Miracle-dz/UniFAR-FTUs huggingface dataset:
A pro-inflammatory genotype predisposes to Barrett's esophagus.

INTRODUCTION Severity of mucosal inflammation is shown to be associated with Barrett's esophagus (BE) development in animals. It has therefore been postulated that a strong pro-inflammatory host response predisposes to BE. AIM To determine the impact of cytokine gene polymorphisms on the development of BE. METHODS The multiplex SNaPshot method was used to determine interleukin (IL)-12B (A+1188C), IL-10 (C-592A, C-819T, A-1082G), IL-8 (A-251T), IL-6 (G-174C) and IL-2 (G-330T) gene polymorphisms in 255 patients with BE and 247 patients with reflux esophagitis (RE). RESULTS The presence of the IL-12B C-allele, which is associated with increased IL-12p70 expression, was more frequently observed in BE than in RE patients [odds ratio (OR) 1.8; 95% confidence interval (CI) 1.2-2.7; P = 0.007). The risk of BE was increased in patients in whom the IL-12B C-allele coincided with a hiatal hernia (OR 2.9; 95% CI 1.32-6.58; P = 0.008). The IL-10(-1082) GG genotype, which is associated with higher IL-10 levels, was also associated with a decreased risk of BE when it was associated with the IL-12B C-allele, indicating IL-10-dependent down-regulation of IL-12p70 expression. A combination of the IL-12B AA genotype and the IL-10 AA or AG genotypes was associated with RE (OR 1.4; 95% CI 1.05-1.85; P = 0.011). CONCLUSION A genetic profile predisposing to a strong pro-inflammatory host response, mediated by IL-12p70 and partially dependent on IL-10, is associated with BE. This risk further increases when this genotype coincides with a hiatal hernia, suggesting that exposure to gastroesophageal reflux in the presence of a pro-inflammatory genetic background is a driving force in the development of BE.
The Response of Mycobacterium Tuberculosis to Reactive Oxygen and Nitrogen Species

The bacteriostatic and bactericidal effects and the transcriptional response of Mycobacterium tuberculosis to representative oxidative and nitrosative stresses were investigated by growth and survival studies and whole genome expression analysis. The M. tuberculosis reaction to a range of hydrogen peroxide (H2O2) concentrations fell into three distinct categories: (1) low level exposure resulted in induction of a few highly sensitive H2O2-responsive genes, (2) intermediate exposure resulted in massive transcriptional changes without an effect on growth or survival, and (3) high exposure resulted in a muted transcriptional response and eventual death. M. tuberculosis appears highly resistant to DNA damage-dependent, mode-one killing caused by low millimolar levels of H2O2 and only succumbs to overwhelming levels of oxidative stress observed in mode-two killing. Nitric oxide (NO) exposure initiated much the same transcriptional response as H2O2. However, unlike H2O2 exposure, NO exposure induced dormancy-related genes and caused dose-dependent bacteriostatic activity without killing. Included in the large shared response to H2O2 and NO was the induction of genes encoding iron–sulfur cluster repair functions including iron acquisition. Stress regulons controlled by IdeR, Sigma H, Sigma E, and FurA comprised a large portion of the response to both stresses. Expression of several oxidative stress defense genes was constitutive, or increased moderately from an already elevated constitutive level, suggesting that bacilli are continually primed for oxidative stress defense.
Fluid observers and tilting cosmology

We study perfect fluid cosmological models with a constant equation of state parameter γ in which there are two naturally defined timelike congruences, a geometrically defined geodesic congruence and a non-geodesic fluid congruence. We establish an appropriate set of boost formulae relating the physical variables, and consequently the observed quantities, in the two frames. We study expanding spatially homogeneous tilted perfect fluid models, with an emphasis on future evolution with extreme tilt. We show that for ultra-radiative equations of state (i.e. γ > 4/3), generically the tilt becomes extreme at late times and the fluid observers will reach infinite expansion within a finite proper time and experience a singularity similar to that of the big rip. In addition, we show that for sub-radiative equations of state (i.e. γ < 4/3), the tilt can become extreme at late times and give rise to an effective quintessential equation of state. To establish the connection with phantom cosmology and quintessence, we calculate the effective equation of state in the models under consideration and we determine the future asymptotic behaviour of the tilting models in the fluid frame variables using the boost formulae. We also discuss spatially inhomogeneous models and tilting spatially homogeneous models with a cosmological constant.
Population structure in the native range predicts the spread of introduced marine species

