Miracle-dz/UniFAR-FTUs huggingface dataset:
TRACING THE REVERBERATION LAG IN THE HARD STATE OF BLACK HOLE X-RAY BINARIES

We report results obtained from a systematic analysis of X-ray lags in a sample of black hole X-ray binaries, with the aim of assessing the presence of reverberation lags and studying their evolution during outburst. We used XMM-Newton and simultaneous Rossi X-ray Timing Explorer (RXTE) observations to obtain broadband energy coverage of both the disk and the hard X-ray Comptonization components. In most cases the detection of reverberation lags is hampered by low levels of variability-power signal-to-noise ratio (typically when the source is in a soft state) and/or short exposure times. The most detailed study was possible for GX 339-4 in the hard state, which allowed us to characterize the evolution of X-ray lags as a function of luminosity in a single source. Over all the sampled frequencies (∼0.05–9 Hz), we observe the hard lags intrinsic to the power-law component, already well known from previous RXTE studies. The XMM-Newton soft X-ray response allows us to detail the disk variability. At low frequencies (long timescales) the disk component always leads the power-law component. On the other hand, a soft reverberation lag (ascribable to thermal reprocessing) is always detected at high frequencies (short timescales). The intrinsic amplitude of the reverberation lag decreases as the source luminosity and the disk fraction increase. This suggests that the distance between the X-ray source and the region of the optically thick disk where reprocessing occurs gradually decreases as GX 339-4 rises in luminosity through the hard state, possibly as a consequence of reduced disk truncation.
Bundle Protocol Header Compression

Delay Tolerant Networks (DTNs), especially the Bundle Protocol (BP), transmit data in self-contained bundles each of which carrying all necessary information to process it and route it to its destination. While this allows for long delays, link disruptions and higher loss rates and makes the BP well-suited for networks such as Wireless Sensor Networks (WSNs), it imposes a significant overhead in terms of the header sizes, as e. g. node addresses are denoted as full URIs, called Endpoint Identifiers (EIDs). While the Compressed Bundle Header Encoding introduces a special naming scheme to eradicate these URIs which reduces the header size to some extent, in this paper we present a novel, full-fledged header compression for the BP that can be applied stateless or stateful, i. e. without or with storing part of the bundle headers on forwarding nodes. The gains achievable with this approach are extensively evaluated with the simulation of bundles carefully generated from real-world network traffic on the one hand, and of realistically moving public transport vehicles with a traffic pattern often found in such Delay Tolerant Wireless Sensor Networks (DTWSNs) on the other hand.
A Summary of Multiple Access Channels ∗

In this summary we attempt to present a brief overview of the classical results on the information-theoretic aspects of multiple access channels (MACs thereafter). We confine our discussion to the basic MAC model which is discrete, memoryless, without any channel side information or feedback, and where the two (or more) senders are synchronized. In Section 1 we introduce the channel model and formulate the problem. In Section 2 this general problem is solved, i.e., the capacity region for a general MAC is established. Corresponding results for the Gaussian MAC is presented in Section 3. Finally some references are listed for further reading. 1 The MAC Model and Problem Formulation Intuitively MAC is a channel via which two (or more) senders send information to a common receiver. To make the point precise, we introduce the following definitions. Definition 1 (Discrete memoryless MAC) A discrete memoryless MAC consists of three alphabets, X1, X2 and Y, and a probability transition matrix p(y|x1, x2). As shown in Figure 1.
Preparing for the unpredictable : Identifying successful performance strategies in human-machine improvisation

We examine the human creative process involved in performing with Mimi (Multimodal Interaction in Musical Improvisation), a system designed for human-machine music improvisation on a keyboard or other MIDI instrument. Mimi makes use of a factor oracle data structure to generate new musical material based on seed material from a human performer. Used in conjunction with a MIDI interface that gives the performer operational control over Mimi and a visualization scheme that gives the performer advance notice of Mimi’s actions, this system presents opportunities and challenges for the improvising musician that differ from other improvisational contexts in significant ways. This study identifies and examines some strategies for successful performance with the system, including managing interpolations, transitions, and formal design, with implications for pedagogy and for future development of human-machine improvisation systems.
Partially supervised k-harmonic means clustering

A popular algorithm for finding clusters in unlabeled data optimizes the k-means clustering model. This algorithm converges quickly but is sensitive to initialization. Two ways to overcome this drawback are fuzzification and harmonic means. We show that k-harmonic means is a special case of reformulated fuzzy k-means. The main focus of this paper is on partially supervised clustering. Partially supervised clustering finds clusters in data sets that contain both unlabeled and labeled data. We review partially supervised k-means, partially supervised fuzzy k-means, and introduce a partially supervised extension of k-harmonic means. Experiments with four benchmark data sets indicate that partially supervised k-harmonic means inherits the advantages of its completely unsupervised variant: It is significantly less sensitive to initialization than partially supervised k-means.
Qualitative categories for the interpretation of sheep welfare: a review

