Miracle-dz/UniFAR-FTUs huggingface dataset:
Regulation of Telomerase in Arabidopsis by BT2, an Apparent Target of TELOMERASE ACTIVATOR1[OA]

Telomerase, an enzyme essential for the synthesis and maintenance of telomeric DNA and the long-term stability of the genome, is developmentally regulated in plants. Telomerase activity is abundant in reproductive organs but low or undetectable in vegetative organs. Treatment with exogenous auxin, however, overrides this developmental control and induces telomerase in mature leaves. The Arabidopsis thaliana transcription factor TELOMERASE ACTIVATOR1 (TAC1) potentiates some responses to auxin, including the induction of telomerase activity in leaves. Here, we report that BT2, a protein with BTB, TAZ, and calmodulin binding domains, is an essential component of the TAC1-mediated telomerase activation pathway. Steady state concentration of BT2 mRNA increases in response to TAC1 expression, and TAC1 specifically binds the BT2 promoter both in vitro and in yeast one-hybrid assays. Constitutive expression of BT2 induces telomerase activity in leaves, whereas a null mutation of BT2 blocks TAC1-mediated telomerase induction, indicating that BT2 acts downstream of TAC1 to regulate telomerase activity in mature vegetative organs.
ERα signaling regulates MMP3 expression to induce FasL cleavage and osteoclast apoptosis

The benefits of estrogens on bone health are well established; how estrogens signal to regulate bone formation and resorption is less well understood. We show here that 17β‐estradiol (E2)‐induced apoptosis of bone‐resorbing osteoclasts is mediated by cleavage and solubilization of osteoblast‐expressed Fas ligand (FasL). U2OS‐ERα osteoblast‐like cells expressing an EGFP‐tagged FasL at the C‐terminus showed decreased fluorescence after E2 treatment, indicative of a cleavage event. Treatment of U2OS‐ERα cultures with a specific MMP3 inhibitor in the presence of E2 blocked FasL cleavage and showed an increase in the number of EGFP‐FasL+ cells. siRNA experiments successfully knocked down MMP3 expression and restored full‐length FasL to basal levels. E2 treatment of both human and murine primary osteoblasts showed upregulation of MMP3 mRNA expression, and calvarial organ cultures showed increased expression of MMP3 protein and colocalization with the osteoblast‐specific RUNX2 after E2 treatment. In addition, osteoblast cell cultures derived from ERαKO mice showed decreased expression of MMP3 but not MMP7 and ADAM10, two known FasL proteases, demonstrating that ERα signaling regulates MMP3. Also, conditioned media of E2‐treated calvarial osteoblasts showed an approximate sixfold increase in the concentration of soluble FasL, indicating extensive cleavage, and soluble FasL concentrations were reduced in the presence of a specific MMP3 inhibitor. Finally, to show the role of soluble FasL in osteoclast apoptosis, human osteoclasts were cocultured with MC3T3 osteoblasts. Both a specific MMP3 inhibitor and an MMP inhibitor cocktail preserved osteoclast differentiation and survival in the presence of E2 and demonstrate the necessity of MMP3 for E2‐induced osteoclast apoptosis. These experiments further define the molecular mechanism of estrogen's bone‐protective effects by inducing osteoclast apoptosis through upregulation of MMP3 and FasL cleavage. © 2013 American Society for Bone and Mineral Research
Influence of duty cycle on near-field diffraction of high-density gratings

Near-field intensity distributions of high-density amplitude gratings with period d=2. 3λ and different duty cycles illuminated by TE and TM polarized waves are simulated by using the finite-difference time-domain method. Numerical results show that intensity distributions of in the grooves change differently when duty cycle varies for TE and TM polarizations. As duty cycle increases, peak intensity in the middle of the first bright stripes and its locations change obviously. The main reason of location variation of the first bright stripes is the variation of the phase difference between the ±2nd orders and the 0th order, which is verified by using rigorous coupled-wave analysis. The investigation of influence of duty cycle on near-field diffraction of high-density gratings should be helpful for practical applications of high-density gratings.
Evaluating 2D and 3D geovisualisations for basic spatial assessment

