Miracle-dz/UniFAR-FTUs huggingface dataset:
In vivo BiFC analysis of Y14 and NXF1 mRNA export complexes: preferential localization within and around SC35 domains

The bimolecular fluorescence complementation (BiFC) assay, which allows the investigation of interacting molecules in vivo, was applied to study complex formation between the splicing factor Y14 and nuclear export factor 1 (NXF1), which evidence indicates are functionally associated with nuclear mRNA. Y14 linked to the COOH terminus of yellow fluorescent protein (YFP; YC-Y14), and NXF1 fused to the NH2 terminus of YFP (YN-NXF1) expressed in MCF7 cells yielded BiFC upon specific binding. Fluorescence accumulated within and around nuclear speckles, suggesting the involvement of speckles in mRNA processing and export. Accordingly, BiFC depended on transcription and full-length NXF1. Coimmunoprecipitation of YC-Y14 with YN-NXF1, NXF1, Y14, and RNA indicated that YC-Y14 and YN-NXF1 functionally associate with RNA. Fluorescence recovery after photobleaching and fluorescence loss in photobleaching revealed that roughly half of the accumulated BiFC complexes were immobile in vivo. This immobile fraction was readily depleted by adenosine triphosphate (ATP) administration in permeabilized cells. These results suggest that a fraction of RNA, which remains in the nucleus for several hours despite its association with splicing and export proteins, accumulates in speckles because of an ATP-dependent mechanism.
Minimization Over Boolean Graphs

This paper presents a systematic procedure for thed esign of gate-type combinational switching circuits without diredted loops. Each such circuit (Boolean graph) is in correspondence with a sequence of decompositions of the Boolean function which it realizes. A general approach to functional decomposition i s given and, in terms oaf convenient positional representation, efficient tests for the detection of decompositions are derived. These results are employed in the development of an alphabetic search procedure for determining minimum-cost Boolean graphs which satisfy any given design specifications.
KRAS mutation testing in the treatment of metastatic colorectal cancer with anti-EGFR therapies

Survival of patients with metastatic CRC (mCRC) has improved steadily over the past several decades, due largely to the development of new combinations of standard chemotherapy, as well as to the introduction of new targeted therapies. Among the available targeted therapies are two monoclonal antibodies that target the epidermal growth factor receptor (EGFR) – cetuximab and panitumumab – which have demonstrated efficacy in the treatment of mCRC. These therapies are associated with a unique set of toxicities and costs, prompting the need for tools to select patients who are most likely to derive a benefit from them. Mutations in the KRAS oncogene have consistently been shown to predict non-response to cetuximab and panitumumab. The role of KRAS as a marker of efficacy of anti-EGFR therapies is reviewed.
Computing Equivalent Transformations for Combinatorial Optimization by Branch-and-Bound Search

Branch-and-Bound search is a basic algorithm for solving combinatorial optimization problems. Here we introduce a new lower-bounding methodology that can be incorporated into any branch-and-bound solver, and demonstraint its use on the MaxSAT constraint optimization problem. The approach is to adapt a “minimum-height equivalent transformation” framework that was first developed in the context of computer vision. We present efficient algorithms to realize this framework within the MaxSAT domain, and demonstrate their feasibility by implementing them within the state-of-the-art maxsatz solver. We evaluate the solver on test sets from the 2009 MaxSAT competition; we observe a basic performance tradeoff whereby the (quadratic) time cost of computing the transformations may or may not be worthwhile in exchange for better bounds and more frequent pruning. For specific test sets, the trade-off does result in significant improvement in both prunings and overall run-time.
Highly purified eicosapentaenoic acid ameliorates cardiac injury and adipose tissue inflammation in a rat model of metabolic syndrome

n‐3 Polyunsaturated fatty acids such as eicosapentaenoic acid (EPA), which are abundant in fish oil, have been shown to delay the onset of cardiovascular events. We previously established DahlS.Z‐Leprfa/Leprfa (DS/obese) rats, which are derived from a cross between Dahl salt‐sensitive and Zucker rats, as a model of metabolic syndrome. This study has now explored the influence of highly purified EPA on cardiac and adipose tissue pathophysiology in this animal model.
Multi-Label Hierarchical Classification for Protein Function Prediction

— Hierarchical classification is a problem with applications in many areas as protein function prediction where the dates are hierarchically structured. Therefore, it is necessary the development of algorithms able to induce hierarchical classification models. This paper presents experimenters using the algorithm for hierarchical classification called Multi-label Hierarchical Classification using a Competitive Neural Network (MHC-CNN). It was tested in ten datasets the Gene Ontology (GO) Cellular Component Domain. The results are compared with the Clus-HMC and Clus-HSC using the hF-Measure.
1 Temporal Rules and Temporal Decision Trees : A C 4 . 5 Approach

