Miracle-dz/UniFAR-FTUs huggingface dataset:
The Equivalence of Half-Quadratic Minimization and the Gradient Linearization Iteration

A popular way to restore images comprising edges is to minimize a cost function combining a quadratic data-fidelity term and an edge-preserving (possibly nonconvex) regularization term. Mainly because of the latter term, the calculation of the solution is slow and cumbersome. Half-quadratic (HQ) minimization (multiplicative form) was pioneered by Geman and Reynolds (1992) in order to alleviate the computational task in the context of image reconstruction with nonconvex regularization. By promoting the idea of locally homogeneous image models with a continuous-valued line process, they reformulated the optimization problem in terms of an augmented cost function which is quadratic with respect to the image and separable with respect to the line process, hence the name "half quadratic. " Since then, a large amount of papers were dedicated to HQ minimization and important results-including edge-preservation along with convex regularization and convergence-have been obtained. In this paper, we show that HQ minimization (multiplicative form) is equivalent to the most simple and basic method where the gradient of the cost function is linearized at each iteration step. In fact, both methods give exactly the same iterations. Furthermore, connections of HQ minimization with other methods, such as the quasi-Newton method and the generalized Weiszfeld's method, are straightforward
Performance of 40, 80 and 112 Gb/s PDM-DQPSK optical label switching system with spectral amplitude code labels

We present the performance comparison of 40, 80 and 112 Gb/s polarization division multiplexing (PDM)-differential quadrature phase shift keying (DQPSK) optical label switching system with frequency swept coherent detected spectral amplitude code (SAC) labels in simulation. Direct detection is selected to demodulate the PDM payload in the receiver. The SAC label is frequency-swept coherently detected. The label and payload signal performances are assessed by the eye diagram opening factor and bit error rate (BER) as function of received optical power (ROP) and optical signal to noise ratio (OSNR). For back-to-back (BTB) system and 156, 138 and 120 km transmission for 40, 80 and 112 Gb/s respectively, label eye opening factors are 0.93 and 0.85 for 40 Gb/s, 0.94 and 0.86 for 80 Gb/s and 0.93 and 0.90 for 112Gb/s respectively, while payload optical signal-to-noise ratio are 29.9, 25.6, 23.4 dB and the payload received optical power are -11.5, -12.6 and -13.3 dBm for a bit error rate of 10-9 after 156, 138 and 120 km for 40, 80 and 112 Gb/s respectively. The payload could well be demodulated after 1,800, 1,260 and 900 km transmission for 40, 80 and 112 Gb/s respectively at a BER of 10-3 using forward error correction (FEC).
A Reinforcement Learning Method for the Weapon Target Assignment Problem with Unknown Hit Rate

The weapon target assignment problem is a combinatorial optimization problem that aims to assign multiple weapons to multiple targets to achieve optimal operational effectiveness. In previous studies, all methods for weapon target assignment problem are based on the assumption that the probabilities of successful interception are all known. In this paper, we take into consideration the situations where the probabilities of successful interception are unknown. We modify the mathematical model of the static weapon target assignment (SWTA) problem and decomposes it as a Markov decision process so as to apply deep reinforcement learning for this problem. Two sets of computational experiments are conducted, and the results show that the proposed reinforcement learning method has validity and generalization ability for the SWTA problem.
TSET MAX : An Algorithm for Mining Frequent Maximal Temporal Patterns

The incorporation of temporal semantics into the traditional data mining techniques has caused the creation of a new area called Temporal Data Mining. This incorporation is especially necessary if we want to extract useful knowledge from dynamic domains, which are time-varying in nature. However, in a lot of cases is practically a computationally intractable problem and therefore it poses more challenges on efficient processing than non-temporal techniques. Based in the inter-transactional framework, in [13] we proposed an algorithm named TSET for mining temporal patterns (sequences) from datasets. One of the main drawbacks of this algorithm is the fact that it is an Aprioristyle and therefore, for each frequent pattern, all subsets of it need to be generated. In datasets with long patterns, this could degenerate into a computationally unfeasible problem. To address this problem, in this paper we present a new algorithm named TSET for mining frequent maximal temporal patterns. This algorithm extract the patterns using a lookahead technique and a depth first search on a temporal set-enumeration tree.
Analytical expressions for the scattering by an electrically small circular aperture on an infinite conducting ground plane

Near-field analytical expressions for the plane-wave scattering from an electrically small circular aperture on an infinite conducting screen were derived based on the Bethe-Bouwkamp (BB) quasi-static model. The formulation of the problem implements the equivalence principle and image theory in order to express the scattered fields in the near zone in terms of the vector potential F⃗. The vector potential is defined as a surface integral of the first-order BB approximation of the magnetic current on the aperture multiplied by the governing free-space Green's function. The free-space Green's function was expanded using Taylor series, thus producing integrals that can be evaluated analytically for the case where the observation point resides on the axis of the aperture. Results for the scattered electric field along the axis of the aperture, using the obtained closed-form near-field expressions, were validated against recently published results in the literature.
Improvements in Automatic Thesaurus Extraction

