Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation and topology of the Mediator middle module

Mediator is the central coactivor complex required for regulated transcription by RNA polymerase (Pol) II. Mediator consists of 25 subunits arranged in the head, middle, tail and kinase modules. Structural and functional studies of Mediator are limited by the availability of protocols for the preparation of recombinant modules. Here, we describe protocols for obtaining pure endogenous and recombinant complete Mediator middle module from Saccharomyces cerevisiae that consists of seven subunits: Med1, 4, 7, 9, 10, 21 and 31. Native mass spectrometry reveals that all subunits are present in equimolar stoichiometry. Ion-mobility mass spectrometry, limited proteolysis, light scattering and small-angle X-ray scattering all indicate a high degree of intrinsic flexibility and an elongated shape of the middle module. Protein–protein interaction assays combined with previously published data suggest that the Med7 and Med4 subunits serve as a binding platform to form the three heterodimeric subcomplexes, Med7N/21, Med7C/31 and Med4/9. The subunits, Med1 and Med10, which bridge to the Mediator tail module, bind to both Med7 and Med4.
STRUCTURE ADAPTIVE METHODS IN IMAGE DENOISING

The nonparametric regression originated in mathematical statistics offers an original approach to signal processing problems (e.g., [1], [2]). It basically results in linear Þltering with the linear Þlters designed using some moving window local approximations. In many applications like speech recognition or image denoising, nonlinear or locally adaptive methods have been shown to be more efficient than the linear ones. The typical examples are given by non-linear wavelet thresholding, [3], and pointwise adaptive kernel smoothing, [4], [5]. The Þrst local pointwise (varying window size) adaptive nonparametric regression statistical procedure was suggested by Lepski [6] (see also [4], [5], and [7]). This approach has been further developed in application to various signal and image processing problems [8][12]. Particularly, [12] offered another view on the problem of local adaptive estimation based on the link between adaptive estimation and multiple testing. This allows to treat in a uniÞed way different types of images, including Gaussian and Poissonian. Another important feature is that the problem of choosing the tuning parameters of the procedure is carefully addressed, leading to an efficient automatic procedure. The presentation extends these ideas to a general approach to spatially adaptive local parametric estimation. Suppose we have independent observations {Zi}i=1 of the form Zi = (Xi, Yi). Here Xi denotes a vector of features or explanatory variables which determines the distribution of the random observation  Yi. The d-dimensional vector Xi ∈ R can be viewed as a location in time or space and Yi as the observation at Xi. Our model assumes that the distribution of each Yi is determined by a parameter fi which may depend on the location Xi, fi = f(Xi). In many cases the natural parametrization is chosen which provides the relation fi = E{Yi}. The estimation problem is to reconstruct f(x) from the data {Zi}i=1,. ,n. This set-up includes Gaussian images Yi = f(Xi) + εi with a regression function f(·) and i.i. d. Gaussian errors εi ∼ N (0, σ); Poisson images with P (Yi = k|Xi = x) = f(x) exp(−f(x))/k! ; Bernoulli (binary response) images with P (Yi = 1) = f(Xi), P (Yi = 0) = 1 − f(Xi). The joint distribution of the samples Y1, . , Yn is given by the log-likelihood L = ! n i=1 log p(Yi, f(Xi)). In the parametric setup, the whole function f(·) is determined by a parameter vector θ: f(·) = f(·,θ). This reduces the problem of estimating f to the problem of estimating θ ∈ Θ ∈ R. The maximum likelihood approach yields the estimates
The effect of azacitidine on interleukin-6 signaling and nuclear factor-κB activation and its in vitro and in vivo activity against multiple myeloma