Decision trees are useful tools for classification and prediction purposes, and have been applied mostly to data that is void of any explicit notion of time. This covers many application areas where the data is about populations of the same entities, but is not suitable for cases where there is a temporal relation among the data. One case is when we are gathering data about a single system over time. In this paper we use a toy domain to show how flattening such data by merging consecutive records into a single one enables a classifier such as C4.5 to be used for rule discovery over time. C4.5 does not understand time, so all temporal information is lost in the output. In this paper we propose to include time in decision trees and rules derived from them. We have modified parts of the C4.5 Release 8 package to make time explicit and generate temporal rules and decision trees. We show that building a temporal decision tree is an instance of solving a Constraint Satisfaction Problem. We finally show how temporal rules or temporal decision trees can be interpreted as plans for robots with sensors and actuators. Such plans tell us what to do at each time step, and what to expect in the following time step.
Structural Damage Detection using Independent Component Analysis

This paper presents a novel approach to detect structural damage based on combining independent component analysis (ICA) extraction of time domain data and artificial neural networks (ANN). The advantage of using time history measurements is that the original vibration information is used directly. However, the volume of data, measurement noise and the lack of reliable feature extraction tools are the major obstacles. To circumvent them, the independent component analysis technique is applied to represent the measured data with a linear combination of dominant statistical independent components and the mixing matrix [A]. Such a representation captures the essential structure of the measured vibration data. The vibration features represented by the mixing matrix provide the relationship between the measured vibration response and the independent components and are then employed to build the simplified neural network model for damage detection. Two examples are included to demonstrate the effectiveness of the method. First, a truss structure with simulated displacement data was used, and the results show that healthy and damage states located in the nine elements may be classified. Second, a bookshelf structure together with measured time history data from 24 piezoelectric single axis accelerometers was used to demonstrate the approach on a physical structure. The results show the successful detection of the undamaged and damaged states with very good accuracy and repeatability.
Freezing injury in onion bulb cells: I. Evaluation of the conductivity method and analysis of ion and sugar efflux from injured cells.

Onion (Allium cepa L.) bulbs were frozen to -4 and -11 C and kept frozen for up to 12 days. After slow thawing, a 2.5-cm square from a bulb scale was transferred to 25 ml deionized H(2)O. After shaking for standard times, measurements were made on the effusate and on the effused cells. The results obtained were as follows.Even when the scale tissue was completely infiltrated, and when up to 85% of the ions had diffused out, all of the cells were still alive, as revealed by cytoplasmic streaming and ability to plasmolyze. The osmotic concentration of the cell sap, as measured plasmolytically, decreased in parallel to the rise in conductivity of the effusate. The K(+) content of the effusate, plus its assumed counterion, accounted for only 20% of the total solutes, but for 100% of the conductivity. A large part of the nonelectrolytes in the remaining 80% of the solutes was sugars.The increased cell injury and infiltration in the -11 C treatment, relative to the -4 C and control (unfrozen) treatments, were paralleled by increases in conductivity, K(+) content, sugar content, and pH of the effusate. In spite of the 100% infiltration of the tissue and the large increase in conductivity of the effusate following freezing, no increase in permeability of the cells to water could be detected.The above observations may indicate that freezing or thawing involves a disruption of the active transport system before the cells reveal any injury microscopically.
A comparative analysis of time-frequency decompositions in polyphonic pitch estimation

In a monaural polyphonic music context, time-frequency information used by most of the multiple fundamental frequency estimation systems, extracted from temporal-domain of the polyphonic signal, is mainly computed using fixed-resolution or variable resolution time-frequency decompositions. This time-frequency information is crucial in the polyphonic estimation process because it must clearly represent all useful information in order to find the set of active pitches. In this paper, we present a preliminary study analyzing two different decompositions, Constant Q Transform and Short Time Fourier Transform, which are integrated in the same multiple fundamental frequency estimation system, with the aim of determining what decomposition is more suitable for polyphonic musical signal analysis and how each of them influences in the accuracy results of the polyphonic estimation considering low-middle-high frequency evaluation.
Sex Differences in the Connectivity of the Subgenual Anterior Cingulate Cortex: Implications for Pain Habituation

