Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation

Image-to-image translation has been made much progress with embracing Generative Adversarial Networks (GANs). However, it's still very challenging for translation tasks that require high quality, especially at high-resolution and photorealism. In this paper, we present Discriminative Region Proposal Adversarial Networks (DRPAN) for high-quality image-to-image translation. We decompose the procedure of image-to-image translation task into three iterated steps, first is to generate an image with global structure but some local artifacts (via GAN), second is using our DRPnet to propose the most fake region from the generated image, and third is to implement "image inpainting" on the most fake region for more realistic result through a reviser, so that the system (DRPAN) can be gradually optimized to synthesize images with more attention on the most artifact local part. Experiments on a variety of image-to-image translation tasks and datasets validate that our method outperforms state-of-the-arts for producing high-quality translation results in terms of both human perceptual studies and automatic quantitative measures.Comment: ECCV 201

EFEITOS DA INTOXICAÇÃO AGUDA COM ETANOL SOBRE A EXSUDAÇÃO DE NEUTRÓFILOS PARA A CAVIDADE PERITOENAL DE EM CAMUNDONGOS INOCULADOS COM Staphilococcus aureus.

Introdução. Há demonstrações que uma intoxicação aguda pelo etanol tem efeitos antiinflamatórios, com redução da exsudação de neutrófilos e com aumento da susceptibilidade a bactérias, especialmente Streptococcus pneumoniae. No entanto não se conhece o tempo durante o qual persistem os efeitos inibidores da exsudação celular e da redução da atividade microbicida de leucócitos, após a intoxicação etílica aguda. Objetivos. Avaliar o tempo após uma intoxicação etílica aguda no qual persistem os efeitos inibidores da exsudação de neutrófilos e a redução da capacidade microbicida do exsudato inflamatório em um modelo de peritonite induzida por Staphylococcus aureus. Métodos. Camundongos C57BL/6 receberam, por gavagem, uma dose de 7mg de etanol/g peso corporal em solução a 40%. Uma, 12,24, 48 e 72 horas após, receberam uma inoculação intraperitoneal de Staphylococcus aureus (0,5 ml contendo 6 a 9x108 UFC/mL; cepa ATCC 25923). Seis horas depois, os animais eram eutanasiados e a cavidade peritoneal lavada com PBS/EDTA 0,01M; uma alíquota era utilizada para contagem do número de UFC e a outra para contagem global e específica das células do exsudato utilizando câmara de Neubauer e citocentrífuga para confecção de esfregaços, corados por corante hematológico rápido (Dipquick). A contagem de UFC foi feita pelo método de diluição seriada com semeadura em placas de ágar Müller-Hinton. Resultados. Todos os animais que receberam etanol apresentaram sinais de embriaguês, que chegou a um estado de letargia profunda do qual todos os animais se recuperavam em, no máximo, 45 minutos. A dose de etanol utilizada induziu involução do timo, evidente 24 horas após a alcoolização, mas com recuperação após 120 horas. Nos animais alcoolizados que receberam o inóculo do estafilococo houve redução significativa da exsudação celular, devido a redução da exsudação de neutrófilos, até 24 horas após a ingestão do etanol. A análise dos esfregaços mostrava maior quantidade de bactérias fora das células no grupo etanol e o número de UFC foi maior no período avaliado, mas a diferença não foi estatisticamente significativa. Conclusão. Confirma-se os efeitos antiinflamatórios da intoxicação etílica aguda, com redução significativa no exsudato de leucócitos, até 24 horas após a exposição ao etanol; essa redução decorre especialmente da redução da exsudação de neutrófilos, já que o número de mononucleares exsudados no período avaliado foi semelhante nos dois grupos experimentais. O poder microbicida da cavidade peritoneal frente aos estafilococos foi menor no grupo etanol embora sem significância estatística, possivelmente porque os macrófagos residentes foram menos afetados pelos efeitos do etanol. Palavras-chaves: Alcoolismo agudo, neutrófilos, inflamação

The incidence of liver injury in Uyghur patients treated for TB in Xinjiang Uyghur autonomous region, China, and its association with hepatic enzyme polymorphisms nat2, cyp2e1, gstm1 and gstt1.

