Neutralization of chemokines RANTES and MIG increases virus antigen expression and spinal cord pathology during Theiler's virus infection.

The role of chemokines during some viral infections is unpredictable because the inflammatory response regulated by these molecules can have two, contrasting effects-viral immunity and immunopathologic injury to host tissues. Using Theiler's virus infection of SJL mice as a model of this type of disease, we have investigated the roles of two chemokines-regulated on activation, normal T cell-expressed and secreted (RANTES) chemokine and monokine induced by IFN-gamma (MIG)-by treating mice with antisera that block lymphocyte migration. Control, infected mice showed virus persistence, mild inflammation and a small degree of demyelination in the white matter of the spinal cord at 6 weeks post-infection. Treatment of mice with RANTES antiserum starting at 2 weeks post-infection increased both viral antigen expression and the severity of inflammatory demyelination at 6 weeks post-infection. MIG antiserum increased the spread of virus and the proportion of spinal cord white matter with demyelination. Overall, viral antigen levels correlated strongly with the extent of pathology. At the RNA level, high virus expression was associated with low IL-2 and high IL-10 levels, and RANTES antiserum decreased the IL-2/IL-10 ratio. Our results suggest that RANTES and MIG participate in an immune response that attempts to restrict viral expression while limiting immunopathology and that anti-chemokine treatment poses the risk of exacerbating both conditions in the long term

Continuum modeling of size-segregation and flow in dense, bidisperse granular media: Accounting for segregation driven by both pressure gradients and shear-strain-rate gradients

Dense mixtures of particles of varying size tend to segregate based on size during flow. Granular size-segregation plays an important role in many industrial and geophysical processes, but the development of coupled, continuum models capable of predicting the evolution of segregation dynamics and flow fields in dense granular media across different geometries has remained a longstanding challenge. One reason is because size-segregation stems from two driving forces: (1) pressure gradients and (2) shear-strain-rate gradients. Another reason is due to the challenge of integrating segregation models with rheological constitutive equations for dense granular flow. In this paper, we build upon our prior work, which combined a model for shear-strain-rate-gradient-driven segregation with a nonlocal continuum model for dense granular flow rheology, and append a model for pressure-gradient-driven segregation. We perform discrete element method (DEM) simulations of dense flow of bidisperse granular systems in two flow geometries, in which both segregation driving forces are present: namely, inclined plane flow and planar shear flow with gravity. Steady-state DEM data from inclined plane flow is used to determine the dimensionless material parameters in the pressure-gradient-driven segregation model for both spheres and disks. Then, predictions of the coupled, continuum model accounting for both driving forces are tested against DEM simulation results across different cases of both inclined plane flow and planar shear flow with gravity, while varying parameters such as the size of the flow geometry, the driving conditions of flow, and the initial conditions. Overall, we find that it is crucial to account for both driving forces to capture segregation dynamics in dense, bidisperse granular media across both flow geometries with a single set of parameters.Comment: 25 pages with 9 figure

OCSO: Off-the-cloud service optimization for green efficient service resource utilization

Many efforts have been made in optimizing cloud service resource management for efficient service provision and delivery, yet little research addresses how to consume the provisioned service resources efficiently. Meanwhile, typical existing resource scaling management approaches often rest on single monitor category statistics and are driven by certain threshold algorithms, they usually fail to function effectively in case of dealing with complicated and unpredictable workload patterns. Fundamentally, this is due to the inflexibility of using static monitor, threshold and scaling parameters. This paper presents Off-the-Cloud Service Optimization (OCSO), a novel user-side optimization solution which specifically deals with service resource consumption efficiency from the service consumer perspective. OCSO rests on an intelligent resource scaling algorithm which relies on multiple service monitor metrics plus dynamic threshold and scaling parameters. It can achieve proactive and continuous service optimizations for both real-world IaaS and PaaS services, through OCSO cloud service API. From the two series of experiments conducted over Amazon EC2 and ElasticBeanstalk using OCSO prototype, it is demonstrated that the proposed approach can make significant improvement over Amazon native automated service provision and scaling options, regardless of scaling up/down or in/out

Launching Return-Oriented Programming Attacks against Randomized Relocatable Executables

Abstract—Since the day it was proposed, return-oriented programming has shown to be an effective and powerful attack technique against the write or execute only (W ⊕ X) protection. However, a general belief in the previous research is, systems deployed with address space randomization where the executables are also randomized at run-time are able to defend against return-oriented programming, as the addresses of all instructions are randomized. In this paper, we show that due to the weakness of current address space randomization technique, there are still ways of launching return-oriented programming attacks against those well-protected systems efficiently. We demonstrate and evaluate our attacks with existing typical web server applications and discuss possible methods of mitigating such threats. Keywords-return-oriented programming; address space randomization; position independent executable; I

