Dimension-independent Harnack inequalities for subordinated semigroups

Dimension-independent Harnack inequalities are derived for a class of subordinate semigroups. In particular, for a diffusion satisfying the Bakry-Emery curvature condition, the subordinate semigroup with power $\alpha$ satisfies a dimension-free Harnack inequality provided $\alpha \in(1/2, 1)$, and it satisfies the log-Harnack inequality for all $\alpha \in (0,1).$ Some infinite-dimensional examples are also presented

A variational Bayesian approach for inverse problems with skew-t error distributions

In this work, we develop a novel robust Bayesian approach to inverse problems with data errors following a skew-t distribution. A hierarchical Bayesian model is developed in the inverse problem setup. The Bayesian approach contains a natural mechanism for regularization in the form of a prior distribution, and a LASSO type prior distribution is used to strongly induce sparseness. We propose a variational type algorithm by minimizing the Kullback-Leibler divergence between the true posterior distribution and a separable approximation. The proposed method is illustrated on several two-dimensional linear and nonlinear inverse problems, e.g. Cauchy problem and permeability estimation problem

Influence of the asexual parasite biomass on in vitro susceptibility of Plasmodium falciparum to antimalarial drugs in Abidjan

The in vitro activities of artemisinin, dihydroartemisinin (the biologically active metabolite of artemisinin derivatives), chloroquine and pyronaridine were assessed in 32 isolates of Plasmodium falciparum from Abobo in the northern of Abidjan district (Cote dfIvoire) using a test based on the standard microtechnique recommended by the World Health Organization (WHO). The parasites densities were ranged between 8,000 and 540,000 rings/ƒÊl of blood. The geometric means 50% inhibitory concentration (GMIC50) values for chloroquine, pyronaridine and artemisinin were 145.5 nM (95% confidence interval (CI) =65-226 nM), 17.69 nM (95% CI=9.1-26.3 nM) and 5.72 nM (95% CI=2.3-9.1 nM), respectively. Dihydroartemisinin was the most potent drug against chloroquine-sensitive and chloroquine-resistant isolates with a geometric mean of 2.72 nM. There was no correlation between the parasite densities and the responses to chloroquine (r2=0.01, p<0.5), pyronaridine (r2=0.13, p<0.05), artemisinin (r2=0.13, p<0.05) and dihydroartemisinin (r2=0.07, p<0.1)

ForestHash: Semantic Hashing With Shallow Random Forests and Tiny Convolutional Networks

Hash codes are efficient data representations for coping with the ever growing amounts of data. In this paper, we introduce a random forest semantic hashing scheme that embeds tiny convolutional neural networks (CNN) into shallow random forests, with near-optimal information-theoretic code aggregation among trees. We start with a simple hashing scheme, where random trees in a forest act as hashing functions by setting `1' for the visited tree leaf, and `0' for the rest. We show that traditional random forests fail to generate hashes that preserve the underlying similarity between the trees, rendering the random forests approach to hashing challenging. To address this, we propose to first randomly group arriving classes at each tree split node into two groups, obtaining a significantly simplified two-class classification problem, which can be handled using a light-weight CNN weak learner. Such random class grouping scheme enables code uniqueness by enforcing each class to share its code with different classes in different trees. A non-conventional low-rank loss is further adopted for the CNN weak learners to encourage code consistency by minimizing intra-class variations and maximizing inter-class distance for the two random class groups. Finally, we introduce an information-theoretic approach for aggregating codes of individual trees into a single hash code, producing a near-optimal unique hash for each class. The proposed approach significantly outperforms state-of-the-art hashing methods for image retrieval tasks on large-scale public datasets, while performing at the level of other state-of-the-art image classification techniques while utilizing a more compact and efficient scalable representation. This work proposes a principled and robust procedure to train and deploy in parallel an ensemble of light-weight CNNs, instead of simply going deeper.Comment: Accepted to ECCV 201

Evaluation de la pollution métallique des eaux souterraines et de surface dans un environnement minier aurifère à Hiré (Côte d’Ivoire)

Cette étude a pour objet l’évaluation du taux de pollution métallique des eaux souterraines et de surface dans un environnement minier. Pour y parvenir, des prélèvements d’eaux ont été effectués au cours de deuxcampagnes d’échantillonnage (mois décembre 2012 et mois de février 2013) dans la Sous-préfecture de Hiré (centre ouest de la Côte d’Ivoire). Les résultats ont montré des concentrations élevées pour tous les paramètres métalliques dans la majorité des stations. En effet, les teneurs d’arsenic, de cadmium, de mercure, de nickel, de plomb sont largement supérieures aux valeurs limites fixées par l’OMS pour les eaux de consommation et  d’irrigation. En outre, elles pourraient constituer des risques sanitaires pour la population de la zone d’étude. Nos résultats serviront de base aux politiques environnementales nationales visant à protéger les populations vivant dans un environnement minier.Mots clés : Pollution, métaux, sols, Hiré, Côte d’Ivoire

