Miracle-dz/UniFAR-FTUs huggingface dataset:
Involvement of caspase-3 in photoreceptor cell apoptosis induced by in vivo blue light exposure.

PURPOSE To investigate the potential role of caspase-3 in blue light-induced apoptosis in photoreceptor cells. METHODS Cyclic light-raised Sprague-Dawley rats were exposed to 400 to 480 nm light for 6 hours at an irradiance of 0.64 W/m(2). The rats were then kept in darkness for recovery and killed at scheduled time points from 0 hours up to 24 hours after exposure to light. The unexposed rats were used as the control. Apoptosis was marked with in situ terminal dUTP nick end labeling (TUNEL). Caspase-3 expression was explored using immunohistochemistry, Western blot analysis, real-time RT-PCR, and enzyme activity assay. RESULTS Exposure to blue light resulted in photoreceptor cell apoptosis, mostly in the superior temporal area of the retina. TUNEL-positive cells were highest during 8 to 16 hours of recovery in darkness. Procaspase-3 protein was constitutively expressed in the rat retina and was apparently upregulated after exposure to light, with expression peaking at 8 to 16 hours and subsiding at 24 hours. The upregulation was further supported by enhanced transcription of caspase-3 in the postexposure retina. Meanwhile, increased cleavage of caspase-3 into its active fragments of 17 and 19 kDa was detected after exposure to light, peaking at 16 hours. Activation of caspase-3 was subsequently located in the photoreceptor cells and predominantly in the superior part of the temporal quadrant. This coincided with elevated caspase-3-like activity at 16 hours after exposure to light. CONCLUSIONS Procaspase-3 protein is temporally upregulated in the retina after in vivo exposure to blue light, and the upregulation is coupled to activation of caspase-3 and concomitant induction of apoptosis in the photoreceptor cells.
Comprehensible Knowledge Discovery: Gaining Insight from Data

Large databases are routinely being collected in government, science, business and medicine. A variety of techniques from statistics, signal processing, pattern recognition, machine learning, and neural networks have been proposed to help people understand the data by discovering predictive models of the data. However, research in data mining has not paid attention to the factors that make learned models comprehensible. A comprehensible model would provide insight to an expert. This insight could be communicated to others and could support a variety of decision-making tasks. For example, knowledge acquired through such methods on a medical database might be published in scientific journals and provide advice on how to reduce the likelihood of getting a certain disease. Analysis of a political database might reveal the conditions under which trade negotiations are likely to be successful and provide advice on strategies that are effective. Knowledge acquired from analyzing a financial database might be taught in a management school.
Nonextensive entropy approach to space plasma fluctuations and turbulence

Spatial intermittency in fully developed turbulence is an established feature of astrophysical plasma fluctuations and in particular apparent in the interplanetary medium by in situ observations. In this situation the classical Boltzmann-Gibbs extensive thermo-statistics, applicable when microscopic interactions and memory are short ranged, fails. Upon generalization of the entropy function to nonextensivity, accounting for long-range interactions and thus for correlations in the system, it is demonstrated that the corresponding probability distributions (PDFs) are members of a family of specific power-law distributions. In particular, the resulting theoretical bi-kappa functional reproduces accurately the observed global leptokurtic, non-Gaussian shape of the increment PDFs of characteristic solar wind variables on all scales. Gradual decoupling is obtained by enhancing the spatial separation scale corresponding to increasing kappa-values in case of slow solar wind conditions where a Gaussian is approached in the limit of large scales. Contrary, the scaling properties in the high speed solar wind are predominantly governed by the mean energy or variance of the distribution. The PDFs of solar wind scalar field differences are computed from WIND and ACE data for different time-lags and bulk speeds and analyzed within the nonextensive theory. Consequently, nonlocality in fluctuations, related to both, turbulence and its large scale driving, should be related to long-range interactions in the context of nonextensive entropy generalization, providing fundamentally the physical background of the observed scale dependence of fluctuations in intermittent space plasmas.
Improved Multi-Rate Video Encoding

Adaptive HTTP streaming is frequently used for both live and on-Demand video delivery over the Internet. Adaptive ness is often achieved by encoding the video stream in multiple qualities (and thus bit rates), and then transparently switching between the qualities according to the bandwidth fluctuations and the amount of resources available for decoding the video content on the end device. For this kind of video delivery over the Internet, H.264 is currently the most used codec, but VP8 is an emerging open-source codec expected to compete with H.264 in the streaming scenario. The challenge is that, when encoding video for adaptive video streaming, both VP8 and H.264 run once for each quality layer, i.e., consuming both time and resources, especially important in a live video delivery scenario. In this paper, we address the resource consumption issues by proposing a method for reusing redundant steps in a video encoder, emitting multiple outputs with varying bit rates and qualities. It shares and reuses the computational heavy analysis step, notably macro-block mode decision, intra prediction and inter prediction between the instances, and outputs video in several rates. The method has been implemented in the VP8 reference encoder, and experimental results show that we can encode the different quality layers at the same rates and qualities compared to the VP8 reference encoder, while reducing the encoding time significantly.
A multilayer fault localization framework for IP over all-optical multilayer networks

