Miracle-dz/UniFAR-FTUs huggingface dataset:
c-Myc Inhibits Ras-Mediated Differentiation of Pheochromocytoma Cells by Blocking c-Jun Up-Regulation

Although mutant Ras proteins were originally described as transforming oncoproteins, they induce growth arrest, senescence, and/or differentiation in many cell types. c-Myc is an oncogenic transcription factor that cooperates with Ras in cellular transformation and oncogenesis. However, the Myc-Ras relationship in cellular differentiation is largely unknown. Here, we have analyzed the effects of c-Myc on PC12-derived cells (UR61 cell line), harboring an inducible N-Ras oncogene. In these cells, Ras activation induces neuronal-like differentiation by a process involving c-Jun activation. We found that c-Myc inhibited Ras-mediated differentiation by a mechanism that involves the blockade of c-Jun induction in response to Ras signal. Accordingly, ectopically expressed c-Jun could bypass c-Myc impediment of Ras-induced differentiation and activator protein 1 activation. Interestingly, it did not rescue the proliferative arrest elicited by Ras and did not enhance the differentiation-associated apoptosis. The blockade of Ras-mediated induction of c-Jun takes place at the level of c-Jun proximal promoter. Mutational analysis revealed that c-Myc regions involved in DNA binding and transactivation are required to block differentiation and c-Jun induction. c-Myc does not seem to require Miz-1 to inhibit differentiation and block c-Jun induction. Furthermore, Max is not required for c-Myc activity, as UR61 cells lack a functional Max gene. c-Myc–inhibitory effect on the Ras/c-Jun connection is not restricted to UR61 cells as it can occur in other cell types as K562 or HEK293. In conclusion, we describe a novel interplay between c-Myc and c-Jun that controls the ability of Ras to trigger the differentiation program of pheochromocytoma cells. (Mol Cancer Res 2008;6(2):325–39)
Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay: A Report of MR Imaging in 5 Patients

SUMMARY: We present findings on MR imaging in 5 patients with autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS). In the literature, early atrophy of the superior vermis as well as progressive atrophy of the cerebellar hemispheres and cervical cord was described. We found linear hypointensity on T2 and T2 fluid-attenuated inversion recovery–weighted images in the pons in all of our 5 patients.
Semantic Interoperability by Aligning Ontologies

A fundamental premise of the semantic web is that a level of interoperability is guaranteed among applications running in an open environment. By the use of ontologies applications are able to share information and exchange meaningful data. In this context ontology alignment is paramount to assure communication among applications. In this paper we propose an ontology alignment strategy based in the concepts of partial alignment and inconsistency tolerance.
Combination of gross shape features, fourier descriptors and multiscale distance matrix for leaf recognition

In this study, we have experimented with different image and shape descriptors on the automatic leaf recognition problem. We have studied the effects of gross shape descriptors, Fourier descriptors, multiscale distance descriptors, and the combination of these on the leaf recognition performance using two different datasets. We have achieved 94.62% recognition performance on Flavia, comparable to PNN 90.31%and SVM-BDT 96%. Our performance on SLID dataset, 96.67%, is comparable to MDM-A 93.60% and hierarchical matching of deformable shapes 96.28%.
norges teknisk-naturvitenskapelige universitet Conservation of phase space properties using exponential integrators on the cubic Schrödinger equation by

preprint numerics no. 1/2006 norwegian university of science and technology trondheim, norway The cubic nonlinear Schrödinger (nls) equation with periodic boundary conditions is solvable using Inverse Spectral Theory. The " nonlinear " spectrum of the associated Lax pair reveals topological properties of the nls phase space that are difficult to assess by other means. In this paper we use the invariance of the nonlinear spectrum to examine the long time behavior of exponential and multisymplectic integrators as compared with the most commonly used split step approach. The initial condition used is a perturbation of the unstable plane wave solution, which is difficult to numerically resolve. Our findings indicate that the exponential integrators from the viewpoint of efficiency and speed have an edge over split step, while a lower order multisymplectic is not as accurate and too slow to compete.
ALZCARE: An information system for screening, management and tracking of demented patients

The ALZCARE project aims at assisting people at risk or already suffering of dementia, their family and health professionals in the dementia care pathway by providing an integrated ICT-enabled information System. The system consists of a mobile platform for screening people at risk, a Clinical Information System and a satellite-based patient tracking system. The system is currently on the evaluation phase focusing on addressing the needs of citizens of the cross-border areas of Greece and Albania.
Cultural Capital, Learning and ICT in a Southern Italian University

In the university setting, e-learning courses represent a flexible resource that can tackle a range of difficulties pertaining to primary degree courses and post-graduate qualifications. With reference to the teaching of Social Science Methodology within a primary degree course in an Italian university, this article suggests that e-learning can help new students with weak cultural capital to overcome some of the difficulties that can often lead them to drop out of university.
Synchronization methods for supporting distributed 3D virtual environments in Java™

