Miracle-dz/UniFAR-FTUs huggingface dataset:
Virtual-reality-based multidimensional therapy for the treatment of body image disturbances in binge eating disorders: a preliminary controlled study

The main goal of this paper is to preliminarily evaluate the efficacy of a virtual-reality (VR)-based multidimensional approach in the treatment of body image attitudes and related constructs. The female binge eating disorder (BED) patients (n=20), involved in a residential weight control treatment including low-calorie diet (1200 cal/day) and physical training, were randomly assigned either to the multidimensional VR treatment or to psychonutritional groups based on the cognitive-behavior approach. Patients were administered a battery of outcome measures assessing eating disorders symptomathology, attitudes toward food, body dissatisfaction, level of anxiety, motivation for change, level of assertiveness, and general psychiatric symptoms. In the short term, the VR treatment was more effective than the traditional cognitive-behavioral psychonutritional groups in improving the overall psychological state of the patients. In particular, the therapy was more effective in improving body satisfaction, self-efficacy, and motivation for change. No significant differences were found in the reduction of the binge eating behavior. The possibility of inducing a significant change in body image and its associated behaviors using a VR-based short-term therapy can be useful to improve the body satisfaction in traditional weight reduction programs. However, given the nature of this research that does not include a followup study, the obtained results are preliminary only.
Obtaining Phase Properties of a Passive Laser Unstable Resonators by Processing the Image of Beam Facula Matrix

The effect of intracavity aberrated perturbation on output mode properties of a confocal unstable resonator is been experimentally researched by adopting H-S wavefront sensor and Zernike modal wavefront reconstruction. By processing the image of beam facula matrix, wavefront phase properties, Zernike aberrations, PV and RMS error, distribution of circle energy can all be acquired, so beam phase distribution can be known fully. Results show that intracavity tilt perturbation notablely affects outcoupled intensity distribution, and will also increase some high-order aberrations of beam phase properties. However, low-order Zernike tilt aberration is the main component when phase-tilted perturbation is introduced into the resonator. Defocus, astigmatism and coma aberration will all be brought, and also they will directly degrade output beam quality. When adaptive optical elements such as deformable mirrors are adopted for intracavity aberration correction, the correction of phase-tilted aberration should be first considered.
RELATIONS OF THE VARIABLES OF POWER AND MORPHOLOGICAL CHARACTERISTICS TO THE KINEMATIC INDICATORS OF MAXIMAL SPEED RUNNING

The aim of the present research was to investigate the relations of 7 variables of power and 12 variables of morphological characteristics with the kinematic indicators (stride frequency, stride length, foot-ground contact duration, flight duration) of maximal speed running. The research was conducted on a sample of 133 physical education male students, 19 to 24 years (age 21.7 p ; ; ; ; 1.08 ; body height 180.8 p ; ; ; ; 6.98 ; body weight 76.6 p ; ; ; ; 7.62), freshmen at the Faculty of Kinesiology University of Zagreb. By means of the component model of factor analysis under the GK-criterion and non-orthogonal rotation under the promax criterion the following factors were obtained: three morphological factors (skeleton dimensionality, in which the longitudinal component prevailed, body voluminosity and subcutaneous fatty tissue) and two factors of power (power of jumping type and ballistic power). Canonical analysis of the morphological factors and power factors with kinematic parameters resulted in two pairs of canonical factors with statistically significant canonical correlations (Rc1=0.76 ; p<0.01, and Rc2=0.57 ; p<0.01). On the basis of the first pair structure of canonical factors it was concluded that the Faculty of Kinesiology students who had pronounced dimensionality of skeleton, a smaller amount of subcutaneous fatty tissue and better developed relative power, performed longer strides in maximal speed running. The structure of the second canonical factor pair indicated that the students with the greater skeleton dimensionality had a smaller frequency of strides and their foot-ground contact lasted longer. It was also determined that stride length and stride frequency were negatively correlated in maximal speed running which was the result of positive correlation between skeleton dimensionality and stride length, on the one hand, and of negative correlation between skeleton dimensionality and stride frequency. The findings may contribute to a better understanding of the factors responsible for sprint performance in the population of athletes who are not top-level sprinters, i.e. they may be useful to PE teachers, coaches who work with novices in athletics and physical conditioning coaches who work in other sports than athletics, to get a more thorough insight into the sprinting efficiency mechanisms.
Improvement of linear spectral mixture analysis and experimentation in estimation of urban vegetation fraction