Women exhibit greater habituation to painful stimuli than men. The neural mechanism underlying this sex difference is unknown. However, pain habituation has been associated with pain-evoked activity of the subgenual anterior cingulate cortex (sgACC), implicating a connection between the sgACC and the descending pain antinociceptive system. Therefore, the thesis hypothesis was that women have stronger connectivity than men between the sgACC and the descending antinociceptive system. Healthy subjects provided informed consent. 3T MRI images included anatomical diffusion-weighted imaging for structural connectivity analyses (SC) with probabilistic tractography and resting-state functional images for functional connectivity (FC) analyses. Women had stronger sgACC FC with nodes of the descending pain modulation system (raphe, PAG) and the medial thalamus. In contrast, men had stronger sgACC FC with nodes of the salience/attention network (anterior insula, TPJ) and stronger sgACC SC with the hypothalamus. These findings implicate a mechanism for pain habituation and its associated sex differences.
Avatar movement in World of Warcraft battlegrounds

Evaluating DVE topology management and message propagation schemes requires avatar movement models. Most models are based on reasoned assumptions rather than measured data, potentially biasing evaluation. We measured player movement in World of Warcraft battlegrounds, and compared our observations against common assumptions about player avatar movement and navigation. We found that when modeling a highly interactive DVE such as a battleground, a waypoint model is not sufficient to describe most avatar movement. We were surprised to find that despite game incentives for grouping, the majority of avatar movement between objectives is individual, not grouped. Finally, we found that a hotspot-based model for avatar movement is consistent with our traces.
A Novel Approach to Evade Attacks in Online Social Networks

Anonymization of published social network data has become an important research topic nowadays. The major concern is to publish data of individuals in such a manner that the released table not only provides the essential information to be used by researchers but also prevents the disclosure of sensitive information. Various techniques like K-anonymity, L-diversity and T-closeness have been proposed to achieve anonymization of the data. K-anonymity suffers from various limitations such as it cannot prevent attribute disclosure and also results in homogeneity and background knowledge attacks. This paper mainly deals with handling these two attacks that break the privacy constraints of K-anonymity. The proposed technique has been evaluated using real-time database gathered from Twitter social network. Experimental results show that the proposed technique not only prevents identity and attribute disclosure but at the same time is capable of handling attacks on K-anonymity by resulting in minimum information loss to the original data.
Three-Dimensional Face Shape by Local Fitting to a Single Reference Model

The authors present a simple method to estimate the three-dimensional shape of a face from an input image using a single reference model, based on least squares between the output of the linear-nonlinear (LN) neuronal model applied to blocks from an intensity image and blocks from a depth reference model. The authors present the results obtained by varying the LN model parameters and estimate their best values, which provide an acceptable reconstruction of each subject's depth. The authors show that increasing the light source angle over the horizontal plane in the input image produces slight increases in reconstruction error, but increasing the ambient light proportion produces greater increases in reconstruction error. The authors applied the method to predict each subject's unknown depth using different individual reference models and an average reference model, which provides the best results. As a noise reduction technique, the authors perform a point by point weighted averaging with the average reference model with weights equal to the fractions of the squares of the Laplacian of a Gaussian applied to the prediction and to the reference depth over the sum of both. Finally, the authors present acceptable visual results obtained from external images of faces under arbitrary illumination, having performed an illumination estimation previously.
RADIO OBSERVATIONS OF STELLAR WINDS FROM EARLY TYPE STARS

FifteenOandBsupergiantshavebeenobservedwith the Very Large Array (VLA) at 4.85, 8.45, and 14.95 GHz in order to make a detailed comparative study of the mass loss rates evaluated from H and radio continuum observations and revealandquantifypossibledeparturesfromstandardwindcon- ditions. We detected 12 sources, 7 of which for the rst time, thus increasing by 30% the total number of detections of OB supergiants in the northern sky. Radio spectral slopes indicate that the radio emission is mainly of thermal origin in all objects with one exception (HD 190603) out of the 12 detections. Our results demonstrate the value of using H for mass loss rate de- terminations, especially for stars that are too distant or too faint tobedetectedwithradiotechniques.Therelationship _ M Lfor supergiants turns out to be appreciably flatter than commonly reported, i.e. log _ M =( 1:25 0:30)logL.
Building Strength: Strength Training Attitudes and Behaviors of All-Women's and Coed Gym Exercisers

Research suggests varied reasons why women may avoid engaging in a regular strength training routine at the gym in favor of performing cardiovascular exercise (e.g., Harne & Bixby, 2005). However, there has been little research focused on the potential role of the gym environment itself, specifically in terms of the presence of men. The current study compared women members of all-women’s and coed fitness facilities on their attitudes toward different exercise activities as well as their exercise choices within the gym. A community sample of women from the Northeast US, who attended either an all-women’s or coed gym ( N = 635), filled out a series of online questionnaires. We hypothesized that all-women gym members would report more positive attitudes towards strength training and would report attitudes towards strength training and cardio that were more similar in favorability compared with coed gym members. In addition, we expected all-women exercisers to engage in strength training activities (e.g., weight machine or free weights) more frequently than coed exercisers, especially if they also reported higher body dissatisfaction. Results were mixed and hypotheses received only partial support. Although all-women members rated strength training more positively and more similarly in magnitude to cardio compared with coed members, little differences were found between groups on strength training behaviors. Null findings are discussed in light of existing socio-cultural beauty and exercise norms that may deter women from engaging in strength training irrespective of male presence within the gym environment. More research is needed to explore the potential positive and negative consequences of same-sex and mixed-sex fitness settings for women’s physical and mental health.
Dynamic process monitoring method based on recursive generalized eigenvalue decomposition using temporal covariance matrix