T-cell cytotoxicity in the absence of viral protein synthesis in target cells

CYTOTOXIC T cells lyse only those virus infected target cells in vitro which express, in addition to the viral antigen(s), those K or D region products of the major histocompati-bility complex (MHC) which were present during anti-viral sensitisation in vivo. This 'associative recogniton' by cytotoxic T cells could reflect the interaction of two T-cell receptors with specificity for target K or D gene products and independently for the viral antigen, or one receptor with specificity for virally altered K or D region products (see ref. 1 and refs therein). There are various ways that the MHC antigens could be altered, including 'modification from within', where the virus modifies host protein synthesis by interfering with transcription2, translation or post-translational glycosylation; or 'modification from without' where enzymic or chemical alteration of cell membrane proteins are induced by virus activity at the cell surface. In this report we show that inactivated Sendai virus or isolated Sendai virus envelopes can serve to modify a cell and make it a specific target for Sendai-immune T-cell killing, thus excluding the possibility of 'modification from within' in this system

Development of a thermal sensor to probe cell viability and concentration in cell suspensions

This paper presents a novel biothermal sensor to probe cell viability and concentration of a cell suspension. The sensing technique exploits the thermophysical properties of the suspension, so no labeling of suspended cells is required. When the sensor is periodically heated, the amplitude and phase of the thermal signal are dependent on the thermal properties of the cell suspension, particularly the thermal conductivity k. We measured k of HeLa, hepatocyte, and NIH-3T3 J2 cell suspensions with various concentrations and viabilities. The results demonstrate that the k of a cell suspension has a strong correlation with its concentration and viability. Accordingly, k can be employed as an index of cell concentration and viability. Furthermore, without data processing to obtain k, the electric signal that reflects the thermal response of the sensor can be used as a tool to probe viability of a cell suspension in real time. The proposed thermal sensing technique offers label-free, non-invasive, long-term, and real-time means to probe the viability and concentration of cells in a suspension. (C) 2014 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.X1134sciescopu

Estimating liver weight of adults by body weight and gender

Aim: To estimate the standard liver weight for assessing adequacies of graft size in live donor liver transplantation and remnant liver in major hepatectomy for cancer. Methods: In this study, anthropometric data of body weight and body height were tested for a correlation with liver weight in 159 live liver donors who underwent donor right hepatectomy including the middle hepatic vein. Liver weights were calculated from the right lobe graft weight obtained at the back table, divided by the proportion of the right lobe on the computed tomography. Results: The subjects, all Chinese, had a mean age of 35.8 ± 10.5 years, and a female to male ratio of 118:41. The mean volume of the right lobe was 710.14 ± 131.46 mL and occupied 64.55% ± 4.47% of the whole liver on computed tomography. Right lobe weighed 598.90 ± 117.39 g and the estimated liver weight was 927.54 ± 168.78 g. When body weight and body height were subjected to multiple stepwise linear regression analysis, body height was found to be insignificant. Females of the same body weight had a slightly lower liver weight. A formula based on body weight and gender was derived: Estimated standard liver weight (g) = 218 + BW (kg) × 12.3 + gender × 51 (R 2=0.48) (female = 0, male = 1). Based on the anthropometric data of these 159 subjects, liver weights were calculated using previously published formulae derived from studies on Caucasian, Japanese, Korean, and Chinese. All formulae overestimated liver weights compared to this formula. The Japanese formula overestimated the estimated standard liver weight (ESLW) for adults less than 60 kg. Conclusion: A formula applicable to Chinese males and females is available. A formula for individual races appears necessary. © 2006 The WJG Press. All rights reserved.published_or_final_versio

Learning Shape Priors for Single-View 3D Completion and Reconstruction

The problem of single-view 3D shape completion or reconstruction is challenging, because among the many possible shapes that explain an observation, most are implausible and do not correspond to natural objects. Recent research in the field has tackled this problem by exploiting the expressiveness of deep convolutional networks. In fact, there is another level of ambiguity that is often overlooked: among plausible shapes, there are still multiple shapes that fit the 2D image equally well; i.e., the ground truth shape is non-deterministic given a single-view input. Existing fully supervised approaches fail to address this issue, and often produce blurry mean shapes with smooth surfaces but no fine details. In this paper, we propose ShapeHD, pushing the limit of single-view shape completion and reconstruction by integrating deep generative models with adversarially learned shape priors. The learned priors serve as a regularizer, penalizing the model only if its output is unrealistic, not if it deviates from the ground truth. Our design thus overcomes both levels of ambiguity aforementioned. Experiments demonstrate that ShapeHD outperforms state of the art by a large margin in both shape completion and shape reconstruction on multiple real datasets.Comment: ECCV 2018. The first two authors contributed equally to this work. Project page: http://shapehd.csail.mit.edu