This study investigates the use of 2D and 3D presentations of maps for the assessment of distances in a geographical context. Different types of 3D representations have been studied: A weak 3D visualisation that provides static monocular depth cues and a strong 3D visualisation that uses stereoscopic and kinetic depth cues. Two controlled experiments were conducted to test hypotheses regarding subjects’ efficiency in visually identifying the shortest distance among a set of market locations in a map. As a general result, we found that participants were able to correctly identify shortest distances when the difference to potential alternatives was sufficiently large, but performance decreased systematically when this difference decreased. Noticeable differences emerged for the investigated visualisation conditions. Participants in this study were equally efficient when using a weak 3D representation and a 2D representation. When the strong 3D visualisation was employed, they reported visual discomfort and tasks solved were significantly less correct. Presentations of intrinsic 2D content (maps) in 3D context did not, in this study, benefit from cues provided by a strong 3D visualisation and are adequately implemented using a weak 3D visualisation.
Role of diclofenac in reducing post‐endoscopic retrograde cholangiopancreatography pancreatitis

Background and Aims: Acute pancreatitis following endoscopic retrograde cholangiography presents a unique opportunity for prophylaxis and early modification of the disease process because the initial triggering event is temporally well defined and takes place in the hospital. We report a prospective, single‐center, randomized, double‐blind controlled trial to determine if rectal diclofenac reduces the incidence of pancreatitis following cholangiopancreatography.
Sensorized robotic sphere for large exterior critical infrastructures supervision

Abstract The surveillance and inspection tasks in large exterior critical infrastructures have arisen as critical processes. More complex challenges are now present, and the traditional approaches are sometimes obsolete for facing these new menaces. An alternative system—a mobile sensor, spherical shaped—that provides a flexible, versatile, and reliable way to perform measurements is proposed. Even more, thanks to its original traction method (based on center of gravity destabilization), the system has a result as an all-terrain vehicle that guarantees a safe and friendly interaction with the environment. It has been widely tested, verifying as well the accurate acquisition performance, resulting in this system as a suitable sensing and monitoring alternative.
Model structure learning: A support vector machine approach for LPV linear-regression models

Accurate parametric identification of Linear Parameter-Varying (LPV) systems requires an optimal prior selection of a set of functional dependencies for the parametrization of the model coefficients. Inaccurate selection leads to structural bias while over-parametrization results in a variance increase of the estimates. This corresponds to the classical bias-variance trade-off, but with a significantly larger degree of freedom and sensitivity in the LPV case. Hence, it is attractive to estimate the underlying model structure of LPV systems based on measured data, i.e., to learn the underlying dependencies of the model coefficients together with model orders etc. In this paper a Least-Squares Support Vector Machine (LS-SVM) approach is introduced which is capable of reconstructing the dependency structure for linear regression based LPV models even in case of rational dynamic dependency. The properties of the approach are analyzed in the prediction error setting and its performance is evaluated on representative examples.
SILK: high level of abstraction leakage simulator for side channel analysis

This paper proposes a new way of simulating leakage traces using high level of abstraction models and presents a proof of concept implementation simulator called SILK -- a tool for leakage simulation for side channel analysis of microcontrollers and microprocessors. SILK is a high level of abstraction simulator that builds a leakage trace based on a source code of an algorithm and several user-defined parameters. One of the main purposes of SILK is data generation for quick analysis of new attacks, countermeasures or preprocessing methods. SILK might also be used to compare different types of attacks, analysis techniques or software countermeasures. This paper presents general structure and parameters of SILK and a typical example of use case. Our experiments were done with two algorithms that run on a microcontroller in order to compare our simulations with real power traces. We compared simulated traces with real power traces using Dynamic Time Warping technique with two different distance metrics. We also compared our simulations with real power traces using Correlation Power Analysis (CPA). We were also able to show that using a high level of abstraction simulation we are able to produce datasets that might be used for side channel analysis.
Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning

High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy.
Interviewing one's peers: methodological issues in a study of health professionals

Objective. Although health professionals are increasingly undertaking qualitative interviews with professional peers, there is little literature regarding the methodological implications of this process. The aim of the study was to elicit from informants their views on being interviewed by a fellow health professional. Design. Semi-structured interviews with nine general practitioners (GPs), three rheumatologists, and three physical therapists, with a substantive focus on perceptions of osteoarthritis. The interviewer was a GP, and informants were asked for their reactions to being interviewed by a fellow professional. Data were analysed by hand, using a thematic approach. Setting. Primary care clinics and practices in the UK. Results. Although reassured to the contrary, many informants viewed the interview as a test of their professional knowledge. The interview was also seen by some GPs as serving an educational process, with the interviewer as an authoritative source of clinical information. There were some indications of professional vulnerability among informants in relation to possible scrutiny of their practice or knowledge, though none reported a negative experience of the interview. Notions of professional identity appeared central to many of the issues that emerged. Conclusion. The nature of the relationship in interviews involving professional peers creates specific methodological issues, which have important implications for qualitative research in primary healthcare. There are both advantages and disadvantages to interviewing professional peers, which should be considered in the light of the objectives of a particular study.
Discovering areas of interest with geo-tagged images and check-ins

