An unsupervised approach to generating generic summaries of documents

We present an optimization-based unsupervised approach to automatic document summarization. In the proposed approach, text summarization is modeled as a Boolean programming problem. This model generally attempts to optimize three properties, namely, (1) relevance: summary should contain informative textual units that are relevant to the user; (2) redundancy: summaries should not contain multiple textual units that convey the same information; and (3) length: summary is bounded in length. The approach proposed in this paper is applicable to both tasks: single- and multi-document summarization. In both tasks, documents are split into sentences in preprocessing. We select some salient sentences from document(s) to generate a summary. Finally, the summary is generated by threading all the selected sentences in the order that they appear in the original document(s). We implemented our model on multi-document summarization task. When comparing our methods to several existing summarization methods on an open DUC2005 and DUC2007 data sets, we found that our method improves the summarization results significantly. This is because, first, when extracting summary sentences, this method not only focuses on the relevance scores of sentences to the whole sentence collection, but also the topic representative of sentences. Second, when generating a summary, this method also deals with the problem of repetition of information. The methods were evaluated using ROUGE-1, ROUGE-2 and ROUGE-SU4 metrics. In this paper, we also demonstrate that the summarization result depends on the similarity measure. Results of the experiment showed that combination of symmetric and asymmetric similarity measures yields better result than their use separately.     

Direct Injection of CRISPR/Cas9-Related mRNA into Cytoplasm of Parthenogenetically Activated Porcine Oocytes Causes Frequent Mosaicism for Indel Mutations

Some reports demonstrated successful genome editing in pigs by one-step zygote microinjection of mRNA of CRISPR/Cas9-related components. Given the relatively long gestation periods and the high cost of housing, the establishment of a single blastocyst-based assay for rapid optimization of the above system is required. As a proof-of-concept, we attempted to disrupt a gene (GGTA1) encoding the α-1,3-galactosyltransferase that synthesizes the α-Gal epitope using parthenogenetically activated porcine oocytes. The lack of α-Gal epitope expression can be monitored by staining with fluorescently labeled isolectin BS-I-B₄ (IB4), which binds specifically to the α-Gal epitope. When oocytes were injected with guide RNA specific to GGTA1 together with enhanced green fluorescent protein (EGFP) and human Cas9 mRNAs, 65% (24/37) of the developing blastocysts exhibited green fluorescence, although almost all (96%, 23/24) showed a mosaic fluorescent pattern. Staining with IB4 revealed that the green fluorescent area often had a reduced binding activity to IB4. Of the 16 samples tested, six (five fluorescent and one non-fluorescent blastocysts) had indel mutations, suggesting a correlation between EGFP expression and mutation induction. Furthermore, it is suggested that zygote microinjection of mRNAs might lead to the production of piglets with cells harboring various mutation types.     

Sol–gel synthesis of Nd-doped BiFeO3 multiferroic and its characterization

Neodymium doped bismuth ferrite (BiFeO₃, BFO) nanoparticles were successfully synthesized by a facile sol–gel route. The influence of annealing temperature, time, Bi content and solvent on the crystal structure of BFO was studied. Results indicated that the optimum processing condition of BFO products was 550–600 °C/1.5 h with excess 3–6% Bi and ethylene glycol as solvent. On the other hand, Nd³⁺ ion was introduced into the BFO system and the effect of Nd³⁺ concentration on the structure, magnetic and dielectric properties of BFO were investigated. It was found that the magnetization of BFO was enhanced significantly with Nd³⁺ substitution, being attributed to the suppression of the spiral cycloidal magnetic structure led by the crystal structure transition. Furthermore, with increasing Nd³⁺ content, the dielectric constant was found to decrease while the dielectric loss was enhanced, which was mainly due to the hoping conduction mechanism with the reduction of oxygen vacancies.     

Glibenclamide for the Treatment of Ischemic and Hemorrhagic Stroke

Ischemic and hemorrhagic strokes are associated with severe functional disability and high mortality. Except for recombinant tissue plasminogen activator, therapies targeting the underlying pathophysiology of central nervous system (CNS) ischemia and hemorrhage are strikingly lacking. Sur1-regulated channels play essential roles in necrotic cell death and cerebral edema following ischemic insults, and in neuroinflammation after hemorrhagic injuries. Inhibiting endothelial, neuronal, astrocytic and oligodendroglial sulfonylurea receptor 1–transient receptor potential melastatin 4 (Sur1–Trpm4) channels and, in some cases, microglial K_ATP (Sur1–Kir6.2) channels, with glibenclamide is protective in a variety of contexts. Robust preclinical studies have shown that glibenclamide and other sulfonylurea agents reduce infarct volumes, edema and hemorrhagic conversion, and improve outcomes in rodent models of ischemic stroke. Retrospective studies suggest that diabetic patients on sulfonylurea drugs at stroke presentation fare better if they continue on drug. Additional laboratory investigations have implicated Sur1 in the pathophysiology of hemorrhagic CNS insults. In clinically relevant models of subarachnoid hemorrhage, glibenclamide reduces adverse neuroinflammatory and behavioral outcomes. Here, we provide an overview of the preclinical studies of glibenclamide therapy for CNS ischemia and hemorrhage, discuss the available data from clinical investigations, and conclude with promising preclinical results that suggest glibenclamide may be an effective therapeutic option for ischemic and hemorrhagic stroke.     

