Miracle-dz/UniFAR-FTUs huggingface dataset:
The yeast PHO5 promoter: from single locus to systems biology of a paradigm for gene regulation through chromatin

Chromatin dynamics crucially contributes to gene regulation. Studies of the yeast PHO5 promoter were key to establish this nowadays accepted view and continuously provide mechanistic insight in chromatin remodeling and promoter regulation, both on single locus as well as on systems level. The PHO5 promoter is a context independent chromatin switch module where in the repressed state positioned nucleosomes occlude transcription factor sites such that nucleosome remodeling is a prerequisite for and not consequence of induced gene transcription. This massive chromatin transition from positioned nucleosomes to an extensive hypersensitive site, together with respective transitions at the co-regulated PHO8 and PHO84 promoters, became a prime model for dissecting how remodelers, histone modifiers and chaperones co-operate in nucleosome remodeling upon gene induction. This revealed a surprisingly complex cofactor network at the PHO5 promoter, including five remodeler ATPases (SWI/SNF, RSC, INO80, Isw1, Chd1), and demonstrated for the first time histone eviction in trans as remodeling mode in vivo. Recently, the PHO5 promoter and the whole PHO regulon were harnessed for quantitative analyses and computational modeling of remodeling, transcription factor binding and promoter input-output relations such that this rewarding single-locus model becomes a paradigm also for theoretical and systems approaches to gene regulatory networks.
Molecular, Biological, and In Vivo Characterization of the Guinea Pig Cytomegalovirus (CMV) Homologs of the Human CMV Matrix Proteins pp71 (UL82) and pp65 (UL83)

ABSTRACT We recently identified the genes encoding the guinea pig cytomegalovirus (GPCMV) homologs of the upper and lower matrix proteins of human CMV, pp71 (UL82) and pp65 (UL83), which we designated GP82 and GP83, respectively. Transient-expression studies with a GP82 plasmid demonstrated that the encoded protein targets the nucleus and that the infectivity and plaquing efficiency of cotransfected GPCMV viral DNA was enhanced by GP82. The transactivation function of GP82 was not limited to GPCMV, but was also observed for a heterologous virus, herpes simplex virus type 1 (HSV-1). This was confirmed by its ability to complement the growth of an HSV-1 VP16 transactivation-defective mutant virus in an HSV viral DNA cotransfection assay. Study of a GP82 “knockout” virus (and its attendant rescuant), generated on a GPCMV bacterial artificial chromosome construct, confirmed the essential nature of the gene. Conventional homologous recombination was used to generate a GP83 mutant to examine the role of GP83 in the viral life cycle. Comparison of the one-step growth kinetics of the GP83 mutant (vAM409) and wild-type GPCMV indicated that GP83 protein is not required for viral replication in tissue culture. The role of GP83 in vivo was examined by comparing the pathogenesis of wild-type GPCMV, vAM409, and a control virus, vAM403, in guinea pigs. The vAM409 mutant was significantly attenuated for dissemination in immunocompromised strain 2 guinea pigs, suggesting that the GP83 protein is essential for full pathogenicity in vivo.
Smooth robust adaptive sliding mode control of manipulators with guaranteed transient performance

A systematic way to combine an adaptive control design technique and sliding mode control methodology for trajectory tracking control of robot manipulators in the presence of parametric uncertainties and external disturbance is developed in this paper. Continuous sliding mode controllers without the unpleasant reaching transient and chattering problem are first developed by using a dynamic sliding mode. Transient performance is guaranteed and globally uniform ultimate boundedness (GUUB) stability is obtained. A conventional adaptive scheme is also developed for comparison. With some modifications to the conventional adaptation law, the control law is redesigned by combining the design methodologies of adaptive control and sliding mode control. The suggested controller preserves the advantages of both methods, namely, asymptotic stability of adaptive systems for parametric uncertainties and GUUB stability with guaranteed transient performance of sliding mode control for both parametric uncertainties and external disturbances. The control law is continuous and the chattering problem of sliding mode control is avoided. A priori knowledge of the bounds of the parameter uncertainties and external disturbances is assumed. Experimental results illustrate the effectiveness of the proposed methods.
High-Performance Germanium pMOSFETs With NiGe Metal Source/Drain Fabricated by Microwave Annealing

