One-Shot Any-Scene Crowd Counting With Local-to-Global Guidance.

Due to different installation angles, heights, and positions of the camera installation in real-world scenes, it is difficult for crowd counting models to work in unseen surveillance scenes. In this paper, we are interested in accurate crowd counting based on the data collected by any surveillance camera, that is to count the crowd from any scene given only one annotated image from that scene. To this end, we firstly pose crowd counting as a one-shot learning task. Through the metric-learning, we propose a simple yet effective method that firstly estimates crowd characteristics and then transfers them to guide the model to count the crowd. Specifically, to fully capture these crowd characteristics of the target scene, we devise the Multi-Prototype Learner to learn the prototypes of foreground and density from the limited support image using the Expectation-Maximization algorithm. To learn the adaptation capability for any unseen scene, estimated multi prototypes are proposed to guide the crowd counting of query images in a local-to-global way. CNN is utilized to activate the local features. And transformer is introduced to correlate global features. Extensive experiments on three surveillance datasets suggest that our method outperforms the SOTA methods in the few-shot crowd counting.

The Information Geometry of Sensor Configuration.

In problems of parameter estimation from sensor data, the Fisher information provides a measure of the performance of the sensor; effectively, in an infinitesimal sense, how much information about the parameters can be obtained from the measurements. From the geometric viewpoint, it is a Riemannian metric on the manifold of parameters of the observed system. In this paper, we consider the case of parameterized sensors and answer the question, "How best to reconfigure a sensor (vary the parameters of the sensor) to optimize the information collected?" A change in the sensor parameters results in a corresponding change to the metric. We show that the change in information due to reconfiguration exactly corresponds to the natural metric on the infinite-dimensional space of Riemannian metrics on the parameter manifold, restricted to finite-dimensional sub-manifold determined by the sensor parameters. The distance measure on this configuration manifold is shown to provide optimal, dynamic sensor reconfiguration based on an information criterion. Geodesics on the configuration manifold are shown to optimize the information gain but only if the change is made at a certain rate. An example of configuring two bearings-only sensors to optimally locate a target is developed in detail to illustrate the mathematical machinery, with Fast Marching methods employed to efficiently calculate the geodesics and illustrate the practicality of using this approach.

MiR-191 downregulation protects against isoflurane-induced neurotoxicity through targeting BDNF.

BACKGROUND: Isoflurane inhalation can cause nerve damage, and miR-191 is abnormally expressed in nerve crush injuries. This study aimed to explore the effect of miR-191 on isoflurane-induced cognition impairment and neurotoxicity in vivo and in vitro, as well as its potential mechanism. METHODS: Sprague-Dawley male rats and primary hippocampal neurons were applied and exposed to 2% isoflurane. The level of miR-191 was regulated both in vitro and in vivo to investigate the role of miR-191 in isoflurane-induced neurotoxicity. Morris water maze assay was used to evaluate the neurological function of rats. The level of miR-191 was measured by qRT-PCR. CCK-8 assay and Flow cytometry were applied to detect the cell viability and apoptosis. Dual luciferase reporter gene detection was used for the target gene analysis. RESULTS: miR-191 was up-regulated in the hippocampal tissues of rats exposed to isoflurane. Downregulation of miR-191 ameliorated isoflurane-induced cognition impairment, including the increase of the neurological score and the escape latency, and the decrease of the time spent in the original quadrant for the rats exposed to isoflurane. Isoflurane exposure inhibited hippocampal neuron viability and promoted cell apoptosis, which was reversed by down-regulation of miR-191. BDNF is a target gene of miR-191. CONCLUSIONS: Isoflurane causes some neurotoxic effect which is mediated through miR-191 abnormal expression targeting BDNF. Downregulation of miR-191 has a protective role against isoflurane-induced neurotoxicity, regulates the vitality and slows down neuronal cell apoptosis.

Effects of atorvastatin on pharmacokinetics of amlodipine in rats and its potential mechanism.