Abundance of vegetation plays an important role in urban ecosystem, urban planning and development. Traditional classification methods on remote sensing data by assigning each pixel membership in one, and only one have the primary shortcomings of their inability to accommodate spectrally mixed pixels in gradational land covers. The traditional classification methods are giving way to spectral mixture analysis (SMA) gradually which is better in acquiring quantitative information for specific land covers. Vegetation fraction, in a general way, is defined as the areal fractions of vegetation within each pixel. This paper, besides introducing the traditional technique of SMA, discusses the improvement of traditional technique from the aspects of data noise removal, least-squares solution with constraining sum of endmembers fractions to unit, pixel purity index and the selection of endmembers. LSMA is tested further with the Shanghai city as an example. Unmixing pixels with root mean square (RMS) error less than 0.02 accounts for the proportion of 98.5%. The spatial distribution of vegetation is corresponding to actual situation. Then we conclude that: the improved LSMA is appropriate for estimating quantitative vegetation fraction and the technique will be widely applied in urban environment. I. INTRODUCTION
Inter-filament attractions narrow the length distribution of actin filaments

We show that the exponential length distribution that is typical of actin filaments under physiological conditions dramatically narrows in the presence of i) crosslinker proteins or ii) polyvalent counterions or iii) depletion-mediated attractions. A simple theoretical model shows that, at equilibrium, short-range attractions that are known to enhance the tendency of filaments to align parallel to each other, lead to an increase in the average filament length and a decrease in the relative width of the distribution of filament lengths.
crash3: cosmological radiative transfer through metals

Here we introduce CRASH3, the latest release of the 3D radiative transfer code CRASH. In its current implementation CRASH3 integrates into the reference algorithm the code Cloudy to evaluate the ionisation states of metals, self-consistently with the radiative transfer through H and He. The feedback of the heavy elements on the calculation of the gas temperature is also taken into account, making of CRASH3 the first 3D code for cosmological applications which treats self-consistently the radiative transfer through an inhomogeneous distribution of metal enriched gas with an arbitrary number of point sources and/or a background radiation. The code has been tested in idealized configurations, as well as in a more realistic case of multiple sources embedded in a polluted cosmic web. Through these validation tests the new method has been proven to be numerically stable and convergent. We have studied the dependence of the results on a number of physical quantities such as the source characteristics (spectral range and shape, intensity), the metal composition, the gas number density and metallicity.
Optimized Current of the Peaking Amplifier for Two-Stage Doherty Power Amplifier

This paper presents a method of improving efficiency for the two-stage Doherty power amplifier (DPA) using the optimized current of the peaking amplifier. The DPA has a two-stage structure for both the carrier and peaking amplifiers. The first stage of the peaking amplifier has an adjusted bias condition for a near Class-B operation, while the first stage of the carrier amplifier has a higher Class-AB operation. The gain expansion of the first stage due to its lower gate bias helps the second stage of the peaking amplifier to be biased for light Class-C operation and to have steeper turn-ON characteristics, which leads higher peak output power and higher back-off efficiency. The two-stage DPA was designed for the 2.655-GHz band. Using a downlink long-term evolution signal with a signal bandwidth of 10 MHz and a peak-to-average power ratio of 6.5 dB, the overall power gain of 25 dB and a peak output power of 54.2 dBm are experimentally obtained. Using an optimized shape of the peaking amplifier’s current, a drain efficiency (DE) of 53% and an adjacent channel leakage power ratio of −30 dBc were obtained at an average output power of 47.8 dBm. A DE of 56.8% and an adjacent channel leakage power ratio of −25 dBc were also obtained at an average output power of 49.5 dBm.
Modelling the co-evolution of trade and culture in past societies

This paper presents a new framework to study the co-evolution of cultural change and trade. The design aims for a trade-off between the flexibility necessary for the implementation of multiple models and the structure necessary for the comparison between the models implemented. To create this framework we propose an Agent-Based Model relying on agents producing, exchanging and associating values to a list of goods. We present the key concepts of the framework and two examples of its implementation which allow us to show the flexibility of our framework. Moreover, we compare the results obtained by the two models, thus validating the structure of the framework. Finally, we validate the implementation of a trading model by studying the price structure it produces.
When to Use a Distributed Dataflow Engine: Evaluating the Performance of Apache Flink

With the increasing amount of available data, distributed data processing systems like Apache Flink, Apache Spark have emerged that allow to analyze large-scale datasets. However, such engines introduce significant computational overhead compared to non-distributed implementations. Therefore, the question arises when using a distributed processing approach is actually beneficial. This paper helps to answer this question with an evaluation of the performance of the distributed data processing framework Apache Flink. In particular, we compare Apache Flink executed on up to 50 cluster nodes to single-threaded implementations executed on a typical laptop for three different benchmarks: TPC-H Query 10, Connected Components,, Gradient Descent. The evaluation shows that the performance of Apache Flink is highly problem dependent, varies from early outperformance in case of TPC-H Query 10 to slower runtimes in case of Connected Components. The reported results give hints for which problems, input sizes,, cluster resources using a distributed data processing system like Apache Flink or Apache Spark is sensible.
Nrf2 plays a pivotal role in protection against burn trauma-induced intestinal injury and death

