Miracle-dz/UniFAR-FTUs huggingface dataset:
PromoterExplorer: an effective promoter identification method based on the AdaBoost algorithm

MOTIVATION Promoter prediction is important for the analysis of gene regulations. Although a number of promoter prediction algorithms have been reported in literature, significant improvement in prediction accuracy remains a challenge. In this paper, an effective promoter identification algorithm, which is called PromoterExplorer, is proposed. In our approach, we analyze the different roles of various features, that is, local distribution of pentamers, positional CpG island features and digitized DNA sequence, and then combine them to build a high-dimensional input vector. A cascade AdaBoost-based learning procedure is adopted to select the most 'informative' or 'discriminating' features to build a sequence of weak classifiers, which are combined to form a strong classifier so as to achieve a better performance. The cascade structure used for identification can also reduce the false positive. RESULTS PromoterExplorer is tested based on large-scale DNA sequences from different databases, including the EPD, DBTSS, GenBank and human chromosome 22. Experimental results show that consistent and promising performance can be achieved.
Top-k Publish-Subscribe for Social Annotation of News

Social content, such as Twitter updates, often have the quickest first-hand reports of news events, as well as numerous commentaries that are indicative of public view of such events. As such, social updates provide a good complement to professionally written news articles. In this paper we consider the problem of automatically annotating news stories with social updates (tweets), at a news website serving high volume of pageviews. The high rate of both the pageviews (millions to billions a day) and of the incoming tweets (more than 100 millions a day) make real-time indexing of tweets ineffective, as this requires an index that is both queried and updated extremely frequently. The rate of tweet updates makes caching techniques almost unusable since the cache would become stale very quickly. We propose a novel architecture where each story is treated as a subscription for tweets relevant to the story's content, and new algorithms that efficiently match tweets to stories, proactively maintaining the top-k tweets for each story. Such top-k pub-sub consumes only a small fraction of the resource cost of alternative solutions, and can be applicable to other large scale content-based publish-subscribe problems. We demonstrate the effectiveness of our approach on realworld data: a corpus of news stories from Yahoo! News and a log of Twitter updates.
Tests for High-Dimensional Covariance Matrices

We propose tests for sphericity and identity of high-dimensional covariance matrices. The tests are nonparametric without assuming a specific parametric distribution for the data. They can accommodate situations where the data dimension is much larger than the sample size, namely the “large p, small n” situations. We demonstrate by both theoretical and empirical studies that the tests have good properties for a wide range of dimensions and sample sizes. We applied the proposed test on a microarray dataset on Yorkshire Gilts and tested for the covariance structure for the expression levels for sets of genes.
Accurate Classification of Diffuse Large B-Cell Lymphoma into Germinal Center and Activated B-Cell Subtypes Using a Nuclease Protection Assay on Formalin-Fixed, Paraffin-Embedded Tissues

Classification of diffuse large B-cell lymphoma (DLBCL) into cell-of-origin (COO) subtypes based on gene expression profiles has well-established prognostic value. These subtypes, termed germinal center B cell (GCB) and activated B cell (ABC) also have different genetic alterations and overexpression of different pathways that may serve as therapeutic targets. Thus, accurate classification is essential for analysis of clinical trial results and planning new trials by using targeted agents. The current standard for COO classification uses gene expression profiling (GEP) of snap frozen tissues, and a Bayesian predictor algorithm. However, this is generally not feasible. In this study, we investigated whether the qNPA technique could be used for accurate classification of COO by using formalin-fixed, paraffin-embedded (FFPE) tissues. We analyzed expression levels of 14 genes in 121 cases of R-CHOP-treated DLBCL that had previously undergone GEP by using the Affymetrix U133 Plus 2.0 microarray and had matching FFPE blocks. Results were evaluated by using the previously published algorithm with a leave-one-out cross-validation approach. These results were compared with COO classification based on frozen tissue GEP profiles. For each case, a probability statistic was generated indicating the likelihood that the classification by using qNPA was accurate. When data were dichotomized into GCB or non-GCB, overall accuracy was 92%. The qNPA technique accurately categorized DLBCL into GCB and ABC subtypes, as defined by GEP. This approach is quantifiable, applicable to FFPE tissues with no technical failures, and has potential for significant impact on DLBCL research and clinical trial development. Clin Cancer Res; 17(11); 3727–32. ©2011 AACR.
Leaping Multiple Headers in a Single Bound: Wire-Speed Parsing Using the Kangaroo System

