Miracle-dz/UniFAR-FTUs huggingface dataset:
The Coordination of Gene Expression within Photosynthesis Pathway for Acclimation of C4 Energy Crop Miscanthus lutarioriparius

As a promising candidate for the second-generation C4 energy crop, Miscanthus lutarioriparius has well acclimated to the water-limited and high-light Loess Plateau in China by improving photosynthesis rate and water use efficiency (WUE) compared to its native habitat along Yangtze River. Photosynthetic genes were demonstrated as one major category of the candidate genes underlying the physiological superiority. To further study how photosynthetic genes interact to improve the acclimation potential of M. lutarioriparius, population expression patterns within photosynthesis pathway were explored between one mild environment and one harsh environment. We found that 108 transcripts in assembled transcriptome of M. lutarioriparius were highly similar to genes in three Kyoto Encyclopedia of Genes and Genomes (KEGG) photosynthesis pathways of sorghum and maize. Phylogenetic analyses using sorghum, maize, rice, and Arabidopsis genes of dark reaction identified 23 orthologs and 30 paralogs of M. lutarioriparius photosynthetic genes. These genes were also clustered into two kinds of expression pattern. 87% of transcripts in dark reaction were up-regulated and all 14 chloroplast-encoded transcripts in light reaction increased degradation in the harsh environment compared to the mild environment. Moreover, 80.8% of photosynthetic transcripts were coordinated at transcription level under the two environments. Interestingly, LHCI and PSI were significantly correlated with F-ATPase and C4 cycle. Overall, this study indicates the coordinated expression between cyclic electron transport (consisting of LHCI, PSI, and ATPase) and CO2-concentrating mechanism (C4 cycle) could account for photosynthesis plasticity on M. lutarioriparius acclimation potential.
The World Wide Web Presents Significant Opportunities Redips: Backlink Search and Analysis on the Web for Business Intelligence Analysis

for business intelligence analysis as it can provide information about a company's external environment and its stakeholders. Traditional business intelligence analysis on the Web has focused on simple keyword searching. Recently, it has been suggested that the incoming links, or backlinks, of a company's Web site (i.e., other Web pages that have a hyperlink pointing to the company of interest) can provide important insights about the com-pany's " online communities. " Although analysis of these communities can provide useful signals for a company and information about its stakeholder groups, the manual analysis process can be very time-consuming for business analysts and consultants. In this article, we present a tool called Redips that automatically integrates backlink meta-searching and text-mining techniques to facilitate users in performing such business intelligence analysis on the Web. The architectural design and implementation of the tool are presented in the article. To evaluate the effectiveness, efficiency, and user satisfaction of Redips, an experiment was conducted to compare the tool with two popular business intelligence analysis methods—using backlink search engines and manual browsing. The experiment results showed that Redips was statistically more effective than both benchmark methods (in terms of Recall and F-measure) but required more time in search tasks. In terms of user satisfaction, Redips scored statistically higher than backlink search engines in all five measures used, and also statistically higher than manual browsing in three measures. Introduction Business intelligence can be defined as the process of monitoring a firm's external environment to obtain information relevant to its decision-making process (Gilad & Gilad, 1988). In the past, the sources of business intelligence information mainly consisted of published company reports, subscription-based online databases, and other kinds of printed information. However, this practice has changed significantly in the past 10 years. With the advances in information technologies, many resources and information are now accessible on the Web. In late 2004, Google announced that they had indexed more than 8 billion Web pages. The Web has become a large repository of information that could be relevant to a firm's decision making. For example, looking into the Web sites of a firm's competitors can reveal useful information about the firm's competitive environment (Chen, Chau, & Zeng, 2002). The Web sites of other stakeholders of the firm, like customers, suppliers, and pressure groups, can also provide important information about the firm's competitive environment. As the Web sites of these stakeholders often have …
Association Study on ADAM33 Polymorphisms in Mite-Sensitized Persistent Allergic Rhinitis in a Chinese Population

