The dynamics of neutrino-driven supernova explosions after shock revival in 2D and 3D

We study the growth of the explosion energy after shock revival in neutrino-driven explosions in two and three dimensions (2D/3D) using multi-group neutrino hydrodynamics simulations of an 11.2 M⊙ star. The 3D model shows a faster and steadier growth of the explosion energy and already shows signs of subsiding accretion after one second. By contrast, the growth of the explosion energy in 2D is unsteady, and accretion lasts for several seconds as confirmed by additional long-time simulations of stars of similar masses. Appreciable explosion energies can still be reached, albeit at the expense of rather high neutron star masses. In 2D, the binding energy at the gain radius is larger because the strong excitation of downward-propagating g modes removes energy from the freshly accreted material in the downflows. Consequently, the mass outflow rate is considerably lower in 2D than in 3D. This is only partially compensated by additional heating by outward-propagating acoustic waves in 2D. Moreover, the mass outflow rate in 2D is reduced because much of the neutrino energy deposition occurs in downflows or bubbles confined by secondary shocks without driving outflows. Episodic constriction of outflows and vertical mixing of colder shocked material and hot, neutrino-heated ejecta due to Rayleigh–Taylor instability further hamper the growth of the explosion energy in 2D. Further simulations will be necessary to determine whether these effects are generic over a wider range of supernova progenitors.

Indications for and limits of conservative surgery in breast cancer

Improvements in diagnostic techniques and, above all, breast cancer screening campaigns - essential for early diagnosis - have enabled the objectives of conservative surgery to be pursued: disease control, no or low incidence of recurrences and an excellent esthetic result. However, to reach these objectives, it is essential to ensure a careful evaluation of the medical history of every patient, a detailed clinical examination and the correct interpretation of imaging. Particular attention should be paid to all factors influencing the choice of treatment and/or possible local recurrence: age, site, tumor volume, genetic predisposition, pregnancy, previous radiotherapy, pathological features, and surgical margins. The decision to undertake conservative treatment thus requires a multidisciplinary approach involving pathologists, surgeons and oncological radiologists, as well, of course, as the patient herself.

MANIPULATION OF IONS, ELECTRONS, AND PHOTONS IN 2D MATERIALS BY ION INTERCALATION

2D materials have attracted tremendous attention due to their unique physical and chemical properties since the discovery of graphene. Despite these intrinsic properties, various modification methods have been applied to 2D materials that yield even more exciting results. Among all modification methods, the intercalation of 2D materials provides the highest possible doping and/or phase change to the pristine 2D materials. This doping effect highly modifies 2D materials, with extraordinary electrical transport as well as optical, thermal, magnetic, and catalytic properties, which are advantageous for optoelectronics, superconductors, thermoelectronics, catalysis and energy storage applications. To study the property changes of 2D materials, we designed and built a planar nanobattery that allows electrochemical ion intercalation in 2D materials. More importantly, this planar nanobattery enables characterization of electrical, optical and structural properties of 2D materials in situ and real time upon ion intercalation. With this device, we successfully intercalated Li-ions into few layer graphene (FLG) and ultrathin graphite, heavily dopes the graphene to 0.6 x 10^15 /cm2, which simultaneously increased its conductivity and transmittance in the visible range. The intercalated LiC6 single crystallite achieved extraordinary optoelectronic properties, in which an eight-layered Li intercalated FLG achieved transmittance of 91.7% (at 550 nm) and sheet resistance of 3 ohm/sq. We extend the research to obtain scalable, printable graphene based transparent conductors with ion intercalation. Surfactant free, printed reduced graphene oxide transparent conductor thin film with Na-ion intercalation is obtained with transmittance of 79% and sheet resistance of 300 ohm/sq (at 550 nm). The figure of merit is calculated as the best pure rGO based transparent conductors. We further improved the tunability of the reduced graphene oxide film by using two layers of CNT films to sandwich it. The tunable range of rGO film is demonstrated from 0.9 um to 10 um in wavelength. Other ions such as K-ion is also studied of its intercalation chemistry and optical properties in graphitic materials. We also used the in situ characterization tools to understand the fundamental properties and improve the performance of battery electrode materials. We investigated the Na-ion interaction with rGO by in situ Transmission electron microscopy (TEM). For the first time, we observed reversible Na metal cluster (with diameter larger than 10 nm) deposition on rGO surface, which we evidenced with atom-resolved HRTEM image of Na metal and electron diffraction pattern. This discovery leads to a porous reduced graphene oxide sodium ion battery anode with record high reversible specific capacity around 450 mAh/g at 25mA/g, a high rate performance of 200 mAh/g at 250 mA/g, and stable cycling performance up to 750 cycles. In addition, direct observation of irreversible formation of Na2O on rGO unveils the origin of commonly observed low 1st Columbic Efficiency of rGO containing electrodes. Another example for in situ characterization for battery electrode is using the planar nanobattery for 2D MoS2 crystallite. Planar nanobattery allows the intrinsic electrical conductivity measurement with single crystalline 2D battery electrode upon ion intercalation and deintercalation process, which is lacking in conventional battery characterization techniques. We discovered that with a “rapid-charging” process at the first cycle, the lithiated MoS2 undergoes a drastic resistance decrease, which in a regular lithiation process, the resistance always increases after lithiation at its final stage. This discovery leads to a 2- fold increase in specific capacity with with rapid first lithiated MoS2 composite electrode material, compare with the regular first lithiated MoS2 composite electrode material, at current density of 250 mA/g.