Atorvastatin combined with amlodipine (ALDP) can efficiently treat the hypertension with coronary heart disease. However, the drug-drug interaction between atorvastatin and ALDP are still unknown.This study investigates the effects of atorvastatin on the pharmacokinetics of ALDP in rats and clarifies its main mechanism.The pharmacokinetic profiles of oral administration of ALDP (1 mg/kg) in Sprague-Dawley rats, with or without pretreatment of atorvastatin (1.5 mg/kg/d for 7 d) were investigated. The effects of atorvastatin on the metabolism of ALDP were also investigated using rat liver microsomes.The results showed that atorvastatin could significantly increase the peak plasma concentration (from 18.28 ± 2.65 to 24.13 ± 1.96 ng/mL) and decrease the oral clearance (from 4.57 ± 1.15 to 1.79 ± 0.28 L/h/kg) of ALDP. In the rat liver microsome systems, the intrinsic clearance rate of ALDP was decreased by the pretreatment with atorvastatin (39.26 ± 2.1 vs. 33.24 ± 3.3 µL/min/mg protein).Those results indicated that atorvastatin could significantly affect the pharmacokinetic of ALDP, via inhibiting the metabolism of ALDP in rats.

Terrain constrained path planning for long-haul cables.

A method for path planning for a long-haul submarine optical fiber cable connecting two locations on the surface of the Earth is presented. Previous work on path planning takes account of the laying cost of the cable including material, labor, and its survivability, with consideration of risk of future cable break arising from laying of the cable in sensitive and risky areas, such as, in particular, earthquake prone areas. Previous work has also taken account of variation in the cost per unit length to optimize shielding (and associated increased costs) in higher risk areas. The key novelty here is to take account of the important requirement to reduce the likelihood of capsize of a remotely operated cable laying vehicle as it buries the cable in an uneven terrain. This instability risk depends on the direction of the path and slope of the terrain and is included here in the laying cost. Minimization of the cable laying cost and the expected number of potential cable repairs are the two objectives used to formulate the multi-objective optimal control problem. Using a Pareto approach, we solve the problem via dynamic programming and a computationally efficient algorithm based on the Ordered Upwind Method. Numerical results are consistent with an intuitive assessment of path quality, e.g., we can observe that the algorithm avoids high slope areas when better solutions are clearly available. Pareto optimal solutions and an approximate Pareto front are obtained to provide insight and guidance for cable path design that considers trade-offs between cost effectiveness (that includes consideration for stability of the remotely operated cable laying vehicle) and seismic resilience.

An Iterative Nonlinear Filter Using Variational Bayesian Optimization.

We propose an iterative nonlinear estimator based on the technique of variational Bayesian optimization. The posterior distribution of the underlying system state is approximated by a solvable variational distribution approached iteratively using evidence lower bound optimization subject to a minimal weighted Kullback-Leibler divergence, where a penalty factor is considered to adjust the step size of the iteration. Based on linearization, the iterative nonlinear filter is derived in a closed-form. The performance of the proposed algorithm is compared with several nonlinear filters in the literature using simulated target tracking examples.

Video Super-Resolution Using Non-Simultaneous Fully Recurrent Convolutional Network.

Video super-resolution (SR) aims at restoring fine details and enhancing visual experience for low-resolution (LR) videos. In this paper, we propose a very deep non-simultaneous fully recurrent convolutional network for video SR. To make full use of temporal information, we employ motion compensation, very deep fully recurrent convolutional layers and late fusion in our system. Residual connection is also employed in our recurrent structure for more accurate SR. Finally a new model ensemble strategy is used to combine our method with single-image SR method. Experimental results demonstrate that the proposed method is better than state-of-the-art SR methods on quantitative visual quality assessment.

Effects of diclofenac on the pharmacokinetics of celastrol in rats and its transport.

