Speeding up the spatial adiabatic passage of matter waves in optical microtraps by optimal control

We numerically investigate the performance of atomic transport in optical microtraps via the so called spatial adiabatic passage technique. Our analysis is carried out by means of optimal control methods, which enable us to determine suitable transport control pulses. We investigate the ultimate limits of the optimal control in speeding up the transport process in a triple well configuration for both a single atomic wave packet and a Bose-Einstein condensate within a regime of experimental parameters achievable with current optical technology.     

Inferring (Biological) Signal Transduction Networks via Transitive Reductions of Directed Graphs

In this paper we consider the p-ary transitive reduction (TR _p ) problem where p>0 is an integer; for p=2 this problem arises in inferring a sparsest possible (biological) signal transduction network consistent with a set of experimental observations with a goal to minimize false positive inferences even if risking false negatives. Special cases of TR _p have been investigated before in different contexts; the best previous results are as follows:

Dynamic Verification of Memory Consistency in Cache-Coherent Multithreaded Computer Architectures

Multithreaded servers with cache-coherent shared memory are the dominant type of machines used to run critical network services and database management systems. To achieve the high availability required for these tasks, it is necessary to incorporate mechanisms for error detection and recovery. Correct operation of the memory system is defined by the memory consistency model. Errors can therefore be detected by checking if the observed memory system behavior deviates from the specified consistency model. Based on recent work, we design a framework for dynamic verification of memory consistency (DVMC). The framework consists of mechanisms to verify three invariants that are proven to guarantee that a specified memory consistency model is obeyed. We describe an implementation of the framework for the SPARCv9 architecture, and we experimentally evaluate its performance using full-system simulation of commercial workloads.     

A large anisotropic damage theory based on an incremental complementary energy equivalence model

This paper presents a large anisotropic damage theory of continuum damage mechanics. It is developed via a new hypothesis of incremental complementary elastic energy equivalence. This hypothesis is more versatile and accurate if compared to the original hypothesis of total complementary energy equivalence. To model the large damage, we assumed that it occurs as a series of incremental small damage. An expression for the damage effect tensor M(D) for large damage is derived. It is shown that when the damage is small, that is, D _i1, the proposed large damage theory reduces to the small damage model of Chow and Wang [1]. To demonstrate this large damage theory, it is applied to model the following cases: (a) uniaxial tension, (b) pure torsion and (c) elastic perfectly-plastic material behavior. In all three cases, the results clearly show that when the damage is small, Chow and Wang's model is recovered. However, for large damage, there are significant differences in predictions. Since this large damage theory is formulated on the basis of the incremental complementary energy, it is applicable to a wider range of problems.     

Laser-Printed Plasmonic Metasurface Supporting Bound States in the Continuum Enhances and Shapes Infrared Spontaneous Emission of Coupled HgTe Quantum Dots

In order to advance the development of quantum emitter-based devices, it is essential to enhance light-matter interactions through coupling between semiconductor quantum dots with high quality factor resonators. Here, efficient tuning of the emission properties of HgTe quantum dots in the infrared spectral region is demonstrated by coupling them to a plasmonic metasurface that supports bound states in the continuum. The plasmonic metasurface, composed of an array of gold nanobumps, is fabricated using single-step direct laser printing, opening up new opportunities for creating exclusive 3D plasmonic nanostructures and advanced photonic devices in the infrared region. A 12-fold enhancement of the photoluminescence in the 900–1700 nm range is observed under optimal coupling conditions. By tuning the geometry of the plasmonic arrays, controllable shaping of the emission spectra is achieved, selectively enhancing specific wavelength ranges across the emission spectrum. The observed enhancement and shaping of the emission are attributed to the Purcell effect, as corroborated by systematic measurements of radiative lifetimes and optical simulations based on the numerical solution of Maxwell's equations. Moreover, coupling of the HgTe photoluminescence to high quality factor modes of the metasurface improves emission directivity, concentrating output within an ≈20° angle.     

Unsupervised tissue classification of brain MR images for voxel‐based morphometry analysis

In this article, a fully unsupervised method for brain tissue segmentation of T1‐weighted MRI 3D volumes is proposed. The method uses the Fuzzy C‐Means (FCM) clustering algorithm and a Fully Connected Cascade Neural Network (FCCNN) classifier. Traditional manual segmentation methods require neuro‐radiological expertise and significant time while semiautomatic methods depend on parameter's setup and trial‐and‐error methodologies that may lead to high intraoperator/interoperator variability. The proposed method selects the most useful MRI data according to FCM fuzziness values and trains the FCCNN to learn to classify brain’ tissues into White Matter, Gray Matter, and Cerebro‐Spinal Fluid in an unsupervised way. The method has been tested on the IBSR dataset, on the BrainWeb Phantom, on the BrainWeb SBD dataset, and on the real dataset “University of Palermo Policlinico Hospital” (UPPH), Italy. Sensitivity, Specificity, Dice and F‐Factor scores have been calculated on the IBSR and BrainWeb datasets segmented using the proposed method, the FCM algorithm, and two state‐of‐the‐art brain segmentation software packages (FSL and SPM) to prove the effectiveness of the proposed approach. A qualitative evaluation involving a group of five expert radiologists has been performed segmenting the real dataset using the proposed approach and the comparison algorithms. Finally, a usability analysis on the proposed method and reference methods has been carried out from the same group of expert radiologists. The achieved results show that the segmentations of the proposed method are comparable or better than the reference methods with a better usability and degree of acceptance.     

Effect of brain edema on the recurrence pattern of malignant gliomas

PURPOSE: To assess the influence of initial preoperative brain edema in malignant gliomas on regrowth patterns. SUBJECTS AND METHODS: 79 patients with histologically verified supratentorial malignant glioma were prospectively studied by magnetic resonance imaging (MRI) before and every 2-3 months after surgery. The median follow-up time was 11 months. We correlated the configuration of the initial vasogenic edema on T2-weighted images with tumor regrowth patterns on contrast-enhanced T1-weighted images. RESULTS: 35/47 tumor regrowths (75%) imitated the initial edema configuration, while 11/47 occurred within the initial tumor bed; in one case tumor recurrence was multilocal. CONCLUSION: In glioblastoma, tumor regrowth patterns correlate positively with the configuration of the initial vasogenic brain edema. The initial, "presurgical" peritumoral edema should thus be considered when planning further treatment.