This paper presents a 3D distributed virtual environment (DVE). The DVE, created using Java, is intended to allow for the creation of applications to enable multiple users to collaboratively interact in, and communicate about, a virtual world. This DVE is used to primarily support a flight simulator application. Three client-server synchronization methods were developed and compared. The method of transparent synchronization with non-blocking I/O has been found to be the best method for maintaining synchronization among DVEs. The successful creation of the DVE and the positive results collected in the supporting experimental data, leads to the conclusion that Java, with the addition of the non-blocking I/O and 3D API's, can be successfully used to create high performance 3D DVEs.
Flag Commit: Supporting Efficient Transaction Recovery in Flash-Based DBMSs

Owing to recent advances in semiconductor technologies, flash disks have been a competitive alternative to traditional magnetic disks as external storage media. In this paper, we study how transaction recovery can be efficiently supported in database management systems (dbmss) running on slc flash disks. Inspired by the classical shadow-paging approach, we propose a new commit scheme, called flagcommit, to exploit the unique characteristics of flash disks such as fast random read access, out-place updating, and partial page programming. To minimize the need of writing log records, we embed the transaction status into flash pages through a chain of commit flags. Based on flagcommit, we develop two recovery protocols, namely commit-based flag commit (cfc) and abort-based flag commit (afc), to meet different performance needs. They are flexible to support no-force buffer management and fine-grained concurrency control. Our performance evaluation based on the tpc-c benchmark shows that both cfc and afc outperform the state-of-the-art recovery protocols.
Wind loads and effects on rigid frame bridges with twin-legged high piers at erection stages

This article presents a procedure for analyzing wind effects on the rigid frame bridges with twin-legged high piers during erection stages, taking into account all wind loading components both on the beam and on the piers. These wind loading components include the mean wind load and the load induced by the three turbulence wind components and by the wake excitation. The buffeting forces induced by turbulence wind are formulated considering the modification due to aerodynamic admittance functions. The buffeting responses are analyzed based on the coherence of buffeting forces and using finite element method in conjunction with random vibration theory in the frequency domain. The peak dynamic response is obtained by combining the various response components through gust response factor approach. The procedure is applied to Xiaoguan Bridge under different erection stages using the analytic aerodynamic parameters fitted from computational fluid dynamics. The numerical results indicate that the obtained peak structural responses are more conservative and accurate when considering the effect of each loading component on the beam and on the piers, and the roles of different loading components are different with regard to bridge configurations. Aerodynamic admittance functions are source of the important part of the error margin of the analytical prediction method for buffeting responses of bridges, and buffeting responses based on wind velocity coherence will underestimate the results.
High prevalence of noroviruses among hospitalized diarrheal patients in Bangladesh, 2011.

INTRODUCTION Norovirus is not usually investigated in diarrheal patients in Bangladesh which may account for the many cases where no pathogens are identified. METHODOLOGY Stool specimens collected from diarrheal patients from three hospitals in Bangladesh during 2011 were investigated for norovirus RNA using real-time RT-PCR assay with norovirus type specific primers and probes. RESULTS Of the 257 stool specimens tested, 28.4 % were norovirus positive. GII (71.2%) was the predominant strain followed by GI (20.5%), GI+GII (6.8%) and GIV (1.4%). Half of the norovirus positive stools (n=37) were co-infected with other pathogens. CONCLUSION Continued surveillance of norovirus together with other viral and bacterial pathogens in hospitalized gastroenteritis patients as well as in the community will further elucidate the role and burden of different pathogens in diarrheal diseases.
WebProphet: Automating Performance Prediction for Web Services

Today, large-scale web services run on complex systems, spanning multiple data centers and content distribution networks, with performance depending on diverse factors in end systems, networks, and infrastructure servers. Web service providers have many options for improving service performance, varying greatly in feasibility, cost and benefit, but have few tools to predict the impact of these options. A key challenge is to precisely capture web object dependencies, as these are essential for predicting performance in an accurate and scalable manner. In this paper, we introduce WebProphet, a system that automates performance prediction for web services. WebProphet employs a novel technique based on timing perturbation to extract web object dependencies, and then uses these dependencies to predict the performance impact of changes to the handling of the objects. We have built, deployed, and evaluated the accuracy and efficiency of WebProphet. Applying WebProphet to the Search and Maps services of Google and Yahoo, we find WebProphet predicts the median and 95th percentiles of the page load time distribution with an error rate smaller than 16% in most cases. Using Yahoo Maps as an example, we find that WebProphet reduces the problem of performance optimization to a small number of web objects whose optimization would reduce the page load time by nearly 40%.
CBRAM devices as binary synapses for low-power stochastic neuromorphic systems: Auditory (Cochlea) and visual (Retina) cognitive processing applications

