Miracle-dz/UniFAR-FTUs huggingface dataset:
I&kgr;B&agr; glutathionylation and reduced histone H3 phosphorylation inhibit eotaxin and RANTES

Airway smooth muscle cells (ASMCs) secrete eotaxin and RANTES (regulated on activation, normal T-cell expressed and secreted) in response to tumour necrosis factor (TNF)-&agr;, which is inhibited by the nuclear factor (NF)-&kgr;B inhibitor dimethylfumarate (DMF). NF-&kgr;B/I&kgr;B (inhibitor of NF-&kgr;B) glutathionylation and changes in chromatin remodelling can inhibit NF-&kgr;B activity. In this study, we determined whether NF-&kgr;B/I&kgr;B glutathionylation and reduced histone H3 phosphorylation might underlie the inhibitory effect of DMF on NF-&kgr;B activity, and eotaxin and RANTES secretion. Primary human ASMCs were treated with DMF, diamide and/or glutathione (GSH) ethylester (OEt) prior to TNF-&agr; stimulation and were subsequently analysed by ELISA, electrophoretic mobility shift assay, immunofluorescence, co-immunoprecipitation or immunoblotting. DMF reduced intracellular GSH and induced I&kgr;B&agr; glutathionylation (I&kgr;B&agr;-SSG), which inhibited I&kgr;B&agr; degradation, NF-&kgr;B p65 nuclear entry and NF-&kgr;B/DNA binding. In addition, DMF inhibited the phosphorylation of histone H3, which was possibly mediated by the inhibitory effect of DMF on mitogen- and stress-activated protein kinase (MSK)-1. However, p38 mitogen-activated protein kinase (MAPK), extracellular signal-regulated kinase MAPK and MAPK phosphatase-1, upstream of MSK-1, were not inhibited by DMF. Importantly, DMF-mediated effects on NF-&kgr;B, histone H3, eotaxin and RANTES were reversed by addition of GSH-OEt. Our data suggest that DMF inhibits NF-&kgr;B-dependent eotaxin and RANTES secretion by reduction of GSH with subsequent induction of I&kgr;B&agr;-SSG and inhibition of histone H3 phosphorylation. Our findings offer new potential drug targets to reduce airway inflammation in asthma.
Adaptive Agent in a FPS Game

: In this work I design and implement an adaptive oponent for the computer game Unreal Tournament for its Deathmatch mode. The agent has been designed using reinforcement learning and implemented on the Pogamut platform. A k-means clustering algorithm has been used for state abstraction. Furthermore an agent performance testing framework has been developed for the Pogamut platform aswell and used in this work. Several experiments testing diﬀerent action-selection policies and diﬀerent parameters of the Q-Learning algorithm were conducted. The resulting behaviour has a performance comparative to other implementations of reinforcement learning from other literature
Statistical Properties of Portals' Users Activity

We investigate the behavior of users at the web portal. We focus on transitions between two subpages, using the information about the path of the users. We construct a weighted network with portal subpages being its nodes and the weights of edges defined as a number of transition from between different subpages. We scrutinize the properties of such a network as a distribution of weights and strengths that corresponds to the power-law relation, as well as the statistics of users behavior. The latter brings interesting results: the average number of distinct subpages visited during the n-th step of a visit scales as a square root relation.
Smad 4 mediates activation of mitogen-activated protein kinases by TGF-b in pancreatic acinar cells

