UAV swarm attack: protection system alternatives for Destroyers

Systems Engineering Project ReportThe Navy needs to protect Destroyers (DDGs) from Unmanned Aerial Vehicle (UAV) attacks. The team, focusing on improving the DDG’s defenses against small radar cross section UAVs making suicide attacks, established a DRM, identified current capability gaps, established a functional flow, created requirements, modeled the DDG’s current sensing and engagement capabilities in Microsoft Excel, and used Monte Carlo analysis of 500 simulation runs to determine that four out of eight incoming IED UAVs are likely to hit the ship. Sensitivity analysis showed that improving weapon systems is more effec-tive than improving sensor systems, inspiring the generation of alternatives for improving UAV defense. For the eight feasible alternatives the team estimated cost, assessed risk in accordance with the requirements, simulated performance against the eight incoming UAVs, and performed cost benefit analysis. Adding CIWS mounts is the most cost effec-tive alternative, reducing the average number of UAV hits from a baseline of 3.82 to 2.50, costing $816M to equip the 62-DDG fleet for a 12-year life cycle. Combining that with upgraded EW capabilities to jam remote-controlled UAVs reduces the hits to 1.56 for$1844M, and combining those with decoy launchers to defeat the radar-seeking Har-py UAVs reduces the hits to 1.12 for $2862M.http://archive.org/details/uavswarmttackpro1094528669Approved for public release; distribution is unlimited.Approved for public release; distribution is unlimited

Prospective evaluation of GeneXpert for the diagnosis of HIV- negative pediatric TB cases

Background The GeneXpertMTB/RIF (Xpert) assay is now recommended by WHO for diagnosis of tuberculosis (TB) in children but evaluation data is limited. Methods One hundred and fifty consecutive HIV negative children (<15 years of age) presenting with suspected TB were enrolled at a TB referral hospital in Ho Chi Minh City, Vietnam. 302 samples including sputum (n = 79), gastric fluid (n = 215), CSF (n = 3), pleural fluid (n = 4) and cervical lymphadenopathic pus (n = 1) were tested by smear, automated liquid culture (Bactec MGIT) and Xpert. Patients were classified retrospectively using the standardised case definition into confirmed, probable, possible, TB unlikely or not TB categories. Test accuracy was evaluated against 2 gold standards: [1] clinical (confirmed, probable and possible TB) and [2] ‘confirmed TB’ alone. Results The median age of participants was 18 months [IQR 5–170]. When test results were aggregated by patient, the sensitivity of smear, Xpert and MGIT against clinical diagnosis as the gold standard were 9.2% (n = 12/131) [95%CI 4.2; 14.1], 20.6% (n = 27/131) [95%CI 13.7; 27.5] and 29.0% (n = 38/131) [21.2;36.8], respectively. Specificity 100% (n = 19/19), 94.7% (n = 18/19), 94.7% (n = 18/19), respectively. Xpert was more sensitive than smear (P = <0.001) and less sensitive than MGIT (P = 0.002). Conclusions The systematic use of Xpert will increase early TB case confirmation in children and represents a major advance but sensitivity of all tests remains unacceptably low. Improved rapid diagnostic tests and algorithm approaches for pediatric TB are still an urgent research priority

Compositional Verification of Heap-Manipulating Programs through Property-Guided Learning

Analyzing and verifying heap-manipulating programs automatically is challenging. A key for fighting the complexity is to develop compositional methods. For instance, many existing verifiers for heap-manipulating programs require user-provided specification for each function in the program in order to decompose the verification problem. The requirement, however, often hinders the users from applying such tools. To overcome the issue, we propose to automatically learn heap-related program invariants in a property-guided way for each function call. The invariants are learned based on the memory graphs observed during test execution and improved through memory graph mutation. We implemented a prototype of our approach and integrated it with two existing program verifiers. The experimental results show that our approach enhances existing verifiers effectively in automatically verifying complex heap-manipulating programs with multiple function calls