BACKGROUND AND OBJECTIVE: Of three first-line anti-tuberculosis (anti-TB) drugs, isoniazid is most commonly associated with hepatotoxicity. Differences in INH-induced toxicity have been attributed to genetic variability at several loci, NAT2, CYP2E1, GSTM1and GSTT1, that code for drug-metabolizing enzymes. This study evaluated whether the polymorphisms in these enzymes were associated with an increased risk of anti-TB drug-induced hepatitis in patients and could potentially be used to identify patients at risk of liver injury. METHODS AND DESIGN: In a cross-sectional study, 2244 tuberculosis patients were assessed two months after the start of treatment. Anti-TB drug-induced liver injury (ATLI) was defined as an ALT, AST or bilirubin value more than twice the upper limit of normal. NAT2, CYP2E1, GSTM1 and GSTT1 genotypes were determined using the PCR/ligase detection reaction assays. RESULTS: 2244 patients were evaluated, there were 89 cases of ATLI, a prevalence of 4% 9 patients (0.4%) had ALT levels more than 5 times the upper limit of normal. The prevalence of ATLI was greater among men than women, and there was a weak association with NAT2*5 genotypes, with ATLI more common among patients with the NAT2*5*CT genotype. The sensitivity of the CT genotype for identifying patients with ATLI was 42% and the positive predictive value 5.9%. CT ATLI was more common among slow acetylators (prevalence ratio 2.0 (95% CI 0.95,4.20) )compared to rapid acetylators. There was no evidence that ATLI was associated with CYP2E1 RsaIc1/c1genotype, CYP2E1 RsaIc1/c2 or c2/c2 genotypes, or GSTM1/GSTT1 null genotypes. CONCLUSIONS: In Xinjiang Uyghur TB patients, liver injury was associated with the genetic variant NAT2*5, however the genetic markers studied are unlikely to be useful for screening patients due to the low sensitivity and low positive predictive values for identifying persons at risk of liver injury

Building robust prediction models for defective sensor data using Artificial Neural Networks

Predicting the health of components in complex dynamic systems such as an automobile poses numerous challenges. The primary aim of such predictive systems is to use the high-dimensional data acquired from different sensors and predict the state-of-health of a particular component, e.g., brake pad. The classical approach involves selecting a smaller set of relevant sensor signals using feature selection and using them to train a machine learning algorithm. However, this fails to address two prominent problems: (1) sensors are susceptible to failure when exposed to extreme conditions over a long periods of time; (2) sensors are electrical devices that can be affected by noise or electrical interference. Using the failed and noisy sensor signals as inputs largely reduce the prediction accuracy. To tackle this problem, it is advantageous to use the information from all sensor signals, so that the failure of one sensor can be compensated by another. In this work, we propose an Artificial Neural Network (ANN) based framework to exploit the information from a large number of signals. Secondly, our framework introduces a data augmentation approach to perform accurate predictions in spite of noisy signals. The plausibility of our framework is validated on real life industrial application from Robert Bosch GmbH.Comment: 16 pages, 7 figures. Currently under review. This research has obtained funding from the Electronic Components and Systems for European Leadership (ECSEL) Joint Undertaking, the framework programme for research and innovation Horizon 2020 (2014-2020) under grant agreement number 662189-MANTIS-2014-

Semi-analytic results for quasi-normal frequencies

The last decade has seen considerable interest in the quasi-normal frequencies [QNFs] of black holes (and even wormholes), both asymptotically flat and with cosmological horizons. There is wide agreement that the QNFs are often of the form omega_n = (offset) + i n (gap), though some authors have encountered situations where this behaviour seems to fail. To get a better understanding of the general situation we consider a semi-analytic model based on a piecewise Eckart (Poeschl-Teller) potential, allowing for different heights and different rates of exponential falloff in the two asymptotic directions. This model is sufficiently general to capture and display key features of the black hole QNFs while simultaneously being analytically tractable, at least for asymptotically large imaginary parts of the QNFs. We shall derive an appropriate "quantization condition" for the asymptotic QNFs, and extract as much analytic information as possible. In particular, we shall explicitly verify that the (offset)+ i n (gap) behaviour is common but not universal, with this behaviour failing unless the ratio of rates of exponential falloff on the two sides of the potential is a rational number. (This is "common but not universal" in the sense that the rational numbers are dense in the reals.) We argue that this behaviour is likely to persist for black holes with cosmological horizons.Comment: V1: 28 pages, no figures. V2: 3 references added, no physics changes. V3: 29 pages, 9 references added, no physics changes; V4: reformatted, now 27 pages. Some clarifications, comparison with results obtained by monodromy techniques. This version accepted for publication in JHEP. V5: Minor typos fixed. Compatible with published versio