Background Azacitidine is a DNA methyltransferase inhibitor and cytotoxic agent known to induce apoptosis of some cancer cells. This study evaluated the pre-clinical potential of azacitidine as a therapeutic agent for multiple myeloma. Design and Methods Dose responsiveness to azacitidine was determined utilizing a panel of genetically heterogenous human multiple myeloma cell lines. Azacitidine was also tested against primary multiple myeloma cells and in the 5T33MM murine model of systemic myelomatosis. Mechanistic studies included immunoblotting of key apoptosis signaling proteins, analysis of p16 gene methylation status, and characterization of both the interleukin-6 and nuclear factor-κB signaling pathways following azacitidine treatment. Results Human myeloma cell lines and primary multiple myeloma cells underwent apoptosis following exposure to clinically achievable concentrations of azacitidine (1 μM–20 μM). Similarly, azacitidine prolonged survival from 24.5 days to 32 days (p=0.001, log rank) in the 5T33MM model. At a mechanistic level azacitidine down-regulated two crucial cell survival pathways in multiple myeloma. First, it inhibited the elaboration of both interleukin-6 receptor-α and interleukin- 6 resulting in the reduced expression of both phospho-STAT3 and Bcl-xl. Secondly, azacitidine inhibited both nuclear factor-κB nuclear translocation and DNA binding in a manner independent of IκB. The kinetics of these azacitidine-induced responses was more consistent with protein synthesis inhibition than with either hypomethylation or another DNA-mediated effect. Conclusions Azacitidine rapidly induces apoptosis of multiple myeloma cells, is effective in vivo against multiple myeloma and inhibits two crucial cell survival pathways in this disease. We conclude that azacitidine demonstrates novel and highly relevant anti-myeloma effects and warrants further evaluation in a clinical context.
Should the Same Side of the Market always move first in a Transaction? An Experimental Study

We investigate whether transactions where the buyer (or seller) always moves first and the seller (or buyer) always moves second in the exchange give higher payoffs than transactions in which it is randomly determined who moves first. We examine the effect of two treatment variables: partners versus strangers, and fixed versus changing positions. We find that both with fixed and with changing positions, second movers take advantage of their position by exploiting the first mover. But with fixed positions, exploitation occurs significantly less, while reciprocal exchanges happen more often. However, fixed positions result in very unevenly distributed payoffs.
Functional roles of the sweet taste receptor in oral and extraoral tissues

Purpose of review This review summarizes and discusses the current knowledge about the physiological roles of the sweet taste receptor in oral and extraoral tissues. Recent findings The expression of a functional sweet taste receptor has been reported in numerous extragustatory tissues, including the gut, pancreas, bladder, brain and, more recently, bone and adipose tissues. In the gut, this receptor has been suggested to be involved in luminal glucose sensing, the release of some satiety hormones, the expression of glucose transporters, and the maintenance of glucose homeostasis. More recently, the sweet taste receptor was proposed to regulate adipogenesis and bone biology. Summary The perception of sweet taste is mediated by the T1R2/T1R3 receptor, which is expressed in the oral cavity, wherein it provides input on the caloric and macronutrient contents of ingested food. This receptor recognizes all the chemically diverse compounds perceived as sweet by human beings, including natural sugars and sweeteners. Importantly, the expression of a functional sweet taste receptor has been reported in numerous extragustatory tissues, wherein it has been proposed to regulate metabolic processes. This newly recognized role of the sweet taste receptor makes this receptor a potential novel therapeutic target for the treatment of obesity and related metabolic dysfunctions, such as diabetes and hyperlipidemia.
Enhancing the Lifespan and Energy Efficiency of Wireless Sensor Network Using Clustering and Routing Protocol

Energy efficiency is one of the major parameters in Wireless Sensor Networks. In this paper we attempt for a solution to balance the energy usage for maximizing the network lifetime, increase the packet delivery ratio and throughput. Our proposed algorithm is based on Energy Density of the clusters in Wireless Sensor Networks. The cluster head is selected using two step method and ondemand routing approach to calculate the balanced energy shortest path from source to sink. This unique approach maintains the balanced energy utilization among all nodes by selecting the different cluster heads dynamically. Our simulation results have compared with one of the plain routing scheme (EBRP) and cluster based routing (TSCHS), which shows the significant improvements in minimizing the delay and energy utilization and maximizing the network lifetime and throughput with respect to these works
Interactive Segmentation of Capsule Endoscopy Images Using Grow Cut Method