Conservative management in very elderly patients with severe aortic stenosis: Time to change?

Despite current recommendations, a high percentage of patients with severe symptomatic aortic stenosis are managed conservatively. The aim of this study was to study symptomatic patients undergoing conservative management from the IDEAS registry, describing their baseline clinical characteristics, mortality, and the causes according to the reason for conservative management. Consecutive patients with severe aortic stenosis diagnosed at 48 centers during January 2014 were included. Baseline clinical characteristics, echocardiographic data, Charlson index, and EuroSCORE-II were registered, including vital status and performance of valve intervention during one-year follow-up. For the purpose of this substudy we assessed symptomatic patients undergoing conservative management, including them in 5 groups according to the reason for performing conservative management [I: comorbidity/frailty (128, 43.8%); II: dementia 18 (6.2%); III: advanced age 34 (11.6%); IV: patients’ refusal 62 (21.2%); and V: other reasons 50 (17.1%)]. We included 292 patients aged 81.5 ± 9 years. Patients from group I had higher Charlson index (4 ± 2.3), higher EuroSCORE-II (7.5 ± 6), and a higher overall (42.2%) and non-cardiac mortality (16.4%) than the other groups. In contrast, patients from group III had fewer comorbidities, lower EuroSCORE-II (4 ± 2.5), and low overall (20.6%) and non-cardiac mortality (5.9%). Patients with severe symptomatic aortic stenosis managed conservatively have different baseline characteristics and clinical course according to the reason for performing conservative management. A prospective assessment of comorbidity and other geriatric syndromes might contribute to improve therapeutic strategy in this clinical setting.

Mobile application for Asian soybean rust tracking in Brazil.

ABSTRACT: Brazil is the second - largest soybean producer. With the arrival of Asian soybean rust in the Western Hemisphere in 2001, a considerable amount of resources has been allocated to understand and control this important yield - limiting disease. Due its rapidly dissemination, in 2004, the federal government led an effort to create the Asian soybean rust consortium, with the main goal of coordinating research activities involving public and private sector. This paper describes the development of a mobile application, designed to support the Asian Soybean Rust Consortium to monitor, in time and space, occurrences of Asian soybean rust in Brazil. RESUMO: O Brasil é o segundo maior produtor de soja do mundo. Com a chegada da ferrugem da soja no hemisfério ocidental em 2001, uma quantidade considerável de recursos foram alocados para entender e controlar esta importante doença. Devido a sua rápida disseminação, em 2004, o governo federal uniu esforços e criou o Consórcio Antiferrugem, cujo objetivo principal seria de coordenar atividades de pesquisa envolvendo empresas públicas e privadas. Este artigo apresenta o desenvolvimento de um aplicativo móvel, projetado para auxiliar este Consórcio no monitoramento em tempo e espaço, de ocorrências de ferrugem asiática de soja no Brasil.

Correlating Multiple 2D Vision Trackers for 3D Object Tracking on Construction Sites

Tracking methods have the potential to retrieve the spatial location of project related entities such as personnel and equipment at construction sites, which can facilitate several construction management tasks. Existing tracking methods are mainly based on Radio Frequency (RF) technologies and thus require manual deployment of tags. On construction sites with numerous entities, tags installation, maintenance and decommissioning become an issue since it increases the cost and time needed to implement these tracking methods. To address these limitations, this paper proposes an alternate 3D tracking method based on vision. It operates by tracking the designated object in 2D video frames and correlating the tracking results from multiple pre-calibrated views using epipolar geometry. The methodology presented in this paper has been implemented and tested on videos taken in controlled experimental conditions. Results are compared with the actual 3D positions to validate its performance.