Geo-tagged image is an ideal source for the discovery of popular travel places. However, the aspects of popular venues for daily-life purposes like dining and shopping are often missing in the mined locations from geo-tagged images. Fortunately check-in websites provide us a unique opportunity of analyzing people's preferences in their daily lives to complement the knowledge mined from geo-tagged images. This paper presents a novel approach for the discovery of Areas of Interest (AoI). By analyzing both geo-tagged images and check-ins, the approach exploits travelers' flavors as well as the preferences of daily-life activities of local residents to find AoI in a city. The proposed approach consists of two major steps. Firstly, we devise a density-based clustering method to discover AoI, mainly based on the image densities but also reinforced by the secondary densities from the images' neighboring venues. Then we propose a novel joint authority analysis framework to rank AoI. The framework simultaneously considers both the location-location transitions, and the user-location relations. An interactive presentation interface for visualizing AoI is also presented. The approach is tested with very large datasets for Shanghai city. They consist of 49,460 geo-tagged images from Panoramio.com, and 1,361,547 check-ins from the check-in website Qieke.com. By evaluating the ranking accuracy and quality of AoI, we demonstrate great improvements of our method over compared methods.
GPU accelerated reconstruction of Electrical Impedance Tomography Images through

EIT image reconstruction may be performed by a Simulated Annealing algorithm that minimizes the differences between the superficial impedance behavior of a virtual body simulated using the Finite Element Method and real data acquired on a physical body. The evaluation of objective functions - that involve solving FEM linear systems - is responsible for the majority of the process computational cost. This work presents a strategy for implementing the Preconditioned Conjugate Gradient algorithm on a GPU in order to benefit from its massive parallel computing capacities. This strategy takes in account the specificities of the EIT reconstruction through SA. It involves heavy preprocessing to identify the computations that may be performed in parallel. Initial results show that this strategy greatly improves not only on sequential approaches, but also on other generic GPU approaches.
Real mechanisms for mobile networks modeling and engineering

As mobile networks are growing fast in size and complexity, radio network resource planning needs to be optimized to cope with both increased traffic demand and spectrum scarcity. Although many studies have been reported in the area of mobile network planning in terms of traffic distribution analysis and mobility modeling, relatively few studies have been achieved regarding network planning based on real-world data and measurements. A realistic model has been developed in order to evaluate the performance of a real GSM network providing a voice service in an urban area. In this framework, our contribution addresses an important issue: how to monitor the performance measurements collected in the operations and maintenance centre (OMC) to propose a complete study including a realistic mobility model and a qualitative and quantitative traffic characterization that constitute a generic planning model which can be customized by any operator for mobile network deployment.
Iterative interference suppression algorithm based on EST

In this paper, an iterative interference suppression algorithm based on energy spreading transform (EST) is proposed. The performance of interference suppression can be significantly improved by our proposed iteration scheme between demodulator and parameter estimator. The energy of residual interference after initial narrowband interference (NBI) suppression is spread over the whole band by EST, which can reduce the influence of residual interference and improve detection precision. Furthermore, the accuracy of interference estimation can be improved by reconstructing transmitted signal and eliminating it from received signal through our proposed method. The principle of proposed iterative process between demodulator and parameter estimator is analyzed theoretically and then validated through computer simulation. Simulation results show that only a few iterations are required to effectively suppress NBI through our proposed method.
Diminished serotonin-mediated prolactin responses in nondepressed stroke patients compared with healthy normal subjects.

