Boundaries of Disk-like Self-affine Tiles

Let $T:= T(A, {\mathcal D})$ be a disk-like self-affine tile generated by an integral expanding matrix $A$ and a consecutive collinear digit set ${\mathcal D}$, and let $f(x)=x^{2}+px+q$ be the characteristic polynomial of $A$. In the paper, we identify the boundary $\partial T$ with a sofic system by constructing a neighbor graph and derive equivalent conditions for the pair $(A,{\mathcal D})$ to be a number system. Moreover, by using the graph-directed construction and a device of pseudo-norm $\omega$, we find the generalized Hausdorff dimension $\dim_H^{\omega} (\partial T)=2\log \rho(M)/\log |q|$ where $\rho(M)$ is the spectral radius of certain contact matrix $M$. Especially, when $A$ is a similarity, we obtain the standard Hausdorff dimension $\dim_H (\partial T)=2\log \rho/\log |q|$ where $\rho$ is the largest positive zero of the cubic polynomial $x^{3}-(|p|-1)x^{2}-(|q|-|p|)x-|q|$, which is simpler than the known result.Comment: 26 pages, 11 figure

Antioxidant treatment enhances human mesenchymal stem cell anti-stress ability and therapeutic efficacy in an acute liver failure model

published_or_final_versio

In situ evidence for the structure of the magnetic null in a 3D reconnection event in the Earth's magnetotail

Magnetic reconnection is one of the most important processes in astrophysical, space and laboratory plasmas. Identifying the structure around the point at which the magnetic field lines break and subsequently reform, known as the magnetic null point, is crucial to improving our understanding reconnection. But owing to the inherently three-dimensional nature of this process, magnetic nulls are only detectable through measurements obtained simultaneously from at least four points in space. Using data collected by the four spacecraft of the Cluster constellation as they traversed a diffusion region in the Earth's magnetotail on 15 September, 2001, we report here the first in situ evidence for the structure of an isolated magnetic null. The results indicate that it has a positive-spiral structure whose spatial extent is of the same order as the local ion inertial length scale, suggesting that the Hall effect could play an important role in 3D reconnection dynamics.Comment: 14 pages, 4 figure

Lineage Divergence and Historical Gene Flow in the Chinese Horseshoe Bat (Rhinolophus sinicus)

PMCID: PMC3581519This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Realistic Standard Model Fermion Mass Relations in Generalized Minimal Supergravity (GmSUGRA)

Grand Unified Theories (GUTs) usually predict wrong Standard Model (SM) fermion mass relation m_e/m_{\mu} = m_d/m_s toward low energies. To solve this problem, we consider the Generalized Minimal Supergravity (GmSUGRA) models, which are GUTs with gravity mediated supersymmetry breaking and higher dimensional operators. Introducing non-renormalizable terms in the super- and K\"ahler potentials, we can obtain the correct SM fermion mass relations in the SU(5) model with GUT Higgs fields in the {\bf 24} and {\bf 75} representations, and in the SO(10) model. In the latter case the gauge symmetry is broken down to SU(3)_C X SU(2)_L X SU(2)_R X U(1)_{B-L}, to flipped SU(5)X U(1)_X, or to SU(3)_C X SU(2)_L X U(1)_1 X U(1)_2. Especially, for the first time we generate the realistic SM fermion mass relation in GUTs by considering the high-dimensional operators in the K\"ahler potential.Comment: JHEP style, 29 pages, no figure,references adde

Towards Intelligent Crowd Behavior Understanding through the STFD Descriptor Exploration

Realizing the automated and online detection of crowd anomalies from surveillance CCTVs is a research-intensive and application-demanding task. This research proposes a novel technique for detecting crowd abnormalities through analyzing the spatial and temporal features of input video signals. This integrated solution defines an image descriptor (named spatio-temporal feature descriptor - STFD) that reflects the global motion information of crowds over time. A CNN has then been adopted to classify dominant or large-scale crowd abnormal behaviors. The work reported has focused on: 1) detecting moving objects in online (or near real-time) manner through spatio-temporal segmentations of crowds that is defined by the similarity of group trajectory structures in temporal space and the foreground blocks based on Gaussian Mixture Model (GMM) in spatial space; 2) dividing multiple clustered groups based on the spectral clustering method by considering image pixels from spatio-temporal segmentation regions as dynamic particles; 3) generating the STFD descriptor instances by calculating the attributes (i.e., collectiveness, stability, conflict and crowd density) of particles in the corresponding groups; 4) inputting generated STFD descriptor instances into the devised convolutional neural network (CNN) to detect suspicious crowd behaviors. The test and evaluation of the devised models and techniques have selected the PETS database as the primary experimental data sets. Results against benchmarking models and systems have shown promising advancements of this novel approach in terms of accuracy and efficiency for detecting crowd anomalies

Towards Intelligent Crowd Behavior Understanding through the STFD Descriptor Exploration

