Multi-speckle diffusing wave spectroscopy with a single mode detection scheme

We present a detection scheme for diffusing wave spectroscopy (DWS) based on a two cell geometry that allows efficient ensemble averaging. This is achieved by putting a fast rotating diffuser in the optical path between laser and sample. We show that the recorded (multi-speckle) correlation echoes provide an ensemble averaged signal that does not require additional time averaging. We find the performance of our experimental scheme comparable or even superior to camera based multi-speckle techniques that rely on direct spatial averaging. Furthermore, combined with traditional two-cell DWS, the full intensity autocorrelation function can be measured with a single experimental setup covering more than 10 decades in correlation time.Comment: Submitted to PR

Gelation as arrested phase separation in short-ranged attractive colloid-polymer mixtures

We present further evidence that gelation is an arrested phase separation in attractive colloid-polymer mixtures, based on a method combining confocal microscopy experiments with numerical simulations recently established in {\bf Nature 453, 499 (2008)}. Our results are independent of the form of the interparticle attractive potential, and therefore should apply broadly to any attractive particle system with short-ranged, isotropic attractions. We also give additional characterization of the gel states in terms of their structure, inhomogeneous character and local density.Comment: 6 figures, to be published in J. Phys. Condens. Matter, special issue for EPS Liquids Conference 200

A knowledge based framework to support active aging at home based environments

Information and Communication Technologies can support Active Aging strategies in a scenario like the Smart Home. This paper details a person centered distributed framework, called TALISMAN+, whose aim is to promote personal autonomy by taking advantage of knowledge based technologies, sensors networks, mobile devices and internet. The proposed solution can support an elderly person to keep living alone at his house without being obliged to move to a residential center. The framework is composed by five subsystems: a reasoning module that is able to take local decisions at home in order to support active aging, a biomedical variables telemonitorisation platform running on a mobile device, a hybrid reasoning middleware aimed to assess cardiovascular risk in a remote way, a private vision based sensor subsystem, and a secure telematics solution that guarantees confidentiality for personal information. TALISMAN+ framework deployment is being evaluated at a real environment like the Accessible Digital Home

Towards Pose-Invariant 2D Face Classification for Surveillance

A key problem for "face in the crowd" recognition from existing surveillance cameras in public spaces (such as mass transit centres) is the issue of pose mismatches between probe and gallery faces. In addition to accuracy, scalability is also important, necessarily limiting the complexity of face classification algorithms. In this paper we evaluate recent approaches to the recognition of faces at relatively large pose angles from a gallery of frontal images and propose novel adaptations as well as modifications. Specifically, we compare and contrast the accuracy, robustness and speed of an Active Appearance Model (AAM) based method (where realistic frontal faces are synthesized from non-frontal probe faces) against bag-of-features methods (which are local feature approaches based on block Discrete Cosine Transforms and Gaussian Mixture Models). We show a novel approach where the AAM based technique is sped up by directly obtaining pose-robust features, allowing the omission of the computationally expensive and artefact producing image synthesis step. Additionally, we adapt a histogram-based bag-of-features technique to face classification and contrast its properties to a previously proposed direct bag-of-features method. We also show that the two bag-of-features approaches can be considerably sped up, without a loss in classification accuracy, via an approximation of the exponential function. Experiments on the FERET and PIE databases suggest that the bag-of-features techniques generally attain better performance, with significantly lower computational loads. The histogram-based bag-of-features technique is capable of achieving an average recognition accuracy of 89% for pose angles of around 25 degrees

Association of CRTC1 polymorphisms with obesity markers in subjects from the general population with lifetime depression.

