Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-scale maximally stable extremal regions for object recognition

To solve the problem that maximally stable extremal regions (MSER) will become unstable when the image is blurred due to the change of scale, a novel affine invariant feature called Multi-Scale Maximally Stable Extremal Region (MMSER) which is maximally stable both in the image space and the scale space is proposed by defining a criterion to evaluate the stability of extremal regions in scale space. And a fast extraction algorithm based on N-tree disjoint set forest and seeded growing algorithm is designed for MMSER. At the same time, according to the property that MMSER can describe the contour of local features fairly well, a new kind of descriptor is designed for MMSER by combining the local gray grads and the shape context information. The experimental results prove that MMSER is much more stable and discernable under different affine transformation conditions.
A Hybrid Approach for Emotion Detection in Support of Affective Interaction

Affective interaction is a new emerging area of interest for interaction designers. This research explores the potential of our hybrid approach that relies on both, lexical and machine learning techniques for detection of Ekman's six emotional categories in user's text. The initial results of the performance evaluation of the proposed hybrid approach are encouraging and comparable to related research. A demonstrative mobile application that employs the proposed approach was developed to engage the users in a dialogue that solicits their reflections on various daily events and provides appropriate affective responses.
Automatic image registration framework for Remote Sensing Data using Harris Corner Detection and Random Sample Consensus (RANSAC) Model

Image registration is a fundamental image processing task to match and align physically two images which could have been imaged by different sensors, view angles or and at different times. It is necessary to have robust single frame image registration software especially an automated one. Automatic image registration framework overlays two images for geometric conformity aligning common features by establishing a transformation model using distinguishable feature points collected simultaneously in both the images in a completely un assisted manner. The critical steps in image registration are collection of feature points and estimating a spatial transformation especially when outliers are present besides feature matching and resampling the slave image to the master image geometry. In this paper, the details and merit of employing automatic Harris corner detection and building a transformation model using Random Sample Consensus (RANSAC) algorithm is brought out while registering a pair of AWIFS images from Indian Remote Sensing Satellite (IRS) platform. Potential available with this approach for performing large scale image registration tasks such as time series processing for change detection are highlighted.
Game-Changing: Fast Dynamic Updates in a Flexible Navigation Mesh

Games and simulations frequently model scenarios where obstacles move, appear, and disappear in an environment. A city environment changes as new buildings and roads are constructed, and routes can become partially blocked by small obstacles many times in a typical day. This paper studies the effect of using local updates to repair only the affected regions of a navigation mesh in response to a change in the environment. The techniques are inspired by incremental methods for Voronoi diagrams. The main novelty of this paper is that we show how to maintain a 2D or 2.5D navigation mesh in an environment that contains dynamic polygonal obstacles. Experiments show that local updates are fast enough to permit real-time updates of the navigation mesh.
The association between hearing ability and psychosocial health before the age of 70 years

There is a substantial lack of knowledge on the impact of reduced hearing on psychosocial functioning in adults younger than 70 years. The aim of this study is to examine the association between hearing ability and psychosocial health in adults aged between 18 and 70 years. Cross-sectional cohort study. Baseline data of the National Longitudinal Study on Hearing are analyzed, using regression models. The cohort consisted of 1511 participants. Hearing ability was determined using the National Hearing Test, a recently launched speech-in-noise screening test over the Internet. We assessed self-reported psychosocial health using a set of online questionnaires. Adjusting for confounding variables, significant adverse associations between hearing ability and distress, somatization, depression and loneliness are found. For every dB signal-to noise-ratio (dB SNR) reduction of hearing ability both the distress and somatization score increased by 2% p<0.001). The odds for developing moderate or severe depression increase by 5% for every dB SNR reduction in hearing (OR=1.05; 95%CI=1.00-1.09; p=0.03). The odds for developing severe or very severe loneliness significantly increase by 7% for every dB SNR reduction in hearing (OR = 1.07; 95%CI = 1.02-1.12; p=0.004). Different age groups exhibit different associations between hearing ability and psychosocial health, with loneliness being an issue particularly in the youngest age group (18-30 years). In the group of middle-aged adults (40-50 years), the number of significant associations is highest. Hearing ability is negatively associated with higher distress, depression, somatization and loneliness in young and middle-aged adults. The associations are different in different age groups. The findings underline the need to seriously address the adverse effects of limited hearing among young and middle-aged adults both in future research and in clinical practice.
Epigenetic therapy in urologic cancers: an update on clinical trials