Nuclear factor (erythroid-derived 2)–like 2 (NRF2) is a basic leucine zipper transcription factor that principally defends against oxidative stress and also plays a unique role in severe sepsis. However, its contribution to intestinal injury and death after burn trauma is unclear.In this study, wild-type (Nrf2+/+) and Nrf2-deficient (Nrf2−/−) mice were subjected to 15% or 30% total body surface area burn or sham injury. Survival, systemic inflammation, and gut injury were determined. Nrf2−/− mice were more susceptible to burn-induced intestinal injury, as characterized by increases in damage to the gut structure and in intestinal permeability. This exacerbation was associated with an increase in the intestinal mRNA expression of inflammatory cytokines (interleukin [IL]–6, IL-1B, monocyte chemotactic protein 1, intercellular adhesion molecule, and vascular cell adhesion molecule) and a decrease in the intestinal mRNA expression of Nrf2-regulated genes (NAD(P)H dehydrogenasequinine-1 and glutamate-cysteine ligase modifier subunit). Nrf2-deficient mice also showed a lower survival rate and higher levels of systemic cytokines (IL-6 and IL-1B) and high-mobility group protein B1 than wild-type mice. This study demonstrates for the first time that mice that lack Nrf2 are more susceptible to burn-induced intestinal injury and have more systemic inflammation and a lower survival rate.
Excelling in R&D

OVERVIEW: R&D directors in both high- and low-R&D effective organizations were found to attach similar importance to the skills and knowledge bases needed to have an impact on overall business performance. However, organizations that were rated by their directors as “high-R&D effective” are significantly more capable than their “low-R&D effective” counterparts in almost all areas. They are especially better prepared in accelerating new-product development, forming strategic R&D and marketing alliances, understanding customer needs, and commercializing technology. High-R&D effective organizations develop these capabilities and excel in performance by building extensive internal and external linkages, by pursuing business-driven R&D while encouraging experimentation and risk-taking, and by learning from their prior NPD introduction experiences and quickly launching the next generation of products. Senior management in high-R&D effective organizations is more tolerant of failure, perceives R&D to be an important contributor to business performance, and gets involved during the early stages of NPD.
Learning from Positive and Unlabeled Examples: A Survey

This paper surveys the existing method of learning from positive and unlabeled examples. We divide the existing methods into three families, and review the main algorithms, respectively. The first Family of methods takes a two-step strategy, extracting some reliable negative examples, and then applying the supervised or semi-supervised learning method. The second family of methods estimates statistical queries over positive and unlabeled examples. The third family of methods reduces this problem to the problem of learning with high one-sided noise by treating the unlabeled set as noisy negative examples. Finally, we conclude and issue future works.
The Conceptualization and Role of Impulsivity: Bipolar Disorder and Substance Abuse

Impulsive behaviors play an important role in both bipolar and substance abuse disorders. However, results of studies investigating this link are often ambiguous, in part, due to the multidimensional nature of the impulsivity construct and the fact that many studies use a single measurement technique. We describe a model of impulsivity characterized by three components: response initiation, response inhibition and consequence sensitivity. How these components differ from one another in terms of their use, behavioral theory and biological function is discussed, along with measurement techniques.
Truth and What Is

A notion of truth as applicable to events of fact-stating use (utterances) of a sentence type is arguably presupposed and required by our evaluative practices of the use of language. The truth of an utterance clearly depends on what the utterance says. This fundamental dependence seems to be captured by the schema that if an utterance u says that P , then u is true iff P . Such a schema may thus be thought to constitute a suitable basis for an adequate theory of utterance truth, so much so that it seems straightforwardly to avoid the problems arising from context dependence and the semantic paradoxes which notoriously beset theories of utterance truth based on a simple disquotational schema. The paper argues that appearances are deceptive in both cases. On the one hand, the schema cannot allow for non-indexical forms of context-dependence, arising from the fact that what an utterance says can be the case or not as evaluated with respect to different situations and that the truth of an utterance u of a sentence φ arguably depends on the truth of φ at the situation “associated” with u’s context of utterance. On the other hand, a quantified utterance-truth variation on the liar paradox shows that the schema entails some consequence φ and at the same time the untruth of any utterance of φ; moreover, a resilient quantified propositional variation on the contingent liar paradox is offered, which only relies on resources usually employed by theories of utterance truth based on the schema.
Recursive Fréchet Mean Computation on the Grassmannian and Its Applications to Computer Vision