Adaptation des composants centrée sur l'utilisation

Avec la notion de composant logiciel, la démarche de conception d'applications informatiques a vu apparaître une alternative intéressante à l'approche classique, où le développement est mené selon une approche centralisée. L'idée est en effet de permettre la construction d'applications adaptées aux besoins spécifiques de chaque utilisateur par assemblage de composants préexistants. Néanmoins, le choix de composants prédéfinis, sur étagère, pose le problème de leur adéquation à une utilisation spécifique. Dans ce contexte, la possibilité d'adapter les composants semble cruciale, si l'on souhaite rendre réellement effective l'approche de développement par assemblage de composants. Cette thèse introduit une nouvelle approche de l'adaptation de composants logiciels qui consiste à adapter le composant à ses contextes d'utilisation en se basant sur le point de vue de l'utilisateur. Nous décrivons le profil d'utilisation sous la forme d'un ensemble de triplets dont chacun spécifie les propriétés souhaitées, les réactions correspondantes à traiter dans le cas où une condition n'est pas vérifiée et les échéanciers d'évaluation des propriétés. Nous proposons aussi un service de supervision de composant (SSC) qui repose sur la surveillance de l'état des composants pour obtenir des clichés qui reflètent l'état actuel du composant et les changements récents. Nous définissons également le service de sûreté de service (SSS) qui intercepte les requêtes clientes et qui les délègue vers le composant le plus convenable, tout en gérant l'exécution du composant en fonction du profil d'usage. ABSTRACT : The concept of software component, provides an interesting alternative to the traditional way of designing data-processing applications, where the development is undertaken according to a centralized approach. The idea is indeed to allow the construction of applications adapted to the specific needs for each user by assembling preexistent components. Nevertheless, the choice of off-the-shelf components, raises the problem of their adequacy to a specific use. In this context, the ability to adapt components appears to be crucial, if one wishes to make really effective the approach of development by assembling components. This thesis introduces a new approach of the adaptation of software components which consists in adapting the component to its contexts of use centered on the point of view of the user. We describe a user profile as a set of triples, where each triple specifies the desired properties, the reactions to be run if a condition is not checked and the schedule of evaluation of properties. We propose also a service of supervision of component (SSC) which is based on the monitoring of the state of the components to obtain snapshots which reflect the current state of the component and the recent changes. We also define the service of safety of service (SSS) which intercepts the user requests and delegates them towards the most suitable component, while managing the execution of the component according to the profile of use

Impact of Image Denoising Techniques on CNN-based Liver Vessel Segmentation using Synthesis Low-dose Contrast Enhanced CT Images

Liver vessel segmentation in contrast enhanced CT (CECT) image is relevant for several clinical applications. However, the liver segmentation on noisy images obtain incorrect liver vessel segmentation which may lead to distortion in the simulation of cooling effect near the vessels during the planning. In this study, we present a framework that consists of three well-known and state-of-the-art denoising techniques, Vesssel enhancing diffusion (VED), RED-CNN, and MAP-NN and using a state-of-the-art Convolution Neural Networks (nn-Unet) to segment the liver vessels from the CECT images. The impact of denoising methods on the vessel segmentation are ablated using with multi-level simulated low-dose CECT of the liver. The experiment is carried on CECT images of the liver from two public and one private datasets. We evaluate the performance of the framework using Dice score and sensitivity criteria. Furthermore, we investigate the efficient of denoising on roughness of the surface of liver vessel segmentation. The results from our experiment suggest that denoising methods can improve the liver vessel segmentation quality in the CECT image with high low-dose noise while they degrade the liver vessel segmentation accuracy for low-noise-level CECT images

Association studies between IRF6-TP63 pathway and GREM1 with non-syndromic orofacial clefts among Vietnamese population

愛知学院大学博士（歯学）thesi

S2TD: a Separation Logic Verifier that Supports Reasoning of the Absence and Presence of Bugs