High incidence of Gastrointestinal (GI) tract related diseases are common nowadays, which leads to cancer. Diagnose of these kind of diseases is not easy in the early stage. This makes the researchers to develop an automated screening technique for early detection, many modalities are employed to view the GI tract but complete visualization is not possible. Wireless Capsule Endo scopy (WCE) is a modern modality which helps to view the complete GI tract, This claims an computational assistances which automatically segment the defective frames with the help of computer assisted diagnosis, In this paper the author describes an semi-automated interactive grow cut algorithm for segmenting capsule endoscopy (CE) images as foreground and background image by iterative process with a small number of user-labeled pixel the rest of the images are segmented with less human input. User can view and guide the algorithm without any additional user effort a semi automated segmentation is computed using mat lab.
On the Perception of Intonationally Marked Givenness after Auditory and Visual Priming

This paper deals with the intonational marking of different activation degrees of discourse referents. Following Chafe (1994), we distinguish three activation states corresponding to given, accessible, and new information. In a perception experiment using synthetic speech and pictures, we investigate whether the mode of presentation (auditory vs. visual) has an influence on a referent’s assumed activation state and how appropriate different accent patterns are for different activation states. Our findings suggest that auditorily primed referents are activated to a higher degree than visually primed ones, and that the type of the nuclear accent is a relevant cue for the perception of different degrees of givenness.
Diffuse Gallium-67 Accumulation in the Left Atrial Wall Detected Using SPECT/CT Fusion Images

Gallium-67 scintigraphy is useful for detecting active inflammation. We show a 66-year-old female patient with atrial fibrillation and diffuse thickening of the left atrial wall due to acute myocarditis, who presented diffuse abnormal accumulation of gallium-67 in the left atrium on single photon emission computed tomography/computed tomography (SPECT/CT) fusion images. In the second gallium-67 scan 2 months after the first scintigraphy, the abnormal accumulation in the heart was no longer visible. Gallium-67 SPECT/CT images helped understanding the disease condition that temporary inflammation in the left atrium caused atrial fibrillation.
Comp . aring baekhauling strategies in vehicle rout-mg using Ant Colony Optimization

In the Vehicle Routing Problem with Backhauls and Time Windows (VRPBTW) customers either receive goods from the depot or send goods to the depot and pickup or delivery at a customer has to occur within a pre-specified time window. The main objective is to minimize the total required fleet size for serving all customers. Secondary objectives are to minimize the total distance travelled or to minimize the total route duration of all vehicles. In this paper we consider a variant of the mixed VRPBTW where backhauls may be served before linehauls on any given route. Besides the modelling aspect of this variant we will study its performance implications when compared to the standard VRPBTW using a heuristic algorithm based on Ant Colony Optimization.
Class quantification of aerial images using Maximum Likelihood Estimation

Class quantification of aerial images plays a vital role in remote sensing. One of the class quantification method is discussed in this paper. Proposed method uses Maximum Likelihood Estimation based classifier for class quantification. Algorithm is trained by the sample classes derived from parent image. Feature space is estimated from each training sample. Different classes are labeled in test image by maximizing the likelihood function. The experimentation is done on aerial images obtained by Geo eye satellite at the elevation of 0.6km. The percentage area covered by the labeled classes is computed for all test images.
Leveraging diversity to improve business performance: Research findings and recommendations for organizations

Research findings from industrial and organizational psychology and other disciplines cast doubt on the simple assertion that a diverse workforce inevitably improves business performance. Instead, research and theory suggest several conditions necessary to manage diversity initiatives successfully and reap organizational benefits. This article reviews empirical research and theory on the relationship between workforce diversity and organizational performance and outlines practical steps HR practitioners can take to manage diversity initiatives successfully and enhance the positive outcomes. © 2004 Wiley Periodicals, Inc.
Increase of black hole entropy in higher curvature gravity.