More fundamental than IP lookups and packet classification in routers is the extraction of fields such as IP Dest and TCP Ports that determine packet forwarding. While parsing of packet fields used to be easy, new shim layers (e.g., MPLS, 802.1Q, MAC-in-MAC) of possibly variable length have greatly increased the worst-case path in the parse tree. The problem is exacerbated by the need to accommodate new packet headers and to extract other higher layer fields. Programmable routers for projects such as GENI will need such flexible parsers. In this paper, we describe the design and implementation of the Kangaroo system, a flexible packet parser that can run at 40 Gbps even for worst-case packet headers. Because conventional solutions that traverse the parse tree one protocol at a time are too slow, Kangaroo uses lookahead to parse several protocol headers in one step using a new architecture in which a CAM directs the next set of bytes to be extracted. The challenge is to keep the number of CAM entries from growing exponentially with the amount of lookahead. We deal with this challenge using a non-uniform traversal of the parse tree, and an offline dynamic programming algorithm that calculates the optimal walk. Our experiments on a NetFPGA prototype show a speedup of 2 compared to an architecture with a lookahead of 1. The architecture can be implemented as a parsing block in a standard 400 MHz ASIC at 40 Gbps using less than 1% of chip area.
Adaptive Sliding-Mode Control for a Multiple-User Inductive Power Transfer System Without Need for Communication

A complicating aspect in the control design of resonant inductive power transfer systems is the absence of a direct communication link between primary and (multiple) secondary system sides. This paper introduces a new adaptive sliding-mode control surface, which continuously adapts the inductive system's input power to the required, but unknown, variable load power. As a result, an indirect communication link is redundant. Furthermore, due to matching input and output power, optimum relative system efficiency is automatically guaranteed in the entire system's output power range. The controller design, which has a simple analog implementation, has been verified with a dual-load experimental contactless system.
Sources of carbon and the evolution of the abundance of CNO elements

Using the standard infall model of Galactic chemical evolution, we explore the origin of carbon and calculate the abundance evolution of CNO elements for 8 dierent models of stellar nucleosynthesis yields. The results show that, in the early stage of the Galaxy, massive stars are the main producer of carbon, and that as our Galaxy evolves to the late stage, the longer lived intermediate- and low-mass stars play an increasingly important role, while at the same time, metal-rich Wolf-Rayet stars eject a signicant amount of carbon into the ISM by radiative-driven stellar winds. However, from the present published nucleosynthesis yields we cannot distinguish whether the main source of carbon in the late Galactic stage is just the massive stars ( M> 8 M) alone, or just the intermediate-, low-mass stars and M 40 M massive stars that do not go through the Wolf-Rayet stage. The 12 C(; ) 16 O reaction rate is very important in the stellar nucleosynthesis calculations: a lower rate will give a higher yield of carbon. The contribution to nitrogen is dominated by intermediate- and low-mass stars, and the secondary source of massive stars cannot explain the observed (N/Fe) in metal-poor stars. Most of oxygen is produced by massive stars. The fact that a higher O abundance in metal-poor stars is derived from the O i 7771 7775 A triplet than from the forbidden (O i) line at 6300 A poses a problem.
One-class methods for separating plant/pathogen sequences