Mechanical damage characterization of glass fiber-reinforced polymer laminates by ultrasonic maps

A method for simultaneous measurement of the thickness and density for Glass Fiber-Reinforced Polymer (GFRP) laminate plates with ultrasonic waves in C-Scan mode is presented in the form of maps. The method uses three different signals in immersion pulse-echo C-Scan mode. The maps obtained based on the density show the heterogeneity of the material at high resolution at the pixel level (1 × 1 mm²) and therefore they represent an efficient tool to assess and evaluate the damage of the composite structures after manufacturing and after an applied mechanical loading.     

基于词法特征的恶意域名快速检测算法

针对互联网中恶意域名攻击事件频发，现有域名检测方法实时性不强的问题，提出一种基于词法特征的恶意域名快速检测算法。该算法根据恶意域名的特点，首先将所有待测域名按照长度进行正则化处理后赋予权值；然后利用聚类算法将待测域名划分成多个小组，并利用改进的堆排序算法按照组内权值总和计算各域名小组优先级，根据优先级降序依次计算各域名小组中每一域名与黑名单上域名之间的编辑距离；最后依据编辑距离值快速判定恶意域名。算法运行结果表明，基于词法特征的恶意域名快速检测算法与单一使用域名语义和单一使用域名词法的恶意域名检测算法相比，准确率分别提高1.7%与2.5%，检测速率分别提高13.9%与6.8%，具有更高的准确率和实时性。     

A methodology for the estimation of transverse failure strength of an oxidized lamina from isothermal aging studies

Surface oxidation and ensuing damage substantially decrease the service life of High Temperature Polymer Matrix Composite (HTPMC) structures. Oxidative degradation behavior of composites is strongly dependent on the coupling between chemical and mechanical responses of the material. In a composite lamina, the onset of damage and subsequent coupled acceleration of both damage and oxidation are controlled by the transverse failure strength of the oxidized regions. The direct measurement of this strength from experimentation is challenging and cumbersome. A model-based methodology for estimating the mean transverse failure strength of the oxidized regions of a unidirectional composite is described in this paper. As the strength of the oxidized region is expected to show a high-degree of spatial variability, the estimated mean is shown to be relatively insensitive to the effect of strength variance. The developed methodology is illustrated with isothermal aging data available for a typical high-temperature composite system.     

An adaptive image steganographic scheme based on Noise Visibility Function and an optimal chaotic based encryption method

Steganography is the science of hiding secret message in an appropriate digital multimedia in such a way that the existence of the embedded message should be invisible to anyone apart from the sender or the intended recipient. This paper presents an irreversible scheme for hiding a secret image in the cover image that is able to improve both the visual quality and the security of the stego-image while still providing a large embedding capacity. This is achieved by a hybrid steganography scheme incorporates Noise Visibility Function (NVF) and an optimal chaotic based encryption scheme. In the embedding process, first to reduce the image distortion and to increase the embedding capacity, the payload of each region of the cover image is determined dynamically according to NVF. NVF analyzes the local image properties to identify the complex areas where more secret bits should be embedded. This ensures to maintain a high visual quality of the stego-image as well as a large embedding capacity. Second, the security of the secret image is brought about by an optimal chaotic based encryption scheme to transform the secret image into an encrypted image. Third, the optimal chaotic based encryption scheme is achieved by using a hybrid optimization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) which is allowing us to find an optimal secret key. The optimal secret key is able to encrypt the secret image so as the rate of changes after embedding process be decreased which results in increasing the quality of the stego-image. In the extracting process, the secret image can be extracted from the stego-image losslessly without referring to the original cover image. The experimental results confirm that the proposed scheme not only has the ability to achieve a good trade-off between the payload and the stego-image quality, but also can resist against the statistics and image processing attacks.     

Synergistic effect of co-alloying elements on site preferences and elastic properties of Ni3Al: A first-principles study

The site preferences of co-alloying elements (Mo–Ta, Mo–Re, Mo–Cr) in Ni₃Al are studied using first-principles calculations, and the effects of these alloying elements on the elastic properties of Ni₃Al are evaluated by elastic property calculations. The results show that the Mo–Ta, Mo–Re and Mo–Cr atom pairs all prefer Al–Al sites and the spatial neighbor relation of substitution sites almost has no influence on the site preference results. Furthermore, the Young's modulus of Ni₃Al increases much higher by substituting Al–Al sites with co-alloying atoms, among which Mo–Re has the best strengthening effect. The enhanced chemical bondings between alloying atoms and their neighbor host atoms are considered to be the main strengthening mechanism of the alloying elements in Ni₃Al.     

Elitist clonal selection algorithm for optimal choice of free knots in B-spline data fitting

Data fitting with B-splines is a challenging problem in reverse engineering for CAD/CAM, virtual reality, data visualization, and many other fields. It is well-known that the fitting improves greatly if knots are considered as free variables. This leads, however, to a very difficult multimodal and multivariate continuous nonlinear optimization problem, the so-called knot adjustment problem. In this context, the present paper introduces an adapted elitist clonal selection algorithm for automatic knot adjustment of B-spline curves. Given a set of noisy data points, our method determines the number and location of knots automatically in order to obtain an extremely accurate fitting of data. In addition, our method minimizes the number of parameters required for this task. Our approach performs very well and in a fully automatic way even for the cases of underlying functions requiring identical multiple knots, such as functions with discontinuities and cusps. To evaluate its performance, it has been applied to three challenging test functions, and results have been compared with those from other alternative methods based on AIS and genetic algorithms. Our experimental results show that our proposal outperforms previous approaches in terms of accuracy and flexibility. Some other issues such as the parameter tuning, the complexity of the algorithm, and the CPU runtime are also discussed.