IP over all-optical multilayer networks is a promising solution to combine highspeed transmission using end-to-end lightpaths with the flexibility required to handle traffic increases and fluctuations at layer-2 (e.g., Ethernet) and/or layer-3 (e.g., IP). Fault management is a key issue for the successful deployment of these networks due to their high bit-rate and service-quality demands. To decrease complexity, the problems of locating the roots of multiple failures and initiating recovery actions in a network traditionally were approached from a single-layer perspective. This article analyzes the major challenges for fault detection, fault localization, and survivability in wavelength-routed, IP over all-optical multilayer networks and then, proposes a framework for efficient fault localization in this kind of network.
Functional Characterization of the Poplar R2R3-MYB Transcription Factor PtoMYB216 Involved in the Regulation of Lignin Biosynthesis during Wood Formation

Because of the importance of wood in many industrial applications, tremendous studies have been performed on wood formation, especially in lignin biosynthesis. MYB transcription factors (TFs), which consist of a large family of plant TFs, have been reported to directly regulate lignin biosynthetic genes in a number of plants. In this study, we describe the cloning and functional characterization of PtoMYB216, a cDNA isolated from Chinese white poplar (Populus tomentosa Carr.). PtoMYB216 encodes a protein belonging to the R2R3-MYB family and displays significant similarity with other MYB factors shown to regulate lignin synthesis in Arabidopsis. Gene expression profiling studies showed that PtoMYB216 mRNA is specifically expressed during secondary wall formation in wood. The 1.8-kb promoter sequence of PtoMYB216 was fused to the GUS coding sequence and introduced into wild-type A. thaliana. GUS expression was shown to be restricted to tissues undergoing secondary cell wall formation. Overexpression of PtoMYB216 specifically activated the expression of the upstream genes in the lignin biosynthetic pathway and resulted in ectopic deposition of lignin in cells that are normally unligninified. These results suggest that PtoMYB216 is specific transcriptional activators of lignin biosynthesis and involved in the regulation of wood formation in poplar.
A New Localization Method for Iris Recognition Based on Angular Integral Projection Function

Iris recognition is one of the most reliable and accurate biometric technologies. Iris localization is crucial for the performance of an iris recognition system, it includes finding the iris boundaries (inner and outer) and the eyelids (lower and upper). In this paper, we propose an efficient iris localization method based on the angular integral projection function (AIPF) to detect the iris boundaries in iris images. The proposed algorithm adopts boundary points detection and curve fitting. First, the approximate pupil center is obtained. Then, two sets of radial boundary points are detected for the iris inner and outer boundaries using AIPF method. Finally, we get the iris boundaries by fitting a circle for each of the above boundary points set. In the recognition stage, we used 2D Gabor filter to extract the iris code for the normalized iris image. At last, the proposed algorithm was tested on CASIA V1.0 iris images database. We evaluate the performance based on the analysis of both False Accept Rate(FAR) and False Reject Rate(FRR) curves. Experimental results show that the proposed iris localization algorithm is efficient and improves iris recognition.
Dictionary and Gene Ontology Based Similarity for Named Entity Relationship Protein-protein Interaction Prediction from Biotext Corpus

Protein-protein interactions functions as a significant key role in several biological systems. These involves in complex formation and many pathways which are used to perform biological processes. By accurate identification of the set of interacting proteins can get rid of new light on the functional role of various proteins in the complex surroundings of the cell. The ability to construct biologically consequential gene networks and identification of the exact relationship in the gene network is critical for present-day systems biology. In earlier research, the power of presented gene modules to shed light on the functioning of complex biological systems is studied. Most of modules in these networks have shown small link with meaningful biological function, because these methods doesn't exactly calculate the semantic relationship between the entities. In order to overcome these problems and improve the PPI results in the biotext corpus a new method is proposed in this research. The proposed method which directly incorporates Gene Ontology (GO) annotation in construction of gene modules and Dictionary-based text is proposed to extract biotext information. Dictionary-Based Text and Gene Ontology (DBTGO) approach that integrates with various gene-gene pairwise similarity values, protein-protein interaction relationship obtained from gene expression, in order to gain better biotext information retrieval result. A result analysis has been carried out on Biotext Project at UC Berkley. Testing the DBTGO algorithm indicates that it is able to improve PPI relationship identification result with all previously suggested methods in terms of the precision, recall, F measure and Normalized Discounted Cumulative Gain (NDCG). The proposed DBTGO algorithm can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level.
Query sampling for ranking learning in web search