The aim of this paper is to discuss the relationship between qualitative categories of sheep welfare and associated quantitative behavioural observations. Most scientific studies rely on quantitative measures, however to interpret those measures in terms of an animal's experience of welfare, the use of qualitative terminologies denoting various emotional states (eg fear, pain, distress) seems hard to avoid. This is especially so in cases where the same behavioural or physiological indicator could have different meanings for welfare; high levels of locomotion, for example, could indicate fear, aggression, or both. To resolve such dilemmas, scientists often resort to judging an animal's most likely state through direct observation; indeed qualitative characterisations are often intertwined with reported quantitative results. This paper reviews frequently used qualitative categories of sheep welfare and the behavioural context in which these categories are applied. Qualitative judgements of welfare tend to habitually be regarded as ‘subjective’, ie as anthropomorphic and unreliable; however from this review it appears that such judgements reflect the overall demeanour of an animal's behaviour, and as such may provide a useful empirical basis for the investigation of emotional expression in sheep. Further development of a qualitative behavioural approach may provide a more complete picture of the expressive repertoire of sheep, and enhance our understanding of ways in which these animals experience well-being or distress.
Evaluation of initialization procedures for estimating upper limb kinematics with MARG sensors

Instrumentation able to estimate upper limbs kinematics has a lot of relevance in the context of rehabilitation of stroke patients. The systems based on inertial systems seem to be well suited for clinical environment and numerous authors have presented wearable systems interesting in terms of accuracy and easiness of implementation. These systems always require an initialization procedure and the authors do not justify clearly why they are using one method rather than another. In this paper two common initialization methods are presented and they are evaluated and compared on the basis of the kinematics tracking of upper limbs daily living activities. The experimental results show that an initialization based on functional axes is less sensitive to the respect of initialization conditions than a static initialization.
Some Results In Passive-Dynamic Walking

Human walking can be approximated as a mechanical process governed by Newton’s laws of motion, and not controlled. Tad McGeer first demonstrated, and we have confirmed, that a two-dimensional legged mechanism with four moving parts can exhibit stable, human-like walking on a range of shallow slopes with no actuation and no control (energy lost in friction and collisions is recovered from gravity). More recently, we have found a simple walking mechanism that also balances from side to side. There is much that might be understood about walking by considering it as a natural motion of a simple uncontrolled and unpowered dynamical system, or a passive-dynamic system. As seen from a control perspective, our work largely involves investigation of control parameters which are physical properties rather than the traditional active-control parameters (such as feedback gains, neural net parameters, genetic algorithm reward schemes, etc.). We are testing the hypothesis that human walking is based on an uncontrolled mechanical process by designing, building, and studying uncontrolled or minimallycontrolled walking devices and seeing how well they mimic human motion.
Present Bias and Everyday Self-Control Failures: A Day Reconstruction Study

Everyday life is full of self-control problems. The economist's favorite explanation for self-control problems is present bias. This paper tests whether experimentally elicited present bias predicts self-control problems in everyday life. We measure present bias by using a standard incentivized delay discounting task and everyday self-control by using the day reconstruction method (DRM). Because this is the first study to measure everyday self-control by using the DRM, we also validate the method by showing that its data replicate key results from the seminal Everyday Temptation Study. We find that present bias does not predict everyday self-control. This points to a distinction between decreasing impatience (as measured in delay discounting tasks) and visceral influences (as occurring in everyday life) as determinants of self-control problems. We argue that decision making research can benefit from the DRM as a cost-effective tool that complements lab and field experiments to better understand economic preference measures and their correlates in everyday life decision making. Copyright © 2017 John Wiley & Sons, Ltd.
Tissue specific expression of extracellular microRNA in human breast cancers and normal human breast tissue in vivo