CONTEXT: Diclofenac and celastrol are always used together for the treatment of rheumatoid arthritis; the herb-drug interaction potential between diclofenac and celastrol is still unknown. OBJECTIVE: This study investigates the effects of diclofenac on the pharmacokinetics of celastrol in rats. MATERIALS AND METHODS: Twelve male Sprague-Dawley rats were divided into two groups and received celastrol (1 mg/kg) or both celastrol (1 mg/kg) and diclofenac (10 mg/kg) by oral gavage, and blood samples were collected via the oculi chorioideae vein and determined using the LC-MS method developed in this study. Additionally, the effects of diclofenac on the transport of celastrol were investigated using a Caco-2 cell transwell model. RESULTS: Diclofenac could significantly (p < 0.05) decrease the Cmax (from 66.93 ± 10.28 to 41.25 ± 8.06 ng/mL) and AUC0-t (from 765.84 ± 163.61 to 451.33 ± 110.88 µg × h/L) of celastrol in rats. The efflux ratio of celastrol increased significantly (p < 0.05) from 3.12 to 4.55 with the treatment of diclofenac. DISCUSSION AND CONCLUSION: These results indicated that diclofenac could decrease the system exposure of celastrol in rats when they are co-administered, and these effects might be exerted via decreasing its absorption in intestine.

Resveratrol ameliorates hyperglycemia-induced renal tubular oxidative stress damage via modulating the SIRT1/FOXO3a pathway.

AIMS: Oxidative stress plays an important role in the development and progression of diabetic nephropathy (DN). We aimed to investigate if resveratrol (RSV) could ameliorate hyperglycemia-induced oxidative stress in renal tubules via modulating the SIRT1/FOXO3a pathway. METHODS: The effects of RSV on diabetes rats were assessed by periodic acid-Schiff, Masson staining, immunohistochemistry, and western blot analyses. Additionally, oxidative indicators (such as catalase, superoxide dismutase, reactive oxygen species, and malondialdehyde), the deacetylase activity of SIRT1 and protein expressions of SIRT1, FOXO3a, and acetylated-FOXO3a were measured. These indicators were similarly evaluated in an in vitro study. Furthermore, the silencing of SIRT1 was used to confirm its role in the resistance to oxidative stress and the relationship between SIRT1 and FOXO3a in vitro. RESULTS: After 16weeks of RSV treatment, the renal function and glomerulosclerosis of rats with DN was dramatically ameliorated. RSV treatment increased SIRT1 deacetylase activity, subsequently decreasing the expression of acetylated-FOXO3a and inhibiting the oxidative stress caused by hyperglycemia both in vivo and in vitro. The silencing of SIRT1 in HK-2 cells aggravated the high glucose-induced oxidative stress and overexpression of acetylated-FOXO3a; RSV treatment failed to protect against these effects. CONCLUSIONS: RSV modulates the SIRT1/FOXO3a pathway by increasing SIRT1 deacetylase activity, subsequently ameliorating hyperglycemia-induced renal tubular oxidative stress damage. This mechanism provides the basis for a new approach to developing an effective DN treatment, which is of great clinical significance for reducing the morbidity and mortality associated with DN.

Interferon-γ inhibits nonopsonized phagocytosis of macrophages via an mTORC1-c/EBPß pathway.

Bacterial infection often follows virus infection due to pulmonary interferon-γ (IFN-γ) production during virus infection, which down-regulates macrophage phagocytosis. The molecular mechanisms for this process are still poorly understood. In the present study, IFN-γ treatment significantly inhibited the ability of mouse macrophages to phagocytize nonopsonized chicken red blood cells (cRBCs), bacteria and beads in vitro, while it enhanced IgG- and complement-opsonized phagocytosis. IFN-γ treatment decreased the expression of MARCO (macrophage receptor with collagenous structure) in macrophages. Macrophages showed lower binding to and phagocytic ability of cRBCs when MARCO was blocked with antibody. In addition, IFN-γ induced high activity of mTOR (mammalian target of rapamycin) and decreased the expression of c/EBPß (CCAAT enhancer-binding protein ß) in macrophages. Rapamycin, a specific mTOR inhibitor, significantly reversed the inhibitory effect of IFN-γ on nonopsonized phagocytosis of macrophages and restored c/EBPß and MARCO expression. Biochemical assays showed that c/EBPß directly bound to the MARCO gene promoter. Rapamycin significantly hampered the viral-bacterial synergy and protected influenza-infected mice from subsequent bacterial infection. Thus, IFN-γ inhibited the nonopsonized phagocytosis of macrophages through the mTOR-c/EBPß-MARCO pathway. The present study offered evidence indicating that mTOR may be one of the key target molecules for the prevention of secondary bacterial infection caused by primary virus infection.

