Feature Fusion Multi-View Hashing Based on Random Kernel Canonical Correlation Analysis

Hashing technology has the advantages of reducing data storage and improving the efficiency of the learning system,making it more and more widely used in image retrieval.Multi-view data describes image information more comprehensively than traditional methods using a single-view.How to use hashing to combine multi-view data for image retrieval is still a challenge.In this paper,a multi-view fusion hashing method based on RKCCA(Random Kernel Canonical Correlation Analysis)is proposed.In order to describe image content more accurately,we use deep learning dense convolutional network feature DenseNet to construct multi-view by combining GIST feature or BoW_SIFT(Bag-of-Words model+SIFT feature)feature.This algorithm uses RKCCA method to fuse multi-view features to construct association features and apply them to image retrieval.The algorithm generates binary hash code with minimal distortion error by designing quantization regularization terms.A large number of experiments on benchmark datasets show that this method is superior to other multi-view hashing methods.

Statistical Modeling of Gate Capacitance Variations Induced by Random Dopants in Nanometer MOSFETs Reserving Correlations

We consider intrinsic gate capacitance variations due to random dopants in the nanometer metal oxide semi- conductor field effect transistor （MOSFET） channel. The variations of total gate capacitance and gate transcapacitances are investigated and the strong correlations between the trans-capacitance variations are discovered. A simple statistical model is proposed for accurately capturing total gate capacitance variability based on the correlations. The model fits very well with the Monte Carlo simulations and the average errors are -0.033% for n-type metal-oxide semiconductor and -0.012% for p-type metal-oxide semiconductor, respectively. Our simulation studies also indicate that, owing to these correlations, the total gate capacitance variability will not dominate in gate capacitance variations.

Progression-free survival as surrogate endpoint in advanced pancreatic cancer: meta-analysis of 30 randomized first-line trials

BACKGROUND：Progression-free survival（PFS）has not been extensively investigated as a surrogate for survival in the firstline treatments of pancreatic cancer.The aim of this review was to evaluate PFS as a potential surrogate endpoint for overall survival（OS）in advanced pancreatic cancer in trials comparing poly-chemotherapy to gemcitabine alone.DATA SOURCES： A systematic literature search in PubMed, Embase, Web of Science, and the Cochrane Central Register of Controlled Trials was conducted. The key words included randomized trial, first-line chemotherapy, pancreatic cancer, gemcitabine and poly-chemotherapy. Adjusted weighted linear regression was used to calculate Rs （Spearman＇s rank-order correlation coefficient） between PFS and post-progression survival （PPS） with OS （Rs） and between treatment effects on PFS and OS （RHR）. RESUEFS： A total of 30 trials including 8467 patients met the inclusion criteria. Correlation between the treatment effects on PFS and OS （RHR=0.78） and between the endpoint PFS and OS was high across all studies （Rs=0.75）. The slope of the re- gression line was 0.76±0.26, indicating that an agent produc- ing a 10% risk reduction for PFS will provide a 7.6%±2.6% risk reduction for OS. Correlation between PPS and OS was very strong （Rs=0.71） and accounted for more than 50% of the whole OS variability （R2=0.57）. CONCLUSION： Because of the robust correlation with OS and the potential influence of PPS caused by the second line therapies, it may be justified to consider PFS as a surrogate endpoint in trials evaluating new cytotoxic agents when gemcitabine is the control arm.

Movement Patterns of the Eastern Chipmunk (<i>Tamias striatus</i>) in Four Fragmented Landscapes of Prince Edward Island, Canada

The analysis of animal movement patterns can provide important information on animals’ responses to habitat features. In this study, the movement paths of eastern chipmunks (Tamias striatus) were examined in four landscapes, with different levels of habitat fragmentation, using either fluorescent powdering or spool-and-line tracking. Descriptions of the tree and ground vegetation communities were performed in the vicinity of the trail to obtain information on habitat use and habitat selection. Several key movement variables were calculated, including the total path length, net distance, fractal dimension, and radius of gyration. Despite statistically significant differences in some of the movement metrics between the four landscapes, the overall movement patterns were generically the same for all of chipmunk paths examined in this study. The data were compared to trends expected based on random or correlated random walks, as well as Lévy-walk models. The mean squared net displacement did not support the correlated random walk predictions, except at smaller spatial scales, but overall demonstrated Lévy-like super diffusive behaviour. Lévy-like patterns were also confirmed from the move-length distributions that demonstrated truncated-tail power-law behaviour. Although this would suggest invariance of the movement patterns at all spatial scales studied, fractal analysis revealed at least two transitions in movement patterns at scales of around 2 and 5 m. The transition point at 2 m was negatively correlated with the density of small trees, while the transition at ~5 m was positively correlated with the spatial distribution of large trees. As the habitat-preference data showed that small trees are among the least preferred habitat component, while large trees were among the most preferred habitat, chipmunks are likely to alter their movement behaviour to avoid small trees, and attracted towards large trees possibly to avoid predators. Overall, we determined three principal domains of movement: at smaller spatio-temporal scales, foraging activities dominate and the movement is highly correlated but also random;at intermediate spatial scales, chipmunks may be moving to avoid predators, using different environmental cues, and the movement is more directed (but still influenced by vegetation patterns at intermediate scales);at larger spatio-temporal scales, the movement is dominated by long-range/long-term memory and homing to burrows and other key habitat features, such as food caches, drives more directed movement. The fact that scale-dependent movement mechanisms could give rise to LW patterns is consistent with recent studies.