Extracellular circulating microRNAs (miRNAs) have been suggested to be biomarkers for disease monitoring but data are inconsistent, one reason being that blood miRNA is of heterogeneous origin. Here, we sampled extracellular microRNAs locally in situ using microdialysis. Three different cohorts of women were included; postmenopausal women with ongoing breast cancer investigated within the cancer and in normal adjacent breast tissue, postmenopausal women investigated in their normal healthy breast and subcutaneous fat before and after six weeks of tamoxifen therapy, premenopausal women during the menstrual cycle. Samples were initially screened using TaqMan array cards with subsequently absolute quantification. 124 miRNA were expressed in microdialysates. After absolute quantifications extracellular miRNA-21 was found to be significantly increased in breast cancer. In addition, the levels were significantly higher in pre-menopausal breast tissue compared with postmenopausal. In breast tissue of pre-menopausal women miRNA-21 exhibited a cyclic variation during the menstrual cycle and in postmenopausal women six weeks of tamoxifen treatment decreased miRNA-21 suggesting that this miRNA may be important for breast carcinogenesis. None of these changes were found in plasma or microdialysates from subcutaneous fat. Our data revealed tissue specific changes of extracellular circulating miRNAs that would be otherwise unraveled using blood samples.
APRO: All-Pairs Ranking Optimization for MT Tuning

We present APRO, a new method for machine translation tuning that can handle large feature sets. As opposed to other popular methods (e.g., MERT, MIRA, PRO), which involve randomness and require multiple runs to obtain a reliable result, APRO gives the same result on any run, given initial feature weights. APRO follows the pairwise ranking approach of PRO (Hopkins and May, 2011), but instead of ranking a small sampled subset of pairs from thekbest list, APRO efficiently ranks all pairs. By obviating the need for manually determined sampling settings, we obtain more reliable results. APRO converges more quickly than PRO and gives similar or better translation results.
Mutually unbiased bases and finite projective planes

It is conjectured that the question of the existence of a set of d +1 mutu ally unbiased bases in a d-dimensional Hilbert space if d differs from a power of ap rimenumber is intimately linked with the problem of whether there exist projective planes whose order d is not a power of a prime number.
Design of a soft-switched three-port converter with DSP control for power flow management in hybrid fuel cell systems

A zero-voltage-switched three-port bidirectional converter which is able to handle wide input voltage ranges such as fuel cells and supercapacitors is presented in this paper. The converter consists of three active bridges coupled by a three-winding transformer. A simplified duty cycle control method is introduced to extend the soft-switching range. The system is modeled and a dual-PI-loop control strategy is proposed to achieve regulated output voltage and power flow management. In addition, the soft start-up procedure for the converter is discussed. Simulation and experimental results on a 1 kW prototype verify the effectiveness of the proposed converter and its control strategy
Design of the first neuronal connectomics challenge: From imaging to connectivity

We are organizing a challenge to reverse engineer the structure of neuronal networks from patterns of activity recorded with calcium fluorescence imaging. Unraveling the brain structure at the neuronal level at a large scale is an important step in brain science, with many ramifications in the comprehension of animal and human intelligence and learning capabilities, as well as understanding and curing neuronal diseases and injuries. However, uncovering the anatomy of the brain by disentangling the neural wiring with its very fine and intertwined dendrites and axons, making both local and far reaching synapses, is a very arduous task: traditional methods of axonal tracing are tedious, difficult, and time consuming. This challenge proposes to approach the problem from a different angle, by reconstructing the effective connectivity of a neuronal network from observations of neuronal activity of thousands of neurons, which can be obtained with state-of-the-art fluorescence calcium imaging. To evaluate the effectiveness of proposed algorithms, we will use data obtained with a realistic simulator of real neurons for which we have ground truth of the neuronal connections. We produced simulated calcium imaging data, taking into account a model of fluorescence and light scattering. The task of the participants is to reconstruct a network of 1000 neurons from time series of neuronal activities obtained with this model. This challenge is part of the official selection of the WCCI 2014 competition program.
An empirical investigation of fault types in space mission system software

As space mission software becomes more complex, the ability to effectively deal with faults is increasingly important. The strategies that can be employed for fighting a software bug depend on its fault type. Bohrbugs are easily isolated and removed during software testing. Mandelbugs appear to behave chaotically. While it is more difficult to detect these faults during testing, it may not be necessary to correct them; a simple retry after a failure occurrence may work. Aging-related bugs, a sub-class of Mandelbugs, can cause an increasing failure rate. For these faults, proactive techniques may prevent future failures. In this paper, we analyze the faults discovered in the on-board software for 18 JPL/NASA space missions. We present the proportions of the various fault types and study how they have evolved over time. Moreover, we examine whether or not the fault type and attributes such as the failure effect are independent.
High-Performance Code Generation for FIR Filters and the Discrete Wavelet Transform Using SPIRAL ∗

