Visual Tracking by Sampling in Part Space

In this paper, we present a novel part-based visual tracking method from the perspective of probability sampling. Specifically, we represent the target by a part space with two online learned probabilities to capture the structure of the target. The proposal distribution memorizes the historical performance of different parts, and it is used for the first round of part selection. The acceptance probability validates the specific tracking stability of each part in a frame, and it determines whether to accept its vote or to reject it. By doing this, we transform the complex online part selection problem into a probability learning one, which is easier to tackle. The observation model of each part is constructed by an improved supervised descent method and is learned in an incremental manner. Experimental results on two benchmarks demonstrate the competitive performance of our tracker against state-of-the-art methods

Discriminative tracking using tensor pooling

How to effectively organize local descriptors to build a global representation has a critical impact on the performance of vision tasks. Recently, local sparse representation has been successfully applied to visual tracking, owing to its discriminative nature and robustness against local noise and partial occlusions. Local sparse codes computed with a template actually form a three-order tensor according to their original layout, although most existing pooling operators convert the codes to a vector by concatenating or computing statistics on them. We argue that, compared to pooling vectors, the tensor form could deliver more intrinsic structural information for the target appearance, and can also avoid high dimensionality learning problems suffered in concatenation-based pooling methods. Therefore, in this paper, we propose to represent target templates and candidates directly with sparse coding tensors, and build the appearance model by incrementally learning on these tensors. We propose a discriminative framework to further improve robustness of our method against drifting and environmental noise. Experiments on a recent comprehensive benchmark indicate that our method performs better than state-of-the-art trackers

A new anionic exchange stir bar sorptive extraction coating based on monolithic material for the extraction of inorganic anion

A novel anionic exchange stir bar sorptive extraction (SBSE) coating based on poly(2(methacryloyloxy)ethyltrimethylammonium chloride-co-divinylbenzene) monolithic material for the extraction of inorganic anion was prepared. The effect of preparation conditions such as ratio of functional monomer to cross-linker, content of porogenic solvent on the extraction efficiencies were investigated in detailed. The monolithic material was characterized by elemental analysis, scanning electron microscopy and infrared spectroscopy. In order to investigate the extraction capacity of the new coating for inorganic anion, the new SBSE was combined with ionic chromatography with conductivity detection, Br-, NO3-, PO43- and SO42- were selected as detected solutes. Several extractive parameters, including pH value and ionic strength in sample matrix, desorption solvent, extraction and desorption time were optimized. The results showed that strongly ionic strength did not favor the extraction of anlaytes. Under the optimum experimental conditions, low detection limits (S/N = 3) and quantification limits (S/N = 10) of the proposed method for the target anions were achieved within the range of 0.92-2.62 and 3.03-9.25 mu g/L, respectively. The method also showed good linearity, simplicity, practicality and low cost for the extraction inorganic anions. Finally, the proposed method was successfully used to detect the two different trademarks of commercial purified water with satisfactory recovery in the range of 70.0-92.6%. To the best of our knowledge, this is the first to use SBSE to enrich inorganic anions. (C) 2010 Elsevier By. All rights reserved.National Nature Science Foundation of China [20805039]; Youth Talent Foundation of Fujian Province [2006F3117]; Start-up foundation of Xiamen University ; Innovation Foundation of Xiamen University [XDKJCX20063007

Fine-grained data access control with attribute-hiding policy for cloud-based IoT

The final publication is available at Elsevier via https://doi.org/10.1016/j.comnet.2019.02.008. © 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Ciphertext-policy attribute-based encryption (CP-ABE) is a promising approach to achieve fine-grained access control over the outsourced data in Internet of Things (IoT). However, in the existing CP-ABE schemes, the access policy is either appended to the ciphertext explicitly or only partially hidden against public visibility, which results in privacy leakage of the underlying ciphertext and potential recipients. In this paper, we propose a fine-grained data access control scheme supporting expressive access policy with fully attribute hidden for cloud-based IoT. Specifically, the attribute information is fully hidden in access policy by using randomizable technique, and a fuzzy attribute positioning mechanism based on garbled Bloom filter is developed to help the authorized recipients locate their attributes efficiently and decrypt the ciphertext successfully. Security analysis and performance evaluation demonstrate that the proposed scheme achieves effective policy privacy preservation with low storage and computation overhead. As a result, no valuable attribute information in the access policy will be disclosed to the unauthorized recipients

