Hz or respiratory induced oscillations during deep breathing (DB) at a rate of 6/min have been used so far. We investigated 168 patients with severe carotid stenosis or occlusion to evaluate transfer function analysis and compare the SPO and DB approaches. ABP was assessed non-invasively (Finapres), CBFV was measured in the middle cerebral artery using transcranial Doppler sonography. Transfer function phase (P) and gain (G) were extracted from the respective spectra in a low (0.06–0.12 Hz) and high (0.20–0.30 Hz) frequency range (LF, HF) of SPO and from the 0.1 (LF) and 0.2 (HF) Hz peaks induced by DB. For SPO, significant side-to-side differences and differences between groups of severe and critical stenosis were found for P(LF), while P(HF) did not prove to be a significant parameter. G(LF) showed significant side-to-side differences, while G(HF) additionally differed significantly between severe and critical stenosis and occlusion, respectively. For DB, significant side-to-side differences were found for P(LF, HF). Mainly G(HF) differed significantly between the affected and contralateral sides, while both HF and LF gains showed lower values in groups with a higher degree of stenosis. Correlation between G and P values was generally poor. Using Bland–Altman plots a poor inter-method agreement was found mainly for P. Correlations between SPO and DB were higher for G than for P (LF r = 0.64 versus 0.44, HF 0.69 versus 0.28). Analysing reproducibility in 16 patients, only for P(LF, HF) of DB was a highly significant correlation found (Spearman's r up to 0.78). For G(LF, HF) correlations were significant for both SPO and DB with slightly higher r coefficients for SPO. In conclusion, the present study showed that (1) transfer functions P and G represent different information for characterization of dynamic cerebral autoregulation in the frequency domain. (2) Inter-method agreement between DB and SPO is poor for P and moderate for G values. (3) P extracted from DB has a higher reproducibility. (4) The extraction of P and G from the SPO phase spectra is critical and future work on standardizing this process is needed. (5) At present, the DB protocol might be slightly advantageous as a routine diagnostic tool.
Hydrodynamics and light scattering

Hydrodynamics describes the low-frequency, long-wavelength behavior of a system that is disturbed from equilibrium. When a system is disturbed from equilibrium, some quantities and parameters decay very quickly back to their equilibrium state, while others take a long time to relax [1]. Con­ served quantities, such as particle number, momentum, and energy, take a long time to relax to equilibrium, while non-conserved quantities decay quickly [1]. Similarly, order parameters, such as average magnetization, take a long time to relax to equilibrium, while parameters which are not order parameters decay quickly [1]. Therefore, at long times, a non-equilibrium system can be com­ pletely described by order parameters and the densities of conserved quantities [1]. Hydrodynamic equations are the equations of motion for these quantities and parameters.
Semantics-preserving bag-of-words models for efficient image annotation

The Bag-of-Words (BoW) model is a promising image representation for annotation. One critical limitation of existing BoW models is the semantic loss during the codebook generation process, in which BoW simply clusters visual words in Euclidian space. However, distance between two visual words in Euclidean space does not necessarily reflect the semantic distance between the two concepts, due to the semantic gap between low-level features and high-level semantics. In this paper, we propose a novel scheme for learning a codebook such that semantically related features will be mapped to the same visual word. In particular, we consider the distance between semantically identical features as a measurement of the semantic gap, and attempt to learn an optimized codebook by minimizing this gap. We refer to such a new codebook method as Semantics-Preserving Codebook (SPC) and the corresponding model as Semantics-Preserving Bag-of-Words model (SPBoW). This novel model generates codebook for each object category and only needs to update the codebook for a specific category when incomes an object, which makes it convenient to scale up with the increasing number of objects. Experiments on image annotation tasks with a public testbed from MIT's Labelme project, which contains 11,281 objects of 495 categories, show that the SPC learning scheme is efficient in handling large number of objects and is able to greatly improve the performance of the existing BoW model.