Diamagnetic and paramagnetic shifts in self-assembled InAs lateral quantum dot molecules

We uncover the underlying physics that explains the energy shifts of discrete states of individual InAs lateral quantum dot molecules (LQDMs) as a function of magnetic fields applied in the Faraday geometry. We observe that ground states of the LQDM exhibit a diamagnetic shift while excited states exhibit a paramagnetic shift. We explain the physical origin of the transition between these two behaviors by analyzing the molecular exciton states with effective mass calculations. We find that charge carriers in delocalized molecular states can become localized in single QDs with increasing magnetic field. We further show that the net effects of broken symmetry of the molecule and Coulomb correlation lead to the paramagnetic response.NSF DMR-0844747 DMR 1309989 GV VALi+d Grant APOSTD/2013/052 NRF of Korea 2011-C0030821/2013R1A1A1007118 MINECO Project CTQ2011-2732

Renormalization group and nonequilibrium action in stochastic field theory

We investigate the renormalization group approach to nonequilibrium field theory. We show that it is possible to derive nontrivial renormalization group flow from iterative coarse graining of a closed-time-path action. This renormalization group is different from the usual in quantum field theory textbooks, in that it describes nontrivial noise and dissipation. We work out a specific example where the variation of the closed-time-path action leads to the so-called Kardar-Parisi-Zhang equation, and show that the renormalization group obtained by coarse graining this action, agrees with the dynamical renormalization group derived by directly coarse graining the equations of motion.Comment: 33 pages, 3 figures included in the text. Revised; one reference adde

Broken symmetry and the variation of critical properties in the phase behaviour of supramolecular rhombus tilings

The degree of randomness, or partial order, present in two-dimensional supramolecular arrays of isophthalate tetracarboxylic acids is shown to vary due to subtle chemical changes such as the choice of solvent or small differences in molecular dimensions. This variation may be quantified using an order parameter and reveals a novel phase behaviour including random tiling with varying critical properties as well as ordered phases dominated by either parallel or non-parallel alignment of neighbouring molecules, consistent with long-standing theoretical studies. The balance between order and randomness is driven by small differences in the intermolecular interaction energies, which we show, using numerical simulations, can be related to the measured order parameter. Significant variations occur even when the energy difference is much less than the thermal energy highlighting the delicate balance between entropic and energetic effects in complex self-assembly processes

Exciton swapping in a twisted graphene bilayer as a solid-state realization of a two-brane model

It is shown that exciton swapping between two graphene sheets may occur under specific conditions. A magnetically tunable optical filter is described to demonstrate this new effect. Mathematically, it is shown that two turbostratic graphene layers can be described as a "noncommutative" two-sheeted (2+1)-spacetime thanks to a formalism previously introduced for the study of braneworlds in high energy physics. The Hamiltonian of the model contains a coupling term connecting the two layers which is similar to the coupling existing between two braneworlds at a quantum level. In the present case, this term is related to a K-K' intervalley coupling. In addition, the experimental observation of this effect could be a way to assess the relevance of some theoretical concepts of the braneworld hypothesis.Comment: 15 pages, 3 figures, final version published in European Physical Journal

Analytical methods in wineries: is it time to change?

A review of the methods for the most common parameters determined in wine—namely, ethanol, sulfur dioxide, reducing sugars, polyphenols, organic acids, total and volatile acidity, iron, soluble solids, pH, and color—reported in the last 10 years is presented here. The definition of the given parameter, official and usual methods in wineries appear at the beginning of each section, followed by the methods reported in the last decade divided into discontinuous and continuous methods, the latter also are grouped in nonchromatographic and chromatographic methods because of the typical characteristics of each subgroup. A critical comparison between continuous and discontinuous methods for the given parameter ends each section. Tables summarizing the features of the methods and a conclusions section may help users to select the most appropriate method and also to know the state-of-the-art of analytical methods in this area

ST-V-Net: Incorporating Shape Prior Into Convolutional Neural Netwoks For Proximal Femur Segmentation

We aim to develop a deep-learning-based method for automatic proximal femur segmentation in quantitative computed tomography (QCT) images. We proposed a spatial transformation V-Net (ST-V-Net), which contains a V-Net and a spatial transform network (STN) to extract the proximal femur from QCT images. The STN incorporates a shape prior into the segmentation network as a constraint and guidance for model training, which improves model performance and accelerates model convergence. Meanwhile, a multi-stage training strategy is adopted to fine-tune the weights of the ST-V-Net. We performed experiments using a QCT dataset which included 397 QCT subjects. During the experiments for the entire cohort and then for male and female subjects separately, 90% of the subjects were used in ten-fold stratified cross-validation for training and the rest of the subjects were used to evaluate the performance of models. In the entire cohort, the proposed model achieved a Dice similarity coefficient (DSC) of 0.9888, a sensitivity of 0.9966 and a specificity of 0.9988. Compared with V-Net, the Hausdorff distance was reduced from 9.144 to 5.917 mm, and the average surface distance was reduced from 0.012 to 0.009 mm using the proposed ST-V-Net. Quantitative evaluation demonstrated excellent performance of the proposed ST-V-Net for automatic proximal femur segmentation in QCT images. In addition, the proposed ST-V-Net sheds light on incorporating shape prior to segmentation to further improve the model performance