Realizing the automated and online detection of crowd anomalies from surveillance CCTVs is a research-intensive and application-demanding task. This research proposes a novel technique for detecting crowd abnormalities through analyzing the spatial and temporal features of input video signals. This integrated solution defines an image descriptor (named spatio-temporal feature descriptor - STFD) that reflects the global motion information of crowds over time. A CNN has then been adopted to classify dominant or large-scale crowd abnormal behaviors. The work reported has focused on: 1) detecting moving objects in online (or near real-time) manner through spatio-temporal segmentations of crowds that is defined by the similarity of group trajectory structures in temporal space and the foreground blocks based on Gaussian Mixture Model (GMM) in spatial space; 2) dividing multiple clustered groups based on the spectral clustering method by considering image pixels from spatio-temporal segmentation regions as dynamic particles; 3) generating the STFD descriptor instances by calculating the attributes (i.e., collectiveness, stability, conflict and crowd density) of particles in the corresponding groups; 4) inputting generated STFD descriptor instances into the devised convolutional neural network (CNN) to detect suspicious crowd behaviors. The test and evaluation of the devised models and techniques have selected the PETS database as the primary experimental data sets. Results against benchmarking models and systems have shown promising advancements of this novel approach in terms of accuracy and efficiency for detecting crowd anomalies

Two loop electroweak corrections to Bˉ→Xsγ\bar B\rightarrow X_s\gamma and Bs0→μ+μ−B_s^0\rightarrow \mu^+\mu^- in the B-LSSM

The rare decays $\bar B\rightarrow X_s\gamma$ and $B_s^0\rightarrow \mu^+\mu^-$ are important to research new physics beyond standard model. In this work, we investigate two loop electroweak corrections to $\bar B\rightarrow X_s\gamma$ and $B_s^0\rightarrow \mu^+\mu^-$ in the minimal supersymmetric extension of the SM with local $B-L$ gauge symmetry (B-LSSM), under a minimal flavor violating assumption for the soft breaking terms. In this framework, new particles and new definition of squarks can affect the theoretical predictions of these two processes, with respect to the MSSM. Considering the constraints from updated experimental data, the numerical results show that the B-LSSM can fit the experimental data for the branching ratios of $\bar B\rightarrow X_s\gamma$ and $B_s^0\rightarrow \mu^+\mu^-$. The results of the rare decays also further constrain the parameter space of the B-LSSM.Comment: 33 pages, 9 figures, Published in EPJ

Vector assembly of colloids on monolayer substrates

The key to spontaneous and directed assembly is to encode the desired assembly information to building blocks in a programmable and efficient way. In computer graphics, raster graphics encodes images on a single-pixel level, conferring fine details at the expense of large file sizes, whereas vector graphics encrypts shape information into vectors that allow small file sizes and operational transformations. Here, we adapt this raster/vector concept to a 2D colloidal system and realize 'vector assembly' by manipulating particles on a colloidal monolayer substrate with optical tweezers. In contrast to raster assembly that assigns optical tweezers to each particle, vector assembly requires a minimal number of optical tweezers that allow operations like chain elongation and shortening. This vector approach enables simple uniform particles to form a vast collection of colloidal arenes and colloidenes, the spontaneous dissociation of which is achieved with precision and stage-by-stage complexity by simply removing the optical tweezers

Neurogenic inflammation after traumatic brain injury and its potentiation of classical inflammation

Background: The neuroinflammatory response following traumatic brain injury (TBI) is known to be a key secondary injury factor that can drive ongoing neuronal injury. Despite this, treatments that have targeted aspects of the inflammatory pathway have not shown significant efficacy in clinical trials. Main body: We suggest that this may be because classical inflammation only represents part of the story, with activation of neurogenic inflammation potentially one of the key initiating inflammatory events following TBI. Indeed, evidence suggests that the transient receptor potential cation channels (TRP channels), TRPV1 and TRPA1, are polymodal receptors that are activated by a variety of stimuli associated with TBI, including mechanical shear stress, leading to the release of neuropeptides such as substance P (SP). SP augments many aspects of the classical inflammatory response via activation of microglia and astrocytes, degranulation of mast cells, and promoting leukocyte migration. Furthermore, SP may initiate the earliest changes seen in blood-brain barrier (BBB) permeability, namely the increased transcellular transport of plasma proteins via activation of caveolae. This is in line with reports that alterations in transcellular transport are seen first following TBI, prior to decreases in expression of tight-junction proteins such as claudin-5 and occludin. Indeed, the receptor for SP, the tachykinin NK1 receptor, is found in caveolae and its activation following TBI may allow influx of albumin and other plasma proteins which directly augment the inflammatory response by activating astrocytes and microglia. Conclusions: As such, the neurogenic inflammatory response can exacerbate classical inflammation via a positive feedback loop, with classical inflammatory mediators such as bradykinin and prostaglandins then further stimulating TRP receptors. Accordingly, complete inhibition of neuroinflammation following TBI may require the inhibition of both classical and neurogenic inflammatory pathways.Frances Corrigan, Kimberley A. Mander, Anna V. Leonard and Robert Vin