Study of the Effect of Centrifugal Force on Rotor Blade Icing Process

In view of the rotor icing problems, the influence of centrifugal force on rotor blade icing is investigated. A numerical simulation method of three-dimensional rotor blade icing is presented. Body-fitted grids around the rotor blade are generated using overlapping grid technology and rotor flow field characteristics are obtained by solving N-S equations. According to Eulerian two-phase flow, the droplet trajectories are calculated and droplet impingement characteristics are obtained. The mass and energy conservation equations of ice accretion model are established and a new calculation method of runback water mass based on shear stress and centrifugal force is proposed to simulate water flow and ice shape. The calculation results are compared with available experimental results in order to verify the correctness of the numerical simulation method. The influence of centrifugal force on rotor icing is calculated. The results show that the flow direction and distribution of liquid water on rotor surfaces change under the action of centrifugal force, which lead to the increasing of icing at the stagnation point and the decreasing of icing on both frozen limitations

HKC: An Algorithm to Predict Protein Complexes in Protein-Protein Interaction Networks

With the availability of more and more genome-scale protein-protein interaction (PPI) networks, research interests gradually shift to Systematic Analysis on these large data sets. A key topic is to predict protein complexes in PPI networks by identifying clusters that are densely connected within themselves but sparsely connected with the rest of the network. In this paper, we present a new topology-based algorithm, HKC, to detect protein complexes in genome-scale PPI networks. HKC mainly uses the concepts of highest k-core and cohesion to predict protein complexes by identifying overlapping clusters. The experiments on two data sets and two benchmarks show that our algorithm has relatively high F-measure and exhibits better performance compared with some other methods

A Novel Algorithm for Finding Interspersed Repeat Regions

The analysis of repeats in the DNA sequences is an important subject in bioinformatics. In this paper, we propose a novel projection-assemble algorithm to find unknown interspersed repeats in DNA sequences. The algorithm employs random projection algorithm to obtain a candidate fragment set, and exhaustive search algorithm to search each pair of fragments from the candidate fragment set to find potential linkage, and then assemble them together. The complexity of our projection-assemble algorithm is nearly linear to the length of the genome sequence, and its memory usage is limited by the hardware. We tested our algorithm with both simulated data and real biology data, and the results show that our projection-assemble algorithm is efficient. By means of this algorithm, we found an un-labeled repeat region that occurs five times in Escherichia coli genome, with its length more than 5,000bp, and a mismatch probability less than 4%

Advances in Emotion Recognition: Link to Depressive Disorder

Emotion recognition enables real-time analysis, tagging, and inference of cognitive affective states from human facial expression, speech and tone, body posture and physiological signal, as well as social text on social network platform. Recognition of emotion pattern based on explicit and implicit features extracted through wearable and other devices could be decoded through computational modeling. Meanwhile, emotion recognition and computation are critical to detection and diagnosis of potential patients of mood disorder. The chapter aims to summarize the main findings in the area of affective recognition and its applications in major depressive disorder (MDD), which have made rapid progress in the last decade

90 K Tl-Ba-Ce-Cu-O superconductor and processes for making same

Describes a high temperature superconductor system having the nominal composition: Tl-Ba-Ce-Cu-O. The high temperature superconductor of the present invention has a transition temperature of about 90 K. Processes for making the high temperature superconductor are also provided

Hydrodynamic Performance of an Asymmetry OWC Device Mounted on a Box-Type Breakwater

To share the construction and maintenance cost, an asymmetric oscillating water column (OWC) device integrated with a pile-fixed box-typed offshore breakwater is considered experimentally and numerically. A fully nonlinear numerical wave tank is established and validated with the open source solver OpenFOAM. The effects of the width and draft of rear box, and the incident wave height on the wave energy conversion efficiency, reflection and transmission coefficients, and energy dissipation coefficient are examined. In addition, the superiority of the present coupling system, compared to the traditional box-type breakwater, is discussed. With well comparisons, the results show that the existence of the rear breakwater is beneficial for the formation of partial standing waves and further wave energy conversion. In the range of wave heights tested, the higher the incident wave height, the larger the energy absorption efficiency except for the short-wave regimes. Moreover, the OWC-breakwater coupling system can obtain a similar wave blocking ability to the traditional one, and simultaneously extract wave energy and decrease wave reflection