Psychiatric disorders have been hypothesized to share common etiological pathways with obesity, suggesting related neurobiological bases. We aimed to examine whether CRTC1 polymorphisms were associated with major depressive disorder (MDD) and to test the association of these polymorphisms with obesity markers in several large case-control samples with MDD. The association between CRTC1 polymorphisms and MDD was investigated in three case-control samples with MDD (PsyCoLaus n1=3,362, Radiant n2=3,148 and NESDA/NTR n3=4,663). The effect of CRTC1 polymorphisms on obesity markers was then explored. CRTC1 polymorphisms were not associated with MDD in the three samples. CRTC1 rs6510997C>T was significantly associated with fat mass in the PsyCoLaus study. In fact, a protective effect of this polymorphism was found in MDD cases (n=1,434, β=-1.32%, 95% CI -2.07 to -0.57, p<0.001), but not in controls. In the Radiant study, CRTC1 polymorphisms were associated with BMI, exclusively in individuals with MDD (n=2,138, β=-0.75kg/m(2), 95% CI -1.30 to -0.21, p=0.007), while no association with BMI was found in the NESDA/NTR study. Estimated fat mass using bioimpedance that capture more accurately adiposity was only present in the PsyCoLaus sample. CRTC1 polymorphisms seem to play a role with obesity markers in individuals with MDD rather than non-depressive individuals. Therefore, the weak association previously reported in the population-based samples was driven by cases diagnosed with lifetime MDD. However, CRTC1 seems not to be implicated directly in the development of psychiatric diseases

Snippet based trajectory statistics histograms for assistive technologies

Due to increasing hospital costs and traveling time, more and more patients decide to use medical devices at home without traveling to the hospital. However, these devices are not always very straight-forward for usage, and the recent reports show that there are many injuries and even deaths caused by the wrong use of these devices. Since human supervision during every usage is impractical, there is a need for computer vision systems that would recognize actions and detect if the patient has done something wrong. In this paper, we propose to use Snippet Based Trajectory Statistics Histograms descriptor to recognize actions in two medical device usage problems; inhaler device usage and infusion pump usage. Snippet Based Trajectory Statistics Histograms encodes the motion and position statistics of densely extracted trajectories from a video. Our experiments show that by using Snippet Based Trajectory Statistics Histograms technique, we improve the overall performance for both tasks. Additionally, this method does not require heavy computation, and is suitable for real-time systems. © Springer International Publishing Switzerland 2015

A Passive Monitoring System in Assisted Living Facilities: 12-Month Comparative Study

The GE QuietCare® passive monitoring system uses advanced motion sensor technology that learns the daily living patterns of senior community residents and sends alerts when certain out-of-the-ordinary events occur. This study compared falls, hospitalizations, care level changes, and resident attrition between two similar assisted living facilities where one facility adopted the QuietCare® monitoring system and the other did not over a 12-month period. Average falls per week were significantly lower in the QuietCare® facility than the control facility. There was also a trend toward fewer weekly hospitalizations in the QuietCare® facility. There was higher resident retention at the QuietCare® facility. This study provides evidence of direct benefits to both the resident and the facility for the use of QuietCare®. There was a significant reduction in the number of falls, as well as a general facility performance improvement measured by care level consistency and higher resident retention rates

Multiple glass transitions in star polymer mixtures: Insights from theory and simulations

The glass transition in binary mixtures of star polymers is studied by mode coupling theory and extensive molecular dynamics computer simulations. In particular, we have explored vitrification in the parameter space of size asymmetry $\delta$ and concentration $\rho_2$ of the small star polymers at fixed concentration of the large ones. Depending on the choice of parameters, three different glassy states are identified: a single glass of big polymers at low $\delta$ and low $\rho_2$, a double glass at high $\delta$ and low $\rho_2$, and a novel double glass at high $\rho_2$ and high $\delta$ which is characterized by a strong localization of the small particles. At low $\delta$ and high $\rho_2$ there is a competition between vitrification and phase separation. Centered in the $(\delta, \rho_2)$-plane, a liquid lake shows up revealing reentrant glass formation. We compare the behavior of the dynamical density correlators with the predictions of the theory and find remarkable agreement between the two.Comment: 15 figures, to be published in Macromolecule