Epigenetic dysregulation is one of many factors that contribute to cancer development and progression. Numerous epigenetic alterations have been identified in urologic cancers including histone modifications, DNA methylation changes, and microRNA expression. Since these changes are reversible, efforts are being made to develop epigenetic drugs that restore the normal epigenetic patterns of cells, and many clinical trials are already underway to test their clinical potential. In this review we analyze multiple clinical trials (n=51) that test the efficacy of these drugs in patients with urologic cancers. The most frequently used epigenetic drugs were histone deacetylase inhibitors followed by antisense oligonucleotides, DNA methyltransferase inhibitors and histone demethylase inhibitors, the last of which are only being tested in prostate cancer. In more than 50% of the clinical trials considered, epigenetic drugs were used as part of combination therapy, which achieved the best results. The epigenetic regulation of some cancers is still matter of research but will undoubtedly open a window to new therapeutic approaches in the era of personalized medicine. The future of therapy for urological malignancies is likely to include multidrug regimens in which epigenetic modifying drugs will play an important role.
Research on geomagnetic-matching technology based on improved ICP algorithm

Using geomagnetism aided navigation (GAN) is a new branch of the integrated navigation technique. The principle and the developments of the GAN are introduced and the feature of the geomagnetism field is analyzed in the paper. ICP matching method based on geomagnetic anomaly map is studied. The traditional ICP algorithm is improved in two aspects: firstly, inspired by simulated annealing, sector scan method is proposed to search the optimal match. The sector scan method can help ICP jump out of the local minimum convergence field and to the global one, improving the precision of localization greatly. Secondly, the RANSAN method is used to remove the outliers, which effectively enhances the robustness of the matching method. Computer simulation is used to test the proposed method and good performance is received.
Brainstem raphe pallidus and the adjacent area contain a novel action site in the melanocortin circuitry regulating energy balance

The central melanocortin system plays a critical role in the regulation of energy balance in rodents and humans. The melanocortin signals in both the hypothalamus and brainstem contribute to this regulation. However, how the melanocortin signals of the hypothalamus interact with those intrinsic to the brainstem in the regulation of energy balance is poorly understood. The brainstem raphe pallidus (RPa) and adjacent areas contain melanocortin 4 receptor (MC4-R)-bearing neurons and sympathetic premotor neurons regulating thermogenesis. Here we report that α-melanocyte-stimulating hormone (α-MSH)-immunoreactive (IR) fibers are in close apposition to MC4-R neurons in the RPa. Retrograde tracing studies revealed a unique direct projection from hypothalamic proopiomelanocortin (POMC) neurons to the RPa and adjacent areas of the brainstem in mice and rats. Furthermore, microinjection of the MC3/4-R agonist MTII into the RPa area dose-dependently stimulated oxygen consumption and inhibited feeding, whereas microinjection of the antagonist, SHU9119, enhanced feeding. These data suggest a novel pathway of hypothalamic POMC neuronal efferents to brainstem RPa area MC4-R neurons in the melanocortin circuitry that contribute to coordinate regulation of energy balance. [Life Science Journal. 2008; 5(3): 1 – 13] (ISSN: 1097 – 8135).
Interval-based models for run-time DVFS orchestration in superscalar processors

We develop two simple interval-based models for dynamic superscalar processors. These models allow us to: i) predict with great accuracy performance and power consumption under various frequency and voltage combinations and ii) implement targeted DVFS policies at run-time. The models analyze program execution in intervals - steady-state and miss-event intervals. Intervals are signalled by miss events (L2-misses in our case) that upset the "steady state" execution of the program and are ended when the pipeline reaches again a steady state. The first model is fed by an approximation of the stall cycles (the time the processor instruction window is blocked) due to long-latency L2-misses. The second model improves on this approximation using as input the occupancy of the L2's miss-handling registers (MSHRs). Despite their simplicity these models prove to be accurate in predicting the performance (and energy) for any target frequency/voltage setting, yielding average errors of 2.1% and 0.2% respectively. Besides modelling, we show that the methodology we propose is powerful enough to implement (at run-time) various DVFS policies: "operate at optimal EDP" or "ED2P," or even "reduce ED2P within specific performance constraints. " Approaches based on the two models require minimal hardware cost: two counters for measuring the duration of the steady state and the miss-event intervals and some comparison logic. To validate our methodology we use a cycle-accurate simulator and the benchmarks provided by the SPEC2K suite. Our results indicate that our proposed run-time mechanism is able to orchestrate different DVFS policies with great success yielding negligible errors - bellow 1.5% on average.
Experimental Evaluation of Vehicle Detection Based on Background Modelling in Daytime and Night-Time Video