A Deep Learning-Based Method for Automatic Segmentation of Proximal Femur from Quantitative Computed Tomography Images

Purpose: Proximal femur image analyses based on quantitative computed tomography (QCT) provide a method to quantify the bone density and evaluate osteoporosis and risk of fracture. We aim to develop a deep-learning-based method for automatic proximal femur segmentation. Methods and Materials: We developed a 3D image segmentation method based on V-Net, an end-to-end fully convolutional neural network (CNN), to extract the proximal femur QCT images automatically. The proposed V-net methodology adopts a compound loss function, which includes a Dice loss and a L2 regularizer. We performed experiments to evaluate the effectiveness of the proposed segmentation method. In the experiments, a QCT dataset which included 397 QCT subjects was used. For the QCT image of each subject, the ground truth for the proximal femur was delineated by a well-trained scientist. During the experiments for the entire cohort then for male and female subjects separately, 90% of the subjects were used in 10-fold cross-validation for training and internal validation, and to select the optimal parameters of the proposed models; the rest of the subjects were used to evaluate the performance of models. Results: Visual comparison demonstrated high agreement between the model prediction and ground truth contours of the proximal femur portion of the QCT images. In the entire cohort, the proposed model achieved a Dice score of 0.9815, a sensitivity of 0.9852 and a specificity of 0.9992. In addition, an R2 score of 0.9956 (p<0.001) was obtained when comparing the volumes measured by our model prediction with the ground truth. Conclusion: This method shows a great promise for clinical application to QCT and QCT-based finite element analysis of the proximal femur for evaluating osteoporosis and hip fracture risk

Intrinsic connectivity network disruption in progressive supranuclear palsy

Objective Progressive supranuclear palsy (PSP) has been conceptualized as a large-scale network disruption, but the specific network targeted has not been fully characterized. We sought to delineate the affected network in patients with clinical PSP. Methods Using task-free functional magnetic resonance imaging, we mapped intrinsic connectivity to the dorsal midbrain tegmentum (dMT), a region that shows focal atrophy in PSP. Two healthy control groups (1 young, 1 older) were used to define and replicate the normal connectivity pattern, and patients with PSP were compared to an independent matched healthy control group on measures of network connectivity. Results Healthy young and older subjects showed a convergent pattern of connectivity to the dMT, including brainstem, cerebellar, diencephalic, basal ganglia, and cortical regions involved in skeletomotor, oculomotor, and executive control. Patients with PSP showed significant connectivity disruptions within this network, particularly within corticosubcortical and cortico-brainstem interactions. Patients with more severe functional impairment showed lower mean dMT network connectivity scores. Interpretation This study defines a PSP-related intrinsic connectivity network in the healthy brain and demonstrates the sensitivity of network-based imaging methods to PSP-related physiological and clinical changes. Ann Neurol 2013;73:603-61

Prognosis of HIV Patients Receiving Antiretroviral Therapy According to CD4 Counts: A Long-term Follow-up study in Yunnan, China

We aim to evaluate the overall survival and associated risk factors for HIV-infected Chinese patients on antiretroviral therapy (ART). 2517 patients receiving ART between 2006 and 2016 were prospectively enrolled in Yunnan province. Kaplan-Meier analyses and Cox proportional hazard regression analyses were performed. 216/2517 patients died during a median 17.5 (interquartile range [IQR] 6.8-33.2) months of follow-up. 82/216 occurred within 6 months of starting ART. Adjusted hazard ratios were10.69 (95%CI 2.38-48.02, p = 0.002) for old age, 1.94 (95%CI 1.40-2.69, p < 0.0001) for advanced WHO stage, and 0.42 (95%CI 0.27-0.63, p < 0.0001) for heterosexual transmission compared to injecting drug users. Surprisingly, adjusted hazard ratios comparing low CD4 counts group (<50 cells/μl) with high CD4 counts group (≥500 cells/μl) within six months after starting ART was 20.17 (95%CI 4.62-87.95, p < 0.0001) and it declined to 3.57 (95%CI 1.10-11.58, p = 0.034) afterwards. Age, WHO stage, transmission route are significantly independent risk factors for ART treated HIV patients. Importantly, baseline CD4 counts is strongly inversely associated with survival in the first six months; whereas it becomes a weak prognostic factor after six months of starting ART