Miracle-dz/UniFAR-FTUs huggingface dataset:
Still Searching for Principles

The authors reply to a comment on their article "How robust are probabilistic models of higher-level cognition? ," by G. F. Marcus, et al. The authors debated that multiple, equally probable, Bayesian models could be made for the tasks under consideration, and that Bayesian theories do not restrict which model applies in any given case.
Can a Near Win Kindle Motivation? The Impact of Nearly Winning on Motivation for Unrelated Rewards

Common intuition and research suggest that winning is more motivating than losing. However, we propose that just failing to obtain a reward (i.e., nearly winning it) in one task leads to broader, positive motivational effects on subsequent unrelated tasks relative to clearly losing or actually obtaining the reward. We manipulated a near-win experience using a game app in Experiments 1 through 3 and a lottery in Experiment 4. Our findings showed that nearly winning in one task subsequently led participants to walk faster to get to a chocolate bar (Experiment 1), salivate more for money (Experiment 2), and increase their effort to earn money in a card-sorting task (Experiment 3). A field study (Experiment 4) demonstrated that nearly winning led people to subsequently spend more money on desirable consumer products. Finally, our findings showed that when the activated motivational state was dampened in an intervening task, the nearly-winning effect was attenuated.
A depth recovery algorithm using defocus information

Pentland (1987) proposed an algorithm for sensing scene depth by measuring the amount of defocus of an image. The algorithm is interesting in the sense that no correspondence problems are involved. The authors discuss the difference between shape from defocus and shape from focus and then present a two-phase algorithm where the defocus process is modeled as a two-dimensional Gaussian point-spread function. During the first phase (calibration phase), a camera system parameter is determined off-line. In the next phase (depth-recovery phase), this parameter is used to recover on-line the scene depth by taking two images of the same scene, but with a different amount of defocus. Some implementation issues are addressed, and test results on real images are provided. <<ETX>>
Remodelação miocárdica após infarto agudo do miocárdio experimental em ratos: efeito do bloqueio do sistema renina angiotensina aldosterona

OBJECTIVE: To assess the effect of lisinopril and losartan on myocardial remodeling in experimental infarction in rats. METHODS: Male Wistar rats underwent myocardial infarction and were either treated with lisinopril [20 mg/kg/day (LIS, n=13)] or losartan [20 mg/kg/day (LOS, n=11)], or kept without any treatment (NT, n=11) for 3 months. Their results were compared with those of a control group (CONT, n=11) comprising noninfarcted rats. After euthanasia, the left ventricle was isolated and weighed. The following measurements were taken: the sectional area of myocytes (AC), interstitial collagen fraction (CVF), and myocardial hydroxyproline (HOP). The variables were compared by using 1-way ANOVA, with a significance level of P<0.05. RESULTS: Acute myocardial infarction caused left ventricular hypertrophy. The treatments with lisinopril or losartan could prevent hypertrophy, which was quantified by use of left ventricular weight (LOS=1.06±0.12g, LIS=0.97±0.18g, NT=1.26±0.17g, CONT=1.02±0.09g; P<0.05), of left ventricular weight-to-body weight ratio LV/BW (LOS=2.37± 0.21mg/g, LIS=2.41±0.38mg/g, NT=2.82±0.37mg/g, CONT=2.27± 0.15mg/g), and of left ventricular AC measure-ment (LOS=210±39µ2, LIS=217±35µ2, NT=256±35µ2, CONT=158±06 µ2; P<0.05). The CVF was significantly greater in the left ventricle of the infarcted group, and its increase was prevented with treatment (LOS=1.16±0.4%, LIS=1.27±0.5%, NT=1.8± 0.4%, CONT=0.7±0.5%). Myocardial hydroxyproline was greater in the infarcted group (NT=6.91±2.98mg/g vs. CONT=2.81± 1.21mg/g) and did not change with treatment. CONCLUSION: Myocardial remodeling after infarction is characterized by an increase in the remaining ventricular mass and in interstitial collagen. The angiotensin-converting-enzyme blockers and the selective angiotensin II AT1 antagonist prevent hypertrophy of the myocyte and interstitial fibrosis.
Philanthropy. Wellcome Trust to shift from projects to people.