A microwave annealing technique has been developed to fabricate superior NiGe/n-Ge Schottky junctions. The impacts of the microwave conditions on the electrical properties of NiGe/n-Ge Schottky junctions have been systematically investigated. It is found that the Schottky-barrier height for holes is significantly reduced to 0.03 eV, attributable to the suppression of metal-induced gap states-induced Fermi level pinning effect. As a result, the junction leakage of the NiGe metal source/drain (S/D) has been sufficiently reduced. An enhanced on current and a record high on/off ratio of 104 were achieved in the high-performance Schottky-barrier Ge pMOSFETs with a NiGe metal S/D formed by microwave annealing.
EFFICIENT PARALLELIZATION OF STOCHASTIC SIMULATION ALGORITHM FOR CHEMICALLY REACTING SYSTEMS ON THE GRAPHICS PROCESSING UNIT

: In biological systems formed by living cells, the small populations of some reactant species can result in inherent randomness which cannot be captured by traditional deterministic approaches. In that case, a more accurate simulation can be obtained by using the Stochastic Simulation Algorithm (SSA). Many stochastic realizations are required to capture accurate statistical information of the solution. This carries a very high computational cost. The current generation of graphics processing units (GPU) is well-suited to this task. We describe our implementation, and present some computational experiments illustrating the power of this technology for this important and challenging class of problems.
Lack of spatial segregation in the representation of pheromones and kairomones in the mouse medial amygdala

The nervous system is organized to detect, internally represent and process sensory information to generate appropriate behaviors. Despite the crucial importance of odors that elicit instinctive behaviors, such as pheromones and kairomones, their neural representation remains little characterized in the mammalian brain. Here we used expression of the immediate early gene product c-Fos as a marker of neuronal activity to find that a wide range of pheromones and kairomones produces activation in the medial nucleus of the amygdala, a brain area anatomically connected with the olfactory sensory organs. We see that activity in this nucleus depends on vomeronasal organ input, and that distinct vomeronasal stimuli activate a dispersed ensemble of cells, without any apparent spatial segregation. This activity pattern does not reflect the chemical category of the stimuli, their valence or the induced behaviors. These findings will help build a complete understanding of how odor information is processed in the brain to generate instinctive behaviors.
15 . 14 : Motion Estimator Based On Hierarchical Clusters