Head Tracking via Robust Registration in Texture Map Images

A novel method for 3D head tracking in the presence of large head rotations and facial expression changes is described. Tracking is formulated in terms of color image registration in the texture map of a 3D surface model. Model appearance is recursively updated via image mosaicking in the texture map as the head orientation varies. The resulting dynamic texture map provides a stabilized view of the face that can be used as input to many existing 2D techniques for face recognition, facial expressions analysis, lip reading, and eye tracking. Parameters are estimated via a robust minimization procedure; this provides robustness to occlusions, wrinkles, shadows, and specular highlights. The system was tested on a variety of sequences taken with low quality, uncalibrated video cameras. Experimental results are reported.

Exploiting spatio-temporal constraints for robust 2D pose tracking

We present a Spatio-temporal 2D Models Framework (STMF) for 2D-Pose tracking. Space and time are discretized and a mixture of probabilistic "local models" is learnt associating 2D Shapes and 2D Stick Figures. Those spatio-temporal models generalize well for a particular viewpoint and state of the tracked action but some spatio-temporal discontinuities can appear along a sequence, as a direct consequence of the discretization. To overcome the problem, we propose to apply a Rao-Blackwellized Particle Filter (RBPF) in the 2D-Pose eigenspace, thus interpolating unseen data between view-based clusters. The fitness to the images of the predicted 2D-Poses is evaluated combining our STMF with spatio-temporal constraints. A robust, fast and smooth human motion tracker is obtained by tracking only the few most important dimensions of the state space and by refining deterministically with our STMF.

2D silhouette and 3D skeletal models for human detection and tracking

In this paper we propose a statistical model for detection and tracking of human silhouette and the corresponding 3D skeletal structure in gait sequences. We follow a point distribution model (PDM) approach using a Principal Component Analysis (PCA). The problem of non-lineal PCA is partially resolved by applying a different PDM depending of pose estimation; frontal, lateral and diagonal, estimated by Fisher's linear discriminant. Additionally, the fitting is carried out by selecting the closest allowable shape from the training set by means of a nearest neighbor classifier. To improve the performance of the model we develop a human gait analysis to take into account temporal dynamic to track the human body. The incorporation of temporal constraints on the model increase reliability and robustness.

Bio-inspired plume tracking algorithm for UAVS

There is an increased interest on the use of UAVs for environmental research and to track bush fire plumes, volcanic plumes or pollutant sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A memory based and gradient based approach, were developed and compared. A method for generating sparse plumes was also developed. Results indicate the ability of the algorithms to track plumes in 2D and 3D.

New approach to improved detection and tracking performance in track-while-scan radars. Part 1: Introduction and review

The paper presents a new approach to improve the detection and tracking performance of a track-while-scan (TWS) radar. The contribution consists of three parts. In Part 1 the scope of various papers in this field is reviewed. In Part 2, a new approach for integrating the detection and tracking functions is presented. It shows how a priori information from the TWS computer can be used to improve detection. A new multitarget tracking algorithm has also been developed. It is specifically oriented towards solving the combinatorial problems in multitarget tracking. In Part 3, analytical derivations are presented for quantitatively assessing, a priori, the performance of a track-while-scan radar system (true track initiation, false track initiation, true track continuation and false track deletion characteristics). Simulation results are also shown.

Design and flight testing of a bio-inspired plume tracking algorithm for unmanned serial vehicles

There is an increased interest on the use of UAVs for environmental research such as tracking bush fires, volcanic eruptions, chemical accidents or pollution sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A method for generating sparse plumes in a virtual environment was also developed. Results indicated the ability of the algorithms to track plumes in 2D and 3D. The system has been tested with hardware in the loop (HIL) simulations and in flight using a CO2 gas sensor mounted to a multi-rotor UAV. The UAV is controlled by the plume tracking algorithm running on the ground control station (GCS).