Vision-based detection of vehicles at urban intersections is an interesting alternative to commonly applied hardware solutions such as inductive loops. The standard approach to that problem is based on a background model consisting of independent per-pixel Gaussian mixtures. However, there are several notable shortcomings of that approach, including large computational complexity, blending of stopped vehicles with background and sensitivity to changes in image acquisition parameters (gain, exposure). We address these problems by proposing the following three improvements: (i) dispersed and delayed background modeling, (ii) modeling patch gradient distributions instead of absolute values of individual pixels, and (iii) significant speed-up through use of integral images. We present a detailed performance comparison on a realistic dataset with handcrafted groundtruth information. The obtained results indicate that significant gains with respect to the standard approach can be obtained both in performance and computational speed. Experiments suggest that the proposed combined technique would enable robust real-time performance on a lowcost embedded computer.
PRIVATE EXPERIENCE IN ADAPTIVE LEARNING MODELS

Here I provide a model that gives some insights regarding questions about actual economic behavior. I take as a source for stylized facts the experiments conducted by Marimon and Sunder as reported in Econometrica, 1993, in which it is shown that people initially do not behave according to the rational expectations assumption, but eventually learn to do so. I propose a slight generalization of the adaptive learning model in order to explain, besides the long run equilibrium observed, the stochastic-like time paths in the aggregate variables. In fact, the introduction of heterogeneity in private experience accumulated over time in a simple adaptive model with fixed decision rules shown is shown to be necessary and sufficient to generate the complex kind of dynamics present in the experiments. In our version of the Marcet- Sargent OLS model, people can not be using useful public information available, but only private experience instead, when they do price forecasting. Otherrwise, we would not be able to explain the data with this model. This result sheds light on the experimental results, in the sense of suggesting a stronger degree of bounded rationality in experimental subjects. In addition, I provide examples within the proposed environment that improve upon the explanatory power of existing adaptive learning models.
Circulating endothelin in children with congenital heart disease.

OBJECTIVE--To evaluate whether circulating endothelin, a peptide that is thought to play a part in mediating vascular tone, might be high in pulmonary hypertensive congenital heart disease. DESIGN--A prospective study with a radioimmunoassay technique to estimate urinary and plasma endothelin concentrations. SETTING--A supraregional referral centre for patients with congenital heart disease. PATIENTS--The 12 hour urinary endothelin concentration in young children with an increased pulmonary blood flow (n = 24, median age eight months) were compared with those in children with right ventricular outflow tract obstruction (n = 14, median age 1.5 years) and with those in healthy controls (n = 16, median age 1.8 years). The concentrations were also measured in adolescents with irreversible pulmonary vascular disease (n = 17, median age 18 years) and compared with those in controls of similar age (n = 19, median age 18.5 years). Also the plasma concentrations in the left atrium and pulmonary artery were measured in young children with either high (n = 11, median age 10.8 months) or low (n = 5, median age 1.0 year) pulmonary blood flow, in the peripheral arterial and venous blood of young children with either high (n = 13, median age 10.8 months) or low (n = 6 median age 1.9 years) pulmonary blood flow, and in the peripheral venous blood of seven healthy young children (median age 1.7 years). RESULTS--The urinary excretion of endothelin was similar in young children of a similar age, whether they had high, low, or normal pulmonary blood flow. Also, urinary endothelin excretion in older patients with irreversible pulmonary vascular disease was similar to that in normal subjects of similar age. Urinary endothelin excretion in normal young children, however, was significantly greater than that in normal older subjects (p = 0.0001). There was no transpulmonary or arteriovenous difference detected in either children with high or low pulmonary blood flow, and plasma concentrations sampled from the left atrium, pulmonary artery, and systemic artery and vein were similar in both groups. CONCLUSION--There was no evidence to implicate circulating endothelin in the pathogenesis of pulmonary vascular disease.
Quantifying Urban Form: Compactness versus 'Sprawl'

This paper develops a set of quantitative variables to characterise urban forms at the metropolitan level and, in particular, to distinguish compactness from 'sprawl'. It first reviews and analyses past research on the definitions of urban form, compactness and sprawl, and corresponding quantitative variables. Four quantitative variables are developed to measure four dimensions of urban form at the metropolitan level: metropolitan size, activity intensity, the degree that activities are evenly distributed, and the extent that high-density sub-areas are clustered. Through a series of simulation analyses, the global Moran coefficient, which characterises the fourth dimension, distinguishes compactness from sprawl. It is high, intermediate and close to zero for monocentric, polycentric and decentralised sprawling forms respectively. In addition, the more there is more local sprawl, composed of discontinuity and strip development, the lower is the Moran coefficient.
Quantum Hair on D-branes and Black Hole Information in String Theory

We introduce a notion of quantum hair which completely characterizes the state of a D-brane in perturbative string theory. The hair manifests itself as a phase (more generally a unitary matrix in subspaces of degenerate string eigenstates) in the scattering amplitudes of elementary strings on the D brane. As the separation of the D-brane and the string center of mass becomes large, the phase goes to zero if we keep the string excitation level fixed. However, by letting the level number increase with the distance, we can keep the phase constant. We argue that this implies that scattering experiments with highly excited strings can detect the state of a D-brane long after it has ``fallen into a black hole'' .
Space-vector PWM techniques for dual three-phase AC machine: analysis, performance evaluation, and DSP implementation