Simeone, Diane M. , Lizhi Zhang, Kathleen Graziano, Barbara Nicke, Trinh Pham, Claus Schaefer, and Craig D. Logsdon. Smad4 mediates activation of mitogen-activated protein kinases by TGF-b in pancreatic acinar cells. Am J Physiol Cell Physiol 281: C311–C319, 2001. —Transforming growth factor-b (TGF-b) inhibits pancreatic acinar cell growth. In many cell types, TGF-b mediates its growth inhibitory effects by activation of Smad proteins. Recently, it has been reported that Smad proteins may interact with the mitogen-activated protein (MAP) kinase signaling pathways. In this study, we report on the interactions between the TGF-b and MAP kinase signaling pathways in isolated rat pancreatic acinar cells. TGF-b activated the MAP kinases extracellular signal-related kinases (ERKs) and p38 in pancreatic acinar cells, but had no effect on c-jun NH2-terminal kinase activity. Activation of MAP kinase by TGF-b was maximal 4 h after treatment. The ability of TGF-b to activate ERKs was concentration dependent and dependent on protein synthesis. TGF-b’s stimulation of ERK activation was blocked by PD-98059, an inhibitor of MAP kinase kinase 1, and by adenoviral transfer of dominant negative RasN17. Furthermore, adenoviral-mediated expression of dominant negative Smad4 blocked the ability of TGF-b to activate acinar cell MAP kinase, demonstrating that this activation is downstream of Smads. The biological relevance of ERK activation by TGF-b was indicated by demonstrating that inhibition of ERK signaling by PD-98059 blocked the ability of TGF-b to activate the transcription factor activator protein-1. These studies provide new insight into the signaling mechanisms by which TGF-b mediates biological actions in pancreatic acinar cells.
Opportunistic Data Dissemination Using Real-World User Mobility Traces

Opportunistic communication allows humans equipped with mobile devices to exchange information via a wireless link whenever they are nearby. This work examines the performance of a profile-based data dissemination scheme. We use a 2- step simulation approach which combines realistic user mobility traces with synthetic mobility models. We consider different system configurations and evaluate their effects on the data dissemination scheme. In particular, we look at how different wireless networking technologies affect the system and how much can we benefit from the installation of fixed information sprinkler nodes. Furthermore, we investigate the effects of user behavior by comparing selfish and generous users. Our results clearly demonstrate that realistic user mobility patterns result in a feasible opportunistic data dissemination scheme. In most of the studies scenarios, the effectiveness of the dissemination is very high, with over 90% of the users reached within a week of real time. Our results on user behavior show that although the effects of selfish behavior can be mitigated, they cannot be completely eliminated.
Compact Designs of Waveguide Butler Matrices

Architectures of waveguide Butler matrices, for linear and planar arrays, utilizing both short-slot and top-wall hybrids, yield short path from input to output, minimize losses, save flanges, and reduces network size and weight. Novel three-dimensional (3-D) Butler matrix beamformer for volumetric multibeam from planar array is also presented.
A simple hierarchical infinite HMM with efficient inference

We propose a simple hierarchical infinite HMM (iHMM) model, an extension to (iHMM) with efficient inference scheme. The model can capture dynamics of a sequence in two timescales and does not suffer from the problems of other related models in terms of implementation and time complexity. We use the model to analyze the dynamics in two timescales of some synthetic and real physiological data. We show that the model performs reasonably well compared to a baseline on two physiological datasets.
Associations between contrast sensitivity and aging.

OBJECTIVE The aim of this study was to assess age-related visual functions (visual acuity and contrast sensitivity) and compare the results by different age groups. MATERIAL AND METHODS A total of 231 patients were examined. The patients were divided into 5 age groups: 10 patients in group 1, 30-39 years; 40 patients in the group 2, 40-49 years; 77 patients in the group 3, 50-59 years; 71 patients in the group 4, 60-70 years; and 33 patients in the group 5, 71-85 years. A typical Snellen's chart (the direction of the gap in Landolt C) was used for noncorrected and best-corrected visual acuity testing. Contrast sensitivity was evaluated by employing a Ginsburg Box, VSCR-CST-6500. RESULTS Noncorrected visual acuity was significantly better in the group 2 than the group 3 (0.86 [0.28] vs. 0.69 [0.33], P=0.018). Moreover, noncorrected and best-corrected visual acuity was significantly better in the group 4 than the group 5 (0.52 [0.35] vs. 0.35 [0.28], P<0.001; and 0.9 [0.21] vs. 0.69 [0.27], P<0.005, respectively). Contrast sensitivity at the nighttime without glare was significantly worse in the group 2 than the group 1 at the spatial frequencies of 3, 12, and 18 cycles per degree (P=0.001, P=0.05, and P=0.01, respectively). The patients in the group 2 had significantly worse contrast sensitivity at the nighttime and daytime with glare at the spatial frequencies of 1.5, 12, and 18 cycles per degree (P=0.054, P=0.04, and P=0.01 and P=0.011, P=0.031, and P=0.011, respectively). The greatest differences in contrast sensitivity were observed between the groups 4 and 5, and it was 2 to 4 times better in the group 4. Comparing these groups, all the differences at the nighttime and daytime with and without glare were significant. CONCLUSIONS Contrast sensitivity was worst among the oldest persons (71-85 years), and it began to worsen already in the persons aged 40-49 years. Contrast sensitivity was very similar in the age groups of 40-49 and 50-59 years.
Grasp Recognition with Uncalibrated Data Gloves - A Comparison of Classification Methods