In this paper, we describe the use of statistically derived hierarchical clusters of weather data to derive movement estimates from pairs of frames in a time sequence. We show that the use of hierarchical clusters enables small cells to be tracked over short periods of time while using the movement of the larger scale features they are embedded in for longer periods. The motion estimator has been applied both to reflectivity data obtained from the National Weather Service Radar (WSR-88D) and to cloud-top infrared temperatures obtained from the GOES-11 satellite. We demonstrate the results on both these sensors. 1. Short-term forecast methods The operational way of identifying storms from radar images involves the use of multiple thresholds and counting runs of values above a threshold along a radial. The centroids are then used as proxy for the storms (Johnson et al. 1998) and tracked either on the basis of proximity to expected position or through a a linear programming approach (Dixon 1994). Change in position is extrapolated. A second technique is to use rectangular sub-grids and find the maximum correlation within a search radius (Rinehart and Garvey 1978; Tuttle and Gall 1999). A modification of this technique is to pre-filter the data so as to track only the larger scales (Wolfson et al. 1999; Lakshmanan 2000). It is also possible to use sub-grids ranging in size from that of the entire image to small ∗Corresponding author address: lakshman@ou.edu, also affiliated with NOAA/OAR/National Severe Storms Laboratory. 16km x 16km grids and to compute motion estimates at each of these scales. Smoothness criteria can be used to constrain these estimates at different scales. Identifying, matching and extrapolating storm core locations is suitable for small scale storms. The large scale features and cross-correlation technique is suitable for longer forecasts, but with loss of detailed motion estimates. An assumption here is that the storms are of the scale of the sub-grid, not larger. The multiscale estimation is suitable also for large scale forecasts, but with less precise detailed motion estimates. When used for advection, all the correlation techniques rely on reverse projection, so there needs to be wind speed at the spot where the storm is moving to. The image template methods also assume that all pixels within a grid are moving together. We use a hybrid approach where motion estimates are made for groups of storms (rather than for sub-grids of the image), but at various scales. The motion estimate for a storm cell is the movement that minimizes the mean-absolute-error between the current frame and corresponding pixels in the previous frame, except that the template is not a sub-grid of the image, but is instead the actual shape of the storm cell. Instead of simply matching storm cells across frames, motion estimates are made by finding the best match for the storm-template. Thus, the major steps in the technique are: 1. Find storms at different scales. 2. Estimate motion at the various scales. 3. Forecast for different periods using motion at different scales.
A Framework for Automatic Identification of Learning Styles in Learning Management Systems

A current concern of modern societies is the quality of their educational systems. Learning Management Systems (LMSs) are tech- nological tools that have been used to improve and extend the tradi- tional educational system. Although LMSs have greatly beneted from technological advances, this type of educational platforms are still in need of mechanisms to provide virtual educational environments in which students are considered the main actor in the design of the learning pro- cess, thus contributing to increase the quality of educational systems. In particular, LMSs usually lack mechanisms for recognizing users' learning styles, which describe the way a learner acquires and process information. In this work we propose a framework for automatic identication of learning styles in LMSs and present a specic implementation. A key goal of the framework design is to provide researchers and practitioners with a tool that facilitates the specication of expert knowledge for classifying students with respect to their learning styles in LMSs.
Working Paper 0805 July 2008 Investment Spikes and Uncertainty in the Petroleum Refi ning Industry

Working papers of the Federal Reserve Bank of Cleveland are preliminary materials circulated to stimulate discussion and critical comment on research in progress. They may not have been subject to the formal editorial review accorded offi cial Federal Reserve Bank of Cleveland publications. The views stated herein are those of the authors and are not necessarily those of the Federal Reserve Bank of Cleveland or of the Board of Governors of the Federal Reserve System. This paper investigates the effect of uncertainty on the investment decisions of petroleum refi neries in the US. We construct uncertainty measures from commodity futures market and use data on actual capacity changes to measure investment episodes. Capacity changes in US refi neries occur infrequently and a small number of investment spikes account for a large fraction of the change in industry capacity. Given the lumpy nature of investment adjustment in this industry, we empirically model the investment process using hazard models. An increase in uncertainty decreases the probability a refi nery adjusts its capacity. The results are robust to various investment thresholds. Our fi ndings lend support to theories that emphasize the role of irreversibility in investment decisions. for helpful comments. We also benefi t from conversations with Dennis O
Lipopolysaccharide-specific antibodies in plasma and stools of children with Shigella-associated leukemoid reaction and hemolytic-uremic syndrome