The major drawback of dual three-phase ac machines (6phiM), when supplied by a voltage-source inverter (VSI), is the occurrence of extra harmonic currents. These extra currents circulate only in the stator windings and cause additional losses. One solution to reduce their amplitude is to act on the supply side using dedicated pulsewidth modulation (PWM) control strategies. The aim of this paper is to investigate new space-vector PWM (SVPWM) techniques suitable for 6phiM and to perform a detailed analysis and a performance evaluation. The proposed performance criteria, specific to VSI-fed 6phiM, lead to analytical formulas and graphics, which aid the design of high-performance PWM techniques and demonstrate the superiority of the proposed SVPWM techniques. Experimental results carried out on a 15-kW prototype machine and using a low-cost fixed-point TMS320F240 digital signal processor are given and discussed
Multimodal Annotation of Conversational Data

We propose in this paper a broad-coverage approach for multimodal annotation of conversational data. Large annotation projects addressing the question of multimodal annotation bring together many different kinds of information from different domains, with different levels of granularity. We present in this paper the first results of the OTIM project aiming at developing conventions and tools for multimodal annotation.
“I can’t tell whether it’s my hand”: a pilot study of the neurophenomenology of body representation during the rubber hand illusion in trauma-related disorders

Background Early traumatic experiences are thought to be causal factors in the development of trauma-related dissociative experiences, including depersonalization and derealization. The rubber hand illusion (RHI), a well-known paradigm that measures multi-sensorial integration of a rubber hand into one's own body representation, has been used to investigate alterations in the experience of body ownership and of body representation. Critically, however, it has never been studied in individuals with trauma-related disorders. Objective To investigate body representation distortions occurring in trauma-related disorders in response to the RHI. Method The RHI was administered to three individuals with the dissociative subtype of posttraumatic stress disorder (PTSD), and subjective, behavioral, cardiovascular and skin conductance responses were recorded. Results Participants’ subjective experiences of the RHI were differentiated and complex. The illusion was induced following both synchronous and asynchronous brushing and variably evoked subjective distress, depersonalization and derealization experiences, tonic immobility, increased physiological arousal and flashbacks. Conclusions The present findings point towards the RHI as a strong provocation stimulus that elicits individual patterns of symptom presentation, including experiences of distress and dissociation, in individuals with trauma-related disorders, including the dissociative subtype of PTSD. Highlights of the article The rubber hand illusion (RHI) elicits distress, tonic immobility, depersonalization and derealization, and autonomic responses in individuals with trauma-related disorders, including the dissociative subtype of posttraumatic stress disorder (PTSD). RHI effects related to body misrepresentation may trigger altered experiences related to body ownership. The RHI represents a promising paradigm for studying the neurophenomenology of body distortion in individuals experiencing trauma-related altered states of consciousness (TRASC).
Cohesive crack model for geomaterials : Stability analysis and rate effect

Thl:' cohesi~'1:' (or ficti~ious) crack model. characterized by softening stress-displacement relatJOns. prOVIdes a good description of fracture of quasibrittle materials such as conrete. rock. or tough ceramics. The cohesive crack model is formulated i~ . terms of compliancl:' influence functions and the failure is analyzed as a stabIlity. probll:'m. The size effect is determined by means of an eigenvalue problem. In thIs p.roblem. the structure size for which a given relative crack length yields the maXlmum load is the eigenvalue. The model is further generalized to time dependence. ' The opening displacement is considered as a function of the cohesive stress and the opening rate of the crack. Finally. applications to rock and concrE'te are discussed.
Reweighted l1 Dual Averaging Approach for Sparse Stochastic Learning

Recent advances in stochastic optimization and regularized dual averaging approaches revealed a substantial interest for a simple and scalable stochastic method which is tailored to some more specific needs. Among the latest one can find sparse signal recovery and l0-based sparsity inducing approaches. These methods in particular can force many compo- nents of the solution shrink to zero thus clarifying the importance of the features and simplifying the evaluation. In this paper we concentrate on enhancing sparsity of the recently proposed l1 Regularized Dual Averaging (RDA) method with a simple reweighting iterative procedure which in a limit applies the l0-norm penalty. We present some theoretical justifica- tions of a bounded regret for a sequence of convex repeated games where every game stands for a separate reweighted l1-RDA problem. Numeri- cal results show an enhanced sparsity of the proposed approach and some improvements over the l1-RDA method in generalization error.