The Wellcome Trust, the giant biomedical research charity in the United Kingdom, wants to give no-strings-attached funding to nearly all the independent researchers it supports. This week, Wellcome Trust officials announced that they are phasing out their biomedical research grants for U.K. scientists, which consists of 3-year to 5-year awards focused on a specific problem. Instead, starting in 2011, the organization will put that money, about 20% of its total budget, or $183 million, into a new program called Investigator Awards. The awards will be bigger, more flexible, and longer—up to 7 years.
Design and development of a low-cost Autonomous Surface Vehicle

Marine robotics is a rapidly growing field, with applications of both Autonomous Underwater Vehicles (AUV) and Autonomous Surface Vehicles (ASV) becoming extensive and within reach for many people. Presented is a low-cost design for an ASV, focusing on the ability for the average person with only little mechanical and electrical skills to assemble. The ASV also incorporates a winch into its design, allowing the ASV to perform many tasks that make it stand out from other ASV systems available in the market, A novel system containing both an ASV and an AUV is introduced, where the designed ASV would be able to work with AUV systems to find and collect underwater objects.
Early-Childhood Social Reticence Predicts Brain Function in Preadolescent Youths During Distinct Forms of Peer Evaluation

Social reticence is expressed as shy, anxiously avoidant behavior in early childhood. With development, overt signs of social reticence may diminish but could still manifest themselves in neural responses to peers. We obtained measures of social reticence across 2 to 7 years of age. At age 11, preadolescents previously characterized as high (n = 30) or low (n = 23) in social reticence completed a novel functional-MRI-based peer-interaction task that quantifies neural responses to the anticipation and receipt of distinct forms of social evaluation. High (but not low) social reticence in early childhood predicted greater activity in dorsal anterior cingulate cortex and left and right insula, brain regions implicated in processing salience and distress, when participants anticipated unpredictable compared with predictable feedback. High social reticence was also associated with negative functional connectivity between insula and ventromedial prefrontal cortex, a region commonly implicated in affect regulation. Finally, among participants with high social reticence, negative evaluation was associated with increased amygdala activity, but only during feedback from unpredictable peers.
When Lightning Strikes Twice

The educational, occupational, and creative accomplishments of the profoundly gifted participants (IQs ⩾ 160) in the Study of Mathematically Precocious Youth (SMPY) are astounding, but are they representative of equally able 12-year-olds? Duke University’s Talent Identification Program (TIP) identified 259 young adolescents who were equally gifted. By age 40, their life accomplishments also were extraordinary: Thirty-seven percent had earned doctorates, 7.5% had achieved academic tenure (4.3% at research-intensive universities), and 9% held patents; many were high-level leaders in major organizations. As was the case for the SMPY sample before them, differential ability strengths predicted their contrasting and eventual developmental trajectories—even though essentially all participants possessed both mathematical and verbal reasoning abilities far superior to those of typical Ph.D. recipients. Individuals, even profoundly gifted ones, primarily do what they are best at. Differences in ability patterns, like differences in interests, guide development along different paths, but ability level, coupled with commitment, determines whether and the extent to which noteworthy accomplishments are reached if opportunity presents itself.
Surface reconstruction using neural networks

A surface reconstruction method using multilayer feedforward neural networks is proposed. The parametric form represented by multilayer neural networks can model piecewise smooth surfaces in a way that is more general and flexible than many of the classical methods. The approximation method is based on a robust backpropagation (BP) algorithm, which extends the basic BP algorithm to handle errors, especially others, in the training data. <<ETX>>
Model indexing: the graph-hashing approach

The problem of object recognition in computer vision is addressed. A method for model indexing, which, given a group of image features, rapidly extracts from the list of objects those objects containing this group of features, is presented. The method operates on an abstract representation of features, more precisely, groups of features. In practice, this abstract representation takes the form of a graph. The present study deals with binary graphs only, that is, only one feature-type and one feature-relationship-type can be embedded in the representation. <<ETX>>
Underactuated ship global tracking under relaxed conditions

A controller is developed for underactuated surface ships with only surge force and yaw moment available to globally asymptotically track a reference trajectory generated by a suitable virtual ship in a frame attached to the ship body. The reference trajectory is allowed too be a curve including a straight line. The control development is based on Lyapunov's direct method and backstepping technique, and utilizes several properties of ship dynamics and their interconnected structure. Numerical simulations are provided to validate the effectiveness of the proposed controller.
Object-based video indexing for virtual-studio productions

This paper introduces an object-based approach for temporal video partitioning and content-based indexing, where the basic indexing unit is "lifespan of a video object", rather than a "camera shot" or "story unit". We propose a system to extract content-based features of video objects (VOs), based on a compact 2D triangular mesh representation of them. An adaptive mesh-based video object tracking scheme is then employed to compute the motion trajectories of all node points. A set of "key snapshots" which constitute a visual summary of the lifespan of the object are automatically selected using motion and shape information. The system provides direct access to the VOs and gives the functionalities such as object-based search, manipulation, animation, and tracking.
Semiglobal stabilization and output regulation of singular linear systems with input saturation