Discovery of host and pathogen genes expressed at the plant/pathogen interface often requires the construction of mixed libraries that contain sequences from both genomes. Recently, methods for identifying plant and pathogen sequences based on codon usage bias have been developed. However, in these methods to have sequence information from both the plant and the pathogen before hand is required. Although sequences from the former are easy to obtain, sequences from the pathogen may not be available. For instance, this sequences are difficult to obtain for obligate parasites or when the parasite is not known. In this work we apply one-class methods to this problem of separating sequences from plants and pathogens. One-class methods are used to tell two class apart, but the classifier is designed using only information for one of the two classes. In this way, our approach allows the distinction between plant and pathogen sequences having only information from sequences of the plant. Different one-class methods are applied and their results are discussed.
Isorhamnetin Protects against Doxorubicin-Induced Cardiotoxicity In Vivo and In Vitro

Doxorubicin (Dox) is an anthracycline antibiotic for cancer therapy with limited usage due to cardiotoxicity. Isorhamnetin is a nature antioxidant with obvious cardiac protective effect. The aim of this study is going to investigate the possible protective effect of isorhamnetin against Dox-induced cardiotoxicity and its underlying mechanisms. In an in vivo investigation, rats were intraperitoneally (i.p.) administered with Dox to duplicate the model of Dox-induced chronic cardiotoxicity. Daily pretreatment with isorhamnetin (5 mg/kg, i.p.) for 7 days was found to reduce Dox-induced myocardial damage significantly, including the decline of cardiac index, decrease in the release of serum cardiac enzymes and amelioration of heart vacuolation. In vitro studies on H9c2 cardiomyocytes, isorhamnetin was effective to reduce Dox-induced cell toxicity. A further mechanism study indicated that isorhamnetin pretreatment can counteract Dox-induced oxidative stress and suppress the activation of mitochondrion apoptotic pathway and mitogen-activated protein kinase pathway. Isorhamnetin also potentiated the anti-cancer activity of Dox in MCF-7, HepG2 and Hep2 cells. These findings indicated that isorhamnetin can be used as an adjuvant therapy for the long-term clinical use of Dox.
PEPPHER: Efficient and Productive Usage of Hybrid Computing Systems

PEPPHER, a three-year European FP7 project, addresses efficient utilization of hybrid (heterogeneous) computer systems consisting of multicore CPUs with GPU-type accelerators. This article outlines the PEPPHER performance-aware component model, performance prediction means, runtime system, and other aspects of the project. A larger example demonstrates performance portability with the PEPPHER approach across hybrid systems with one to four GPUs.
Error mining: Bug detection through comparison with large code databases

Bugs are hard to find. Static analysis tools are capable of systematically detecting predefined sets of errors, but extending them to find new error types requires a deep understanding of the underlying programming language. Manual reviews on the other hand, while being able to reveal more individual errors, require much more time. We present a new approach to automatically detect bugs through comparison with a large code database. The source file is analyzed for similar but slightly different code fragments in the database. Frequent occurrences of common differences indicate a potential bug that can be fixed by applying the modification back to the original source file. In this paper, we give an overview of the resulting algorithm and some important implementation details. We further evaluate the circumstances under which good detection rates can be achieved. The results demonstrate that consistently high detection rates of up to 50% are possible for certain error types across different programming languages.
Differential remodeling of mono‐ and trimethylated H3K27 during porcine embryo development

