The Hydro-Modeling Platform (HydroMP) - Enabling Cloud-Based Environmental Modeling Using Software-As-A-Service (SaaS) Cloud Computing

Hydro-model has become important tool for water resources management, with higher demand in simulation precision and speed of decision support, models designed for sectoral application becoming outmoded, and original mode that massive schemes are run sequentially cannot meet the real-time requirements, especially with the computation increase by finer discretization granularity and broader research range. Water management organizations are increasingly looking for new generation tools that allow integration across domains, and can provide extensible computing resources to assist their decision making processes. In response to this need, a hydro-modeling platform(HydroMP) based on cloud computing is designed and implemented, which can deployed in distributed HPC Cluster and center HPC Cluster use a resources balancer to manage load balancing. This platform integrates multi models and computing resources (i.e. blade computer) dynamically to assure models integrated in platform get extensible computing capacity. A server, hosting HydroMP Web Service and interfaces, is connected to the HPC Cluster and Internet constituting the gateway for registered users. Any terminal (i.e. decision making system) can reference library and Web service of HydroMP in their systems. Massive modeling schemes can be submitted by different users simultaneously, and terminal can get simulation results from HydroMP real-time. Some key approaches and techniques are utilized including: i) a standard model component wrapper communicating with platform by named pipe have developed. OpenMI-compliant model-components can be integrated to this wrapper; ii) API and Event-Handler interface provided by HPC Server, task scheduler and calculation management table is employed to dispatch computing resource, while controlling multiple concurrent scheme submitting; iii) Interface array(i.e. SchemesSubmit, StatusInquiry, GetResult) in the Web Service is supplied to make terminal communicate with platform; iv) Oracle database is used to manage massive model data, results and model-components. This paper describes the details of design and implementation, and gives a case presentation platform application

CEO’s Communication Styles and their Effect on Organizational Performance

Several studies have highlighted the importance of leadership communication in establishing stakeholder alignment, implementing strategy, and achieving superior organizational performance. In this way, this study investigates the impact of CEO’s communication styles on organizational performance using text-mining approach on CEOs tweets from social media. This study aims to examine the relationship between CEO communication styles and organizational performance. The contribution of our study is three-folded: 1) From a methodological standpoint, we present a model to establish a relationship between CEO communication styles on social media and firm performance. Additionally, we apply text mining to identify communication styles of CEOs. 2) From a performance management, we evaluate organizational performance in three types: Operational, Financial, and Reputational. 3) From a management practice and policy perspective, our study results will help organizations evaluate the CEO candidates from a communication style standpoint

Adversarial erasing attention for person re-identification in camera networks under complex environments

Person re-identification (Re-ID) in camera networks under complex environments has achieved promising performance using deep feature representations. However, most approaches usually ignore to learn features from non-salient parts of pedestrian, which results in an incomplete pedestrian representation. In this paper, we propose a novel person Re-ID method named Adversarial Erasing Attention (AEA) to mine discriminative completed features using an adversarial way. Specifically, the proposed AEA consists of the basic network and the complementary network. On the one hand, original pedestrian images are used to train the basic network in order to extract global and local deep features. On the other hand, to learn features complementary to the basic network, we propose the adversarial erasing operation, that locates non-salient areas with the help of attention map, to generate erased pedestrian images. Then, we utilize them to train the complementary network and adopt the dynamic strategy to match the dynamic status of AEA in the learning process. Hence, the diversity of training samples is enriched and the complementary network could discover new clues when learning deep features. Finally, we combine the features learned from the basic and complementary networks to represent the pedestrian image. Experiments on three databases (Market1501, CUHK03 and DukeMTMC-reID) demonstrate the proposed AEA achieves great performances

Effects of transplantation with bone marrow-derived mesenchymal stem cells modified by Survivin on experimental stroke in rats

<p>Abstract</p> <p>Background</p> <p>This study was performed to determine whether injury induced by cerebral ischemia could be further improved by transplantation with bone marrow-derived mesenchymal stem cells (MSCs) modified by Survivin (SVV).</p> <p>Methods</p> <p>MSCs derived from bone marrow of male Sprague-Dawley rats were infected by the self-inactive lentiviral vector GCFU carrying green fluorescent protein (GFP) gene and SVV recombinant vector (GCFU-SVV). In vitro, vascular endothelial growth factor (VEGF) and basic fibroblast growth factor (bFGF) were detected in infected MSCs supernatants under hypoxic conditions by ELSIA. In vivo, experiments consisted of three groups, one receiving intravenous injection of 500 μl of phosphate-buffered saline (PBS) without cells (control group) and two groups administered the same volume solution with either three million GFP-MSCs (group GFP) or SVV/GFP-MSCs (group SVV). All animals were submitted to 2-hour middle cerebral artery occlusion (MCAO) and then reperfusion. Differentiation and survival of the transplanted MSCs were determined by confocal microscope. Western blot was used to detect the expression of VEGF and bFGF in ischemic tissue. A 2,3,5-triphenyltetrazolium chloride (TTC) staining was used to assess the infarct volume. Evaluation of neurological function was performed using a modified Neurological Severity Score (mNSS).</p> <p>Results</p> <p>In vitro, modification with SVV further increased secretion of VEGF and bFGF under hypoxic condition. In vivo, only very few transplantated cells co-expressed GFP and NeuN. The survival transplanted cells in the group SVV was 1.3-fold at 4 days after transplantation and 3.4-fold higher at 14 days after transplantation, respectively, when compared with group GFP. Expression of VEGF and bFGF in the ischemic tissue were further up-regulated by modification with SVV. Moreover, modification with SVV further reduced the cerebral infarct volume by 5.2% at 4 days after stroke and improved post-stroke neurological function at 14 days after transplantation.</p> <p>Conclusion</p> <p>Modification with SVV could further enhance the therapeutic effects of MSCs possibly through improving the MSCs survival capacity and up-regulating the expression of protective cytokines in the ischemic tissue.</p