Learning to rank has become a popular approach to build a ranking model for Web search recently. Based on our observation, the constitution of the training set will greatly influence the performance of the learned ranking model. Meanwhile, the number of queries in Web search is nearly infinite and the human labeling cost is expensive, hence a subset of queries need to be carefully selected for training. In this paper, we develop a greedy algorithm to sample the queries, by simultaneously taking the query density, difficulty and diversity into consideration. The experimental results on a collected Web search dataset comprising 2024 queries show that the proposed method can lead to a more informative training set for building an effective model.
Hidden Markov Models with Spectral Features for 2D Shape Recognition

We present a technique using Markov models with spectral features for recognizing 2D shapes. We analyze the properties of Fourier spectral features derived from closed contours of 2D shapes and use these features for 2D pattern recognition. We develop algorithms for reestimating parameters of hidden Markov models. To demonstrate the effectiveness of our models, we have tested our methods on two image databases: hand-tools and unconstrained handwritten numerals. We are able to achieve high recognition rates of 99.4 percent and 96.7 percent without rejection on these two sets of image data, respectively.
Remote Supervision of IV-tPA for Acute Ischemic Stroke by Telemedicine or Telephone Before Transfer to a Regional Stroke Center Is Feasible and Safe

Background and Purpose— Because of a shortage of stroke specialists, many outlying or “spoke” hospitals initiate intravenous (IV) thrombolysis using telemedicine or telephone consultation before transferring patients to a regional stroke center (RSC) hub. We analyzed complications and outcomes of patients treated with IV tissue plasminogen activator (tPA) using the “drip and ship” approach compared to those treated directly at the RSC. Methods— A retrospective review of our Get With the Guidelines Stroke (GWTG-Stroke) database from 01/2003 to 03/2008 identified 296 patients who received IV tPA within 3 hours of symptom onset without catheter-based reperfusion. GWTG-Stroke definitions for symptomatic intracranial (sICH), systemic hemorrhage, discharge functional status, and destination were applied. Follow-up modified Rankin Score was recorded when available. Results— Of 296 patients, 181 (61.1%) had tPA infusion started at an outside spoke hospital (OSH) and 115 (38.9%) at the RSC hub. OSH patients were younger with fewer severe strokes than RSC patients. Patients treated based on telestroke were more frequently octogenarians than patients treated based on a telephone consult. Mortality, sICH, and functional outcomes were not different between OSH versus RSC and telephone versus telestroke patients. Among survivors, mean length of stay was shorter for OSH patients but discharge status was similar and 75% of patients walked independently at discharge. Conclusions— Outcomes in OSH “drip and ship” patients treated in a hub-and-spoke network were comparable to those treated directly at an RSC. These data suggest that “drip and ship” is a safe and effective method to shorten time to treatment with IV tPA.
Toward a New Generation of Semantic Web Applications

Although research on integrating semantics with the Web started almost as soon as the Web was in place, a concrete Semantic Web that is, a large-scale collection of distributed semantic metadata emerged only over the past four to five years. The Semantic Web's embryonic nature is reflected in its existing applications. Most of these applications tend to produce and consume their own data, much like traditional knowledge- based applications, rather than actually exploiting the Semantic Web as a large-scale information source. These first-generation semantic Web applications typically use a single ontology that supports integration of resources selected at design time.
Development of a Topical Treatment for Psoriasis Targeting RORγ: From Bench to Skin

Background Psoriasis is a chronic inflammatory skin disorder involving marked immunological changes. IL-17-targeting biologics have been successful in reducing the disease burden of psoriasis patients with moderate-to-severe disease. Unfortunately, the stratum corneum prevents penetration of large molecule weight proteins, including monoclonal antibodies. Thus, for the majority of psoriasis patients ineligible for systemic treatments, a small molecule targeting RORγt, the master regulator of IL-17 family cytokines, may represent an alternative topical medicine with biologic-like efficacy. Methods and Findings The preclinical studies described in this manuscript bridge the gap from bench to bedside to provide the scientific foundation for a compound entering clinical trials for patients with mild to moderate psoriasis. In addition to several ex vivo reporter assays, primary T cell cultures, and the imiquimod mouse model, we demonstrate efficacy in a newly developed human ex vivo skin assay, where Th17-skewed cytokine expression is induced from skin-resident immune cells. Importantly, the skin barrier remains intact allowing for the demonstration of topical drug delivery. With the development of this novel assay, we demonstrate potent compound activity in the target tissue: human skin. Finally, target engagement by this small molecule was confirmed in ex vivo lesional psoriatic skin. Conclusions Our work describes a progressive series of assays to demonstrate the potential clinical value of a novel RORγ inverse agonist small molecule with high potency and selectivity, which will enter clinical trials in late 2015 for psoriasis patients.
Revealing PIR protocols protected users