In bed with technology: Challenges and opportunities for sleep tracking

In recent years a variety of mobile apps, wearable technologies and embedded systems have emerged that allow individuals to track the amount and the quality of their sleep in their own beds. Despite the widespread adoption of these technologies, little is known about the challenges that current users face in tracking and analysing their sleep. Hence we conducted a qualitative study to examine the practices of current users of sleep tracking technologies and to identify challenges in current practice. Based on data collected from 5 online forums for users of sleep-tracking technologies, we identified 22 different challenges under the following 4 themes: tracking continuity, trust, data manipulation, and data interpretation. Based on these results, we propose 6 design opportunities to assist researchers and practitioners in designing sleep-tracking technologies.

A MatLAB Based Virtual Phantom for 2D Electrical Impedance Tomography (MatVP2DEIT): Studying the Medical Electrical Impedance Tomography Reconstruction in Computer

Electrical Impedance Tomography (EIT) is a computerized medical imaging technique which reconstructs the electrical impedance images of a domain under test from the boundary voltage-current data measured by an EIT electronic instrumentation using an image reconstruction algorithm. Being a computed tomography technique, EIT injects a constant current to the patient's body through the surface electrodes surrounding the domain to be imaged (Omega) and tries to calculate the spatial distribution of electrical conductivity or resistivity of the closed conducting domain using the potentials developed at the domain boundary (partial derivative Omega). Practical phantoms are essentially required to study, test and calibrate a medical EIT system for certifying the system before applying it on patients for diagnostic imaging. Therefore, the EIT phantoms are essentially required to generate boundary data for studying and assessing the instrumentation and inverse solvers a in EIT. For proper assessment of an inverse solver of a 2D EIT system, a perfect 2D practical phantom is required. As the practical phantoms are the assemblies of the objects with 3D geometries, the developing of a practical 2D-phantom is a great challenge and therefore, the boundary data generated from the practical phantoms with 3D geometry are found inappropriate for assessing a 2D inverse solver. Furthermore, the boundary data errors contributed by the instrumentation are also difficult to separate from the errors developed by the 3D phantoms. Hence, the errorless boundary data are found essential to assess the inverse solver in 2D EIT. In this direction, a MatLAB-based Virtual Phantom for 2D EIT (MatVP2DEIT) is developed to generate accurate boundary data for assessing the 2D-EIT inverse solvers and the image reconstruction accuracy. MatVP2DEIT is a MatLAB-based computer program which simulates a phantom in computer and generates the boundary potential data as the outputs by using the combinations of different phantom parameters as the inputs to the program. Phantom diameter, inhomogeneity geometry (shape, size and position), number of inhomogeneities, applied current magnitude, background resistivity, inhomogeneity resistivity all are set as the phantom variables which are provided as the input parameters to the MatVP2DEIT for simulating different phantom configurations. A constant current injection is simulated at the phantom boundary with different current injection protocols and boundary potential data are calculated. Boundary data sets are generated with different phantom configurations obtained with the different combinations of the phantom variables and the resistivity images are reconstructed using EIDORS. Boundary data of the virtual phantoms, containing inhomogeneities with complex geometries, are also generated for different current injection patterns using MatVP2DEIT and the resistivity imaging is studied. The effect of regularization method on the image reconstruction is also studied with the data generated by MatVP2DEIT. Resistivity images are evaluated by studying the resistivity parameters and contrast parameters estimated from the elemental resistivity profiles of the reconstructed phantom domain. Results show that the MatVP2DEIT generates accurate boundary data for different types of single or multiple objects which are efficient and accurate enough to reconstruct the resistivity images in EIDORS. The spatial resolution studies show that, the resistivity imaging conducted with the boundary data generated by MatVP2DEIT with 2048 elements, can reconstruct two circular inhomogeneities placed with a minimum distance (boundary to boundary) of 2 mm. It is also observed that, in MatVP2DEIT with 2048 elements, the boundary data generated for a phantom with a circular inhomogeneity of a diameter less than 7% of that of the phantom domain can produce resistivity images in EIDORS with a 1968 element mesh. Results also show that the MatVP2DEIT accurately generates the boundary data for neighbouring, opposite reference and trigonometric current patterns which are very suitable for resistivity reconstruction studies. MatVP2DEIT generated data are also found suitable for studying the effect of the different regularization methods on reconstruction process. Comparing the reconstructed image with an original geometry made in MatVP2DEIT, it would be easier to study the resistivity imaging procedures as well as the inverse solver performance. Using the proposed MatVP2DEIT software with modified domains, the cross sectional anatomy of a number of body parts can be simulated in PC and the impedance image reconstruction of human anatomy can be studied.