The use of semantic resources is common in modern NLP systems, but methods to extract lexical semantics have only recently begun to perform well enough for practical use. We evaluate existing and new similarity metrics for thesaurus extraction, and experiment with the trade-off between extraction performance and efficiency. We propose an approximation algorithm, based on canonical attributes and coarse- and fine-grained matching, that reduces the time complexity and execution time of thesaurus extraction with only a marginal performance penalty.
Social Justice in the Wisdom Literature

contributions to such a topic. According to this view, old wisdom in Israel was consistently secular. It later became religious and ethical through the influence of Israel’s faith (Gunkel: 383; McKane, 1965:15). Thus, according to this perspective, social justice was not an indigenous theme of wisdom. Wisdom adopted it at a late period under the influence of prophecy. If this viewpoint were true, wisdom would have little to contribute to the understanding of justice. Wisdom’s approaches to the subject would have been borrowed from prophecy and contain nothing unique. Today the former view of wisdom is seen to be decreasingly adequate. A number of authors have shown that it is impossible to separate religion and ethics from wisdom at any stage of its development. Wisdom in Israel always had
An Informal Survey of Assessment Use in Child Art Therapy

AbstractThe authors surveyed participants at a national art therapy conference on the use of assessments in art therapy with children. Different levels of experience, geographical areas and training programs were represented by thirty-seven respondents. Relative familiarity with projective tools was greater than with ari therapy assessments. However, most respondents cited preferred tools which relied on modifications of existing projectives and art therapy techniques, and unpublished assessments. The authors infer from their results that art therapists have a great diversity in training and approach to assessments, coupled with a strong need to innovate. The results, although from a small sample, have implications for both clinicians and researchers.
Appetite-focused dialectical behavior therapy for the treatment of binge eating with purging: a preliminary trial.

OBJECTIVE This treatment development study investigated the acceptability and efficacy of a modified version of dialectical behavior therapy (DBT) for bulimia nervosa (BN), entitled appetite focused DBT (DBT-AF). METHOD Thirty-two women with binge/purge episodes at least one time per week were randomly assigned to 12 weekly sessions of DBT-AF (n = 18) or to a 6-week delayed treatment control (n = 14). Participants completed the EDE interview and self-report measures at baseline, 6 weeks, and posttreatment. RESULTS Treatment attrition was low, and DBT-AF was rated highly acceptable. At 6 weeks, participants who were receiving DBT-AF reported significantly fewer BN symptoms than controls. At posttest, 26.9% of the 26 individuals who entered treatment (18 initially assigned and 8 from the delayed treatment control) were abstinent from binge/purge episodes for the past month; 61.5% no longer met full or subthreshold criteria for BN. Participants demonstrated a rapid rate of response to treatment and achieved clinically significant change. DISCUSSION Results suggest that DBT-AF warrants further investigation as an alternative to DBT or cognitive behavior therapy for BN.
Two minds rationality

I argue that views of human rationality are strongly affected by the adoption of a two minds theory in which humans have an old mind which evolved early and shares many features of animal cognition, as well as new mind which evolved later and is distinctively developed in humans. Both minds have a form of instrumental rationality—striving for the attainment of goals—but by very different mechanisms. The old mind relies on a combination of evolution and experiential learning, and is therefore driven entirely by repeating behaviours which succeeded in the past. The new mind, however, permits the solution of novel problems by reasoning about the future, enabling consequential decision making. I suggest that the concept of epistemic rationality—striving for true knowledge—can only usefully be applied to the new mind with its access to explicit knowledge and beliefs. I also suggest that we commonly interpret behaviour as irrational when the old mind conflicts with the new and frustrates the goals of the conscious person.
Familiarity of faces: Sense or feeling? An exploratory investigation with eye movements and skin conductance

Where does the experience of familiarity come from? Is it the same as sensory perception? Two novel approaches were combined to investigate the highly adaptive process of familiar face recognition: the inclusion of friends and family members as personally familiar faces and measures of eye movements and skin conductance responses (SCR). A sample of 16 university students was asked to look at photographs of 8 personally familiar faces (friends and relatives) and 8 unfamiliar faces. From the analysis of eye movement patterns, a preference for internal features (mouth, eyes, nose) for both familiar and unfamiliar faces emerged and a significant increase in electrodermal activity was found for personally familiar compared to unfamiliar faces. Higher SCR recovery values were found in response to friends. Findings from this exploratory investigation suggest that familiar faces are not looked at in a special way; instead we “feel” a sense of familiarity that comes and goes faster for relatives than for close fri.
Simulation-Based Proportional Integral Derivative driven Frequency Compensation of Grid-connected AC Microgrids

