Electrorheological Rayleigh-Taylor Instability at the Interface between a Porous Layer and Thin Shell with Poorly Conducting Couple Stress Fluid

This paper is concerned with the study of the Electrorheological Rayleigh-Taylor instability (ERTI) at the interface between a densely packed saturated poorly conducting couple stress porous layer accelerated by a lighter poorly conducting couple stress fluid in a thin shell in the presence of a transverse electric field and laser radiation. A simple theory based on fully developed flow approximations is used to derive the dispersion relation for the growth rate of ERTI. The cutoff and the maximum wave numbers and the corresponding maximum frequencies are obtained. It is shown that the effects of couple stress parameter and the electric field reduce the growth rate considerably compared to a non-conducting fluid in the absence of an electric field. These are favorable to control the surface instabilities in many practical applications discussed in this paper

Feature tracking for automated volume of interest stabilization on 4D-OCT images

A common representation of volumetric medical image data is the triplanar view (TV), in which the surgeon manually selects slices showing the anatomical structure of interest. In addition to common medical imaging such as MRI or computed tomography, recent advances in the field of optical coherence tomography (OCT) have enabled live processing and volumetric rendering of four-dimensional images of the human body. Due to the region of interest undergoing motion, it is challenging for the surgeon to simultaneously keep track of an object by continuously adjusting the TV to desired slices. To select these slices in subsequent frames automatically, it is necessary to track movements of the volume of interest (VOI). This has not been addressed with respect to 4DOCT images yet. Therefore, this paper evaluates motion tracking by applying state-of-the-art tracking schemes on maximum intensity projections (MIP) of 4D-OCT images. Estimated VOI location is used to conveniently show corresponding slices and to improve the MIPs by calculating thin-slab MIPs. Tracking performances are evaluated on an in-vivo sequence of human skin, captured at 26 volumes per second. Among investigated tracking schemes, our recently presented tracking scheme for soft tissue motion provides highest accuracy with an error of under 2.2 voxels for the first 80 volumes. Object tracking on 4D-OCT images enables its use for sub-epithelial tracking of microvessels for image-guidance. © 2017 SPIE

Numerical Investigation of Spatial Effects on the Silicon Solar Cell

Investigating the effect of device dimension on the silicon solar cell, by using the PC1D numerical simulation environment, we report strong correlation of efficiency of the silicon solar cell with its size. The results showcase finer efficiency at the lower n-type thickness and higher p-type thickness. The internal quantum efficiency (IQE) and external quantum efficiency (EQE) too exhibit variation with the device size. As a whole, based on the statistical analysis, especially regression, variance, and best subsets selection, the paper depicts that the p-type thickness, ISC and VOC are the preeminent parameters to model the silicon solar cell

Meta-Tracker: Fast and Robust Online Adaptation for Visual Object Trackers

This paper improves state-of-the-art visual object trackers that use online adaptation. Our core contribution is an offline meta-learning-based method to adjust the initial deep networks used in online adaptation-based tracking. The meta learning is driven by the goal of deep networks that can quickly be adapted to robustly model a particular target in future frames. Ideally the resulting models focus on features that are useful for future frames, and avoid overfitting to background clutter, small parts of the target, or noise. By enforcing a small number of update iterations during meta-learning, the resulting networks train significantly faster. We demonstrate this approach on top of the high performance tracking approaches: tracking-by-detection based MDNet and the correlation based CREST. Experimental results on standard benchmarks, OTB2015 and VOT2016, show that our meta-learned versions of both trackers improve speed, accuracy, and robustness.Comment: Code: https://github.com/silverbottlep/meta_tracker

Kinematic deprojection and mass inversion of spherical systems of known velocity anisotropy

Traditionally, the mass / velocity anisotropy degeneracy (MAD) inherent in the spherical, stationary, non-streaming Jeans equation has been handled by assuming a mass profile and fitting models to the observed kinematical data. Here, the opposite approach is considered: the equation of anisotropic kinematic projection is inverted for known arbitrary anisotropy to yield the space radial velocity dispersion profile in terms of an integral involving the radial profiles of anisotropy and isotropic dynamical pressure. Then, through the Jeans equation, the mass profile is derived in terms of double integrals of observable quantities. Single integral formulas for both deprojection and mass inversion are provided for several simple anisotropy models (isotropic, radial, circular, general constant, Osipkov-Merritt, Mamon-Lokas and Diemand-Moore-Stadel). Tests of the mass inversion on NFW models with these anisotropy models yield accurate results in the case of perfect observational data, and typically better than 70% (in 4 cases out of 5) accurate mass profiles for the sampling errors expected from current observational data on clusters of galaxies. For the NFW model with mildly increasing radial anisotropy, the mass is found to be insensitive to the adopted anisotropy profile at 7 scale radii and to the adopted anisotropy radius at 3 scale radii. This anisotropic mass inversion method is a useful complementary tool to analyze the mass and anisotropy profiles of spherical systems. It provides the practical means to lift the MAD in quasi-spherical systems such as globular clusters, round dwarf spheroidal and elliptical galaxies, as well as groups and clusters of galaxies, when the anisotropy of the tracer is expected to be linearly related to the slope of its density.Comment: Accepted in MNRAS. 19 pages. Minor changes from previous version: Table 1 of nomenclature, some math simplifications, paragraph in Discussion on alternative deprojection method by deconvolution. 19 pages. 6 figure