Background The ADAM33 gene has been identified as a potentially important asthma candidate gene and polymorphisms in this gene have been shown to be associated with asthma and seasonal allergic rhinitis. Objective To assess whether the ADAM33 polymorphisms are associated with persistent allergic rhinitis (PER) due to house dust mites in a Chinese population. Methods In a hospital-based case-control study of 515 patients with mite-sensitized PER and 495 healthy controls, we genotyped seven single nucleotide polymorphisms (SNPs) in ADAM33. Serum levels of eosinophil cationic protein, total IgE and allergen-specific IgE against Dermatophagoides pteronyssinus and Dermatophagoides farinae were measured by the ImmunoCAP assays. Results In the single-locus analysis, three polymorphisms, rs3918392 (F1), rs528557 (S2) and rs2787093, were significantly associated with mite-sensitized PER. SNP S2 was associated with significantly increased risk both of asthmatic and nonasthmatic mite-sensitized PER. In the combined genotypes analysis, individuals with 2–4 risk alleles had a significantly higher risk of mite-sensitized PER (adjusted OR = 1.99, 95% CI = 1.50–2.62) than those with 0–1 risk alleles. Haplotype-based association analysis revealed that the ACAGCCT haplotype might have potential to protect against mite-sensitized PER (adjusted OR = 0.67; 95% CI = 0.49–0.90). Conclusions Polymorphisms in the ADAM33 gene may contribute to susceptibility of mite-sensitized PER in this Chinese population.
Discovering Leadership Roles in Email Workgroups

Email is a key communication tool for collaborative workgroups. In this paper, we investigate how team leadership roles can be inferred from a collection of email messages exchanged among team members. This task can be useful to monitor group leader’s performance, as well as to study other aspects of work group dynamics. Using a large email collection with several workgroups whose leaders were previously defined, we demonstrate that leadership positions can be predicted by a combination of trac-based and textbased email patterns. Trac-based patterns consist of information patterns that can be extracted from the message headers, such as frequency counts, message thread position and whether the message was broadcast to the entire workgroup or not. Textual patterns are represented by the message’s “email speech acts”,i.e., semantic information with the sender’s intent that can be automatically inferred by language usage. Using o-the-shelf learning algorithms, we obtained 96% accuracy and 88.2% in F-measure in predicting the leadership roles on 34 email-centered work groups.
Exploiting User and Business Attributes for Personalized Business Recommendation

Data sparsity and cold-start are two major problems in personalized recommendation. They are especially severe in business recommendation, because business transactions are usually completed offline and customers generally do not provide ratings after a transaction. Due to these two problems, matrix factorization (MF) models, which are shown to be effective in many recommendation tasks, are likely to fail on business recommendation tasks, especially for new users and new items. In this paper, we propose an Integrated Bias and Factorization Model (IBFM), which exploits user and business attributes. The user attributes include demographic information, vote information, point-of-interests; the business attributes include check-in information, locations, business names, categories, etc. To handle the cold-start problem, we employ a sampling strategy to generate the latent factor vectors for new users and new businesses based on similar users/businesses. Our methods are evaluated on the data set used in the RecSys 2013 Yelp business rating prediction challenge. Experimental results show that our proposed methods significantly outperform several existing state-of-the-art methods. In particular, the single model IBFM performs the best in this challenge on both public and private leaderboards.
A Survey of Reasoning in Parallelization

We elaborate on reasoning in contemporary (semi) automatic parallelizing refactoring. As the main contribution we summarize contemporary approaches and show that all attempts to reason in parallelization thus far, have amounted to local code analysis given data and control dependencies. We conclude that, by retaining this perspective only, parallelization continues to exploit merely a subset of the reasoning methods available today and is likely to remain limited. To address this problem we suggest to expand the local analyses, such that, they take seriously relations between individual local parallelizing transformations. We argue that such a coupling allows to process sparser parallelizable constructs, such as, producer-consumer coordination. We identify questions to be addressed to put this principle into action and report on-going work on (reasoning) mechanisms able to support this.
Profiling Microblog Authors using Concreteness and Sentiment - Know-Center at PAN 2016 Author Profiling

The PAN 2016 author profiling task is a supervised classification problem on cross-genre documents (tweets, blog and social media posts). Our system makes use of concreteness, sentiment and syntactic information present in the documents. We train a random forest model to identify gender and age of a document’s author. We report the evaluation results received by the shared task.
Testing a Statistical Word Stemmer based on Affixality Measurements in INEX 2012 Tweet Contextualization Track

This paper presents an experiment of statistical word stemming based on a xality measurements. These measurements quantify three characteristics of language. In this experiment we tested one strategy of stemming with three di erent sizes of training data. The developed stemmer was used by the automatic summarization system Cortex to preprocess input texts and produce readable summaries. All summaries were evaluated as part of the INEX 2012 Tweet Contextualization Track. We present the results of evaluation and a discussion about our stemming strategy.
Acoustic Look-Ahead for More Efficient Decoding in LVCSR