A video, text, and speech-driven realistic 3-d virtual head for human-machine interface.

A multiple inputs-driven realistic facial animation system based on 3-D virtual head for human-machine interface is proposed. The system can be driven independently by video, text, and speech, thus can interact with humans through diverse interfaces. The combination of parameterized model and muscular model is used to obtain a tradeoff between computational efficiency and high realism of 3-D facial animation. The online appearance model is used to track 3-D facial motion from video in the framework of particle filtering, and multiple measurements, i.e., pixel color value of input image and Gabor wavelet coefficient of illumination ratio image, are infused to reduce the influence of lighting and person dependence for the construction of online appearance model. The tri-phone model is used to reduce the computational consumption of visual co-articulation in speech synchronized viseme synthesis without sacrificing any performance. The objective and subjective experiments show that the system is suitable for human-machine interaction.

Digital multi-focusing from a single photograph taken with an uncalibrated conventional camera.

The demand to restore all-in-focus images from defocused images and produce photographs focused at different depths is emerging in more and more cases, such as low-end hand-held cameras and surveillance cameras. In this paper, we manage to solve this challenging multi-focusing problem with a single image taken with an uncalibrated conventional camera. Different from all existing multi-focusing approaches, our method does not need to include a deconvolution process, which is quite time-consuming and will cause ringing artifacts in the focused region and low depth-of-field. This paper proposes a novel systematic approach to realize multi-focusing from a single photograph. First of all, with the optical explanation for the local smooth assumption, we present a new point-to-point defocus model. Next, the blur map of the input image, which reflects the amount of defocus blur at each pixel in the image, is estimated by two steps. 1) With the sharp edge prior, a rough blur map is obtained by estimating the blur amount at the edge regions. 2) The guided image filter is applied to propagate the blur value from the edge regions to the whole image by which a refined blur map is obtained. Thus far, we can restore the all-in-focus photograph from a defocused input. To further produce photographs focused at different depths, the depth map from the blur map must be derived. To eliminate the ambiguity over the focal plane, user interaction is introduced and a binary graph cut algorithm is used. So we introduce user interaction and use a binary graph cut algorithm to eliminate the ambiguity over the focal plane. Coupled with the camera parameters, this approach produces images focused at different depths. The performance of this new multi-focusing algorithm is evaluated both objectively and subjectively by various test images. Both results demonstrate that this algorithm produces high quality depth maps and multi-focusing results, outperforming the previous approaches.

Rapid fabrication of micro-nanometric tapered fiber lens and characterization by a novel scanning optical microscope with submicron resolution.

In numerous applications of optical scanning microscopy, a reference tapered fiber lens with high symmetry at sub-wavelength scale remains a challenge. Here, we demonstrate the ability to manufacture it with a wide range of geometry control, either for the length from several hundred nanometers to several hundred microns, or for the curvature radius from several tens of nanometers to several microns on the endface of a single mode fiber. On this basis, a scanning optical microscope has been developed, which allows for fast characterization of various sub-wavelength tapered fiber lenses. Focal position and depth of microlenses with different geometries have been determined to be ranged from several hundreds of nanometers to several microns. FDTD calculations are consistent with experimental results.

