Miracle-dz/UniFAR-FTUs huggingface dataset:
Expression of Sme Efflux Pumps and Multilocus Sequence Typing in Clinical Isolates of Stenotrophomonas maltophilia

Background Stenotrophomonas maltophilia has emerged as an important opportunistic pathogen, which causes infections that are often difficult to manage because of the inherent resistance of the pathogen to a variety of antimicrobial agents. In this study, we analyzed the expressions of smeABC and smeDEF and their correlation with antimicrobial susceptibility. We also evaluated the genetic relatedness and epidemiological links among 33 isolates of S. maltophilia. Methods In total, 33 S. maltophilia strains were isolated from patients in a tertiary hospital in Daejeon. Minimum inhibitory concentrations (MICs) of 11 antimicrobial agents were determined by using agar dilution method and E-test (BioMérieux, France). Real-time PCR analysis was performed to evaluate the expression of the Sme efflux systems in the S. maltophilia isolates. Additionally, an epidemiological investigation was performed using multilocus sequence typing (MLST) assays. Results The findings of susceptibility testing showed that the majority of the S. maltophilia isolates were resistant to β-lactams and aminoglycosides. Twenty-one clinical isolates overexpressed smeABC and showed high resistance to ciprofloxacin. Moreover, a high degree of genetic diversity was observed among the S. maltophilia isolates; 3 sequence types (STs) and 23 allelic profiles were observed. Conclusions The smeABC efflux pump was associated with multidrug resistance in clinical isolates of S. maltophilia. In particular, smeABC efflux pumps appear to perform an important role in ciprofloxacin resistance of S. maltophilia. The MLST scheme for S. maltophilia represents a discriminatory typing method with stable markers and is appropriate for studying population structures.
Variational Mesh Denoising Using Total Variation and Piecewise Constant Function Space

Mesh surface denoising is a fundamental problem in geometry processing. The main challenge is to remove noise while preserving sharp features (such as edges and corners) and preventing generating false edges. We propose in this paper to combine total variation (TV) and piecewise constant function space for variational mesh denoising. We first give definitions of piecewise constant function spaces and associated operators. A variational mesh denoising method will then be presented by combining TV and piecewise constant function space. It is proved that, the solution of the variational problem (the key part of the method) is in some sense continuously dependent on its parameter, indicating that the solution is robust to small perturbations of this parameter. To solve the variational problem, we propose an efficient iterative algorithm (with an additional algorithmic parameter) based on variable splitting and augmented Lagrangian method, each step of which has closed form solution. Our denoising method is discussed and compared to several typical existing methods in various aspects. Experimental results show that our method outperforms all the compared methods for both CAD and non-CAD meshes at reasonable costs. It can preserve different levels of features well, and prevent generating false edges in most cases, even with the parameters evaluated by our estimation formulae.
Using Machine Learning to Maintain Rule-based Named-Entity Recognition and Classification Systems

This paper presents a method that assists in maintaining a rule-based named-entity recognition and classification system. The underlying idea is to use a separate system, constructed with the use of machine learning, to monitor the performance of the rule-based system. The training data for the second system is generated with the use of the rule-based system, thus avoiding the need for manual tagging. The disagreement of the two systems acts as a signal for updating the rule-based system. The generality of the approach is illustrated by applying it to large corpora in two different languages: Greek and French. The results are very encouraging, showing that this alternative use of machine learning can assist significantly in the maintenance of rule-based systems.
Ju n 20 05 Off-perturbative states in disordered systems

The systematic approach for the off-perturbative calculations in disordered systems is developed. The proposed scheme is applied for the random temperature and the random field ferromagnetic Ising models. It is shown that away from the critical point, in the paramagnetic phase of the random temperature model, and in the ferromagnetic phase of the random field one, the free energy contains non-analytic contributions which have the form of essential singularities. It is demonstrated that these contributions appear due to localized in space instanton-like excitations.
Monitoring the heart rate in cerebral oximetry signals

Cerebral oximetry of the frontal lobes based on Near InfraRed Spectroscopy (NIRS) is used to monitor brain tissue oxygen saturation in 2–4 s intervals. However, higher sampling rates may enable heart rate (HR) monitoring. In total, 29 subjects were enrolled in 40 min recording sessions. Cerebral oxy-haemoglobin (O2Hb) concentration at 50 Hz and the ECG were concurrently recorded. ECG was the reference for the HR algorithms based on the O2Hb signal. The results show that accurate heart rate monitoring and beat detection on cerebral frontal lobe oximetry signals is feasible for normal heart conditions when the NIRS signals are sampled at high rates.
Suppressing traffic-driven epidemic spreading by edge-removal strategies