In this work, we demonstrate an original methodology to use Conductive-Bridge RAM (CBRAM) devices as binary synapses in low-power stochastic neuromorphic systems. A new circuit architecture, programming strategy and probabilistic STDP learning rule are proposed. We show, for the first time, how the intrinsic CBRAM device switching probability at ultra-low power can be exploited to implement probabilistic learning rule. Two complex applications are demonstrated: real-time auditory (from 64-channel human cochlea) and visual (from mammalian visual cortex) pattern extraction. A high accuracy (audio pattern sensitivity >2, video detection rate >95%) and ultra-low synaptic-power dissipation (audio 0.55μW, video 74.2μW) are obtained.
Consistency and Diversity of Spike Dynamics in the Neurons of Bed Nucleus of Stria Terminalis of the Rat: A Dynamic Clamp Study

Neurons display a high degree of variability and diversity in the expression and regulation of their voltage-dependent ionic channels. Under low level of synaptic background a number of physiologically distinct cell types can be identified in most brain areas that display different responses to standard forms of intracellular current stimulation. Nevertheless, it is not well understood how biophysically different neurons process synaptic inputs in natural conditions, i.e., when experiencing intense synaptic bombardment in vivo. While distinct cell types might process synaptic inputs into different patterns of action potentials representing specific “motifs” of network activity, standard methods of electrophysiology are not well suited to resolve such questions. In the current paper we performed dynamic clamp experiments with simulated synaptic inputs that were presented to three types of neurons in the juxtacapsular bed nucleus of stria terminalis (jcBNST) of the rat. Our analysis on the temporal structure of firing showed that the three types of jcBNST neurons did not produce qualitatively different spike responses under identical patterns of input. However, we observed consistent, cell type dependent variations in the fine structure of firing, at the level of single spikes. At the millisecond resolution structure of firing we found high degree of diversity across the entire spectrum of neurons irrespective of their type. Additionally, we identified a new cell type with intrinsic oscillatory properties that produced a rhythmic and regular firing under synaptic stimulation that distinguishes it from the previously described jcBNST cell types. Our findings suggest a sophisticated, cell type dependent regulation of spike dynamics of neurons when experiencing a complex synaptic background. The high degree of their dynamical diversity has implications to their cooperative dynamics and synchronization.
Gravitational Softening in Simulations with Adaptive Mass Resolution

Pairwise forces between particles in cosmological N-body simulations are generally softened to avoid hard collisions. Physically, this softening corresponds to treating the particles as diffuse clouds rather than point masses. For particles of unequal mass (and hence unequal softening length), computing the softened force involves a nontrivial double integral over the volumes of the two particles. We show that Plummer force softening is consistent with this interpretation of softening while spline softening is not. We provide closed-form expressions and numerical implementation for pairwise gravitational force laws for pairs of particles of general softening scales ε1 and ε2 assuming the commonly used cloud profiles: NGP, CIC, TSC, and PQS. Similarly, we generalize Plummer force law into pairs of particles of general softenings. We relate our expressions to the gaussian, Plummer and spline force softenings known from literature. Our expressions allow inclusions of pointlike particles such as stars or supermassive black holes.
Sympathetic Neural Adaptation to Hypocaloric Diet With or Without Exercise Training in Obese Metabolic Syndrome Subjects

OBJECTIVE Sympathetic nervous system (SNS) overactivity contributes to the pathogenesis and target organ complications of obesity. This study was conducted to examine the effects of lifestyle interventions (weight loss alone or together with exercise) on SNS function. RESEARCH DESIGN AND METHODS Untreated men and women (mean age 55 ± 1 year; BMI 32.3 ± 0.5 kg/m2) who fulfilled Adult Treatment Panel III metabolic syndrome criteria were randomly allocated to either dietary weight loss (WL, n = 20), dietary weight loss and moderate-intensity aerobic exercise (WL+EX, n = 20), or no treatment (control, n = 19). Whole-body norepinephrine kinetics, muscle sympathetic nerve activity by microneurography, baroreflex sensitivity, fitness (maximal oxygen consumption), metabolic, and anthropometric measurements were made at baseline and 12 weeks. RESULTS Body weight decreased by −7.1 ± 0.6 and −8.4 ± 1.0 kg in the WL and WL+EX groups, respectively (both P < 0.001). Fitness increased by 19 ± 4% (P < 0.001) in the WL+EX group only. Resting SNS activity decreased similarly in the WL and WL+EX groups: norepinephrine spillover by −96 ± 30 and −101 ± 34 ng/min (both P < 0.01) and muscle sympathetic nerve activity by −12 ± 6 and −19 ± 4 bursts/100 heart beats, respectively (both P < 0.01), but remained unchanged in control subjects. Blood pressure, baroreflex sensitivity, and metabolic parameters improved significantly and similarly in the two lifestyle intervention groups. CONCLUSIONS The addition of moderate-intensity aerobic exercise training to a weight loss program does not confer additional benefits on resting SNS activity. This suggests that weight loss is the prime mover in sympathetic neural adaptation to a hypocaloric diet.
Building change detection based on 3D reconstruction

