A laminated hollow porous carbon with high surface area of 2368
m
2/g was synthesized using a nonporous metal organic coordinate polymer as template. When used as electrode materials for electric ...double layer capacitors, the synthesized porous carbon presents a high specific capacitance of 234
F/g at a current density of 10
mA/g in 6
M KOH electrolyte and the capacitance retention can obtain 87% at current density of 20,000
mA/g.
A new anticancer ligustrazine derivative, 3beta-hydroxyolea-12-en-28-oic acid-3,5,6-trimethylpyrazin-2-methyl ester (T-OA, C38H58O3N2), was previously reported. It was synthesized via conjugating the ...effective antitumor ingredients of a classic traditional Chinese medicine (TCM) formulation. In the present study, anticancer efficacy of T-OA was evaluated in vivo using a murine sarcoma S180 model. Reduction of the tumor weight and tumor HE staining regions demonstrated that T-OA had promising inhibition effects and a 50% inhibitory rate in S180 mice. Combining the immunohistochemistry, we found T-OA exerted its antitumor activity by preventing the expression of nuclear transcription factor NF-kappaB/p65 and COX-2 in S180 mice. The acute toxic test showed that LD50 value of T-OA exceeded 6.0 g/kg via gavage in mice. In addition, a simple and rapid HPLC-UV method was developed and validated to study the pharmacokinetic characteristics of the compound. After single-dose oral administration, time to reach peak concentration of T-OA (3.97 microg/mL) was 8.33 h; the elimination half-life and area under the concentration-time curve from t = 0 to the last time of T-OA was 4.50 h and 48.01 microg x h/mL, respectively.
To evaluate antifungal combination strategy in children with hematologic diseases and invasive fungal disease( IFD).
A retrospective clinical study was performed based on 67 childhood patients with ...hematologic diseases and IFD who firstly accepted combination antifungal therapy for ≥ 7 days during January 2012 and December 2014. Of them, 11 cases received combination of echinocandin with azole, 10 cases received combination of echinocandin with amphotericin B, and 46 cases received combination of azole with amphotericin B.
Overall response rate was 79.1%. Univariate analysis revealed that granulocyte recovery (P=0.031), status of underling disease (P=0.023) and the duration of the therapy (P=0.046) were significantly associated with efficacy. Multivariate analysis showed that the independent prognostic factor was the duration of combination antifungal therapy (OR=0.229, 95% CI 0.061- 0.863, P=0.029). The response rates of echinocandin combined with azole, echinocandin combined with amphotericin B and azole co
A facile synthesis of -sulfonylimines by the condensation of aldehydes, sulfonylamide, and sodium arenesulfinate in the presence of sulfamic acid (NHSOH) in water-alcohol solvent and subsequent ...aqueous-biphasic basic elimination is reported.
A main goal of heterogeneous transfer learning algorithms is to solve the domain adaptation problem of different feature spaces. However, some existing heterogeneous transfer learning methods usually ...only extract common features from the source domain and target domain, ignoring specific features, which may damage the performance of transfer learning. Therefore, a hierarchical filter transfer learning algorithm (HFTLA) for heterogeneous domains in is proposed. First, a nonlinear mapping is constructed to learn the potential relationship between the features of different domains. Then, the feature space can be aligned by learning common features and specific features, which can ensure the integrity of the features. Second, a hierarchical filter framework is developed to play different roles in different stages of transfer learning. In the pretransfer phase, a knowledge filter based on genetic principle is designed to increase the diversity of knowledge with different genetic operators. In the post-transfer phase, a guided filter is established to achieve a coupling balance between source knowledge and target information. Finally, experimental results on heterogeneous domains illustrate the effectiveness of HFTLA.
Manually designed deep neural networks have successfully forwarded waste recognition tasks in the resource recycling field. However, due to the diversity of waste samples, the feature extraction ...ability of inherently designed models fails to fully satisfy the requirements of real world applications. In this article, an attention-aware based differentiable architecture search (ADAS) network for waste recognition is proposed, which self-organizes to generate an optimal network structure according to diverse waste data. First, a structured search space with attention-aware modules is designed to enhance the diverse feature representations of waste data. Secondly, an efficient and differentiable structure search is achieved by continuously relaxing the representation of the network architecture and search space. Finally, the optimal architecture search process is evaluated by a bi-level optimization algorithm. Experimental results show that the proposed method achieves more satisfactory classification performances than the manually designed ResNet, DenseNet networks in the TrashNet dataset and the self-built household waste dataset.