The interplay between traffic dynamics and epidemic spreading on complex networks has received increasing attention in recent years. However, the control of traffic-driven epidemic spreading remains to be a challenging problem. In this Brief Report, we propose a method to suppress traffic-driven epidemic outbreak by properly removing some edges in a network. We find that the epidemic threshold can be enhanced by the targeted cutting of links among large-degree nodes or edges with the largest algorithmic betweenness. In contrast, the epidemic threshold will be reduced by the random edge removal. These findings are robust with respect to traffic-flow conditions, network structures, and routing strategies. Moreover, we find that the shutdown of targeted edges can effectively release traffic load passing through large-degree nodes, rendering a relatively low probability of infection to these nodes.
Role for Matrix Metalloproteinase 9 in Granuloma Formation during Pulmonary Mycobacterium tuberculosis Infection

ABSTRACT Recent studies have shown that matrix metalloproteinases (MMPs) are induced by Mycobacterium tuberculosis during pulmonary infection. Here, expression of MMP-9 during pulmonary M. tuberculosis infection was characterized to determine whether its production correlated with disease resistance in vivo and to determine what role, if any, MMP-9 might have in granuloma formation. Following aerosol infection with M. tuberculosis, dissemination of bacilli occurred earlier in the C57BL/6 resistant mouse strain than in the susceptible CBA/J strain, as was evident from an increased number of bacteria in the blood, spleen, and liver at day 14 after infection. In addition, early dissemination of the bacilli was associated with early induction of protective immunity as assessed from gamma interferon levels. Nonspecific blocking of MMPs in C57BL/6 mice early during infection reduced hematogenous spread of the bacilli, suggesting that MMPs indeed play a role in facilitating dissemination, likely via extracellular matrix degradation. The concentration of active MMP-9, specifically, was greater in the lungs of C57BL/6 mice than in those of the CBA/J mice at day 28, thereby suggesting that MMP-9 is not one of the MMPs directly involved in promoting early dissemination of M. tuberculosis. Instead, however, histological lung sections and flow cytometric analysis of lung cells from MMP-9-knockout mice showed that MMP-9 is involved in macrophage recruitment and granuloma development. These combined data support the idea that early MMP activity is an essential component of resistance to pulmonary mycobacterial infection and that MMP-9, specifically, is required for recruitment of macrophages and tissue remodeling to allow for the formation of tight, well-organized granulomas.
Reconstructing fiber networks from confocal image stacks

We present a numerically efficient method to reconstruct a disordered network of thin biopolymers, such as collagen gels, from three-dimensional (3D) image stacks recorded with a confocal microscope. Our method is based on a template matching algorithm that simultaneously performs a binarization and skeletonization of the network. The size and intensity pattern of the template is automatically adapted to the input data so that the method is scale invariant and generic. Furthermore, the template matching threshold is iteratively optimized to ensure that the final skeletonized network obeys a universal property of voxelized random line networks, namely, solid-phase voxels have most likely three solid-phase neighbors in a $3\times3$ neighborhood. This optimization criterion makes our method free of user-defined parameters and the output exceptionally robust against imaging noise.
A state-space model to derive bluefin tuna movement and habitat from archival tags

Archival tagging provides a unique way to study the spatial dynamics and habitat of pelagic fish. This technique generates lagrangian data of a particular type in marine ecology: although highly informative about processes at different scales (e.g. horizontal movements versus diving behaviour), such data are impaired by location errors and the lack of combination with actual environmental variability. The present paper introduces a framework for modelling bluefin tuna movement in relation to its habitat, using records of light, depth and temperature from archival tags. Based on data assimilation concepts and methods, we show how an explicit formulation of the observation process and the statistics of external variables (e.g. ambient temperature) can improve precision in geolocation. The proposed method is tested on synthetic data: significant reduction (40 to 50%) in the initial root-mean square error is achieved under different noise scenarios. Assimilating sea surface temperature also allows to perform on-line estimation of a range of observation biases. The performance of the model greatly benefits from the adequate formalisation of different variability sources, and allows potentially to reveal interactions between the fish and its habitat. Using this probabilistic approach, we, however, show that some patterns of interest (e.g. foraging in surface fronts) can hardly be retrieved in a context of large observational and environmental noise.
Factors associated with the decline in stunting among children and adolescents in Pernambuco, Northeastern Brazil.