In the past decade, Grassmann manifolds (Grassmannian) have been commonly used in mathematical formulations of many Computer Vision tasks. Averaging points on a Grassmann manifold is a very common operation in many applications including but not limited to, tracking, action recognition, video-face recognition, face recognition, etc. Computing the intrinsic/Fréchet mean (FM) of a set of points on the Grassmann can be cast as finding the global optimum (if it exists) of the sum of squared geodesic distances cost function. A common approach to solve this problem involves the use of the gradient descent method. An alternative way to compute the FM is to develop a recursive/inductive definition that does not involve optimizing the aforementioned cost function. In this paper, we propose one such computationally efficient algorithm called the Grassmann inductive Fréchet mean estimator (GiFME). In developing the recursive solution to find the FM of the given set of points, GiFME exploits the fact that there is a closed form solution to find the FM of two points on the Grassmann. In the limit as the number of samples tends to infinity, we prove that GiFME converges to the FM (this is called the weak consistency result on the Grassmann manifold). Further, for the finite sample case, in the limit as the number of sample paths (trials) goes to infinity, we show that GiFME converges to the finite sample FM. Moreover, we present a bound on the geodesic distance between the estimate from GiFME and the true FM. We present several experiments on synthetic and real data sets to demonstrate the performance of GiFME in comparison to the gradient descent based (batch mode) technique. Our goal in these applications is to demonstrate the computational advantage and achieve comparable accuracy to the state-of-the-art.
A Threefold Assessment of the Romanian Economy's Eco-Efficiency

The present paper assesses the ecological sustainability of the Romanian economy from three different angles. The first two applications use the economy’s energy and material consumption as proxy for its overall environmental impact. The third assessment approach is a qualitative and context-based one: the main obstacles to and opportunities for incorporating sustainability-competitiveness synergies into the Romanian industrial firms’ management are identified. In the period 2000-2007, GDP growth was an important contributor to the Romanian economy’s eco-efficiency levels, while the material and energy consumption remained constant or even increased. The predominance of competitive advantages based on low labour costs, high potential of increasing labour productivity, deficient environmental and industrial policies, and lack of awareness in both business and policy environment as to the beneficial role of resource productivity increase constitute significant obstacles to adopting competitive sustainability strategies. Fortunately, the relatively low levels of eco-efficiency and eco-innovation in industry offer in fact a wide scope of still unexploited win-win solutions. On the basis of the results, further research directions are sketched and several desirable public policy actions for enhancing the ecological sustainability of the Romanian economy are put forward.
TableMaker: An ad hoc Query Tool for Relational Databases

This paper discusses an ad hoc query tool for relational databases. Most Web servers hosting biological data limit users to a defined set of search options and output formats that are short of the whole range of options available to users with direct database access. However, to make full use of the wealth of data in the database resource, it is desirable to have an intermediate solution that provides a broad range of flexible query and output options through a Web portal.
Facial age estimation using spatial Weber Local Descriptor

This paper introduces a novel age estimation method using a new texture descriptor Weber Local Descriptor (WLD). This texture descriptor is analyzed in depth for age estimation problem. In the study, the multi-scale versions of holistic and spatial WLD (SWLD) descriptors are used to extract the age related features from normalized facial images. After finding a lower dimensional feature subspace, age estimation is performed using multiple linear regression. In addition a new approach of dividing image into regions for spatial texture extraction is proposed. Experiments on FG-NET, MORPH and PAL databases have shown that the proposed method gives better accuracy than the state of art age estimation approaches.
Artificial and online acquired noise dictionaries for noise robust ASR

Recent research has shown that speech can be sparsely represented using a dictionary of speech segments spanning multiple frames, exemplars, and that such a sparse representation can be recovered using Compressed Sensing techniques. In previous work we proposed a novel method for noise robust automatic speech recognition in which we modelled noisy speech as a sparse linear combination of speech and noise exemplars extracted from the training data. The weights of the speech exemplars were then used to provide noise robust HMM-state likelihoods. In this work we propose to acquire additional noise exemplars during decoding and the use of a noise dictionary which is artificially constructed. Experiments on AURORA-2 show that the artificial noise dictionary works better for noises not seen during training and that acquiring additional exemplars can improve recognition accuracy.
Content-Based Image Retrieval based on efficient fuzzy color signature

Content-Based Image Retrieval (CBIR) Systems are becoming increasingly important and finding application in diverse areas of discipline. Due to disturbing factors present in images, e.g. non-uniform illumination and lightening intensities, the retrieval results are not always satisfactory. In this paper, we discuss how fuzzy set theory can be used to formulate an efficient image signature. This signature is 1-D Fuzzy Color Histogram (FCH) consisting of a small number of bins. The signature is obtained from image contents by considering the contribution of each pixels color to all the histogram bins through the use of fuzzy-sets membership functions. Experimental results on a database of over 10,000 images demonstrate that the proposed system is less sensitive light intensity changes and more robust than the Conventional Color Histogram (CCH) in retrieval precision.