Enhanced Transport of Overdamped Particles in a Disordered Biased Periodic Potential

This paper considers the diffusive properties of Brownian motion driven by an Ornstein-Uhlenbeck (OU) colored noise in a biased periodic potential corrugated by spatial disorders in the form of zero-mean random correlated potential. Through Langevin Monte-Carlo simulation, a giant enhancement diffusion is observed in a range of bias forces. Then, theoretical analysis based on the trajectory of a particle in the random correlated potential (RCP) is performed to investigate the transport phenomenon of particles. The effective diffusion coefficient is measured by the envelope width of the spatial distribution of the particle, and it becomes wider due to the emergence of the RCP. This is because the roughness of the potential causes a large proportion of the test particles to be locked or trapped. Furthermore, the positive-correlation characteristics of the OU noise are considered, and the optimal value of the effective diffusion coefficient is discussed.

Experimental arena settings might lead to misinterpretation of movement properties

Movement is an important animal behavior contributing to reproduction and survival.Animal movement is often examined in arenas or enclosures under laboratory conditions.We used the red flour beetle(Tribolium castaneum)to examine here the effect of the arena size,shape,number of barriers,access to the arena's center,and illumination on six movement properties.We demonstrate great differences among arenas.For example,the beetles moved over longer distances in clear arenas than in obstructed ones.Movement along the arena's perimeter was greater in smaller arenas than in larger ones.Movement was more directional in round arenas than in rectangular ones.In general,the beetles stopped moving closer to the perimeter and closer to corners(in the square and rectangular arenas)than expected by chance.In some cases,the arena properties interacted with the beetle sex to affect several movement properties.All these suggest that arena properties might also interact with experimental manipulations to affect the outcome of studies and lead to results specific to the arena used.In other words,instead of examining animal movement,we in fact examine the animal interaction with the arena structure.Caution is therefore advised in interpreting the results of studies on movement in arenas under laboratory conditions and we recommend paying attention also to barriers or obstacles in field experiments.For instance,movement along the arena's perimeter is often interpreted as centrophobism or thigmotaxis but the results here show that such movement is arena dependent.

Laws of Large Numbers of Negatively Correlated Random Variables for Capacities

Our aim is to present some limit theorems for capacities. We consider a sequence of pairwise negatively correlated random variables. We obtain laws of large numbers for upper probabilities and 2-alternating capacities, using some results in the classical probability theory and a non-additive version of Chebyshev＇s inequality and Boral-Contelli lemma for capacities.

A hierarchical path-segmentation movement ecology framework

This paper lays out a hierarchical,appropriate-complexity framework for conceptualizing movement-path segments at different spatiotemporal scales in a way that facilitates comparative analyses and bridges behavior and mathematical concepts.It then outlines a process for generating a multimode,multiscale stochastic simulation model that can be used to test animal movement hypotheses and make predictions of movement responses to management and global change.Many methods for analyzing movement data begin by generating step-length(SL)and turning-angle(TA)distributions from relocation time-series data,some of which are linked to ecological,landscape,and environmental covariates.The frequency at which these data are collected may vary from sub-seconds to several hours.The kinds of questions that may be asked of these data,however,are very much scale dependent.The hierarchical path-segmentation(HPS)framework presented here clarifies how the scale at which SL and TA data are collected relates to other sub-and super-diel scales.Difficulties arise because the information contained in SL and TA time series are often not directly relatable to the physiological,ecological,and sociological factors that drive the structure of movement paths at longer scales.These difficulties are overcome by anchoring the classification of movement types around the concept of fixed-period(24 h)diel activity routines and providing a bridge between behavioral/ecological and stochastic-walk concepts(means,variances,correlations,individual-state and local environmental covariates).This bridge is achieved through the generation of relatively short segments conceived as characteristic sequences of fundamental movement elements.These short segments are then used to characterize longer canonical-activity-mode segments that emerge through movement at behaviorally relevant sub-diel scales.HPS thus provides a novel system for integrating sub-minute movement sequences into canonical activity modes(CAMs)that,in turn,can be strung together into various types of diel activity routines(DARs).These DARs both vary among individuals within a given day,and for any given individual across time and under the influence of landscape factors.An understanding of how DARs are influenced by environmental inputs will help us predict the response of supra-diel lifetime movement phases(LiMPs)of individuals,as well as their complete lifetime tracks(LiTs),to anthropogenically induced global change.