Antibody responses to the lipopolysaccharide (LPS) of shigellae were compared between children with uncomplicated and complicated Shigella dysenteriae 1 infection. One hundred fifteen children between 12 and 60 months of age with S. dysenteriae 1 infection were studied. Of these children, 42 had complications (leukemoid reaction and/or hemolytic-uremic syndrome [complicated shigellosis] and 73 had no complications (uncomplicated shigellosis). Antibodies to the LPS of S. dysenteriae 1 and Shigella flexneri Y were measured in plasma and stools, as were total immunoglobulin A (IgA) and IgG concentrations in plasma and the total IgA concentration in stool, on enrollment and 3 to 5 days later. In the plasma, the concentrations of homologous (IgG) and heterologous (IgA) LPS antibodies on enrollment were higher in children with complicated shigellosis than in those with uncomplicated shigellosis. In stool, the concentrations on enrollment were similar between the two groups of children. There was a rise in antibody concentrations in the plasma (homologous and heterologous) and stool (homologous) between the day of enrollment and 3 to 5 days later in children with uncomplicated shigellosis but not in those with complicated shigellosis. These findings suggest that systemic stimulation is more marked in children with complications, so that a subsequent rise in plasma antibody concentrations does not occur in these children. In contrast, the lack of a rise in stool antibody concentrations in children with complicated shigellosis is suggestive of a lower-level mucosal response. Because the duration of diarrhea before enrollment influenced the homologous antibody concentrations, children were further divided into three subgroups (short [3 to 5 days], medium [6 to 9 days], and long [> 9 days] diarrhea durations before enrollment). Comparisons of homologous antibody concentrations between the two groups of children following such subdivisions showed that in children with complicated shigellosis, antibody concentrations were higher in the plasma of children in the short diarrhea duration subgroup but lower in the stool children in the medium diarrhea duration subgroup. No differences in antibody concentrations were observed in children in the other diarrhea duration subgroups. Thus, complications in shigellosis are associated with an early and strong systemic stimulation without a concomitant stimulation of the mucosal antibody response.
Visual context due to speech-reading suppresses the auditory response to acoustic interruptions in speech

Speech reading enhances auditory perception in noise. One means by which this perceptual facilitation comes about is through information from visual networks reinforcing the encoding of the congruent speech signal by ignoring interfering acoustic signals. We tested this hypothesis neurophysiologically by acquiring EEG while individuals listened to words with a fixed portion of each word replaced by white noise. Congruent (meaningful) or incongruent (reversed frames) mouth movements accompanied the words. Individuals judged whether they heard the words as continuous (illusion) or interrupted (illusion failure) through the noise. We hypothesized that congruent, as opposed to incongruent, mouth movements should further enhance illusory perception by suppressing the auditory cortex's response to interruption onsets and offsets. Indeed, we found that the N1 auditory evoked potential (AEP) to noise onsets and offsets was reduced when individuals experienced the illusion during congruent, but not incongruent, audiovisual streams. This N1 inhibitory effect was most prominent at noise offsets, suggesting that visual influences on auditory perception are instigated to a greater extent during noisy periods. These findings suggest that visual context due to speech-reading disengages (inhibits) neural processes associated with interfering sounds (e.g., noisy interruptions) during speech perception.
Error correction via linear programming

Suppose we wish to transmit a vector f ϵ Rn reliably. A frequently discussed approach consists in encoding f with an m by n coding matrix A. Assume now that a fraction of the entries of Af are corrupted in a completely arbitrary fashion by an error e. We do not know which entries are affected nor do we know how they are affected. Is it possible to recover f exactly from the corrupted m-dimensional vector y = Af + e?
Experimental evolution of a microbial predator's ability to find prey

Foraging theory seeks to explain how the distribution and abundance of prey influence the evolution of predatory behaviour, including the allocation of effort to searching for prey and handling them after they are found. While experiments have shown that many predators alter their behaviour phenotypically within individual lifetimes, few have examined the actual evolution of predatory behaviour in light of this theory. Here, we test the effects of prey density on the evolution of a predator's searching and handling behaviours using a bacterial predator, Myxococcus xanthus. Sixteen predator populations evolved for almost a year on agar surfaces containing patches of Escherichia coli prey at low or high density. Improvements in searching rate were significantly greater in those predators that evolved at low prey density. Handling performance also improved in some predator populations, but prey density did not significantly affect the magnitude of these gains. As the predators evolved greater foraging proficiency, their capacity diminished to produce fruiting bodies that enable them to survive prolonged periods of starvation. More generally, these results demonstrate that predators evolve behaviours that reflect at least some of the opportunities and limitations imposed by the distribution and abundance of their prey.
K-Nearest Neighbor Estimation of Forest Attributes: Improving Mapping Efficiency