This paper presents a comparison of various classification methods for the problem of recognizing grasp types involved in object manipulations performed with a data glove. Conventional wisdom holds that data gloves need calibration in order to obtain accurate results. However, calibration is a time-consuming process, inherently user-specific, and its results are often not perfect. In contrast, the present study aims at evaluating recognition methods that do not require prior calibration of the data glove, by using raw sensor readings as input features and mapping them directly to different categories of hand shapes. An experiment was carried out, where test persons wearing a data glove had to grasp physical objects of different shapes corresponding to the various grasp types of the Schlesinger taxonomy. The collected data was analyzed with 28 classifiers including different types of neural networks, decision trees, Bayes nets, and lazy learners. Each classifier was analyzed in six different settings, representing various application scenarios with differing generalization demands. The results of this work are twofold: (1) We show that a reasonably well to highly reliable recognition of grasp types can be achieved - depending on whether or not the glove user is among those training the classifier - even with uncalibrated data gloves. (2) We identify the best performing classification methods for recognition of various grasp types. To conclude, cumbersome calibration processes before productive usage of data gloves can be spared in many situations.
A suite of Perl modules for handling microarray data

UNLABELLED We describe PerlMAT, a Perl microarray toolkit providing easy to use object-oriented methods for the simplified manipulation, management and analysis of microarray data. The toolkit provides objects for the encapsulation of microarray spots and reporters, several common microarray data file formats and GAL files. In addition, an analysis object provides methods for data processing, and an image object enables the visualisation of microarray data. This important addition to the Perl developer's library will facilitate more widespread use of Perl for microarray application development within the bioinformatics community. The coherent interface and well-documented code enables rapid analysis by even inexperienced Perl developers. AVAILABILITY Software is available at http://sourceforge.net/projects/perlmat
Mental disorder prevention and physical activity in Iranian elderly

Objectives: Mental disorders such as depression, anxiety and dementia are common in elderly. However, physical activity is suggested to be effective in preventing such aging-related disorders. The aim of this study was to investigate the role of physical activity on mental health in later life. Methods: Four hundred elderly people were randomly divided into the intervention and control groups. The intervention consisted of exercise twice a week for two months. Mental health status before, just after, and three months after the study was assessed with the 28-item General Health Questionnaire (GHQ-28). Results: The mean of the GHQ-28 total scale decreased in the case group and this change remained significant after three months (before: 8 ± 5.5, after three months: 5.6 ± 4.6, p < .001). GHQ subscales including somatization, anxiety, social dysfunction, and depression decreased significantly in the case group just after and three months after the intervention. Conclusions: Physical activity significantly prevents mental disorder in older adults. Although it has effects on anxiety, social dysfunction, and depression, the greatest influence is on improving the somatization symptoms.
Random Forest for the Contextual Bandit Problem