We examine the Zeroth Law and the Second Law of black hole thermodynamics within the context of effective gravitational actions including higher curvature interactions. We show that entropy can never decrease for quasi-stationary processes in which a black hole accretes positive energy matter, independent of the details of the gravitational action. Within a class of higher curvature theories where the Lagrangian consists of a polynomial in the Ricci scalar, we use a conformally equivalent theory to establish that stationary black hole solutions with a Killing horizon satisfy the Zeroth Law, and that the Second Law holds in general for any dynamical process. We also introduce a new method for establishing the Second Law based on a generalization of the area theorem, which may prove useful for a wider class of Lagrangians. Finally, we show how one can infer the form of the black hole entropy, at least for the Ricci polynomial theories, by integrating the changes of mass and angular momentum in a quasistationary accretion process.
Twenty-two years of accounting disclosure research: Themes, concepts and relationships

To explore the intellectual structure of accounting disclosure research in the last decade, this study identified the most important publications and the most influential scholars as well as the correlations among these scholar's publications. In this study, bibliometric and social network analysis techniques are used to investigate the intellectual pillars of the accounting disclosure literature. By analyzing 74,742 citation of 2,015 articles published in SSCI journal in accounting disclosure area between 1989 and 2010, this study maps a knowledge network of accounting disclosure studies. The results of the mapping can help identify the research direction of accounting disclosure research and provide a valuable tool for researchers to access the literature in this area.
Object Recognition Using Words Model of Optimal Size in Histograms of Oriented Gradients

This paper presents a new bag-of-words based algorithm for object recognition. Our algorithm also includes five steps: feature detection and representation, codebook generation, learning and recognition. All features are extracted as dense grids of images instead of interest point for computationally efficiency and effectiveness. While features are described by Histograms of Oriented Gradients (HOG) rather than widely used Scale Invariant Feature Transform (SIFT). Different from previous work that randomly determine codebook size, the influence of the codebook size on the performance is also explored as another key problem. Then optimum sizes are chosen for further operation. In the training part, linear Support Vector Machine (SVM) as well as Support Vector Regression (SVR) is adopted due to their sati. Experiment are done on various cars from one of the most challenging databases Gaze; and the results show that our algorithm achieves desirable effect while the computational cost hardly increases.
Volitional Muscle Strength in the Legs Predicts Changes in Walking Speed Following Locomotor Training in People With Chronic Spinal Cord Injury

Background It is unclear which individuals with incomplete spinal cord injury best respond to body-weight–supported treadmill training. Objective The purpose of this study was to determine the factors that predict whether a person with motor incomplete spinal cord injury will respond to body-weight–supported treadmill training. Design This was a prognostic study with a one-group pretest-posttest design. Methods Demographic, clinical, and electrophysiological measurements taken prior to training were examined to determine which measures best predicted improvements in walking speed in 19 individuals with chronic (>7 months postinjury), motor-incomplete spinal cord injuries (ASIA Impairment Scale categories C and D, levels C1–L1). Results Two initial measures correlated significantly with improvements in walking speed: (1) the ability to volitionally contract a muscle, as measured by the lower-extremity manual muscle test (LE MMT) (r=.72), and (2) the peak locomotor electromyographic (EMG) amplitude in the legs (r=.56). None of the demographics (time since injury, age, body mass index) were significantly related to improvements in walking speed, nor was the clinical measure of balance (Berg Balance Scale). Further analysis of LE MMT scores showed 4 key muscle groups were significantly related to improvements in walking speed: knee extensors, knee flexors, ankle plantar flexors, and hip abductors (r=.82). Prediction using the summed MMT scores from those muscles and peak EMG amplitude in a multivariable regression indicated that peak locomotor EMG amplitude did not add significantly to the prediction provided by the LE MMT alone. Change in total LE MMT scores from the beginning to the end of training was not correlated with a change in walking speed over the same period. Limitations The sample size was limited, so the results should be considered exploratory. Conclusions The results suggest that preserved muscle strength in the legs after incomplete spinal cord injury, as measured by MMT, allows for improvements in walking speed induced by locomotor training.
Peer-to-Peer Data Synchronization Agents