Heap-manipulating programs are known to be challenging to reason about. We present a novel verifier for heap-manipulating programs called S2TD, which encodes programs systematically in the form of Constrained Horn Clauses (CHC) using a novel extension of separation logic (SL) with recursive predicates and dangling predicates. S2TD actively explores cyclic proofs to address the path explosion problem. S2TD differentiates itself from existing CHC-based verifiers by focusing on heap-manipulating programs and employing cyclic proof to efficiently verify or falsify them with counterexamples. Compared with existing SL-based verifiers, S2TD precisely specifies the heaps of de-allocated pointers to avoid false positives in reasoning about the presence of bugs. S2TD has been evaluated using a comprehensive set of benchmark programs from the SV-COMP repository. The results show that S2TD is more effective than state-of-art program verifiers and is more efficient than most of them.Comment: 24 page

Oligodendrocyte Precursor Cells Support Blood-Brain Barrier Integrity via TGF-β Signaling

Trophic coupling between cerebral endothelium and their neighboring cells is required for the development and maintenance of blood-brain barrier (BBB) function. Here we report that oligodendrocyte precursor cells (OPCs) secrete soluble factor TGF-β1 to support BBB integrity. Firstly, we prepared conditioned media from OPC cultures and added them to cerebral endothelial cultures. Our pharmacological experiments showed that OPC-conditioned media increased expressions of tight-junction proteins and decreased in vitro BBB permeability by activating TGB-β-receptor-MEK/ERK signaling pathway. Secondly, our immuno-electron microscopic observation revealed that in neonatal mouse brains, OPCs attach to cerebral endothelial cells via basal lamina. And finally, we developed a novel transgenic mouse line that TGF-β1 is knocked down specifically in OPCs. Neonates of these OPC-specific TGF-β1 deficient mice (OPC-specific TGF-β1 partial KO mice: PdgfraCre/Tgfb1flox/wt mice or OPC-specific TGF-β1 total KO mice: PdgfraCre/Tgfb1flox/flox mice) exhibited cerebral hemorrhage and loss of BBB function. Taken together, our current study demonstrates that OPCs increase BBB tightness by upregulating tight junction proteins via TGF-β signaling. Although astrocytes and pericytes are well-known regulators of BBB maturation and maintenance, these findings indicate that OPCs also play a pivotal role in promoting BBB integrity

Concolic Testing Heap-Manipulating Programs

Concolic testing is a test generation technique which works effectively by integrating random testing generation and symbolic execution. Existing concolic testing engines focus on numeric programs. Heap-manipulating programs make extensive use of complex heap objects like trees and lists. Testing such programs is challenging due to multiple reasons. Firstly, test inputs for such program are required to satisfy non-trivial constraints which must be specified precisely. Secondly, precisely encoding and solving path conditions in such programs are challenging and often expensive. In this work, we propose the first concolic testing engine called CSF for heap-manipulating programs based on separation logic. CSF effectively combines specification-based testing and concolic execution for test input generation. It is evaluated on a set of challenging heap-manipulating programs. The results show that CSF generates valid test inputs with high coverage efficiently. Furthermore, we show that CSF can be potentially used in combination with precondition inference tools to reduce the user effort

Concolic Testing Heap-Manipulating Programs

Concolic testing is a test generation technique which works effectivelyby integrating random testing generation and symbolic execution. Existing concolictesting engines focus on numeric programs. Heap-manipulating programsmake extensive use of complex heap objects like trees and lists. Testing suchprograms is challenging due to multiple reasons. Firstly, test inputs for such programsare required to satisfy non-trivial constraints which must be specified precisely.Secondly, precisely encoding and solving path conditions in such programsare challenging and often expensive. In this work, we propose the firstconcolic testing engine called CSF for heap-manipulating programs based on separation logic. CSF effectively combines specification-based testing and concolic execution for test input generation. It is evaluated on a set of challenging heap-manipulating programs. The results show that CSF generates valid test inputs with high coverage efficiently. Furthermore, we show that CSF can be potentially used in combination with precondition inference tools to reduce the user effort