SALMONELLA ENTERICA INTERACTIONS WITH TOMATO: PLANT GENOTYPE EFFECTS AND SALMONELLA GENETIC RESPONSES

Several outbreaks of Salmonella enterica infections have been linked to tomatoes. One cost-effective way to complement on-farm preventive Good Agricultural Practices would be to identify cultivars with inherent decreased susceptibility to Salmonella colonization. Various tomato cultivars with distinct phenotypes were screened to evaluate their susceptibility to Salmonella epiphytic colonization. The potential role of plant exudates, collected from the same cultivars, on the growth kinetics of Salmonella was examined. These investigations were supplemented with Salmonella genome-wide transcriptomics that showed bacterial responses to colonization of tomato shoots and roots. Epiphytic colonization of fruit by S. enterica was cultivar-dependent and serotype-specific, but did not correlate with leaf colonization. Fruit and leaves of the same cultivar differed in their ability to support Salmonella growth. Quantitative and qualitative analysis of tomato exudates provided a possible explanation for the differential susceptibility to bacterial colonization among tomato cultivars. Tomato exudates alone were capable of supporting Salmonella growth, and the growth kinetics of Salmonella in tomato exudates differed by cultivar. Characterization of the chemical composition of primary and secondary metabolites in tomato exudates pointed to potential causes for the differential growth of Salmonella observed in the exudates of various tomato cultivars. Key transcriptomic signals that were down- and up-regulated in Salmonella upon interacting with tomato were identified, enabling us to elucidate the molecular mechanisms underlying this enteric pathogen-plant interaction. Overall, the identified signals lead to a proposed model that depicts the cellular processes needed to preserve cell viability when multiple abiotic stresses in conjunction with low nutrient availability are encountered, while simultaneously repressing unnecessary energy demands or maintaining them at a level equivalent to growth in a nutritious medium. These findings strongly support the hypothesis that plant-regulated mechanisms influence enteric pathogen colonization. It is clear that Salmonella can sense subtle environmental cues brought about by the genotype or physiological state of plants and can respond with distinct patterns of gene expression. Future work should focus on whether this bacterial behavior on plants results from an evolutionary adaptation to use plants as a vector to re-enter animal hosts

Dual Attention GANs for Semantic Image Synthesis

In this paper, we focus on the semantic image synthesis task that aims at transferring semantic label maps to photo-realistic images. Existing methods lack effective semantic constraints to preserve the semantic information and ignore the structural correlations in both spatial and channel dimensions, leading to unsatisfactory blurry and artifact-prone results. To address these limitations, we propose a novel Dual Attention GAN (DAGAN) to synthesize photo-realistic and semantically-consistent images with fine details from the input layouts without imposing extra training overhead or modifying the network architectures of existing methods. We also propose two novel modules, i.e., position-wise Spatial Attention Module (SAM) and scale-wise Channel Attention Module (CAM), to capture semantic structure attention in spatial and channel dimensions, respectively. Specifically, SAM selectively correlates the pixels at each position by a spatial attention map, leading to pixels with the same semantic label being related to each other regardless of their spatial distances. Meanwhile, CAM selectively emphasizes the scale-wise features at each channel by a channel attention map, which integrates associated features among all channel maps regardless of their scales. We finally sum the outputs of SAM and CAM to further improve feature representation. Extensive experiments on four challenging datasets show that DAGAN achieves remarkably better results than state-of-the-art methods, while using fewer model parameters. The source code and trained models are available at https://github.com/Ha0Tang/DAGAN.Comment: Accepted to ACM MM 2020, camera ready (9 pages) + supplementary (10 pages

Visual Relationship Detection with Relative Location Mining

Visual relationship detection, as a challenging task used to find and distinguish the interactions between object pairs in one image, has received much attention recently. In this work, we propose a novel visual relationship detection framework by deeply mining and utilizing relative location of object-pair in every stage of the procedure. In both the stages, relative location information of each object-pair is abstracted and encoded as auxiliary feature to improve the distinguishing capability of object-pairs proposing and predicate recognition, respectively; Moreover, one Gated Graph Neural Network(GGNN) is introduced to mine and measure the relevance of predicates using relative location. With the location-based GGNN, those non-exclusive predicates with similar spatial position can be clustered firstly and then be smoothed with close classification scores, thus the accuracy of top $n$ recall can be increased further. Experiments on two widely used datasets VRD and VG show that, with the deeply mining and exploiting of relative location information, our proposed model significantly outperforms the current state-of-the-art.Comment: Accepted to ACM MM 201

Photo collage-based photograph display system on mobile computing platform

In the last few decades, mobile computing platform technology has grown rapidly, as observed from smart phones that have quickly become ubiquitous. The mobile computing platform is the most widely used platform in our life today, and digital photographs captured through these devices have become routine for most people. In this study, we propose a novel artistic method for displaying photographs in mobile devices as a photo collage. Using our system, users can view a representative photograph as a collage of photographs associated with a certain event and access each of photographs individually. To implement this, we employ centroidal Voronoi diagram to obtain an even distribution of tiles, and use the sites as the location of tiles. We use the edge avoidance technique to prevent tiles from being located across the edges. To obtain the direction of tiles that follow near a strong edge, we employ the Edge tangent Flow field and use the field as the directions of tiles. Finally, we search for photographs that best match the tiles calculated above by using a thumbnail difference metric

Quantitative local probing of polarization with application on HfO 2 ‐based thin films