The so-called Internet of Things (IoT) presents a tremendous opportunity for multitude of users to be connected to anything, whenever needed, wherever needed, by whoever needs it. Such opportunities, nonetheless, require more advanced and standardized communication interfaces to facilitate interactions between any types of "things" (smart devices, sensors, systems, networks, etc.). Recent standard proposals as the Quantum Lifecycle Management (QLM) messaging standards were developed and are proposed to provide such standardized interfaces for IoT data exchange. These standards make it possible to develop innovative and standardized techniques to address other issues in the IoT such as the management of replicas of a same data between distinct objects in a peer-to-peer, loosely coupled ways. This paper investigates new strategies-based agent models for peer-to-peer data synchronization in the IoT using the standardized interfaces provided by the QLM standards. This enables the development of models not designed domain-, vendor-or application-specific, as is often the case. Our synchronization models are implemented and assessed considering a real home automation platform.
A contract-based formalism for the specification of heterogeneous systems

We present the mathematical formalism and the verification methodology of the contract-based model developed in the framework of the SPEEDS project. SPEEDS aims at developing methods and tools to support ldquospeculative designrdquo, a design methodology in which distributed designers develop different aspects of the overall system, in a concurrent but controlled way. Our generic mathematical model of contract supports this style of development. This is achieved by focusing on behaviors, by supporting the notion of ldquorich componentrdquo where functional and non-functional aspects of the system can be considered and combined, by representing rich components via their set of associated contracts, and by formalizing the process of component composition.
Automatic summarization for popular songs

In this paper, we present an automatic summarization approach for popular songs. The approach includes two stages. First, a rough summary of the song is extracted efficiently by the energy information and the songpsilas structure, and then the segment boundaries of the summary are detected. Different from most previous works, the summary has a more complete meaning and a varied length instead of a fixed length, therefore it is much helpful for popular songpsilas audition and management. The algorithm is tested and evaluated by objective means. Experimental results show that the proposed approach achieves satisfactory results.
Detection, Analysis and Clinical Validation of Chromosomal Aberrations by Multiplex Ligation-Dependent Probe Amplification in Chronic Leukemia

Current diagnostic screening strategies based on karyotyping or fluorescent in situ hybridization (FISH) for detection of chromosomal abnormalities in chronic lymphocytic leukemia (CLL) are laborious, time-consuming, costly, and have limitations in resolution. Multiplex ligation-dependent probe amplification (MLPA) can simultaneously detect copy number changes of multiple loci in one simple PCR reaction, making it an attractive alternative to FISH. To enhance the clinical robustness and further harness MLPA technology for routine laboratory operations, we have developed and validated a protocol for comprehensive, automatic data analysis and interpretation. A training set of 50 normal samples was used to establish reference ranges for each individual probe, for the calling of statistically significant copy number changes. The maximum normal ranges of 2 and 3 standard deviations (SD) are distributed between 0.82 and 1.18 (Mean ± 2SD, 95% CI, P = 0.05), and between 0.73 and 1.27 (Mean ± 3SD, 99% CI, P = 0.01), respectively. We found an excellent correlation between MLPA and FISH with 93.6% concordance (P<0.0001) from a testing cohort of 100 clinically suspected CLL cases. MLPA analyses done on 94/100 patients showed sensitivity and specificity of 94.2% and 92.9%, respectively. MLPA detected additional copy number gains on 18q21.1 and chromosome 19, and novel micro-deletions at 19q13.43 and 19p13.2 loci in six samples. Three FISH-failed samples were tested positive by MLPA, while three 13q- cases with a low percentage of leukemia cells (7%, 12% and 19%) were not detected by MLPA. The improved CLL MLPA represents a high-throughput, accurate, cost-effective and user-friendly platform that can be used as a first-line screening test in a clinical laboratory.