From Ground States to Local Hamiltonians

Traditional quantum physics solves ground states for a given Hamiltonian, while quantum information science asks for the existence and construction of certain Hamiltonians for given ground states. In practical situations, one would be mainly interested in local Hamiltonians with certain interaction patterns, such as nearest neighbour interactions on some type of lattices. A necessary condition for a space $V$ to be the ground-state space of some local Hamiltonian with a given interaction pattern, is that the maximally mixed state supported on $V$ is uniquely determined by its reduced density matrices associated with the given pattern, based on the principle of maximum entropy. However, it is unclear whether this condition is in general also sufficient. We examine the situations for the existence of such a local Hamiltonian to have $V$ satisfying the necessary condition mentioned above as its ground-state space, by linking to faces of the convex body of the local reduced states. We further discuss some methods for constructing the corresponding local Hamiltonians with given interaction patterns, mainly from physical points of view, including constructions related to perturbation methods, local frustration-free Hamiltonians, as well as thermodynamical ensembles.Comment: 11 pages, 2 figures, to be published in PR

Ozone predictabilities due to meteorological uncertainties in the Mexico City basin using ensemble forecasts

The purpose of the present study is to investigate the sensitivity of ozone (O<sub>3</sub>) predictions in the Mexico City Metropolitan Area (MCMA) to meteorological initial uncertainties and planetary boundary layer (PBL) parameterization schemes using state-of-the-art meteorological and photochemical prediction models through ensemble forecasts. The simulated periods (3, 9, 15 and 29 March 2006) represent four typical meteorological episodes ("South-Venting", "O<sub>3</sub>-North", "O<sub>3</sub>-South" and "Convection-North", respectively) in the Mexico City basin during the MCMA-2006/MILAGRO campaign. Our results demonstrate that the uncertainties in meteorological initial conditions have significant impacts on O<sub>3</sub> predictions, including peak time O<sub>3</sub> concentrations ([O<sub>3</sub>]), horizontal and vertical O<sub>3</sub> distributions, and temporal variations. The ensemble spread of the simulated peak [O<sub>3</sub>] averaged over the city's ambient monitoring sites can reach up to 10 ppb. The increasing uncertainties in meteorological fields during peak O<sub>3</sub> period contribute to the largest unpredictability in O<sub>3</sub> simulations, while the impacts of wind speeds and PBL height on [O<sub>3</sub>] are more straightforward and important. The magnitude of the ensemble spreads varies with different PBL schemes and meteorological episodes. The uncertainties in O<sub>3</sub> predictions caused by PBL schemes mainly come from their ability to represent the mixing layer height; but overall, these uncertainties are smaller than those from the uncertainties in meteorological initial conditions

Estimating the Material Properties of Fabric from Video

Passively estimating the intrinsic material properties of deformable objects moving in a natural environment is essential for scene understanding. We present a framework to automatically analyze videos of fabrics moving under various unknown wind forces, and recover two key material properties of the fabric: stiffness and area weight. We extend features previously developed to compactly represent static image textures to describe video textures, such as fabric motion. A discriminatively trained regression model is then used to predict the physical properties of fabric from these features. The success of our model is demonstrated on a new, publicly available database of fabric videos with corresponding measured ground truth material properties. We show that our predictions are well correlated with ground truth measurements of stiffness and density for the fabrics. Our contributions include: (a) a database that can be used for training and testing algorithms for passively predicting fabric properties from video, (b) an algorithm for predicting the material properties of fabric from a video, and (c) a perceptual study of humans' ability to estimate the material properties of fabric from videos and images.National Science Foundation (U.S.) (CGV-1111415)National Science Foundation (U.S.) (CGV-1212928)National Science Foundation (U.S.). Graduate Research FellowshipMassachusetts Institute of Technology (Intelligent Initiative Postdoctoral Fellowship)United States. Intelligence Advanced Research Projects Activity (D10PC20023

Using 3DVAR data assimilation system to improve ozone simulations in the Mexico City basin

This study investigates the improvement of ozone (O<sub>3</sub>) simulations in the Mexico City basin using a three-dimensional variational (3DVAR) data assimilation system in meteorological simulations during the MCMA-2003 field measurement campaign. Meteorological simulations from the NCAR/Penn State mesoscale model (MM5) are used to drive photochemical simulations with the Comprehensive Air Quality Model with extensions (CAMx) during a four-day episode on 13–16 April 2003. The simulated wind circulation, temperature, and humidity fields in the basin with the data assimilation are found to be more consistent with the observations than those from the reference deterministic forecast. This leads to improved simulations of plume position, peak O<sub>3</sub> timing, and peak O<sub>3</sub> concentrations in the photochemical model. The improvement in O<sub>3</sub> simulations is especially strong during the daytime. The results demonstrate the importance of applying data assimilation in meteorological simulations for air quality studies in the Mexico City basin