An approach to unified cloud service access, manipulation and dynamic orchestration via semantic cloud service operation specification framework

Cloud computing offers various computational resources via convenient on-demand service provision. Currently, heterogeneous services and cloud resources are usually utilized and managed through diverse service portals. This significantly limits the effectiveness and efficiency for tasks implementation. Fundamentally, it is due to the lack of adequate specifications for service concepts, operations and interfaces from diverse cloud service models and types. This paper proposes a service management operation semantic description framework for comprehensive cloud service operation specification. Relying on ontological modelling techniques, cloud service operations are specified via entity classification, attribute assertion, relationship assertion and annotation assertion. Further, the proposed framework benefits from operation reasoning application. It enables intelligent assistances for multiple operation preparation and remote execution tasks. Based on the approach, a cloud service operation ontology and a unified service access and manipulation system prototype are implemented. Extensive experiments are conducted over different cloud service providers and for distinct service models. Obtained results demonstrate that the approach outperforms existing practices by facilitating reliable and effective service access, manipulation and interaction tasks

An agility-oriented and fuzziness-embedded semantic model for collaborative cloud service search, retrieval and recommendation

Cloud computing enables a revolutionary paradigm of consuming ICT services. However, due to the inadequately described service information, users often feel confused while trying to find the optimal services. Although some approaches are proposed to deal with cloud service semantic modelling and recommendation issues, they would only work for certain restricted scenarios in dealing with basic service specifications. Indeed, the missing extent is that most cloud services are "agile" whilst there are many vague service terms and descriptions. This paper proposes an agility-oriented and fuzziness-embedded ontology model, which adopts agility-centric design along with OWL2 (Web Ontology Language) fuzzy extensions. The captured cloud service specifications are maintained in an open and collaborative manner, as the fuzziness in the model accepts rating updates from users on the fly. The model enables comprehensive service specification by capturing cloud concept details and their interactions, even across multiple service categories and abstraction levels. Utilizing the model as a knowledge base, a service recommendation system prototype is developed. Case studies demonstrate that the approach can outperform existing practices by achieving effective service search, retrieval and recommendation outcomes

Numerical investigation on shock train control and applications in a scramjet engine

Different factors which help to control the shock train in the scramjet isolator and combustor were analyzed via numerical investigations, and were applied to a whole scramjet engine in the working environment. A streamline traced Busemann inlet is proposed and simulated along with an isolator. During the combustor design, the influence of boundary layer thickness, slot bleeding, cavity and hydrogen injection position on the basic combustor performance with uniform inlet flow condition are investigated, and it was found that the boundary layer bleeding could prevent the shock train from moving upstream, and the cavity could further enhance the combustion efficiency. By arranging hydrogen injections at certain intervals, it could reduce the combustion back pressure. An improved basic model by integrating the aforementioned advantages is then numerically studied. The results have shown that the improved combustor model contained a section of shock train which can reduce the loads on the isolator. Another model with bleeding slots in the isolator is also found able to raise the maximum chemical equivalence ratio from 0.7 to 1, but unfortunately it comes with undesirable combustion efficiency decrease

The Invasion and Metastasis Promotion Role of CD97 Small Isoform in Gastric Carcinoma

CD97 is over-expressed in the majority of gastric adenocarcinomas and is associated with its dedifferentiation and aggressiveness. Our previous results demonstrated that out of three CD97 isoforms tested, only the small one was able to promote increased invasiveness in vitro. Based on these data we further aimed to investigate the role of CD97 small isoform in gastric cancer progression in vivo by employing the cells with a stable CD97 small isoform knock-down and an orthotopic gastric cancer mouse model. We could demonstrate that the knock down of CD97/EGF1,2,5, led to a significant decrease in the number of cells penetrating the gelatin coated membrane as compared with control cells. In the gastric cancer mouse model, both the hypodermic and the orthotopic yielded tumor masses of the CD97/EGF1,2,5kd group and were significantly smaller than the control. Metastatic tumor cell number in early metastatic regional lymph nodes on post-operative day 42 was distinctly decreased in the CD97/EGF1,2,5kd group as compared with the SGC-NS group, and was accompanied with the downregulation of CD44, VEGFR, CD31 and CD97. We concluded in this study that CD97 small isoform not only supported gastric cancer local growth, but also promoted metastatic spread in orthotopically implanted mouse model suggesting involvement of the CD97 small isoform in the preparation of (pre)metastatic niche