This paper describes our efforts in refining k-nearest neighbor forest attributes classification using U.S. Department of Agriculture Forest Service Forest Inventory and Analysis plot data and Landsat 7 Enhanced Thematic Mapper Plus imagery. The analysis focuses on FIA-defined forest type classification across St. Louis County in northeastern Minnesota. We outline three steps in the classification process that highlight improvements in mapping efficiency: (1) using transformed divergence for spectral feature selection, (2) applying a mathematical rule for reducing the nearest neighbor search set, and (3) using a database to reduce redundant nearest neighbor searches. Our trials suggest that when combined, these approaches can reduce mapping time by half without significant loss of accuracy.
New Algorithm for Minimum Multicast Time Problem in Wireless Sensor Networks

Given a wired network of processors, and a source node that needs to broadcast a message to all other processors in the network, the minimum broadcast time problem is to find a scheme that accomplishes the broadcast in a minimum number of time rounds under the constraint that at each time round, no processor can forward the received message to more than one of its neighbors in the network. This NP-hard problem has been extensively studied in literatures. In this paper we focus on a variant of the minimum broadcast time problem: the minimum multicast time problem in wireless sensor networks under collision-free data transmission model. The goal of the problem is to multicast a message from the source node to a set of destination nodes in a minimum number of time rounds. This problem remains NP-hard even in the Euclidean plane and the current best approximation algorithm has performance ratio of 41. In this paper we propose a new algorithm that has performance ratio of 15.
Effect of different dispersing agents on the characteristics of Eudragit microspheres prepared by a solvent evaporation method

Eudragit RS microspheres containing verapamil HCl for oral use were prepared using three different dispersing agents: aluminium tristearate, magnesium stearate and sucrose stearate, by a solvent evaporation method. The effects of the type and concentration of the dispersing agents and the inner phase polymer concentration on the size and T63.2% (the time at which 63.2% of the drug is released) of microspheres were determined by multiple linear regression analysis. The morphology of microspheres was characterized by scanning electron microscopy. The surface of microspheres prepared with sucrose stearate was smoother and non-porous and the drug release from these microspheres was the fastest. When aluminium tristearate or magnesium stearate were used as dispersing agents, the particle size of microspheres became smaller. Increasing amounts of these two dispersing agents led to the accumulation of their free particles onto the surfaces of the microspheres. The drug release from the microspheres was slower than that of the microspheres from sucrose stearate depending on their hydrophobic structures. According to the results of the multiple linear regression analysis among the dispersing agents used, aluminium tristearate showed the best correlation between the examined input (dispersing agent and polymer concentrations) and output (T63.2% and particle size) variables.
Robust control for nonlinear motor-mechanism coupling system using wavelet neural network

A robust controlled toggle mechanism, which is driven by a permanent magnet (PM) synchronous servo motor is studied in this paper. First, based on the principle of computed torque control, a position controller is developed for the motor-mechanism coupling system. Moreover, to relax the requirement of the lumped uncertainty in the design of a computed torque controller, a wavelet neural network (WNN) uncertainty observer is utilized to adapt the lumped uncertainty online. Furthermore, based on the Lyapunov stability a robust control system, which combines the computed torque controller, the WNN uncertainty observer and a compensated controller is proposed to control the position of the motor-mechanism coupling system. The computed torque controller with WNN uncertainty observer is the main tracking controller, and the compensated controller is designed to compensate the minimum approximation error of the uncertainty observer. Finally, simulated and experimental results due to a periodic sinusoidal command show that the dynamic behaviors of the proposed robust control system are robust with regard to parametric variations and external disturbances.