Forecasting invasion success remains a fundamental challenge in invasion biology. The effort to identify universal characteristics that predict which species become invasive has faltered in part because of the diversity of taxa and systems considered. Here, we use an alternative approach focused on the spread stage of invasions. FST, a measure of alternative fixation of alleles, is a common proxy for realized dispersal among natural populations, summarizing the combined influences of life history, behaviour, habitat requirements, population size, history and ecology. We test the hypothesis that population structure in the native range (FST) is negatively correlated with the geographical extent of spread of marine species in an introduced range. An analysis of the available data (29 species, nine phyla) revealed a significant negative correlation (R2 = 0.245–0.464) between FST and the extent of spread of non-native species. Mode FST among pairwise comparisons between populations in the native range demonstrated the highest predictive power (R2 = 0.464, p < 0.001). There was significant improvement when marker type was considered, with mtDNA datasets providing the strongest relationship (n = 21, R2 = 0.333–0.516). This study shows that FST can be used to make qualitative predictions concerning the geographical extent to which a non-native marine species will spread once established in a new area.
Discovering Alzheimer Genetic Biomarkers Using Bayesian Networks

Single nucleotide polymorphisms (SNPs) contribute most of the genetic variation to the human genome. SNPs associate with many complex and common diseases like Alzheimer's disease (AD). Discovering SNP biomarkers at different loci can improve early diagnosis and treatment of these diseases. Bayesian network provides a comprehensible and modular framework for representing interactions between genes or single SNPs. Here, different Bayesian network structure learning algorithms have been applied in whole genome sequencing (WGS) data for detecting the causal AD SNPs and gene-SNP interactions. We focused on polymorphisms in the top ten genes associated with AD and identified by genome-wide association (GWA) studies. New SNP biomarkers were observed to be significantly associated with Alzheimer's disease. These SNPs are rs7530069, rs113464261, rs114506298, rs73504429, rs7929589, rs76306710, and rs668134. The obtained results demonstrated the effectiveness of using BN for identifying AD causal SNPs with acceptable accuracy. The results guarantee that the SNP set detected by Markov blanket based methods has a strong association with AD disease and achieves better performance than both naïve Bayes and tree augmented naïve Bayes. Minimal augmented Markov blanket reaches accuracy of 66.13% and sensitivity of 88.87% versus 61.58% and 59.43% in naïve Bayes, respectively.
Study for Channel Estimation in OFDM System Based on Comb-Pilot

OFDM is an important technology in the high-speed date transmission. The channel estimation is the key technology in the OFDM system. In this paper, the OFDM system is mainly introduced. The channel estimation technology based on the comb- pilot is deeply studied. Through the simulation the different interpolation algorithms based on the comb-pilot are deeply compared. At last we get the important conclusion.
Performance analysis Toolset for wireless intrusion detection systems

This paper presents a Toolset that can be used to evaluate the performance and effectiveness of wireless intrusion detection techniques. Recently, autonomic computing methods have been widely used for intrusion detection [1]. Although some wireless intrusion detection systems (WIDSs) exist on the market, recent studies show that wireless networks are still vulnerable to complex, dynamic, and knowledgeable attacks. In this paper, we review current wireless intrusion detection systems and evaluate their performance to detect a wide range of wireless network attacks. To evaluate the performance of WIDSs, we use several performance metrics to quantify the accuracy, extendibility, adaptability, scalability, overhead, and latency of the examined WIDSs. Our experimental results show that this toolset can reveal different weaknesses in the examined WIDSs.
SAC: semantic adaptive caching for spatial mobile applications