The semi-global stabilization problem and output regulation problem of singular linear systems subject to input saturation are addressed. A reduced-order normal system is obtained by a standard coordinate transformation. It is further shown that the controller that solves the stabilization (output regulation) problem of the reduced-order normal systems also solves the stabilization (output regulation) problem of the original singular systems.
Substance Use and Sexual Risks Among General MSM and Money Boys in Shanghai, China

In China, men who have sex with men (MSM) are at high risk for substance use, HIV, and other sexually transmitted infections (STIs). However, there has been little research into their drug use and the sexual behaviors they engage in after drug and alcohol use. Using respondent-driven sampling methodology, this cross-sectional study of 404 MSM described drug use and examined sexual behaviors after drug and alcohol use among general MSM and money boys (those who engage in same-sex commercial sex) in Shanghai, China. Money boys reported using more drugs in the last week, 3 months and ever, and having sex after drinking and sex after using drugs more frequently than general MSM. It is vital to continue research and begin science-based interventions in these high-risk and underserved populations.
Comparison of Edge Detectors Using an Object Recognition Task

This paper presents a methodology and results of evaluating edge detection algorithms using an object recognition task. A dataset consisting of 37 real images with 5 different jeep-like vehicles is used. Five edge detectors are compared using ROC curve analysis. The Heitger detector gives the best results. The work is being extended to include more images and a train-and-test style evaluation.
Anaesthesia for the obese patient

Abstract The prevalence of obesity is increasing. Obese and morbidly obese patients figure frequently in peri-operative morbidity and mortality reports. Obese and morbidly obese patients present a significant challenge to the anaesthetist. This is in part due to technical challenges, in part due to co-morbidities, and in part to physiological changes consequent on morbid obesity. An understanding of these changes is important for safe anaesthesia in this patient group. Careful pre-operative assessment and evaluation can bring many co-morbidities to light, and allows appropriate preparation of the patient, theatre and care team prior to surgery. Cardiorespiratory problems, reflux and diabetes are common. The high incidence of obstructive sleep apnoea necessitates postoperative intensive or high dependency care in all cases. The key to safe anaesthesia in this population is multi-disciplinary team working.
On designing of sliding-mode control for stochastic jump systems

In this note, we consider the problems of stochastic stability and sliding-mode control for a class of linear continuous-time systems with stochastic jumps, in which the jumping parameters are modeled as a continuous-time, discrete-state homogeneous Markov process with right continuous trajectories taking values in a finite set. By using Linear matrix inequalities (LMIs) approach, sufficient conditions are proposed to guarantee the stochastic stability of the underlying system. Then, a reaching motion controller is designed such that the resulting closed-loop system can be driven onto the desired sliding surface in a limited time. It has been shown that the sliding mode control problem for the Markovian jump systems is solvable if a set of coupled LMIs have solutions. A numerical example is given to show the potential of the proposed techniques.
A unified setting for decoupling with preview and fixed-lag smoothing in the geometric context

Exact decoupling with preview, perfect tracking of previewed references, unknown-input state observation with fixed lag, and left inversion with fixed lag are considered from a unifying perspective where exact decoupling with preview is the basic problem. Necessary and sufficient constructive conditions for decoupling with finite preview are proved in the geometric framework. Structural and stabilizability conditions are considered separately and the use of self-bounded controlled invariant subspaces allows the dynamic compensator with the minimal unassignable dynamics to be straightforwardly derived. A steering along zeros technique is devised to guarantee decoupling with stability also in the presence of unstable unassignable dynamics of the minimal self-bounded controlled invariant.
Robust controls for ship-mounted container cranes with viscoelastic foundation and flexible hoisting cable

This study proposes two robust controllers for a ship-mounted container crane based on the back-stepping sliding mode control technique. The ship crane system is operated under complex conditions, in which the disturbances caused by the viscoelasticity of seawater and the flexibility of handling wire ropes are fully considered. With two actuators consisting of a trolley-moving force and container-hoisting torque, the controllers concurrently stabilize six states: trolley displacement, container-lifting motion, container swing, axial container oscillation, ship roll, and heave. The quality of the control algorithms is investigated through simulation. The results show that the responses of the crane are asymptotically stabilized and that the ship vibrations are significantly reduced.
Emergent Behavior in Flocks

We provide a model (for both continuous and discrete time) describing the evolution of a flock. Our model is parameterized by a constant beta capturing the rate of decay-which in our model is polynomial-of the influence between birds in the flock as they separate in space. Our main result shows that when beta<1/2 convergence of the flock to a common velocity is guaranteed, while for betages1/2 convergence is guaranteed under some condition on the initial positions and velocities of the birds only
Choice of Weighting for Averaged Nonparametric Transfer Function Estimates