Automatic building change detection at different periods is very important for city monitoring, disaster assessment, map updating, etc. Some existing data sources could be used in this task such as 3D geometry model (e.g. Digital Surface Model, Geographic Information System) and radiometric images from satellites or special aircrafts. However, it is too expensive for timely change detection by using these above methods. With the rapid development of UAV technique, capturing the city building images with high resolution camera at a low altitude becomes cheaper and cheaper. Using these easily acquired aerial images, we proposed a novel change detection framework based on RGB-D map generated by 3D reconstruction, which can overcome the large illumination changes. Firstly, an image-based 3D reconstruction is applied to retrieve two point clouds and related camera poses from two aerial image sets captured at different periods. Then an RGB-D map could be generated from each 3D model, followed by a 2D-3D registration procedure to align the two reconstructed 3D point clouds together. At last, a difference depth map could be generated and from which we can use random forest classification and component connectivity analysis techniques to segment the changed building areas out. Experimental results have illustrated the effectiveness and applicability of the proposed framework.
Endotoxemia Is Associated With an Increased Risk of Incident Diabetes

OBJECTIVE Diabetes is accompanied with a chronic low-grade inflammation, which may in part be mediated by endotoxins derived from Gram-negative bacteria. RESEARCH DESIGN AND METHODS We investigated in a population-based cohort whether endotoxemia is associated with clinically incident diabetes. The serum endotoxin activity was measured by limulus assay from the FINRISK97 cohort comprising 7,169 subjects aged 25–74 years and followed up for 10 years. RESULTS Both the subjects with prevalent diabetes (n = 537) and those with incident diabetes (n = 462) had higher endotoxin activity than the nondiabetic individuals (P < 0.001). The endotoxin activity was significantly associated with increased risk for incident diabetes with a hazard ratio 1.004 (95% CI 1.001–1.007; P = 0.019) per unit increase resulting in a 52% increased risk (P = 0.013) in the highest quartile compared with the lowest one. The association was independent of diabetes risk factors: serum lipids, γ-glutamyl transferase, C-reactive protein, BMI, and blood glucose. Furthermore, the association of endotoxemia with an increased risk of incident diabetes was independent of the metabolic syndrome as defined either by the National Cholesterol Educational Program-Adult Treatment Panel III or the International Diabetes Federation. Endotoxin activity was linearly related (P < 0.001) to the number of components of the metabolic syndrome. CONCLUSIONS Both prevalent and incident diabetes were associated with endotoxemia, which may link metabolic disorders to inflammation. The results suggest that microbes play a role in the pathogenesis of diabetes.
Learning submodular functions

There has been much interest in the machine learning and algorithmic game theory communities on understanding and using submodular functions. Despite this substantial interest, little is known about their learnability from data. Motivated by applications, such as pricing goods in economics, this paper considers PAC-style learning of submodular functions in a distributional setting. A problem instance consists of a distribution on {0,1}n and a real-valued function on {0,1}n that is non-negative, monotone, and submodular. We are given poly(n) samples from this distribution, along with the values of the function at those sample points. The task is to approximate the value of the function to within a multiplicative factor at subsequent sample points drawn from the same distribution, with sufficiently high probability. We develop the first theoretical analysis of this problem, proving a number of important and nearly tight results. For instance, if the underlying distribution is a product distribution then we give a learning algorithm that achieves a constant-factor approximation (under some assumptions). However, for general distributions we provide a surprising Omega(n1/3) lower bound based on a new interesting class of matroids and we also show a O(n1/2) upper bound. Our work combines central issues in optimization (submodular functions and matroids) with central topics in learning (distributional learning and PAC-style analyses) and with central concepts in pseudo-randomness (lossless expander graphs). Our analysis involves a twist on the usual learning theory models and uncovers some interesting structural and extremal properties of submodular functions, which we suspect are likely to be useful in other contexts. In particular, to prove our general lower bound, we use lossless expanders to construct a new family of matroids which can take wildly varying rank values on superpolynomially many sets; no such construction was previously known. This construction shows unexpected extremal properties of submodular functions.
PET-SORTEO: a platform for simulating realistic PET studies

We present here the features and validation results of a Monte Carlo-based PET simulation platform designed to address the increasing need of simulated studies. The simulation tool, named PET-SORTEO, includes i) the generation of the raw projections in accordance with both the numerical phantom description as well as with the scanner geometry and physical characteristics, and ii) the correction and reconstruction of the raw data. Validation results show that the platform reliably reproduces the image formation processes and includes correctly the sources of noise and biases