Long-Term Visual Object Tracking Benchmark

We propose a new long video dataset (called Track Long and Prosper - TLP) and benchmark for single object tracking. The dataset consists of 50 HD videos from real world scenarios, encompassing a duration of over 400 minutes (676K frames), making it more than 20 folds larger in average duration per sequence and more than 8 folds larger in terms of total covered duration, as compared to existing generic datasets for visual tracking. The proposed dataset paves a way to suitably assess long term tracking performance and train better deep learning architectures (avoiding/reducing augmentation, which may not reflect real world behaviour). We benchmark the dataset on 17 state of the art trackers and rank them according to tracking accuracy and run time speeds. We further present thorough qualitative and quantitative evaluation highlighting the importance of long term aspect of tracking. Our most interesting observations are (a) existing short sequence benchmarks fail to bring out the inherent differences in tracking algorithms which widen up while tracking on long sequences and (b) the accuracy of trackers abruptly drops on challenging long sequences, suggesting the potential need of research efforts in the direction of long-term tracking.Comment: ACCV 2018 (Oral

Crimean-congo haemorrhagic fever: a global perspective

Crimean-Congo Haemorrhagic Fever (CCHF) is caused by infection with a tick-borne virus (Nairovirus) in the family Bunyaviridae, causing severe and often fatal haemorrhagic fever in humans. CCHF is pervasive, now found in Europe, Asia, Africa, the Middle East and the Indian subcontinent. CCHF spreads to humans either by tick bites or by contact with blood and tissues from infected animals or humans. CCHF outbreaks constitute a threat to public health services because of its epidemic potential, its high case fatality ratio (10-40%), and its potential for nosocomial outbreaks and its quandaries in treatment and prevention. It is characterized by sudden onset with initial sign symptoms including fever, chills, agitations, myalgia, headaches, vomiting, abdominal pain, arthralgia, ecchymosis, melena, haematuria, nose bleeding, vaginal bleeding, bradycardia, thrombocytopenia. It is diagnosed by Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) assay, ELISA test, antigen detection tests. Overall supportive therapy is the mainstay of patient management in CCHF. Seriously ill patients require intensive care. Ribavirin for the treatment of CCHF cases it is most effective, if administered very soon after the onset of clinical signs (e.g., during the first 48 hours). Prevention should be taken which reduce risk of tick to human transmission and human to human transmission

Online, Real-Time Tracking Using a Category-to-Individual Detector

A method for online, real-time tracking of objects is presented. Tracking is treated as a repeated detection problem where potential target objects are identified with a pre-trained category detector and object identity across frames is established by individual-specific detectors. The individual detectors are (re-)trained online from a single positive example whenever there is a coincident category detection. This ensures that the tracker is robust to drift. Real-time operation is possible since an individual-object detector is obtained through elementary manipulations of the thresholds of the category detector and therefore only minimal additional computations are required. Our tracking algorithm is benchmarked against nine state-of-the-art trackers on two large, publicly available and challenging video datasets. We find that our algorithm is 10% more accurate and nearly as fast as the fastest of the competing algorithms, and it is as accurate but 20 times faster than the most accurate of the competing algorithms

Spiritual Pathology Theory of the Sound Heart Model: Socio-Cultural Factors of Spiritual Distress

Introduction: Spiritual Pathology is the study of disturbing factors in the relationship between man and God, the process of disruption in secure attachment to God, which causes spiritual distress in relation to self, people, and the world of creation.Areas covered: Balbi defines attachment as deep emotional bond with special people in life, whose interaction brings security, joy and happiness, and their presence brings peace in times of stress. Kirkpatrick generalized the style of attachment to parents to attachment to God. Expert opinion: In the Sound Heart Model, worship is natural need. The basis of religion is secure attachment to God. Secure attachment to God is belief in the presence and sufficiency of God, as a responsive safe haven. The basis of attachment to God is positive image of God and “recognizing the truth of religion” by the Prophet. The Prophet, as interpreter of Qur’an and spiritual role-model, has healthy spiritual personality. Acceptance of religion, at the time of intellectual maturity, should be done without imitation and coercion, based on knowing the truth of religion, with a free and informed choice. Spiritual pathology is the study of socio-cultural factors that cause misunderstanding of religion, negative image of God and insecure attachment to God