BACKGROUND AND PURPOSE The purpose of this study was to use hormonal responsiveness to d-fenfluramine (d-FEN) challenge as a measure of central serotonin (5-HT) function in a comparative evaluation of serotonergic abnormalities between stroke patients and healthy elderly normal subjects to test the hypothesis that stroke may be associated with diminished serotonergic functioning. METHODS Eight nondepressed medically stable stroke patients and 12 healthy volunteers completed a single-blind, placebo-controlled, fixed-order, crossover design challenge test with 30 mg of oral d-FEN. Baseline prolactin (PRL) and cortisol (CORT) and hormonal responses to d-FEN and placebo were measured at hourly intervals over a 4-hour period. Cardiovascular responses (pulse and blood pressure) and behavioral responses were also recorded at the same time points. RESULTS The 2 groups were comparable in demographics, body weight, plasma drug concentration, and behavioral and CORT responses. A 3-way ANOVA for repeated measures showed group differences for baseline adjusted PRL responses (change of scores from baseline). Peak PRL responses (maximal PRL change from baseline scores after treatment with d-FEN) in nondepressed stroke patients were attenuated compared with healthy elderly subjects, suggesting diminished serotonergic responsiveness in stroke patients. CONCLUSIONS The demonstrated serotonergic hypofunctioning poststroke may contribute to the high incidence of depressive disorders in stroke patients. Serotonergic agents may have a role in augmentation of stroke recovery.
Bayesian Spectral Analysis of “ MAD ”

Getting reliable estimates of coronal metallicity (Z) from X-ray spectra obtained with instruments such as ASCA/SIS and Chandra/ACIS is very difficult, because the sole determinant of Z is the ratio of line to continuum fluxes, which is not well-determined for low-resolution spectra. Here we propose new Bayesian methods which directly model the Poisson nature of the data. Our model also accounts for the Poisson nature of background contamination, blurring due to instrument response, and the absorption of photons in space. The resulting highly structured hierarchical model is fit using the Gibbs sampler, data augmentation, and Metropolis-Hasting. We demonstrate our methods with the X-ray spectral analysis of several apparently coronal metal abundance deficient (”MAD”) stars.
Simple analytic spiral K‐space algorithm

The exact, hardware‐constrained design of a spiral k‐space trajectory requires the solution of a differential equation, thereby making real‐time prescription difficult on scanners with limited computational power. This study describes a closed‐form approximate solution for interleaved Archimedian spiral trajectories that closely matches the exact design. Both slew rate‐limited and amplitude‐limited regimes are incorporated. Magn Reson Med 42:412–415, 1999. © 1999 Wiley‐Liss, Inc.
Dynamics of Polyphosphate-Accumulating Bacteria in Wastewater Treatment Plant Microbial Communities Detected via DAPI (4′,6′-Diamidino-2-Phenylindole) and Tetracycline Labeling

ABSTRACT Wastewater treatment plants with enhanced biological phosphorus removal represent a state-of-the-art technology. Nevertheless, the process of phosphate removal is prone to occasional failure. One reason is the lack of knowledge about the structure and function of the bacterial communities involved. Most of the bacteria are still not cultivable, and their functions during the wastewater treatment process are therefore unknown or subject of speculation. Here, flow cytometry was used to identify bacteria capable of polyphosphate accumulation within highly diverse communities. A novel fluorescent staining technique for the quantitative detection of polyphosphate granules on the cellular level was developed. It uses the bright green fluorescence of the antibiotic tetracycline when it complexes the divalent cations acting as a countercharge in polyphosphate granules. The dynamics of cellular DNA contents and cell sizes as growth indicators were determined in parallel to detect the most active polyphosphate-accumulating individuals/subcommunities and to determine their phylogenetic affiliation upon cell sorting. Phylotypes known as polyphosphate-accumulating organisms, such as a “Candidatus Accumulibacter”-like phylotype, were found, as well as members of the genera Pseudomonas and Tetrasphaera. The new method allows fast and convenient monitoring of the growth and polyphosphate accumulation dynamics of not-yet-cultivated bacteria in wastewater bacterial communities.
Sahayika: A framework for participatory authoring of knowledge structures for education domain

In countries like India, a great deal of diversity exists in language, culture and socio-economic conditions. In order to deliver computer aided education, efforts have to be put for proper management of concerned domain and learning materials keeping in mind this diversity. Participatory authoring of domain knowledge structure is of immense importance in this regard. In this paper, we describe a knowledge structure which is effective in capturing the structure of the learning materials of school level subjects. Ontologies have gained importance in representing the knowledge of the domain in a formal and machine understandable form in areas like intelligent information processing. Thus it can provide the platform for effective extraction of information and many other applications. We describe different aspects of manual ontology engineering in developing application specific domain ontology. The domain of our interest is the education domain where we are interested in retrieving relevant Web documents for the curriculum related requirements of school students. We identify an effective way of structuring the knowledge about these domains, which allows us to clearly demarcate the roles of topics, concepts, and actual words. We also describe applications in the area of information retrieval and in indexing document repositories in connection with e-learning where our ontology plays an important role. In this paper, we have provided a framework, Sahayika, for building knowledge structures in education domain.