In this paper we propose novel approximations of a generalized acoustic look-ahead to speed up the search process in large vocabulary continuous speech recognition (LVCSR). Unlike earlier methods, we do not employ any phoneme-or syllable level heuristics. First we deﬁne and analyze the perfect acoustic look-ahead as a simple pre-evaluation of the original acoustic models into the future. This method is very slow, but reveals the best possible impact on the search space that can be achieved through acoustic look-ahead. In a second step, we derive efﬁcient and simple approximative look-ahead models from the perfect models. We show that the approximative models compare well to the perfect models regarding the search space, and that the approximative models signiﬁcantly improve the ef-ﬁciency in comparison to the baseline, without any negative effect on the precision.
Implementation of blind source separation for multi-input

The present work shows, implementation of neural ICA algorithms with multiple inputs using VHDL Design in a Field Programmable Gate Array (FPGA). We designed an architecture modular using INFOMAX algorithm in order to add n inputs for audio signals. Some simulations results using VHDL are presented using music and voice recorded. The study of performance is made in a net 2times2 and also a net of 3times3.
A Framework For Performance Evaluation Of ASIPS In Network-Based IDS

Nowadays efficient usage of high -tech security tools and appliances is considered as an important criterion for security improvement of computer net works. Based on this assumption, Intrusion Detection and Prevention Systems (IDPS) have key role for applying the defense in depth strategy. In this situation, by increasing network bandwidth in addition to increasing number of threats, Network -based IDPSes have been faced with performance challenge for processing of huge traffic in the networks. A general solution for this bottleneck is exploitation of efficient hardware architectures for performance improvement of IDPS. In this paper a framework for analy sis and performance evaluation of application specific instruction set processors is presented for usage in application of attack detection in Networkbased Intrusion Detection Systems(NIDS). By running this framework as a security application on V850, OR1K, MIPS32, ARM7TDMI and PowerPC32 microprocessors, their performance has been evaluated and analyzed. For performance improvement, the compiler optimization levels are employed and at the end; base on O2 optimization level a new combination of optimization flags is presented. The experiments show that the framework results 18. 10% performance improvements for pattern matching on ARM7TDMI microprocessors.
A Spectral Algorithm with Applications to Exploring Data Graphs Locally

We provide an optimization characterization of a local version of the traditional spectral optimization problem used for finding graph cuts. Rather than computing an approximation to the best partition in the entire input graph, we are motivated by the problem of computing an approximation to the best partition near an input seed set. Such a primitive seems quite useful in improving and refining clusters locally in many settings such as data graphs, machine learning and image segmentation. From a theoretical perspective, we show that the solution to our non-convex optimization relaxation for this problem, referred to as LocalSpectral, may be computed as the solution to a system of linear equations. Interestingly, this also provides an optimization characterization of a generalization of Personalized PageRank vectors, which could be of independent interest. We also show that how to obtain Cheeger-like quality-ofapproximation guarantees when we round the solution to LocalSpectral; and that we can use these ideas to refine and improve given partitions in an input graph. We empirically illustrate the use of LocalSpectral in the analysis of data graphs.
Computationally Manageable Combinatorial Auctions the Authors Gratefully Acknowledge the National Science Foundation for Its Support under Grant Number Sbr 93-09333 to Rutgers University Aliated Graduate Student Member, Dimacs Graduate Assistant

There is interest in designing simultaneous auctions for situations in which the value of assets to a bidder depends upon which other assets he or she wins. In such cases, bidders may well wish to submit bids for combinations of assets. When this is allowed, the problem of determining the revenue maximizing set of noncon icting bids can be a di cult one. We analyze this problem, identifying several di erent structures of combinatorial bids for which computational tractability is constructively demonstrated and some structures for which computational tractability
A feature-adjusted naïve Bayes agorithm

Sentiment classification has been an important issue in natural language processing in recent years. In order to solve the distribution difference problem in cross-domain sentiment classification, we propose a featured-adjusted EM-based naïve Bayes algorithm which combines feature adaption and instance adaption simultaneously, and this algorithm can adjust the parameters in EM algorithm by the results of the feature adaption. The experimental results show that the proposed algorithm can improve the accuracy of cross-domain sentiment classification to some extent compared with the baseline algorithm.
Multi-matcher dynamic signature recognition with protected and renewable templates

In this paper we present a protected multi-matcher dynamic signature verification system which exploits score-level fusion techniques to combine Hidden Markov Model (HMM) and Dynamic Time Warping (DTW) classifiers. The considered on-line signature templates are treated with repeatable and non-invertible transformations, able to generate secure and renewable templates which can be fed to function-based matchers such as HMM and DTW. An extensive set of experiments shows that the combined use of HMM and DTW based classifiers guarantees remarkable performances in terms of both recognition rates and template renewability, while providing proper security to the employed biometrics.
An estimation of collective action cost in condominium reconstruction : the case of Japanese condominium law