Owing to their switchable spontaneous polarization, ferroelectric materials have been applied in various fields, such as information technologies, actuators, and sensors. In the last decade, as the characteristic sizes of both devices and materials have decreased significantly below the nanoscale, the development of appropriate characterization tools became essential. Recently, a technique based on conductive atomic force microscopy (AFM), called AFM‐positive‐up‐negative‐down (PUND), is employed for the direct measurement of ferroelectric polarization under the AFM tip. However, the main limitation of AFM‐PUND is the low frequency (i.e., on the order of a few hertz) that is used to initiate ferroelectric hysteresis. A significantly higher frequency is required to increase the signal‐to‐noise ratio and the measurement efficiency. In this study, a novel method based on high‐frequency AFM‐PUND using continuous waveform and simultaneous signal acquisition of the switching current is presented, in which polarization–voltage hysteresis loops are obtained on a high‐polarization BiFeO3 nanocapacitor at frequencies up to 100 kHz. The proposed method is comprehensively evaluated by measuring nanoscale polarization values of the emerging ferroelectric Hf0.5Zr0.5O2 under the AFM tip

DeepDyve: Dynamic Verification for Deep Neural Networks

Deep neural networks (DNNs) have become one of the enabling technologies in many safety-critical applications, e.g., autonomous driving and medical image analysis. DNN systems, however, suffer from various kinds of threats, such as adversarial example attacks and fault injection attacks. While there are many defense methods proposed against maliciously crafted inputs, solutions against faults presented in the DNN system itself (e.g., parameters and calculations) are far less explored. In this paper, we develop a novel lightweight fault-tolerant solution for DNN-based systems, namely DeepDyve, which employs pre-trained neural networks that are far simpler and smaller than the original DNN for dynamic verification. The key to enabling such lightweight checking is that the smaller neural network only needs to produce approximate results for the initial task without sacrificing fault coverage much. We develop efficient and effective architecture and task exploration techniques to achieve optimized risk/overhead trade-off in DeepDyve. Experimental results show that DeepDyve can reduce 90% of the risks at around 10% overhead

The 'Harmonizing Optimal Strategy for Treatment of coronary artery stenosis - sAfety & effectiveneSS of drug-elUting stents & antiplatelet REgimen' (HOST-ASSURE) trial: study protocol for a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Second-generation drug-eluting stents (DES) have raised the bar of clinical performance. These stents are mostly made from cobalt chromium alloy. A newer generation DES has been developed from platinum chromium alloy, but clinical data regarding the efficacy and safety of the platinum chromium-based everolimus-eluting stent (PtCr-EES) is limited, with no comparison data against the cobalt chromium-based zotarolimus-eluting stent (CoCr-ZES). In addition, an antiplatelet regimen is an integral component of medical therapy after percutaneous coronary intervention (PCI). A 1-week duration of doubling the dose of clopidogrel (double-dose antiplatelet therapy (DDAT)) was shown to improve outcome at 1 month compared with conventional dose in acute coronary syndrome (ACS) patients undergoing PCI. However in Asia, including Korea, the addition of cilostazol (triplet antiplatelet therapy (TAT)) is used more commonly than doubling the dose of clopidogrel in high-risk patients.</p> <p>Methods</p> <p>In the 'Harmonizing Optimal Strategy for Treatment of coronary artery stenosis - sAfety & effectiveneSS of drug-elUting stents & antiplatelet REgimen' (HOST-ASSURE) trial, approximately 3,750 patients are being prospectively and randomly assigned in a 2 × 2 factorial design according to the type of stent (PtCr-EES vs CoCr-ZES) and antiplatelet regimen (TAT vs DDAT). The first primary endpoint is target lesion failure at 1 year for the stent comparison, and the second primary endpoint is net clinical outcome at 1 month for comparison of antiplatelet therapy regimen.</p> <p>Discussion</p> <p>The HOST-ASSURE trial is the largest study yet performed to directly compare the efficacy and safety of the PtCr-EES versus CoCr-ZES in an 'all-comers' population. In addition, this study will also compare the clinical outcome of TAT versus DDAT for 1-month post PCI.</p> <p>Trial registration</p> <p>ClincalTrials.gov number <a href="http://www.clinicaltrials.gov/ct2/show/NCT01267734">NCT01267734</a>.</p

Overexpression of defense response genes in transgenic wheat enhances resistance to Fusarium head blight

Fusarium head blight (FHB) of wheat, caused by Fusarium graminearum and other Fusarium species, is a major disease problem for wheat production worldwide. To combat this problem, large-scale breeding efforts have been established. Although progress has been made through standard breeding approaches, the level of resistance attained is insufficient to withstand epidemic conditions. Genetic engineering provides an alternative approach to enhance the level of resistance. Many defense response genes are induced in wheat during F. graminearum infection and may play a role in reducing FHB. The objectives of this study were (1) to develop transgenic wheat overexpressing the defense response genes α-1-purothionin, thaumatin-like protein 1 (tlp-1), and β-1,3-glucanase; and (2) to test the resultant transgenic wheat lines against F. graminearum infection under greenhouse and field conditions. Using the wheat cultivar Bobwhite, we developed one, two, and four lines carrying the α-1-purothionin, tlp-1, and β-1,3-glucanase transgenes, respectively, that had statistically significant reductions in FHB severity in greenhouse evaluations. We tested these seven transgenic lines under field conditions for percent FHB disease severity, deoxynivalenol (DON) mycotoxin accumulation, and percent visually scabby kernels (VSK). Six of the seven lines differed from the nontransgenic parental Bobwhite line for at least one of the disease traits. A β-1,3-glucanase transgenic line had enhanced resistance, showing lower FHB severity, DON concentration, and percent VSK compared to Bobwhite. Taken together, the results showed that overexpression of defense response genes in wheat could enhance the FHB resistance in both greenhouse and field conditions