Mobile location-based applications rely heavily on network connections. When the mobile devices are offline, such applications become less accessible to users. A cache-based method is proposed to improve the offline accessibility for mobile location-based applications. The central idea is that when users are browsing information, the client program not only submits the current query window to the server, but also attempts to predict the most likely (from a probabilistic standpoint) query windows that would be submitted to the server in the future. The major challenge is the very large number of possible future query windows. This challenge is tackled by proposing a discretization technique that makes predictions over a finite subset of all possible query windows. A probabilistic model is proposed for prediction, which is trained using the query log recorded by the client, so that the prediction can be executed entirely on the client side. The advantage of this technique is that it requires no modification on the existing server side, so it can be adapted by most existing applications easily. The usability of the technique is demonstrated by prototyping it on top the NewsStand system so that the query window is constantly changing as users pan and zoom around the world using a gesturing interface, among others. Evaluation shows the prototype to be effective while decreasing the response time.
Probing the rotation curve of the outer accretion disk in FU Orionis objects with long-wavelength spectroscopy

Studies of the Spectral Energy Distribution of Young Stellar Objects suggest that the outer disk of FU Orionis objects might be self-gravitating. In this paper we propose a method to test directly whether, in these objects, significant deviations from Keplerian rotation occur. In a first approach, we have used a simplified model of the disk vertical structure that allows us to quickly bring out effects related to the disk self-gravity. We find that the often studied optical and near-infrared line profiles are produced too close to the central object to provide significant evidence for non-Keplerian rotation. Based on parameters relevant for the case of FU Ori, we show that high-resolution long-wavelength spectroscopy, of the far-infrared H 2 pure rotational lines (sometimes observed in "passive" protostellar disks) and sub-mm CO lines, should be well suited to probe the rotation curve in the outer disk, thus measuring to what extent it is affected by the disk self-gravity. The results of the present exploratory paper should be extended soon to a more realistic treatment of the disk vertical structure.
Altered Resting State Brain Dynamics in Temporal Lobe Epilepsy Can Be Observed in Spectral Power, Functional Connectivity and Graph Theory Metrics

Despite a wealth of EEG epilepsy data that accumulated for over half a century, our ability to understand brain dynamics associated with epilepsy remains limited. Using EEG data from 15 controls and 9 left temporal lobe epilepsy (LTLE) patients, in this study we characterize how the dynamics of the healthy brain differ from the “dynamically balanced” state of the brain of epilepsy patients treated with anti-epileptic drugs in the context of resting state. We show that such differences can be observed in band power, synchronization and network measures, as well as deviations from the small world network (SWN) architecture of the healthy brain. The θ (4–7 Hz) and high α (10–13 Hz) bands showed the biggest deviations from healthy controls across various measures. In particular, patients demonstrated significantly higher power and synchronization than controls in the θ band, but lower synchronization and power in the high α band. Furthermore, differences between controls and patients in graph theory metrics revealed deviations from a SWN architecture. In the θ band epilepsy patients showed deviations toward an orderly network, while in the high α band they deviated toward a random network. These findings show that, despite the focal nature of LTLE, the epileptic brain differs in its global network characteristics from the healthy brain. To our knowledge, this is the only study to encompass power, connectivity and graph theory metrics to investigate the reorganization of resting state functional networks in LTLE patients.
A 1.3mW 20dB gain low power inductorless LNA with 4dB Noise Figure for 2.45GHz ISM band

This paper presents an inductorless low power (LP) low noise amplifier (LNA) based on a Common Gate (CG) topology. The circuit combines gain boosting techniques to enable high gain LP LNA. The circuit is integrated in a 130nm CMOS technology and shows 20dB gain with 4dB Noise Figure and −12dBm IIP3. The power consumption is 1.32mW from a 1.2V supply.
Serum Levels of Platelet Released CD40 Ligand Are Increased in Early Onset Occlusive Carotid Artery Disease