Visual tracking under motion blur

Most existing tracking algorithms do not explicitly consider the motion blur contained in video sequences, which degrades their performance in real-world applications where motion blur often occurs. In this paper, we propose to solve the motion blur problem in visual tracking in a unified framework. Specifically, a joint blur state estimation and multi-task reverse sparse learning framework are presented, where the closed-form solution of blur kernel and sparse code matrix is obtained simultaneously. The reverse process considers the blurry candidates as dictionary elements, and sparsely represents blurred templates with the candidates. By utilizing the information contained in the sparse code matrix, an efficient likelihood model is further developed, which quickly excludes irrelevant candidates and narrows the particle scale down. Experimental results on the challenging benchmarks show that our method performs well against the state-of-the-art trackers

Histone/Protein Deacetylase 11 Targeting Promotes Foxp3+ Treg Function.

Current interest in Foxp3+ T-regulatory (Treg) cells as therapeutic targets in transplantation is largely focused on their harvesting pre-transplant, expansion and infusion post-transplantation. An alternate strategy of pharmacologic modulation of Treg function using histone/protein deacetylase inhibitors (HDACi) may allow more titratable and longer-term dosing. However, the effects of broadly acting HDACi vary, such that HDAC isoform-selective targeting is likely required. We report data from mice with constitutive or conditional deletion of HDAC11 within Foxp3+ Treg cells, and their use, along with small molecule HDAC11 inhibitors, in allograft models. Global HDAC11 deletion had no effect on health or development, and compared to WT controls, Foxp3+ Tregs lacking HDAC11 showed increased suppressive function, and increased expression of Foxp3 and TGF-β. Likewise, compared to WT recipients, conditional deletion of HDAC11 within Tregs led to long-term survival of fully MHC-mismatched cardiac allografts, and prevented development of transplant arteriosclerosis in an MHC class II-mismatched allograft model. The translational significance of HDAC11 targeting was shown by the ability of an HDAC11i to promote long-term allograft allografts in fully MHC-disparate strains. These data are powerful stimuli for the further development and testing of HDAC11-selective pharmacologic inhibitors, and may ultimately provide new therapies for transplantation and autoimmune diseases

Fuel consumption and exhaust emissions of diesel vehicles in worldwide harmonized light vehicles test cycles and their sensitivities to eco-driving factors

Large amounts of fossil fuels are 14 consumed by motor vehicles annually, and hazardous exhaust emissions from the motor vehicles have caused serious problems to environment and human health. Eco-driving can effectively improve the fuel economy and decrease the exhaust emissions, which makes it vital to analyze the fuel consumption and exhaust emissions at given driving cycle, and investigate their sensitivities to eco-driving factors. In this paper, the fuel consumption and exhaust emissions of a Euro-6 compliant light-duty diesel vehicle were tested in Worldwide Harmonized Light Vehicles Test Cycles on a chassis dynamometer; further, the sensitivities of the eco-driving factors that influence the fuel economy and exhaust emissions were analyzed using validated vehicle model. For the vehicle model simulation, the effect of the coolant temperature on fuel consumption and exhaust emission only considered its effect on lubricating oil viscosity. The results showed that vehicle acceleration and velocity dominates the fuel consumption rates in Worldwide Harmonized Light Vehicles Test Cycles, where more than 50% of the exhaust emissions was emitted in the first 300 seconds; also, fuel economy and exhaust emission factors showed a significant dependency on the road grade, coolant temperature, vehicle velocity and mass. For the driver-controllable factors, high vehicle velocity and low road grade (via route-choice) were recommended to achieve low fuel consumption and exhaust emissions

Salivary Gland Transcriptomes and Proteomes of Phlebotomus tobbi and Phlebotomus sergenti, Vectors of Leishmaniasis

Phlebotomine female sand flies require a blood meal for egg development, and it is during the blood feeding that pathogens can be transmitted to a host. Leishmania parasites are among these pathogens and can cause disfiguring cutaneous or even possibly fatal visceral disease. The Leishmania parasites are deposited into the bite wound along with the sand fly saliva. The components of the saliva have many pharmacologic and immune functions important in blood feeding and disease establishment. In this article, the authors identify and investigate the protein components of saliva of two important vectors of leishmaniasis, Phlebotomus tobbi and P. sergenti, by sequencing the transcriptomes of the salivary glands. We then compared the predicted protein sequences of these salivary proteins to those of other bloodsucking insects to elucidate the similarity in composition, structure, and enzymatic activity. Finally, this descriptive analysis of P. tobbi and P. sergenti transcriptomes can aid future research in identifying molecules for epidemiologic assays and in investigating sand fly-host interactions