This paper presents an empirical examination of the cost of collective action problems inherent in condominium reconstruction in Japan. Because of property co-ownership, problems associated with the decision-making process arise among owners of condominium units. Further, mechanisms of condominium law in Japan potentially induce a holdout problem in the decision-making process, resulting in the development of more serious collective action problems. By comparing the price functions of Japanese condominiums with those of rental apartments in Japan and condominiums in the United States, we clarify the presence of a collective action cost in Japanese condominium reconstruction and confirm that a deficiency exists in Japanese condominium law.
The Bed-Load Function for Sediment Transportation in Open Channel Flows

CONTENTS Page Introduction. 1 Approach to the problem. _ 3 Limitation of the bed-load function _ _ _ 4 The undetermined function 4 The alluvial stream. 5 The sediment mixture 6 Hydraulics of the alluvial channel. 7 The friction formula 7 The friction factor 8 Resistance of the bars 9 The laminar sublayer 10 The transition between hydraulically rough and smooth beds_ 12 The velocity fluctuations 13 Suspension 14 The transportation rate of suspended load 17 Integration of the suspended load. _ 17 Numerical integration of suspended load 19 Limit of suspension. 24 The bed layer 24 Practical calculation of suspended load___ ____ 25 Numerical example 26 Page Bed-load concept 29 Some constants entering the laws of bed-load motion: 31 The bed-load equation 32 The exchange time 33 The exchange probability 34 Determination of the probability V 35 Transition between bed load and. suspended load 38 The necessary graphs 40 Flume tests with sediment mixtures. 42 Sample calculation of a river reachl 44 Choice of a river reach 45 Description of a river reach_____ 45 Application of procedure to Big Sand Creek, Miss 46 Discussion of calculations 60 Limitations of the method____ 65 Summary. 67 Literature cited 68 Appendix 69 List of symbols. 69 Work charts _ 71
Explicit-enumeration based Veri cation made Memory-e cientRatan

| We investigate new techniques for reducing the memory requirements of an on-they model checking tool that employs explicit enumera-tion. Two techniques are studied in depth: exploiting symmetries in the model, and exploiting sequential regions in the model. These techniques can result in a signiicant reduction in memory requirements, and often nd progress violations at much lower stack depths. Both techniques have been implemented as part of the SPIN veriier, a widely used on-they model-checking tool.
Strong Convergence for URN Models with Reducible Replacement Policy

A multitype urn scheme with random replacements is considered. Each time a ball is picked, another ball is added, and its type is chosen according to the transition probabilities of a reducible Markov chain. The vector of frequencies is shown to converge almost surely to a random element of the set of stationary measures of the Markov chain. Its probability distribution is characterized as the solution to a fixed point problem. It is proved to be Dirichlet in the particular case of a single transient state to which no return is possible. This is no longer the case, however, as soon as returns to transient states are allowed.
The transition to early fatherhood: National estimates based on multiple surveys

This study provides systematic information about the prevalence of early male fertility and the relationship between family background characteristics and early parenthood across three widely used data sources: the 1979 and 1997 National Longitudinal Surveys of Youth and the 2002 National Survey of Family Growth. We provide descriptive statistics on early fertility by age, sex, race, cohort, and data set. Because each data set includes birth cohorts with varying early fertility rates, prevalence estimates for early male fertility are relatively similar across data sets. Associations between background characteristics and early fertility in regression models are less consistent across data sets. We discuss the implications of these findings for scholars doing research on early male fertility.
Characteristics of mobile robotic toys for children with pervasive developmental disorders

Pervasive developmental disorders (PDD) refers to a group of disorders characterized by delays in the development of multiple basic functions including socialization and communication. Symptoms may include communication problems such as using and understanding language; difficulty relating to people, objects, and events; unusual play with toys and other objects; difficulty with changes in routine or familiar surroundings, and repetitive body movements or behavior patterns. Autism is the most characteristic and best studied PDD. We are investigating the use of mobile robotic toys that can move in the environment and interact in various manners (vocal messages, music, visual cues, movement, etc.) with children with autism. The hypothesis is that mobile robots can serve as an appropriate pedagogical tool to help children with PDD develop social skills because they are more predictable and less intimidating. The objective is to see how such devices can be used to capture the child's attention and contribute to helping him or her develop social skills. This paper outlines the design considerations for such robots, and presents experimental protocols that are being developed to study the impacts of using these robots on the development of the child.