Cyclophilin E functions as a negative regulator to influenza virus replication by impairing the formation of the viral ribonucleoprotein complex.

BACKGROUND: The nucleoprotein (NP) of influenza A virus is a multifunctional protein that plays a critical role in the replication and transcription of the viral genome. Therefore, examining host factors that interact with NP may shed light on the mechanism of host restriction barriers and the tissue tropism of influenza A virus. Here, Cyclophilin E (CypE), a member of the peptidyl-propyl cis-trans isomerase (PPIase) family, was found to bind to NP and inhibit viral replication and transcription. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, CypE was found to interact with NP but not with the other components of the viral ribonucleoprotein complex (VRNP): PB1, PB2, and PA. Mutagenesis data revealed that the CypE domain comprised of residues 137-186 is responsible for its binding to NP. Functional analysis results indicated that CypE is a negative regulator in the influenza virus life cycle. Furthermore, knock-down of CypE resulted in increased levels of three types of viral RNA, suggesting that CypE negatively affects viral replication and transcription. Moreover, up-regulation of CypE inhibited the activity of influenza viral polymerase. We determined that the molecular mechanism by which CypE negatively regulates influenza virus replication and transcription is by interfering with NP self-association and the NP-PB1 and NP-PB2 interactions. CONCLUSIONS/SIGNIFICANCE: CypE is a host restriction factor that inhibits the functions of NP, as well as viral replication and transcription, by impairing the formation of the vRNP. The data presented here will help us to better understand the molecular mechanisms of host restriction barriers, host adaptation, and tissue tropism of influenza A virus.

Influenza A virus M1 blocks the classical complement pathway through interacting with C1qA.

The matrix (M1) protein of influenza A virus is a conserved multifunctional protein that plays essential roles in regulating the viral life cycle. This study demonstrated that M1 is able to interact with complement C1qA and plays an important inhibitory function in the classical complement pathway. The N-terminal domain of M1 protein was required for its binding to the globular region of C1qA. As a consequence, M1 blocked the interaction between C1qA and heat-aggregated IgG in vitro and inhibited haemolysis. It was shown that M1 protein prevented the complement-mediated neutralization of influenza virus in vitro. In addition, studies on mice indicated that the administration of M1 could promote a higher virus propagation rate in lung and shortened survival of mice infected with the virus. Taken together, these results suggest strongly that the M1 protein plays a critical role in protecting influenza virus from the host innate immune system.

Cyclophilin A interacts with influenza A virus M1 protein and impairs the early stage of the viral replication.

Influenza A virus matrix protein (M1) is the most abundant conservative protein that regulates the replication, assembly and budding of the viral particles upon infection. Several host cell factors have been determined to interact with M1 possibly in regulating influenza virus replication. By yeast two-hybrid screening, the isomerase cyclophilin A (CypA) was identified to interact with the M1 protein. CypA specifically interacted with M1 both in vitro and in vivo. The mutagenesis results showed CypA bound to the functional middle (M) domain of M1. The depletion of endogenous CypA by RNA interference resulted in the increase of influenza virus infectivity while overexpression of CypA caused decreasing the infectivity in affected cells. The immunofluorescence assays indicated that overexpressed CypA deduced the infectivity and inhibited the translocation of M1 protein into the nucleus while did not affect nucleoprotein entering the nucleus. Further studies indicated that overexpression of CypA significantly increased M1 self-association. Western blot with purified virions confirmed that CypA was encapsidated within the virus particle. These results together indicated that CypA interacted with the M1 protein and affected the early stage of the viral replication.

Attractability and location of equilibrium point of cellular neural networks with time-varying delays.

This paper presents new theoretical results on global exponential stability of cellular neural networks with time-varying delays. The stability conditions depend on external inputs, connection weights and delays of cellular neural networks. Using these results, global exponential stability of cellular neural networks can be derived, and the estimate for location of equilibrium point can also be obtained. Finally, the simulating results demonstrate the validity and feasibility of our proposed approach.