To address the contextual bandit problem, we propose an online random forest algorithm. The analysis of the proposed algorithm is based on the sample complexity needed to find the optimal decision stump. Then, the decision stumps are assembled in a random collection of decision trees, Bandit Forest. We show that the proposed algorithm is optimal up to logarithmic factors. The dependence of the sample complexity upon the number of contextual variables is logarithmic. The computational cost of the proposed algorithm with respect to the time horizon is linear. These analytical results allow the proposed algorithm to be efficient in real applications, where the number of events to process is huge, and where we expect that some contextual variables, chosen from a large set, have potentially non- linear dependencies with the rewards. In the experiments done to illustrate the theoretical analysis, Bandit Forest obtain promising results in comparison with state-of-the-art algorithms.
Design of Low-Noise, Low-Power 10-GHz VCO Using 0.18-µm CMOS Technology

A low-noise, low-power 10-GHz CMOS VCO was developed using cost-effective 0.18-μm CMOS technology. A complementary cross-coupled topology was employed to decrease the power dissipation and phase noise. The fabricated VCO demonstrates a low phase noise of -106 dBc/Hz at an offset frequency of 1 MHz and a low power dissipation of 4.4 mW.
From Roman Garments to Haute-couture Collection with the Fashionizer Platform

This paper presents a state of the art in the cloth simulation methods and two case studies on how to simulate ancient and high fashion garments with our new Fashionizer platform. The first application concerns the simulation of garments in a cultural heritage project, the Lifeplus project, where we had to simulate in real-time ancient roman clothes. The second application is the simulation of high fashion complex garments from famous fashion designers and these virtual garments have been shown on a screen in a museum next to the real hanged ones. The specific problems to solve while designing ancient garments and high fashion garments are discussed and the making of these garments is explained. Finally, there is an analysis of avenues of research: what is missing, what would the fashion designers want to have, what is the next step to come?
Data Clustering Using a Modified Kuwahara Filter

In this paper we propose a new density based clustering algorithm. As with other density based clustering algorithms our approach does not require the number of clusters as input. A modification of the Kuwahara filter, used in image processing, is used to generate a special density map in which the brightness of pixels is indicative of the density of the data points. A framework for clustering is derived and its performance is demonstrated on a number of different data sets.
Optimizing QoE of Multiple Users over DASH: A Meta-learning Approach

Dynamic adaptive video streaming over HTTP (DASH) plays a key role in video transmission over the Internet. The conventional DASH adaptation approaches concentrate on optimizing the overall quality of experience (QoE) for all client sides, neglecting the QoE diversity of different users. In this paper, we formulate the QoE optimization of multi-user preferences as a multi-task deep reinforcement learning problem, in which QoE refers to the metrics of visual quality, fluctuation and rebuffing events. Then, we propose a meta-learning framework for multi-user preferences (MLMP) as a new DASH adaptation approach. Finally, the simulation results show that the proposed approach outperforms state-of-the-art DASH adaptation approaches in satisfying the different users’ QoE preferences regarding the three metrics.
Detection and manipulation of live antigen-expressing cells using conditionally stable nanobodies

The ability to detect and/or manipulate specific cell populations based upon the presence of intracellular protein epitopes would enable many types of studies and applications. Protein binders such as nanobodies (Nbs) can target untagged proteins (antigens) in the intracellular environment. However, genetically expressed protein binders are stable regardless of antigen expression, complicating their use for applications that require cell-specificity. Here, we created a conditional system in which the stability of an Nb depends upon an antigen of interest. We identified Nb framework mutations that can be used to rapidly create destabilized Nbs. Fusion of destabilized Nbs to various proteins enabled applications in living cells, such as optogenetic control of neural activity in specific cell types in the mouse brain, and detection of HIV-infected human cells by flow cytometry. These approaches are generalizable to other protein binders, and enable the rapid generation of single-polypeptide sensors and effectors active in cells expressing specific intracellular epitopes. DOI: http://dx.doi. org/10.7554/eLife.15312. 001
A nonlinear disturbance observer for robotic manipulators