Integration of renewable energy sources into the microgrid impacts Load Frequency Control (LFC) negatively. So, an effective solution to tackle the problem of LFC with RES in microgrid is needed. In this paper, Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) are used to optimize the Proportional-Integral-Derivative (Three-term) gain constants for a single-area control system. When the traditional PID is implemented, this leads to the ordinary controller failing to modify the AGC. To optimize the three-term controller variables using PSO and GA. The method applies to single-area systems. The outcomes demonstrate how precisely and reliably the optimized controller variables were implemented. The performance of PSO and GA are also compared with Ziegler Nichols’s method of tuning PID parameters and Conventional PI controller. System equations are solved with MATLAB Simulation. When compared to a traditional controller, the optimized controller that has been suggested exhibits faster response times and higher control quality.
Sulcal basins and sulcal strings as new concepts for describing the human cortical topography

Human brain mapping aims at establishing correspondences between brain function and brain anatomy. One of the most intriguing problems in this field is the high inter-personal variability of human neuroanatomy which makes studies across many subjects very difficult. The cortical folds ("sulci") often serve as landmarks that help to establish correspondences between subjects. Here, the authors present a method that both automatically detects and attributes neuroanatomical names to the cortical folds using image analysis methods applied to magnetic resonance data of human brains. The authors claim that the cortical folds can be subdivided into a number of substructures which they call sulcal basins. In addition to the concept of sulcal basins, the authors introduce the concept of sulcal strings which are groups of sulcal basins arranged as strings that are aligned with the Sylvian fissure and the inter-hemispheric cleft. The concept of sulcal basins allows to establish a complete parcellation of the cortical surface into separate regions. These regions are neuroanatomically meaningful and can be identified from MR data sets across many subjects. At the same time, the parcellation is detailed enough to be useful for brain mapping purposes.
GEO-SPADE - A Generic Google Earth-based Framework for Analyzing and Exploring Spatio-temporal Data

Various frameworks are being developed to support geospatial data processing and exploration. However, these frameworks are insufficient due to their inability to support rapid development and reuse of existing geospatial operations. To cope with the difficulties that arise, more and more Web-based solutions are being implemented incorporating Web services and Open Geospatial Consortium (OGC)a standards for data interchange and distributed geo-processing. Although these solutions often target specific problems, they rarely can be extended by a third party. As a result, analysts are frequently required to implement additional software in order to complete their exploration process. In this paper, we present a unified, extensible framework that can solve generic spatio-temporal analysis tasks. Specifically, we present the prototype of a new framework that allows quick hypothesis definition and testing. The proposed framework, which we term GEO-SPADE, uses Google Earth as a primary visualization platform and data interchange system. Pluggable components can easily be integrated into the framework. We demonstrate the feasibility of the GEO-SPADE framework by following the scenario of analysis of travel sequences near Funchal, Madeira Island. ahttp://www.opengeospatial. org
Love, hate and indifference : the impact of talk about relationships on the interpretation of talk in relationships

Methodologically, one of the things that make linguistic ethnography so interesting is its willingness to confront the challenges posed by different data collection methods within the context of its broader programme, and in this paper I’d like to focus on just one of the issues this raises: the relationship between linguistic data and other evidence from the field. I’d like to suggest that researchers may not have given sufficient attention the dangers of privileging linguistic data over other sources and will explore briefly what the implications of this might be for how we position ourselves as researchers. While issues of trust, researcher identity and field relationships have received considerable attention in the literature (for recent examples see Russell 2005, Gubrium and KoroLjungberg 2005), less attention has been paid to issues of deliberate or unintentional deception, except where interviews are concerned (see, for example, Gardner 2001, Sikes 2000). In the absence of any consideration of direct linguistic evidence as problematic, we might easily assume that it occupies a privileged status, issues of selection (always limited by practical constraints) and transcription aside. However, this paper examines the effects of two cases where undisclosed relationships were discovered towards the end of the data collection process and explores the implications of this for interpretive positioning. The first and more conventional of the two cases will show how relevant contextual information derived from fieldnotes led to a reinterpretation of a previously discrepant exchange involving teachers in a staffroom and the subsequent bracketing out of one participant’s perspective on an important topic of staffroom talk. A second ― and much more problematic ― case reveals how interview data revealed a hitherto unsuspected antipathy that did not, as in the first case, manifest itself in professional interaction but prompted a reinterpretation of hitherto neglected personal interaction. First, though, I’d like to consider briefly some responses to the issue of deception in research.
A Mill Load Identification Method Based on Deep Neural Network