Evaluation of WRF mesoscale simulations and particle trajectory analysis for the MILAGRO field campaign

Accurate numerical simulations of the complex wind flows in the Mexico City Metropolitan Area (MCMA) can be an invaluable tool for interpreting the MILAGRO field campaign results. This paper uses three methods to evaluate numerical simulations of basin meteorology using the MM5 and WRF models: statistical comparisons with observations, "Concentration Field Analysis" (CFA) using measured air pollutant concentrations, and comparison of flow features using cluster analysis. CFA is shown to be a better indication of simulation quality than statistical metrics, and WRF simulations are shown to be an improvement on the MM5 ones. Comparisons with clusters identifies an under-representation of the drainage flows into the basin and an over-representation of wind shear in the boundary layer. Particle trajectories simulated with WRF-FLEXPART are then used to analyse the transport of the urban plume and show rapid venting and limited recirculation during MILAGRO. Lagrangian impacts were identified at the campaign supersites, and age spectra of the pollutants evaluated at those same sites. The evaluation presented in the paper show that mesoscale meteorological simulations are of sufficient accuracy to be useful for MILAGRO data analysis

Estimating the Material Properties of Fabric from Video

Passively estimating the intrinsic material properties of deformable objects moving in a natural environment is essential for scene understanding. We present a framework to automatically analyze videos of fabrics moving under various unknown wind forces, and recover two key material properties of the fabric: stiffness and area weight. We extend features previously developed to compactly represent static image textures to describe video textures, such as fabric motion. A discriminatively trained regression model is then used to predict the physical properties of fabric from these features. The success of our model is demonstrated on a new, publicly available database of fabric videos with corresponding measured ground truth material properties. We show that our predictions are well correlated with ground truth measurements of stiffness and density for the fabrics. Our contributions include: (a) a database that can be used for training and testing algorithms for passively predicting fabric properties from video, (b) an algorithm for predicting the material properties of fabric from a video, and (c) a perceptual study of humans' ability to estimate the material properties of fabric from videos and images

Combined treatment with inhibitors of ErbB Receptors and Hh signaling pathways is more effective than single treatment in reducing the growth of malignant mesothelioma both in vitro and in vivo

Malignant mesothelioma (MM) is a rare orphan aggressive neoplasia with low survival rates. Among the other signaling pathways, ErbB receptors and Hh signaling are deregulated in MM. Thus, molecules involved in these signaling pathways could be used for targeted therapy approaches. The aim of this study was to evaluate the effects of inhibitors of Hh- (GANT-61) and ErbB receptors (Afatinib)-mediated signaling pathways, when used alone or in combination, on growth, cell cycle, cell death and autophagy, modulation of molecules involved in transduction pathways, in three human MM cell lines of different histotypes. The efficacy of the combined treatment was also evaluated in a murine epithelioid MM cell line both in vitro and in vivo. This study demonstrated that combined treatment with two inhibitors counteracting the activation of two different signaling pathways involved in neoplastic transformation and progression, such as those activated by ErbB and Hh signaling, is more effective than the single treatments in reducing MM growth in vitro and in vivo. This study may have clinical implications for the development of targeted therapy approaches for MM

Natural humoral immune response to ribosomal P0 protein in colorectal cancer patients

Tumor associated antigens are useful in colorectal cancer (CRC) management. The ribosomal P proteins (P0, P1, P2) play an important role in protein synthesis and tumor formation. The immunogenicity of the ribosomal P0 protein in head and neck, in breast and prostate cancer patients and the overexpression of the carboxyl-terminal P0 epitope (C-22 P0) in some tumors were reported

Polyphenol-mediated autophagy in cancer: Evidence of in vitro and in vivo studies

One of the hallmarks of cellular transformation is the altered mechanism of cell death. There are three main types of cell death, characterized by different morphological and biochemical features, namely apoptosis (type I), autophagic cell death (type II) and necrosis (type III). Autophagy, or self-eating, is a tightly regulated process involved in stress responses, and it is a lysosomal degradation process. The role of autophagy in cancer is controversial and has been associated with both the induction and the inhibition of tumor growth. Autophagy can exert tumor suppression through the degradation of oncogenic proteins, suppression of inflammation, chronic tissue damage and ultimately by preventing mutations and genetic instability. On the other hand, tumor cells activate autophagy for survival in cellular stress conditions. Thus, autophagy modulation could represent a promising therapeutic strategy for cancer. Several studies have shown that polyphenols, natural compounds found in foods and beverages of plant origin, can efficiently modulate autophagy in several types of cancer. In this review, we summarize the current knowledge on the effects of polyphenols on autophagy, highlighting the conceptual benefits or drawbacks and subtle cell-specific effects of polyphenols for envisioning future therapies employing polyphenols as chemoadjuvants