A new nonlinear disturbance observer (NDO) for robotic manipulators is derived in this paper. The global exponential stability of the proposed disturbance observer (DO) is guaranteed by selecting design parameters, which depend on the maximum velocity and physical parameters of robotic manipulators. This new observer overcomes the disadvantages of existing DOs, which are designed or analyzed by linear system techniques. It can be applied in robotic manipulators for various purposes such as friction compensation, independent joint control, sensorless torque control and fault diagnosis. The performance of the proposed observer is demonstrated by the friction estimation and compensation for a two-link robotic manipulator. Both simulation and experimental results show the NDO works well.
ICA-Based Algorithm Applied to Image Coding

Recently, Narozny et al [1] proposed a new viewpoint in variable high-rate transform coding. They showed that the problem of ﬁnding the optimal 1-D linear block transform for a coding system employing entropy-constrained uniform quantization may be viewed as a modiﬁed independent component analysis (ICA) problem. By adopting this new view-point, two new ICA-based algorithms, called GCGsup and ICAorth , were then derived for computing respectively the optimal linear transform and the optimal orthogonal transform. In this paper, we show that the transforms returned by GCGsup and ICAorth can achieve better visual image quality (better preservation of lines and contours) than the KLT and 2-D Discrete Cosine Transform (DCT) when applied to the compression of well-known grayscale images
Organic Substances Interfere with Reverse Transcription-Quantitative PCR-Based Virus Detection in Water Samples

ABSTRACT Reverse transcription (RT)-PCR-based virus detection from water samples is occasionally hampered by organic substances that are coconcentrated during virus concentration procedures. To characterize these organic substances, samples containing commercially available humic acid, which is known to inhibit RT-PCR, and river water samples were subjected to adsorption-elution-based virus concentration using an electronegative membrane. In this study, the samples before, during, and after the concentration were analyzed in terms of organic properties and virus detection efficiencies. Two out of the three humic acid solutions resulted in RT-quantitative PCR (qPCR) inhibition that caused >3-log10-unit underestimation of spiked poliovirus. Over 60% of the organics contained in the two solutions were recovered in the concentrate, while over 60% of the organics in the uninhibited solution were lost during the concentration process. River water concentrates also caused inhibition of RT-qPCR. Organic concentrations in the river water samples increased by 2.3 to 3.9 times after the virus concentration procedure. The inhibitory samples contained organic fractions in the 10- to 100-kDa size range, which are suspected to be RT-PCR inhibitors. According to excitation-emission matrices, humic acid-like and protein-like fractions were also recovered from river water concentrates, but these fractions did not seem to affect virus detection. Our findings reveal that detailed organic analyses are effective in characterizing inhibitory substances.
On fully parallel Karatsuba Multipliers for �

In this paperwe presenta new approachthat generalizes theclassicKaratsubamultiplier technique.In contrastwith versionsof this algorithm previously discussed[1, 2], in our approachwe do not usecompositefields to perform thegroundfield arithmetic. Themostattracti ve featureof the new algorithmpresentedhereis that the degreeof the definingirreduciblepolynomialcanbearbitrarily selected by thedesigner , allowing theusageof primedegrees.
The Role of Membrane Vesicles in Secretion of Lysobacter sp. Bacteriolytic Enzymes

Membrane vesicles produced by bacteria have been intensively studied in the recent years. Investigators have noted their roles in essential processes in the bacterial cell including secretion of proteins by the ‘eukaryotic' vesicular mechanism. To date, formation of vesicles is not considered to be a spontaneous event. Many believe it to be a programmed process that can be guided by several mechanisms. Vesicles are derivatives of the cell envelope, which in turn is a supramolecular structure where the functioning and biogenesis of all components are interrelated. Proteins secreted beyond the cell in their translocation are also part of the cell envelope. This also suggests their role in vesicle biogenesis. This review presents the results of vesicle studies in the Gram-negative bacterium Lysobacter sp. This bacterium is of interest as it secretes a number of proteins to the environment, including bacteriolytic enzymes. Bacteriolytic enzymes, on the one hand, are important for studies from a medical point of view as they can form the basis of new generation antimicrobial means. On the other hand, they are a convenient subject for studies of vesicle functions in the vital activities of the bacterial cell.