Hard No-Box Adversarial Attack on Skeleton-Based Human Action Recognition with Skeleton-Motion-Informed Gradient

Recently, methods for skeleton-based human activity recognition have been shown to be vulnerable to adversarial attacks. However, these attack methods require either the full knowledge of the victim (i.e. white-box attacks), access to training data (i.e. transfer-based attacks) or frequent model queries (i.e. black-box attacks). All their requirements are highly restrictive, raising the question of how detrimental the vulnerability is. In this paper, we show that the vulnerability indeed exists. To this end, we consider a new attack task: the attacker has no access to the victim model or the training data or labels, where we coin the term hard no-box attack. Specifically, we first learn a motion manifold where we define an adversarial loss to compute a new gradient for the attack, named skeleton-motion-informed (SMI) gradient. Our gradient contains information of the motion dynamics, which is different from existing gradient-based attack methods that compute the loss gradient assuming each dimension in the data is independent. The SMI gradient can augment many gradient-based attack methods, leading to a new family of no-box attack methods. Extensive evaluation and comparison show that our method imposes a real threat to existing classifiers. They also show that the SMI gradient improves the transferability and imperceptibility of adversarial samples in both no-box and transfer-based black-box settings.Comment: Camera-ready version for ICCV 202

Longitudinal in vivo Diffusion Tensor Imaging Detects Differential Microstructural Alterations in the Hippocampus of Chronic Social Defeat Stress-Susceptible and Resilient Mice

Background: Microstructural alterations in the hippocampus may underlie stress-related disorders and stress susceptibility. However, whether these alterations are pre-existing stress vulnerability biomarkers or accumulative results of chronic stress remain unclear. Moreover, examining the whole hippocampus as one unit and ignoring the possibility of a lateralized effect of stress may mask some stress effects and contribute to the heterogeneity of previous findings.Methods: After C57BL/6 mice were exposed to a 10-day chronic social defeat stress (CSDS) paradigm, different stress phenotypes, i.e., susceptible (n = 10) and resilient (n = 7) mice, were discriminated by the behavior of the mice in a social interaction test. With in vivo diffusion tensor imaging (DTI) scans that were conducted both before and after the stress paradigm, we evaluated diffusion properties in the left and right, dorsal (dHi) and ventral hippocampus (vHi) of experimental mice.Results: A significantly lower fractional anisotropy (FA) was found in the right vHi of the susceptible mice prior to the CSDS paradigm than that found in the resilient mice, suggesting that pre-existing microstructural abnormalities may result in stress susceptibility. However, no significant group differences were found in the post-stress FA values of any of the hippocampal regions of interest (ROIs). In addition, mean diffusivity (MD) and radial diffusivity (RD) values were found to be significantly greater only in the right dHi of the resilient group compared to those of the susceptible mice. Furthermore, a significant longitudinal decrease was only observed in the right dHi RD value of the susceptible mice. Moreover, the social interaction (SI) ratio was positively related to post-stress left MD, right dHi MD, and right dHi RD values and the longitudinal right dHi MD percent change. Meanwhile, a negative relationship was detected between the SI ratio and bilateral mean of the post-stress left relative to right vHi FA value, highlighting the important role of right hippocampus in stress-resilience phenotype.Conclusion: Our findings demonstrated different longitudinal microstructural alterations in the bilateral dHi and vHi between stress-susceptible and resilient subgroups and indicated a right-sided lateralized stress effect, which may be useful in the diagnosis and prevention of stress-related disorders as well as their intervention