Objective: Soluble CD40 ligand (sCD40L) has been suggested as a key mediator between inflammation and atherosclerosis, and the CD40-CD40L interaction has a role in atherosclerotic lesion progression. We evaluated if platelet released serum sCD40L and sCD40 levels differ between patients with early onset occlusive carotid artery disease and age-matched controls. Methods: sCD40L and sCD40 levels were measured in serum samples of 60 patients with occlusive carotid artery disease and 30 age-matched controls using ELISA. Degree of stenosis of the internal carotid artery (ICA), and intima-media thickness (IMT) in the common carotid artery were measured by high resolution ultrasound. Values are given as mean ± SD. Results: Mean age was 50.9 ± 3.5 and 50.1 ± 3.5 years in the patient and control groups. IMT was significantly thicker in patients than in controls (0.89 ± 0.14 vs. 0.78 ±0.12 mm, p = 0.0003). Serum levels of sCD40L were significantly higher (6.9 ± 5 vs. 4.5 ± 3.0 ng/mL, p = 0.038) in patients, whereas sCD40 did not differ significantly between patients and controls (85 ± 56.9 vs. 79.3 ± 18.7 pg/mL, p = 0.34). IMT did not correlate with sCD40L or sCD40 levels (R = −0.03, p = 0.77; and R = 0.109, p = 0.308, respectively). Conclusions: sCD40L but not sCD40 levels are significantly higher in patients with occlusive carotid artery disease. Platelet derived sCD40L may be a key mediator among inflammation, thrombosis and atherosclerosis.
On Partially Observable Markov Decision Processes Using Genetic Algorithm Based Q-Learning

As powerful probabilistic models for optimal policy search, partially observable Markov decision processes (POMDPs) still suffer from the problems such as hidden state and uncertainty in action effects. In this paper, a novel approximate algorithm Genetic algorithm based Q-Learning (GAQ-Learning), is proposed to solve the POMDP problems. In the proposed methodology, genetic algorithms maintain a population of policy, whereas the traditional Q-learning obtains predictive rewards to indicate fitness of the evolved policies. GAQ-Learning solves the hidden state problem using a novel hybrid method, in which the historical information is incorporated with the current belief state to find the optimal policy. The experiments conducted on benchmark datasets show that the proposed methodology is superior to other state-of-the-art POMDP approximate methods.
Optimizing Smartphone Power Consumption through Dynamic Resolution Scaling

The extremely-high display density of modern smartphones imposes a significant burden on power consumption, yet does not always provide an improved user experience and may even lead to a compromised user experience. As human visually-perceivable ability highly depends on the user-screen distance, a reduced display resolution may still achieve the same user experience when the user-screen distance is large. This provides new power-saving opportunities. In this paper, we present a flexible dynamic resolution scaling system for smartphones. The system adopts an ultrasonic-based approach to accurately detect the user-screen distance at low-power cost and makes scaling decisions automatically for maximum user experience and power saving. App developers or users can also adjust the resolution manually as their needs. Our system is able to work on existing commercial smartphones and support legacy apps, without requiring re-building the ROM or any changes of apps. An end-to-end dynamic resolution scaling system is implemented on the Galaxy S5 LTE-A and Nexus 6 smartphones, and the correctness and effectiveness are evaluated against 30 games and benchmarks. Experimental results show that all the 30 apps can run successfully with per-frame, real-time dynamic resolution scaling. The energy per frame can be reduced by 30.1% on average and up to 60.5\% at most when the resolution is halved, for 15 apps. A user study with 10 users indicates that our system remains good user experience, as none of the 10 users could perceive the resolution changes in the user study.
La evaluación de lenguas en un colegio plurilingüe: Un estudio de caso de las creencias pedagógicas del profesorado