Histone methylation plays an important role in regulating chromatin structure and gene expression. Methylation of the lysine residue 27 of histone H3 (H3K27) is an epigenetic mark that is closely linked with transcriptional repression; global patterns of H3K27 methylation undergo dramatic changes during cleavage development in the mouse. The aim of this study was to characterize the H3K27 methylation pattern in cleavage stage porcine embryos obtained either by in vivo or in vitro fertilization or parthenogenetic activation and to determine the expression patterns of EED, EZH2, and SUZ12 (regulators of H3K27 methylation). We found that monomethylated H3K27 was detectable in the nuclei of oocytes and pronuclear, 2‐cell, 4‐cell, 8‐cell, and blastocyst stage embryos. Trimethylated H3K27 was detectable in the nuclei of GV stage oocytes, the chromosome of MII stage oocytes and a single pronucleus of the pronuclear stage embryos produced by fertilization; the signals were faint or absent in nuclei of two‐cell through blastocyst stage embryos. In addition, EED transcripts were increased from the four‐cell stage (P < 0.05) in embryos obtained by in vitro fertilization, parthenogenetic activation and in vivo fertilization. EZH2 transcript levels were highest in the GV‐stage oocyte (P < 0.05). SUZ12 transcripts were transiently increased at the four‐cell stage (P < 0.05) in parthenogenetic and in vivo derived embryos. Our results suggest that H3K27 trimethylation is an epigenetic marker of maternally derived chromatin that is globally remodeled during porcine embryogenesis. Mol. Reprod. Dev. 76: 1033–1042, 2009. © 2009 Wiley‐Liss, Inc.
The impact of mobility on HIV control: a modelling study

SUMMARY Mobility is associated with HIV due to more risky sexual behaviour of mobile groups such as travellers and migrants. Limited participation of such groups may reduce the effectiveness of HIV interventions disproportionally. The established STDSIM model, which simulates transmission and control of HIV and STD, was extended to simulate mobility patterns based on data from Tanzania. We explored the impact of non-participation of mobile groups (travellers and recent migrants) on the effectiveness of two interventions: condom promotion and health education aiming at partner reduction. If mobile groups do not participate, the effectiveness of both interventions could be reduced by 40%. The impact of targeting travellers with a combined HIV campaign is close to that of a general population intervention. In conclusion, it is important to account for possible non-participation of migrants and travellers. If non-participation is substantial, impact of interventions can be greatly improved by actively approaching these people.
Evaluation of Models Describing the Growth of Nalidixic Acid-Resistant E. coli O157:H7 in Blanched Spinach and Iceberg Lettuce as a Function of Temperature

The aim of this study was to model the growth of nalidixic acid-resistant E. coli O157:H7 (E. coli O157:H7NR) in blanched spinach and to evaluate model performance with an independent set of data for interpolation (8.5, 13, 15 and 27 °C) and for extrapolation (broth and fresh-cut iceberg lettuce) using the ratio method and the acceptable prediction zone method. The lag time (LT), specific growth rate (SGR) and maximum population density (MPD) obtained from each primary model were modeled as a function of temperature (7, 10, 17, 24, 30, and 36 °C) using Davey, square root, and polynomial models, respectively. At 7 °C, the populations of E. coli O157:H7NR increased in tryptic soy broth with nalidixic acid (TSBN), blanched spinach and fresh-cut iceberg lettuce, while the populations of E. coli O157:H7 decreased in TSB after 118 h of LT, indicating the risk of nalidixic acid-resistant strain of E. coli O157:H7 contaminated in ready-to-eat produce at refrigerated temperature. When the LT and SGR models of blanched spinach was extended to iceberg lettuce, all relative errors (percentage of RE = 100%) were inside the acceptable prediction zone and had an acceptable Bf and Af values. Thus, it was concluded that developed secondary models for E. coli O157:H7NR in blanched spinach were suitable for use in making predictions for fresh cut iceberg lettuce, but not for static TSBN in this work.
Potential of the bioflavonoids in the prevention/treatment of ocular disorders

Objectives Flavonoids are a common group of plant polyphenols that give colour and flavour to fruits and vegetables. In recent years, flavonoids have gained importance in the pharmaceutical field through their beneficial effects on human health and are widely available as nutritional supplements. Several pharmacological actions of the bioflavonoids may be useful in the prevention or treatment of ocular diseases responsible for vision loss such as diabetic retinopathy, macular degeneration and cataract. This review aims to summarize the potential therapeutic applications of various bioflavonoids in different ocular diseases and also discusses delivery of these agents to the ocular tissues.
Synthesis of Broadband True-3D Metamaterial Artificial Magnetic Conductor Ground Planes Using Genetic Programming

