iRGD-reinforced,photo-transformable nanoclusters toward cooperative enhancement of intratumoral penetration and antitumor efficacy

Nano Research - Insufficient intratumoral penetration greatly hurdles the anticancer performance of nanomedicine. To realize highly efficient tumor penetration in a precisely and spatiotemporally...     

First-order modeling and stability analysis of illusory contours

In visual cognition, illusions help elucidate certain intriguing latent perceptual functions of the human vision system, and their proper mathematical modeling and computational simulation are therefore deeply beneficial to both biological and computer vision. Inspired by existent prior works, the current paper proposes a first-order energy-based model for analyzing and simulating illusory contours. The lower complexity of the proposed model facilitates rigorous mathematical analysis on the detailed geometric structures of illusory contours. After being asymptotically approximated by classical active contours, the proposed model is then robustly computed using the celebrated level-set method of Osher and Sethian [S. Osher, J.A. Sethian, Fronts propagating with curvature-dependent speed: algorithms based on Hamilton–Jacobi formulations, J. Comput. Phys., 79 (12) (1988) 12–49] with a natural supervising scheme. Potential cognitive implications of the mathematical results are addressed, and generic computational examples are demonstrated and discussed.     

Automatic classification and prediction models for early Parkinson’s disease diagnosis from SPECT imaging

Early and accurate diagnosis of Parkinson’s disease (PD) is important for early management, proper prognostication and for initiating neuroprotective therapies once they become available. Recent neuroimaging techniques such as dopaminergic imaging using single photon emission computed tomography (SPECT) with ¹²³I-Ioflupane (DaTSCAN) have shown to detect even early stages of the disease. In this paper, we use the striatal binding ratio (SBR) values that are calculated from the ¹²³I-Ioflupane SPECT scans (as obtained from the Parkinson’s progression markers initiative (PPMI) database) for developing automatic classification and prediction/prognostic models for early PD. We used support vector machine (SVM) and logistic regression in the model building process. We observe that the SVM classifier with RBF kernel produced a high accuracy of more than 96% in classifying subjects into early PD and healthy normal; and the logistic model for estimating the risk of PD also produced high degree of fitting with statistical significance indicating its usefulness in PD risk estimation. Hence, we infer that such models have the potential to aid the clinicians in the PD diagnostic process.     

A projection-based decomposition for the scalability of evolvable hardware

Scalability is a main and urgent problem in evolvable hardware (EHW) field. For the design of large circuits, an EHW method with a decomposition strategy is able to successfully find a solution, but requires a large complexity and evolution time. This study aims to optimize the decomposition on large-scale circuits so that it provides a solution for the EHW method to scalability and improves the efficiency. This paper proposes a projection-based decomposition (PD), together with Cartesian genetic programming (CGP) as an EHW system namely PD-CGP, to design relatively large circuits. PD gradually decomposes a Boolean function by adaptively projecting it onto the property of variables, which makes the complexity and number of sub-logic blocks minimized. CGP employs an evolutionary strategy to search for the simple and compact solutions of these sub-blocks. The benchmark circuits from the MCNC library, \(n\)-parity circuits, and arithmetic circuits are used in the experiment to prove the ability of PD-CGP in solving scalability and efficiency. The results illustrate that PD-CGP is superior to 3SD-ES in evolving large circuits in terms of complexity reduction. PD-CGP also outperforms GDD+GA in evolving relatively large arithmetic circuits. Additionally, PD-CGP successfully evolves larger \(n\)-even-parity and arithmetic circuits, which have not done by other approaches.     

Image categorization using a semantic hierarchy model with sparse set of salient regions

Image categorization in massive image database is an important problem. This paper proposes an approach for image categorization, using sparse set of salient semantic information and hierarchy semantic label tree （HSLT） model. First, to provide more critical image semantics, the proposed sparse set of salient regions only at the focuses of visual attention instead of the entire scene was formed by our proposed saliency detection model with incorporating low and high level feature and Shotton＇s semantic texton forests （STFs） method. Second, we also propose a new HSLT model in terms of the sparse regional semantic information to automatically build a semantic image hierarchy, which explicitly encodes a general to specific image relationship. And last, we archived image dataset using image hierarchical semantic, which is help to improve the performance of image organizing and browsing. Extension experimefital results showed that the use of semantic hierarchies as a hierarchical organizing frame- work provides a better image annotation and organization, improves the accuracy and reduces human＇s effort.     

Video Data Delivery using Slotted Patching

In the request-based scheme, a patching channel is initiated on arrival of a request in an interarrival time of two adjacent multicast channels. If two requests are received in a short duration in an interarrival time, two patching channels are needed to service them. Both these channels deliver almost the same data, thus, wasting the bandwidth. This problem may be addressed in two ways: using higher level patching technique, or forcing the first request to wait for the second one. Using higher level patching technique makes the system more complex and thus usually not preferred. In the second case, the bandwidth usage certainly reduces, but the length of the waiting time by the first request for the second request is the main issue. In this paper, this issue is addressed by dividing the video duration into uniform time slots such that there is at least one request in a time slot for initiating the patching channel. The proposed scheme is named as Video Data Delivery using Slotted Patching. In this scheme, the patching channels download much less video data than the request-based scheme and thus require less bandwidth. This scheme may not provide immediate services to all users unlike the request-based scheme, but the user's waiting can be made arbitrarily small without using much resources unlike the request-based scheme.     

Simulation of Cortical and Cancellous Bone to Accelerate Tissue Regeneration

Different tissues have complex anisotropic structures to support biological functions. Mimicking these complex structures in vitro remains a challenge in biomaterials designs. Here, inspired by different types of silk nanofibers, a composite materials strategy is pursued toward this challenge. A combination of fabrication methods is utilized to achieve separate control of amorphous and beta-sheet rich silk nanofibers in the same solution. Aqueous solutions containing two types of silk nanofibers are simultaneously treated with an electric field and with ethylene glycol diglycidyl ether (EGDE). Under these conditions, the beta-sheet rich silk nanofibers in the mixture responded to the electric field while the amorphous nanofibers are active in the crosslinking process with the EGDE. As a result, cryogels with anisotropic structures are prepared, including mimics for cortical- and cancellous-like bone biomaterials as a complex osteoinductive niche. In vitro studies revealed that mechanical cues of the cryogels induced osteodifferentiation of stem cells while the anisotropy inside the cryogels influenced immune reactions of macrophages. These bioactive cryogels also stimulated improved bone regeneration in vivo through modulation of inflammation, angiogenesis and osteogenesis responses, suggesting an effective strategy to develop bioactive matrices with complex anisotropic structures beneficial to tissue regeneration.     

基于SOA居民健康档案与数据挖掘技术研究

传统基于业务管理的离散系统建设,已无法满足区域医疗卫生信息共享和业务协同的需求。区域卫生信息化正向着整合性、遍在性、扩展性方向发展,既满足卫生行业发展和管理的需求又能整合现有的系统保护之前的投入,就需要顶层规划的架构能具备高兼容性和高可扩展性,SOA体系架构将是一个很好的应用。文中结合基于SOA居民健康档案管理系统(EHR)的实际应用,给出了利用Web Service实现SOA的有效方法,平台以服务居民为中心,同时,兼顾卫生管理和辅助决策研究的数据挖掘利用,将是行业整合平台的发展方向。