Protein Microarray On-Demand: A Novel Protein Microarray System

We describe a novel, simple and low-cost protein microarray strategy wherein the microarrays are generated by printing expression ready plasmid DNAs onto slides that can be converted into protein arrays on-demand. The printed expression plasmids serve dual purposes as they not only direct the synthesis of the protein of interest; they also serve to capture the newly synthesized proteins through a high affinity DNA-protein interaction. To accomplish this we have exploited the high-affinity binding (∼3–7×10 −13 M) of E. coli Tus protein to Ter, a 20 bp DNA sequence involved in the regulation of E. coli DNA replication. In our system, each protein of interest is synthesized as a Tus fusion protein and each expression construct directing the protein synthesis contains embedded Ter DNA sequence. The embedded Ter sequence functions as a capture reagent for the newly synthesized Tus fusion protein. This “all DNA” microarray can be converted to a protein microarray on-demand without need for any additional capture reagent.

Proteomic profile of KSR1-regulated signalling in response to genotoxic agents in breast cancer

Kinase suppressor of Ras 1 (KSR1) has been implicated in tumorigenesis in multiple cancers, including skin, pancreatic and lung carcinomas. However, our recent study revealed a role of KSR1 as a tumour suppressor in breast cancer, the expression of which is potentially correlated with chemotherapy response. Here, we aimed to further elucidate the KSR1-regulated signalling in response to genotoxic agents in breast cancer. Stable isotope labelling by amino acids in cell culture (SILAC) coupled to high-resolution mass spectrometry (MS) was implemented to globally characterise cellular protein levels induced by KSR1 in the presence of doxorubicin or etoposide. The acquired proteomic signature was compared and GO-STRING analysis was subsequently performed to illustrate the activated functional signalling networks. Furthermore, the clinical associations of KSR1 with identified targets and their relevance in chemotherapy response were examined in breast cancer patients. We reveal a comprehensive repertoire of thousands of proteins identified in each dataset and compare the unique proteomic profiles as well as functional connections modulated by KSR1 after doxorubicin (Doxo-KSR1) or etoposide (Etop-KSR1) stimulus. From the up-regulated top hits, several proteins, including STAT1, ISG15 and TAP1 are also found to be positively associated with KSR1 expression in patient samples. Moreover, high KSR1 expression, as well as high abundance of these proteins, is correlated with better survival in breast cancer patients who underwent chemotherapy. In aggregate, our data exemplify a broad functional network conferred by KSR1 with genotoxic agents and highlight its implication in predicting chemotherapy response in breast cancer

Quantum Criticality in Heavy Fermion Metals

Quantum criticality describes the collective fluctuations of matter undergoing a second-order phase transition at zero temperature. Heavy fermion metals have in recent years emerged as prototypical systems to study quantum critical points. There have been considerable efforts, both experimental and theoretical, which use these magnetic systems to address problems that are central to the broad understanding of strongly correlated quantum matter. Here, we summarize some of the basic issues, including i) the extent to which the quantum criticality in heavy fermion metals goes beyond the standard theory of order-parameter fluctuations, ii) the nature of the Kondo effect in the quantum critical regime, iii) the non-Fermi liquid phenomena that accompany quantum criticality, and iv) the interplay between quantum criticality and unconventional superconductivity.Comment: (v2) 39 pages, 8 figures; shortened per the editorial mandate; to appear in Nature Physics. (v1) 43 pages, 8 figures; Non-technical review article, intended for general readers; the discussion part contains more specialized topic

A Self-Reference False Memory Effect in the DRM Paradigm: Evidence from Eastern and Western Samples

It is well established that processing information in relation to oneself (i.e., selfreferencing) leads to better memory for that information than processing that same information in relation to others (i.e., other-referencing). However, it is unknown whether self-referencing also leads to more false memories than other-referencing. In the current two experiments with European and East Asian samples, we presented participants the Deese-Roediger/McDermott (DRM) lists together with their own name or other people’s name (i.e., “Trump” in Experiment 1 and “Li Ming” in Experiment 2). We found consistent results across the two experiments; that is, in the self-reference condition, participants had higher true and false memory rates compared to those in the other-reference condition. Moreover, we found that selfreferencing did not exhibit superior mnemonic advantage in terms of net accuracy compared to other-referencing and neutral conditions. These findings are discussed in terms of theoretical frameworks such as spreading activation theories and the fuzzytrace theory. We propose that our results reflect the adaptive nature of memory in the sense that cognitive processes that increase mnemonic efficiency may also increase susceptibility to associative false memories