The development and use of genetic programming (GP) software to synthesize true-3D artificial magnetic conductor (AMC) ground planes is presented, with the focus on achieving a lower frequency response (particularly in the high VHF to low UHF bands), low-profile, broadband designs without the use of absorbing or magnetic materials. Metallic 3D patterns are embedded in one or more substrate layers with a PEC bottom, and the patterning in the unit cell is allowed to extend into neighboring unit cells, thus achieving a lower frequency response with much smaller unit cell size and thickness. Four designs synthesized using the developed GP software are presented with achieved bandwidths ranging from 32.7% to 71.1% when using the ±90° reflection phase criterion. Further, it is shown that through the use of a parametric study, the center frequency (0 ° reflection phase) of one of the designs can be reduced from 381.3 MHz to 87.8 MHz, which is a 77% reduction. The edge of the square unit cell size for this miniaturized design is λ0/51 and the thickness is λ0/61 at 83.9 MHz.
The value and validation of broad spectrum biosensors for diagnosis and biodefense

Broad spectrum biosensors capable of identifying diverse organisms are transitioning from the realm of research into the clinic. These technologies simultaneously capture signals from a wide variety of biological entities using universal processes. Specific organisms are then identified through bioinformatic signature-matching processes. This is in contrast to currently accepted molecular diagnostic technologies, which utilize unique reagents and processes to detect each organism of interest. This paradigm shift greatly increases the breadth of molecular diagnostic tools with little increase in biochemical complexity, enabling simultaneous diagnostic, epidemiologic, and biothreat surveillance capabilities at the point of care. This, in turn, offers the promise of increased biosecurity and better antimicrobial stewardship. Efficient realization of these potential gains will require novel regulatory paradigms reflective of the generalized, information-based nature of these assays, allowing extension of empirical data obtained from readily available organisms to support broader reporting of rare, difficult to culture, or extremely hazardous organisms.
Creating Tutorials with Web-Based Authoring and Heads-Up Capture

Tutorials are one of the most fundamental means of conveying knowledge. Ideally, tutorials not only describe each step via text or audio narration but show it as well using photos or animation. In most cases, tutorial authors capture media from handheld mobile devices to import into these documents, but increasingly they use wearable devices as well. Here, the authors explore the use of head-mounted capture for authoring tutorials. They have developed a media capture tool for Google Glass that requires minimal attention to the capture device and instead allows the author to focus on creating the tutorial content. They describe a study comparing standalone (camera-on-tripod) versus wearable (Google Glass) capture, showing that tutorial authors prefer wearable capture devices, especially when recording activities involving larger objects in nontabletop environments. This article is part of a special issue on digitally enhanced reality.
Learning and the sources of corporate growth

This paper explores the link between learning and corporate growth by developing different models of learning and showing that they produce observably different models of corporate growth. Using data on the growth of a number of firms in the US automobile industry during the 20th century, we compare these different models of growth in an effort to identify the major sources of learning which these firms seem to have relied on. Although there are interesting differences between growth processes before and after the Second World War, the basic conclusion that we are drawn to is that learning in this sector is largely unsystematic and opportunistic. Copyright 2002, Oxford University Press.
Diferentes perfiles de identificación organizacional: influencia sobre el favoritismo endogrupal y las conductas de ciudadanía

Resumen El objetivo principal de este trabajo es explorar los procesos de categorización del yo en niveles subordinados y supraordenados en contextos organizacionales y sus antecedentes y resultados actitudinales y conductuales. Dos perfiles diferentes de identificación social en una muestra de profesores de primaria se han propuesto (N = 119), la orientación hacia el subgrupo y la orientación global. Usando modelos de ecuaciones estructurales los resultados muestran que el tamaño del subgrupo, el contacto del subgrupo, la discriminación percibida y la competición entre grupos son predictores relevantes de los perfiles de identificación social. Más aún, la orientación hacia el subgrupo predice el favoritismo endogrupal mientras la orientación global predice las conductas de ciudadanía globales.