Mill load identification is crucial for the grinding process. Accurate identification of mill load is beneficial for enhancing the overall production efficiency and ensuring safe operation throughout the entire grinding classification process. The internal conditions of the mill are complex and difficult to detect directly, so ore processing plants often identify mill load through grinding sound signals or mill vibration signals generated during the grinding process. Currently, most of the mill load identification methods based on grinding sound signal or mill vibration signals are realized by signal processing and traditional machine learning. However, these methods are difficult to fully extract the features of the signals and the identification effect needs to be improved. In this study, a mill load identification method based on deep neural network from grinding sound is proposed, which takes the Mel spectrogram of the grinding sound signal as input and uses the Resnet34 network as the base network. Combining with the temporal characteristics of spectrogram, a spatial attention mechanism is introduced in the network. And a soft thresholding mechanism based on spatial attention is proposed for the problem that the complex industrial environment makes the grinding sound signal contain a large amount of redundant information. In experimental comparison, the accuracy of the proposed method is 93.5%, which is 4.5% higher than the original Resnet34 and has faster convergence speed, which verifies the effectiveness of the method.
Attention and the processing of natural stimuli : psychophysics, fMRI and single unit recordings in the human brain.

How does the visual system process stimuli it encounters frequently? To address this question, we investigated the attentional requirements associated with processing natural stimuli in isolation and in crowded environments. Using the dual-task paradigm, we tested observers on discriminating the gender of faces presented in isolation, in the near-absence of focal attention. We observed that performance on this task for poorly attended faces suffered only minimally. Furthermore, we also showed that finer discriminations, such as face identification (celebrities and unfamiliar faces), are unimpaired when attention is unavailable. From a computational perspective these results are surprising since observers are unable to categorize computationally simpler stimuli (e.g., a red-green color disk from its mirror image) under identical conditions. The brain mechanisms underlying the processing of face-gender were probed with fMRI. We found that the BOLD signal in the near-absence of attention was not significantly reduced, provided the faces were behaviorally relevant. This finding, that top-down expectations can be sufficient for high levels of the BOLD signal, is in contrast to current views that hold that the signal is reduced in the absence of focused attention. We took a closer look at attentional effects on neuronal activity by recording from individual neurons in the human brain while subjects performed a change detection paradigm (in which they reported whether they noticed changes made to (natural) stimuli presented in a crowded environment). Subjects were epileptic patients, implanted with depth electrodes in the medial temporal lobe (MTL) for identification of the seizure foci for potential surgical resection. We observed that neuronal responses when changes were correctly detected were significantly higher compared to incorrect trials. Under the common assumption that incorrect performance reflects the absence of attention, we show that MTL neuronal activity is reduced when attention is unavailable. For each cell, on a trial-by-trial basis, we were able to predict the occurrence of a change (67%) and the patients’ behavior (58%), significantly above chance. Our results show that the brain can process isolated natural stimuli in the near-absence of attention, while in crowded environments, attention plays a key role, as we have observed at the neuronal level
Roles of reactive oxygen species in angiopoietin‐1/tie‐2 receptor signaling

In this study we identified the involvement of reactive oxygen species (ROS) in signaling and biological effects of the angiopoietin‐1 (Ang‐1)/tie‐2 receptor pathway. Exposure of human umbilical vein endothelial cells to Ang‐1 (50 ng/ml) induced rapid and transient production of ROS, particularly superoxide anions. ROS production was attenuated by preincubation with a peptide (gp91ds‐tat) that inhibits the association of the gp91phox subunit with the p47phox subunit of NADPH oxidase and by the expression of a dominant‐negative form of Rac‐1 (Rac1N17). These results suggest that ROS production in response to Ang‐1 exposure originates mainly from a Rac‐1‐dependent NADPH oxidase. Overexpression of antioxidants (superoxide dismutase and catalase) and Rac1N17, as well as preincubation with selective inhibitors of NADPH oxidase augmented basal p38 phosphorylation, inhibited Ang‐1‐induced PAK‐1 phosphorylation and potentiated Ang‐1‐induced Erk1/2 phosphorylation but had no influence on AKT and SAPK/JNK phosphorylation by Ang‐1. Exposure to Ang‐1 (100 ng/ml) for 5 h induced a threefold increase in endothelial cell migration, a response that was strongly inhibited by overexpression of antioxidants, Rac1N17, and selective NADPH oxidase inhibitors. We conclude that activation of tie‐2 receptors by Ang‐1 triggers the production of ROS through activation of NADPH oxidase and that ROS generation by Ang‐1 promotes endothelial cell migration while negatively regulating Erk1/2 phosphorylation.