To compare the efficacy of hepatic resection (HR) in patients with Barcelona Clinical Liver Cancer (BCLC) Stage B hepatocellular carcinoma (HCC) and examine how that efficacy has changed over time in ...a large medical center.
A consecutive sample of 918 patients with preserved liver function and large and/or multinodular HCC who were treated by initial HR were divided into three groups: those with a single tumor ≥5 cm in diameter (
=582), 2-3 tumors with a maximum diameter>3 cm (
=223), or>3 tumors of any diameter (
=113). Hospital mortality and overall survival (OS) in each group were compared for the years 2001-2007 and 2008-2013.
Patients with >3 tumors showed the highest incidence of hospital mortality of all groups (
<0.05). Kaplan-Meier survival analysis showed that OS varied across the three groups as follows: single tumor>2-3 tumors >3+ tumors (all
<0.05). OS rate at 5 years ranged from 24% to 41% in all three groups for the period 2001-2007, and from 35% to 46% for the period 2008-2013. OS was signific
In this paper, we propose a novel structure automatic change algorithm for neural-network. It can solve the problem that most neural-networks can not change the structure online. This algorithm ...consists of two main steps: 1) The computation of the neural-network ability to judge whether need to add nodes to the hidden layer or pruning, we use the improved support vector machine (SVM) to decide when and where to change the structure of neural-network hidden layer in this step; 2) Adjusting the parameter of the neural-network, this learning rule for the neural-network is a novel approach based on the modified back-propagation (BP). On the basis of the former methods, we propose a structure automatic changed neural network (SACNN). Finally, the SACNN is applied to track the nonlinear functions, the simulation results show that the results by this neural network perform better than the former growing cell structure (GCS) neural-network.
Chlamydomonas reinhardtii is a unicellular green alga that has been used as a model organism for the study of flagella and basal bodies as well as photosynthesis. This report analyzes finished ...genomic DNA sequence for 0.5% of the nuclear genome. We have used three gene prediction programs as well as EST and protein homology data to estimate the total number of genes in Chlamydomonas to be between 12,000 and 16,400. Chlamydomonas appears to have many more genes than any other unicellular organism sequenced to date. Twenty-seven percent of the predicted genes have significant identity to both ESTs and to known proteins in other organisms, 32% of the predicted genes have significant identity to ESTs alone, and 14% have significant similarity to known proteins in other organisms. For gene prediction in Chlamydomonas, GreenGenie appeared to have the highest sensitivity and specificity at the exon level, scoring 71% and 82%, respectively. Two new alternative splicing events were predicted by aligning Chlamydomonas ESTs to the genomic sequence. Finally recombination differs between the two sequenced contigs. The 350-Kb of the Linkage group III contig is devoid of recombination, while the Linkage group I contig is 30 map units long over 33-kb.
Deep Twin Support Vector Machine Dewei Li; Yingjie Tian; Honggui Xu
2014 IEEE International Conference on Data Mining Workshop,
2014-Dec.
Conference Proceeding
We propose a novel machine learning model for classification problems, Deep Twin Support Vector Machine (DTWSVM), which combines TWSVM with deep learning ideas. TWSVM is a successful algorithm for ...classification problems which seeks two nonparallel hyper planes to make each hyper plane close to one class and far from the other as much as possible. And Deep Learning (DL) models have shown good ability in feature extraction and dimension reduction by constructing multi-layer network. Since the feature extraction in DL can reduce feature dimension while maintain the main information of original inputs, we consider constructing a three layer network which contains input layer, hidden layer and output layer. We use two TWSVMs in the hidden layer to extract features based on the projection principle which is derived from Multi-Layer Perceptron (MLP). The two TWSVMs will get four hyper planes by solving four convex quadratic programs. A new dataset which consists of the extracted features with four feature dimensions is produced from the hidden layer and then we can input it to the main TWSVM of the output layer to make final prediction. Similar as TWSVM, we design linear DTWSVM and nonlinear DTWSVM which have been proved to be very effective in classification problems. In numerical experiments, we have obtained 100% prediction accuracy for several datasets which is state-of-the-art performance absolutely!