Privacy preservation is one of the major issue in digital products. In current era, web search engine has become vital tool for internet users. However, most search engines maintains user profile and analyze them which could compromise privacy. In order to preserve the user privacy from a search engine, many privacy preserving solution have been proposed including query obfuscation, anonymizing networks and Peer to Peer Private Information Retrieval Protocols. However, first two solutions cannot preserve user privacy completely and they have their own drawbacks as well, while the Peer-to-Peer Private Information Retrieval protocols are passing through evolution stage. The focus of this paper is to evaluate and quantify the techniques use to preserve privacy by two major protocols of Private Information Retrieval protocols including Useless User Profile and User Private Information Retrieval. In this research association rule mining technique is used to expose the source of query of interest. Each protocol is simulated under varying parameters of Group Size, Number of Query of Interest and association rule mining Window Size over the released data of American Online. The results shows that on the average the proposed adversarial model exposed 85.34% and 80.75% Query of Interest source correctly of Useless User Profile and User Private Information Retrieval protocol respectively. Similarly based on results, it is also concluded that less number of Query of Interest submitted by a user and large groups size offer more protection to the user.
Gini Coefficient Used in the Post-evaluation Theory of Highway Construction

Statistical Gini coefficient has anther name Lorenz curve; it is the index to inspect the average level of revenue and distribution of society. Besides, it can also be used to express the equity. of the distribution of property and test the income and distribution effects of revenue and expenditure, Based on the project of post-evaluation theory of highway construction of Zhangjiakou city, Gini coefficient is introduced as following in this paper: By calculating Gini coefficient of distribution and income of various counties and districts in Zhangjiakou to measure the urban social income distribution of equilibrium of Zhangjiakou: By calculating the Gini coefficient of road share in various counties and districts to measure the equilibrium of the road share: Through contrasting the Gini coefficient before and after the construction to test the balance degree of Zhangjiakou. The Gini coefficient will be rationally used in the post-evaluation theory of highway construction and it will be supplement and improvement of the theory of highway construction. The post-evaluation theory of highway construction focused on data growth, increased benefits, at the same time, it should also focus on the average and fairness, which also profoundly express the concept of "harmonious society, people-oriented" thinking.
Efficient view synthesis scheme with ray casting and pull-push techniques

View synthesis, composed of depth-image-based rendering followed by hole-filling, is a crucial technology for 3D TV and free-viewpoint TV. To realize view synthesis in practical systems, the efficiency of view synthesis must be considered to achieve good a trade-off between the image quality and the computational complexity. We propose a efficient view synthesis scheme that, when compared to state-of-the-art backward warping, requires only half of the runtime with comparable quality. Specifically, the proposed scheme uses ray casting and pull-push processing to render in one pass, which can be regarded as applying 3D filters in the depth-image-based rendering. Moreover, the proposed scheme can benefit the hole-filling process to further improve the efficiency of view synthesis.
The Currency of Reciprocity - Gift-Exchange in the Workplace

What determines reciprocity in employment relations? We conducted a controlled field experiment to measure the extent to which monetary and nonmonetary gifts affect workers' performance. We find that nonmonetary gifts have a much stronger impact than monetary gifts of equivalent value. We also observe that when workers are offered the choice, they prefer receiving money, but reciprocate as if they received a nonmonetary gift. This result is consistent with the common saying, "it's the thought that counts. " We underline this point by showing that monetary gifts can effectively trigger reciprocity if the employer invests more time and effort into the gift's presentation.
Detecting Relations in the Gene Regulation Network

The BioNLP Shared Task 2013 is organised to further advance the field of information extraction in biomedical texts. This paper describes our entry in the Gene Regulation Network in Bacteria (GRN) part, for which our system finished in second place (out of five). To tackle this relation extraction task, we employ a basic Support Vector Machine framework. We discuss our findings in constructing local and contextual features, that augment our precision with as much as 7.5%. We touch upon the interaction type hierarchy inherent in the problem, and the importance of the evaluation procedure to encourage exploration of that structure.