The statistical properties of nonparametric transfer function estimates formed via the weighted sum of empirical transfer function estimates are considered. In the case that the system input is considered deterministic, it is shown that the weighting corresponding to the classical averaged periodogram estimate is optimal. A similar asymptotic result is derived for the case where the input is considered stochastic.
Distributed Probabilistic Synchronization Algorithms for Communication Networks

In this paper, we present a probabilistic synchronization algorithm whose convergence properties are examined using tools of row-stochastic matrices. The proposed algorithm is particularly well suited for wireless sensor network applications, where connectivity is not guaranteed at all times, and energy efficiency is an important design consideration. The tradeoff between the convergence speed and the energy use is studied.
Robust Stability of LTI Systems Over Semialgebraic Sets Using Sum-of-Squares Matrix Polynomials

This paper deals with the robust stability of discrete-time linear time-invariant systems with parametric uncertainties belonging to a semialgebraic set. It is asserted that the robust stability of any system over any semialgebraic set (satisfying a mild condition) is equivalent to solvability of a semidefinite programming (SDP) problem, which can be handled using the available software tools. The particular case of a semialgebraic set associated with a polytope is then investigated, and a computationally appealing method is proposed to attain the SDP problem by means of a sampling technique, introduced recently in the literature. Furthermore, it is shown that the current result encompasses the ones presented in some of the recent works. The efficacy of the proposed method is demonstrated through some illustrative examples, and the results are compared to some of the existing methods.
Surface stereo with soft segmentation

This paper proposes a new stereo model which encodes the simple assumption that the scene is composed of a few, smooth surfaces. A key feature of our model is the surface-based representation, where each pixel is assigned to a 3D surface (planes or B-splines). This representation enables several important contributions: Firstly, we formulate a higher-order prior which states that pixels of similar appearance are likely to belong to the same 3D surface. This enables to incorporate the very popular color segmentation constraint in a soft and principled way. Secondly, we use a global MDL prior to penalize the number of surfaces. Thirdly, we are able to incorporate, in a simple way, a prior which favors low curvature surfaces. Fourthly, we improve the asymmetric occlusion model by disallowing pixels of the same surface to occlude each other. Finally, we use the known fusion move approach which enables a powerful optimization of our model, despite the infinite number of possible labelings (surfaces).
Design of Asymptotically Convergent Frequency Estimator Using Contraction Theory

The problem of estimating unknown frequencies of a sinusoidal signal simultaneously is a classical problem in signal and system theory. Many approaches and algorithms are proposed in literature to develop estimators for a measurable sinusoidal signal having multiple sinusoids with unknown amplitudes, frequencies and phases. In this work, an asymptotically convergent frequency estimator is given for estimation of n-unknown frequencies of a measurable sinusoidal signal. The contraction theory approach is adopted to show the asymptotic convergence of the proposed estimator in quite a simplified manner. Approach given here exploits the results of contraction theory related to semi-contracting systems. The nonlinear estimator based on dynamic system approach, guarantees global boundedness and convergence of the state and frequency estimation for all initial conditions and frequency values. It further ensures simultaneous globally convergent estimation of states and frequencies of a sinusoid involving multiple frequencies. Numerical simulations are presented for different combinations of frequencies to justify the claim.
A rank-order distance based clustering algorithm for face tagging

We present a novel clustering algorithm for tagging a face dataset (e. g., a personal photo album). The core of the algorithm is a new dissimilarity, called Rank-Order distance, which measures the dissimilarity between two faces using their neighboring information in the dataset. The Rank-Order distance is motivated by an observation that faces of the same person usually share their top neighbors. Specifically, for each face, we generate a ranking order list by sorting all other faces in the dataset by absolute distance (e. g., L1 or L2 distance between extracted face recognition features). Then, the Rank-Order distance of two faces is calculated using their ranking orders. Using the new distance, a Rank-Order distance based clustering algorithm is designed to iteratively group all faces into a small number of clusters for effective tagging. The proposed algorithm outperforms competitive clustering algorithms in term of both precision/recall and efficiency.
Practical low-rank matrix approximation under robust L1-norm

A great variety of computer vision tasks, such as rigid/nonrigid structure from motion and photometric stereo, can be unified into the problem of approximating a low-rank data matrix in the presence of missing data and outliers. To improve robustness, the L1-norm measurement has long been recommended. Unfortunately, existing methods usually fail to minimize the L1-based nonconvex objective function sufficiently. In this work, we propose to add a convex trace-norm regularization term to improve convergence, without introducing too much heterogenous information. We also customize a scalable first-order optimization algorithm to solve the regularized formulation on the basis of the augmented Lagrange multiplier (ALM) method. Extensive experimental results verify that our regularized formulation is reasonable, and the solving algorithm is very efficient, insensitive to initialization and robust to high percentage of missing data and/or outliers1.