The discrete wavelet transform (DWT) and filtering algorithms, together with certain classes of trigonometric transforms, are among the most frequently used methods in digital signal processing (DSP) applications. For example, the DWT is used in detection, identification, denoising, prediction, channel coding, and compression such as in the JPEG2000 standard. In many of these applications, filters and the DWT are the computationally most intensive components, and their performance is crucial for the overall efficiency of the application. Creating high-performance software implementations of fast DSP algorithms is a difficult problem. For example, in many cases the data access and data flow patterns of the implementation play a more important role than the computational cost of the algorithm. As a consequence, the best implementation is platformdependent, and, when the platform is changed, the application has to be reimplemented to retain optimal performance. In many cases, the best implementation on one platform is far suboptimal on another. Because of these problems, there is a need for a systematic and automated way to create, modify and adapt implementations across different platforms. The SPIRAL system [1] offers a solution to this problem for the class of linear DSP transforms by automatically generating implementations that are highly optimized and adapted to the given software platform. SPIRAL’s current version generates code for the discrete Fourier transform (DFT), the discrete cosine and sine transforms (DCTs and DSTs), and several other transforms. This paper extends SPIRAL to generate high performance code for FIR filters and the DWT.
Analog dynamics for solving max-SAT problems

In this study we present an analog dynamical system for solving the max-SAT NP-hard constraint satisfaction problem. While in satisfiable instances the fixed points of the dynamics correspond to solutions, in unsatisfiable instances finding the global optimum is much harder. We show a method which running several dynamical trajectories up to a relatively short analog time can predict the value of the global optimum (corresponding to the maximum number of satisfiable constraints) and also efficiently finds states close to the optimum. A CNN SAT-solver model similar to this dynamics has already been developed and the method presented here will also be generalised using CNNs.
LABELS FACILITATE LEARNING OF NOVEL CATEGORIES

A major feature that sets language apart from other communication systems is the use of categorylabels—words. In addition to providing a means of communication, there is growing evidence that category labels play a role in the formation and shaping of concepts. If verbal labels help humans acquire or use category information, one can ask whether it is easier to learn labeled categories compared to unlabeled ones. Normal English-speaking adults participated in a category-learning task in which categories were labeled or unlabeled. The presence of labels facilitated the learning of unfamiliar categories and resulted in more robust category representations. The advantage for acquiring named categories was observed even though the category labels did not convey any additional information and all participants had equivalent experience categorizing the stimuli. This work provides empirical support for the idea of labels as conceptual anchor points (Clark, 1997).
A Study on Enhancement of Loadability of Large-Scale Emerging Power Systems by Using FACTS Controllers

This study presents comprehensive review of various methods/techniques for incorporation of differential algebraic equations (DAE) model of FACTS controllers and different type of loads such as a static, dynamic, and composite load model in large-scale emerging power systems for enhancement of loadability of power system networks. It also reviews various current techniques/methods for incorporation differential algebraic equations (DAE) model of FACTS controllers and different type of loads such as static, dynamic, and composite load model in emerging power system networks through all over world. Authors strongly believe that this survey article will be very much useful to the researchers for finding out the relevant references in the field of incorporation of FACTS controllers in power system environments for enhancement of loadability of power system environments.
Relational Knowledge with Predictive State Representations

Most work on Predictive Representations of State (PSRs) has focused on learning and planning in unstructured domains (for example, those represented by flat POMDPs). This paper extends PSRs to represent relational knowledge about domains, so that they can use policies that generalize across different tasks, capture knowledge that ignores irrelevant attributes of objects, and represent policies in a way that is independent of the size of the state space. Using a blocks world domain, we show how generalized predictions about the future can compactly capture relations between objects, which in turn can be used to naturally specify relational-style options and policies. Because our representation is expressed solely in terms of actions and observations, it has extensive semantics which are statistics about observable quantities.
Case finding and case management of chlamydia and gonorrhea infections among women: what we do and do not know.

This document reviews studies that have assessed the effectiveness of non-laboratory management strategies for finding cases of chlamydia and gonorrhea infection among family planning antenatal care and general populations in developing countries. Overall the meta-analysis of non-laboratory case-finding validation studies found positive predictive values (PPVs) of 13% or less. These low PPVs are disappointing in terms of the prospects of finding cases of chlamydia and gonorrhea without causing concomitant large errors of overdiagnosis among women making routine visits to clinics that offer reproductive health services. It is concluded as do many of the authors cited that these tools are not appropriate for finding cases of chlamydia/gonorrhea. On the other hand studies among female sex workers where chlamydia/gonorrhea prevalence was high (31-40%) showed a better but not excellent ability of screening tools to identify cases accurately achieving PPVs of up to 50%. Based on the findings research and policy analysis for determining the best approach for addressing chlamydia/gonorrhea infection in settings with different prevalence rates program capacity and sexual behavior patterns are lacking. Hence simple and low-cost diagnostics for use in resource-poor settings are needed.