L’article descriu els resultats d’un estudi de cas que investiga les creences, representacions i sabers de professors de llengua, indaga sobre com expliquen aquests professors les seves practiques d’avaluacio amb alumnes que aprenen simultaniament diverses llengues. Amb aquesta finalitat es va escollir un centre internacional que porta mes d’un segle experimentant l’ensenyament plurilingue. Es van realitzar tres entrevistes semi - estructurades, l’analisi de les quals desvela que cada docent enten l’avaluacio com a part integrant del proces d’ensenyament-aprenentatge. Des del punt de vista de l’alumne, els metodes que empren els docents es complementen, encara que el plantejament de la seva avaluacio en cada cas es monolingue.
An asymptotic GLRT for the detection of cyclostationary signals

We derive the generalized likelihood ratio test (GLRT) for detecting cyclostationarity in scalar-valued time series. The main idea behind our approach is Gladyshev's relationship, which states that when the scalar-valued cyclostationary signal is blocked at the known cycle period it produces a vector-valued wide-sense stationary process. This result amounts to saying that the covariance matrix of the vector obtained by stacking all observations of the time series is block-Toeplitz if the signal is cyclostationary, and Toeplitz if the signal is wide-sense stationary. The derivation of the GLRT requires the maximum likelihood estimates of Toeplitz and block-Toeplitz matrices. This can be managed asymptotically (for large number of samples) exploiting Szegö's theorem and its generalization for vector-valued processes. Simulation results show the good performance of the proposed GLRT.
A general approach for calculating coupling impedances of small discontinuities

A general theory of the beam interaction with small discontinuities of the vacuum chamber is developed taking into account the reaction of radiated waves back on the discontinuity. The reactive impedance calculated earlier is reproduced as the first order, and the resistive one as the second order of a perturbation theory based on this general approach. The theory also gives, in a very natural way, the results for the trapped modes due to small discontinuities obtained earlier by a different method.
Primary Biological Motivators in Music Media: Motivated Processing of Sex and Violence

ABSTRACT This study examined the processing of primary biologically motivating content commonly found in popular music videos—sex and violence—from a motivated cognition perspective (Lang, 2006, 2009). Participants (N = 68) were presented with music videos containing different combinations of primary biologically motivating content (i.e., sex, violence, both, neither). Secondary task reaction times were used to index resources available for encoding and a visual recognition task was applied to measure memory. The results indicate that music videos that contained both sex and violence provided the most engaging and memorable experiences, potentially even flow experiences. Implications for processing these types of information in these ways are discussed and future research is suggested.
Geographical Terminology Servers - Closing the Semantic Divide

About the book: As the use of geographical information systems develops apace, a significant strand of research activity is being directed to the fundamental nature of geographic information. This volume contains a collection of essays and discussions on this theme. What is geographic information? What fundamental principles are associated with it? How can it be represented? How does it represent the world? How can geographic information be quantified? How can it be communicated and related to the other information sciences? How does HCI tie in with it? A number of other more specific but relevant issues are considered, such as Spatio-temporal relationships, boundaries, granularity and taxonomy. This book is a revised and updated version of a collection of presentations given by a group of distinguished researchers in the field of Geographic Information Science who gathered in Manchester in July 2001. It should be useful for graduate students as well as researchers and high-level professionals.
Adaptive hybrid optical switching: Performance and energy efficiency

Hybrid optical switching HOS has the potential to provide highly efficient operation through combining various switching paradigms and different implementation options within the same network. The flexibility of choosing between circuit, packet or burst switching and electronic or optical implementation results in an improvement of both energy and data transport efficiency because the most appropriate method and less power consuming elements can be selected and used for transmission of data through the network while temporarily inactive elements are switched off or put in a low-power mode. In this paper, we introduce a novel network concept that we refer to as adaptive hybrid optical switching AHOS and present and investigate several architectures and realization options for AHOS nodes. The corresponding control plane comprises two layers, of which one implements routing, signalling and link management functions as defined in the GMPLS standard while the other is responsible for managing already established circuits and scheduling the transmission of packets and bursts. We present results on both performance and energy consumption for different AHOS node realizations, network configurations and traffic patterns, which prove the potential for a high improvement in energy efficiency with respect to conventional electronic packet-switched networks.