A deep supervised approach for ischemic lesion segmentation from multimodal MRI using Fully Convolutional Network

The principle restorative step in the treatment of ischemic stroke depends on how fast the lesion is delineated from the Magnetic Resonance Imaging (MRI) images. This will serve as a vital aid to estimate the extent of damage caused to the brain cells. However, manual delineation of the lesion is time-consuming and it is subjected to intra-observer and inter-observer variability. Most of the existing methods for ischemic lesion segmentation rely on extracting handcrafted features followed by application of a machine learning algorithm. Identifying such features demand multi-domain expertise in Neuro-radiology as well as Image processing. This can be accomplished by learning the features automatically using Convolutional Neural Network (CNN). To perform segmentation, the spatial arrangement of pixel needs to be preserved in addition to learning local features of an image. Hence, a deep supervised Fully Convolutional Network (FCN) is presented in this work to segment the ischemic lesion. The highlight of this research is the application of Leaky Rectified Linear Unit activation in the last two layers of the network for a precise reconstruction of the ischemic lesion. By doing so, the network was able to learn additional features which are not considered in the existing U-Net architecture. Also, an extensive analysis was conducted in this research to select optimal hyper-parameters for training the FCN. A mean segmentation accuracy of 0.70 has been achieved from the experiments conducted on ISLES 2015 dataset. Experimental observations show that our proposed FCN method is 10% better than the existing works in terms of Dice Coefficient.     

Efficient 3D point clouds classification for face detection using linear programming and data mining

Most of the applications related to security and biometric rely on skin region detection such as face detection, adult 3D objects filtering, and gesture recognition. In this paper, we propose a robust method for skin detection on 3D coloured point clouds. Then, we extend this method to solve the problem of 3D face detection. To do so, we construct a weighted graph from initial coloured 3D point clouds. Then, we present a linear programming algorithm using a predictive model based on a data mining approach to classify and label graph vertices as skin and non-skin regions. Moreover, we apply some refinement rules on skin regions to confirm the presence of a face. Furthermore, we demonstrate the robustness of our method by showing and analysing some experimental results. Finally, we show that our method deals with many data that can be represented by a weighted graph such as 2D images and 3D models.     

Traditional Dough in the Era of Internet of Things: Edible,Renewable, and Reconfigurable Skin‐Like Iontronics

With the rapid development of Internet of Things technology, interactive interfaces that can promote bidirectional communications between human beings and machines will certainly play an important role. Current electronic or iontronic systems meet diverse requirements such as conductivity, mechanical compliance, stimuli responsiveness, long‐time duration, and even biocompatibility. However, for future large‐scale applications, non‐degradable and non‐recyclable components in these devices cause resource waste and environmental pollution. Here, traditional dough is used to replace non‐recyclable conductive components and fabricate a type of renewable and reconfigurable smart skin. These smart skins are self‐healing, mechanically adaptable to irregular interfaces, and can sense different gestures of a prosthetic hand as well as large and subtle scale of human motion. This work greatly extends the material choice and enables new functionality for skin‐like iontronics, and may address the concern about their impact on human health and environmental issues in the era of Internet of Things.     

Prediction and measurement of surfactant action upon human skin under realistic conditions

The lysosomal enzyme acid phosphatase has been characterized and quantified in tapestrip biopsies of human stratum corneum by means of a sensitive spectrofluorometric procedure. When the stratum corneum of panellists was exposed to dilute solutions of various surfactants under realistic exposure conditions, the changes observed in stratum corneum acid phosphatase specific activity have been found to correlate very closely with the visual, macroscopic changes such as dryness and flakiness, that are elicited in skin as a result of surfactants. This method monitors denaturation of stratum corneum proteins, which is an important feature of skin surfactant interactions, and serves as an effective, non-invasive predictive tool for skin irritancy and mildness of surfactants.
Prevention et mesure de l'action des tensio-actifs sur la peau humaine dans des conditions conformes a la réalité     

云南主产区夏黑果皮营养成分及抗氧化活性研究

以云南4个葡萄主产区的夏黑果皮为原料,对其营养成分及抗氧化活性进行了分析。以DPPH、ABTS+自由基清除能力和还原能力评价了四个地区果皮多酚提取物的抗氧化活性。结果发现:同一品种的四个样品,因其生长环境不同,营养成分及组成存在明显差异。葡萄皮中脂质的不饱和脂肪酸含量较高,单糖含量为葡萄糖>阿拉伯糖、半乳糖醛酸、半乳糖。葡萄皮中的原花青素、多酚含量存在显著性差异,酚酸组成中芦丁和儿茶素含量较高。果皮多酚提取物表现较好的抗氧化活性,其在三种抗氧化体系中的IC50值分别在13.34¹4.86μg/m L、9.15¹0.64μg/m L和32.63³4.24μg/m L之间。      

Quality of frankfurter-type sausages with added pig skin and wheat fiber mixture as fat replacers

Pig skin and wheat fiber mixture (PSFM) were assessed as fat replacers in frankfurter-type sausages. The addition of PSFM increased the moisture and protein content in the sausage because of the water binding capacity in wheat fiber and protein content in pig skin. The sausage sample containing 20% PSFM had 50% less fat, 32% fewer calories, and showed 39.5% less cooking loss than those of the control (p < 0.05). High PSFM content resulted in more stable meat emulsions and increased hardness, cohesiveness, gumminess, and chewiness. No significant differences were observed in color, flavor, tenderness, juiciness, warm-off flavor, and overall acceptability between the control and sausage sample with PSFM by the sensory panel. Therefore, PSFM could be used as fat replacers to obtain lower calories, and higher moisture, protein contents, and emulsion stability than in low-fat frankfurter-type sausages without PSFM.     

三重介质油藏干扰试井压力动态特征

在建立三重介质油藏试井解释模型的基础上，对该类油藏的干扰试井压力动态变化进行了研究；分析了井筒储存、表皮系数、窜流系数以及弹性储容比对观测井井底压力的影响。结果表明，表皮系数对观测井的井底压力没有影响，而井筒储存是否会对观测井井底压力造成影响取决于井筒储存系数的大小以及激动井和观测井之间的距离，窜流系数和弹性储容比对观测井井底压力的影响与单井试井的结果相类似。