A new dynamic process monitoring method for flow industry production was investigated. The proposed method utilized generalized eigenvalue decomposition (GED), which involved temporal covariance matrix pencil, to deal with the dynamic character of process. The recursive approach of GED was also used to make the algorithm wieldier to practical applications. Compared with dynamic PCA, the new method performs better in sensitivity and robustness of the monitoring effect and can be hardly affected in computation cost when involving more temporal samples. The simulation using Tennessee-Eastman process shows the validity and superiority of the proposed method.
A Bayesian approach for multi‐model downscaling: Seasonal forecasting of regional rainfall and river flows in South America

This study addresses three issues: spatial downscaling, calibration, and combination of seasonal predictions produced by different coupled ocean‐atmosphere climate models. It examines the feasibility of using a Bayesian procedure for producing combined, well‐calibrated downscaled seasonal rainfall forecasts for two regions in South America and river flow forecasts for the Paraná river in the south of Brazil and the Tocantins river in the north of Brazil. These forecasts are important for national electricity generation management and planning. A Bayesian procedure, referred to here as forecast assimilation, is used to combine and calibrate the rainfall predictions produced by three climate models. Forecast assimilation is able to improve the skill of 3‐month lead November‐December‐January multi‐model rainfall predictions over the two South American regions. Improvements are noted in forecast seasonal mean values and uncertainty estimates. River flow forecasts are less skilful than rainfall forecasts. This is partially because natural river flow is a derived quantity that is sensitive to hydrological as well as meteorological processes, and to human intervention in the form of reservoir management. Copyright © 2006 Royal Meteorological Society.
Intelligent Agents for Bilingual Information Retrieval from the World Wide Web

This paper presents a proposal of a multi-agent information retrieval system to help users in finding the required documents on the WWW. The proposed system architecture contains several components mainly: the interface agent, learning agent, filtering agent, searching agent, user profile, text information extractor, and others. The evolutionary mechanism of the proposed system is based on the concepts of genetic algorithms (GAs). New filtering agents are created by the genetic operators such as crossover and mutation. The filter agent filters the obtained results and lists to the user a reduced number of documents with high probability of being relevant to him/her. That filtering is based on a user profile such that the learning agent builds by analyzing the document examples presented by the user.
Conflict-aware event-participant arrangement

With the rapid development of Web 2.0 and Online To Offline (O2O) marketing model, various online event-based social networks (EBSNs), such as Meetup and Whova, are getting popular. An important task of EBSNs is to facilitate the most satisfactory event-participant arrangement for both sides, i.e. events enroll more participants and participants are arranged with personally interesting events. Existing approaches usually focus on the arrangement of each single event to a set of potential users, and ignore the conflicts between different events, which leads to infeasible or redundant arrangements. In this paper, to address the shortcomings of existing approaches, we first identify a more general and useful event-participant arrangement problem, called Global Event-participant Arrangement with Conflict and Capacity (GEACC) problem, focusing on the conflicts of different events and making event-participant arrangements in a global view. Though it is useful, unfortunately, we find that the GEACC problem is NP-hard due to the conflict constraints among events. Thus, we design two approximation algorithms with provable approximation ratios and an exact algorithm with pruning technique to address this problem. Finally, we verify the effectiveness and efficiency of the proposed methods through extensive experiments on real and synthetic datasets.
Seeding for sirtuins: microseed matrix seeding to obtain crystals of human Sirt3 and Sirt2 suitable for soaking

In the present study, microseed matrix seeding was successfully applied to obtain a large number of crystals of the human sirtuin isotypes Sirt2 and Sirt3. These crystals appeared predictably in diverse crystallization conditions, diffracted to a higher resolution than reported in the literature and were subsequently used to study the protein–ligand interactions of two indole inhibitors.
Term extraction using machine learning

In this term paper I motivate and describe a monolingual term extraction method using the Ripper machine learning algorithm and linguistic and statistical features of n-grams extracted from a patent text corpus. The n-grams are labeled as terms or non-terms using a manually validated term list based on the same patent text corpus. The results for experiments conducted show promise for further research as the method allows for evaluation of termness metrics and provides data for theoretical analysis on termness.