OBJECTIVE To analyze the evolution of stunting among children and adolescents and identify their associated factors. METHODS This was a cross-sectional study using data from the state health and nutrition surveys that were conducted in Pernambuco (Northeastern Brazil) in 1997 and 2006. The sample was probabilistic (random and stratified) and was representative of urban and rural strata of the state. Questionnaires containing precoded questions relating to information on socioeconomic, demographic and anthropometric variables (of the mothers, children and adolescents) were used for data gathering. The population studied comprised 1853 children and 1484 adolescents between the ages of five and 19 years. Multiple regression analysis with hierarchical selection was used to evaluate associations between explanatory variables relating to stunting. RESULTS The prevalence of stunting presented a significant reduction of 43% (from 16.9% in 1997 to 9.6% in 2006). Socioeconomic variables and maternal height were associated with this decline. The reductions ranged from 39% to 60% among the strata analyzed. Analysis on determinants of stunting showed that in 2006, the following remained significant: per capita family income (< 0.25 minimum salary), possession of domestic goods (< three), greater number of people per household, lower schooling level and lower maternal height. CONCLUSIONS The reduction in stunting reflected improvements in social and economic conditions. However, it remains necessary to maintain and improve public policies, in order to increase the purchasing power of the poorest people and to achieve universal access to health and education services for the population.
Game transport protocol: a reliable lightweight transport protocol for massively multiplayer online games (MMPOGs)

With the advent of high-speed access network technologies such as ADSL, increasing numbers of Internet users are participating in various interactive multimedia applications. Among these, the most popular are the massively interactive on-line games, or MMPOGs. In MMPOGs, a large amount of event data is associated with various control objects. This event data has different characteristics from that which is generally used on the Internet. Namely, events occur very frequently with short inter-arrival times and their size is quite small, because they only contain control information. Most commercial MMPOGs use TCP or UDP as the transport protocol for the event data. However, since TCP is such a heavy protocol, due to its complex congestion control algorithm and byte-oriented window scheme, it is difficult to support many concurrent users. On the other hand, UDP is a relatively lightweight protocol, but there are no functions available which permit reliable transmission and session management. In this paper, we propose a new transport protocol, Game Transport Protocol (GTP), which is designed for the transmission of the event data used by MMPOGs. GTP supports several functions designed to meet the various requirements of MMPOGs. Firstly, GTP uses a packet-based window scheme not a byte-based window scheme as in the case of TCP. This scheme is quite simple and suitable for the small size of the event data. Also, GTP performs session management and retransmission using GTP control blocks, and supports an adaptive retransmission scheme that controls the maximum number of retransmissions according to the real-time priority, in order to meet the time constraints of the event data. Although GTP is a specialized transport protocol, optimized for MMPOGs, it could also be utilized as a transport protocol for other interactive multimedia applications.
Motivating the corrective maintenance maturity model (CM/sup 3/)

Many process models have been hitherto suggested. Very few of them, however, deal with the most utilised process today: the maintenance process. The article presents and motivates the "Corrective Maintenance Maturity Model" (CM/sup 3/), a process model entirely dedicated to only software maintenance.
Efficient super-resolution and applications to mosaics

Mosaicing and super resolution are two ways to combine information from multiple frames in video sequences. Mosaicing displays the information of multiple frames in a single panoramic image. Super-resolution uses regions which appear in multiple frames to improve resolution and reduce noise. The aim of this work is constructing a high resolution mosaic from a video sequence in an efficient way. Simple combination of the two methods is problematic, since the alignment used in mosaicing may not be accurate enough for super resolution. Another issue is the efficiency of the super resolution algorithm, which requires heavy computations, especially when applied to large images such as panoramic mosaics. This paper introduces two novelties. First, a framework for super resolution algorithms is presented, which enables the development of very efficient algorithms. Second, a method for applying super resolution to panoramic mosaics is presented. This method preserves the geometry of the original mosaic image, while improving its resolution.
The Threshold of Anxiety in Low-Stakes Testing for Foreign Language Reading.

The following question has yet to be answered by researchers: when does anxiety have a systematic downward bias on foreign language (FL) reading test scores? The results of the correlation and regression analyses conducted in this study indicate that, at least in the case of university-level English learners in Japan, anxiety-induced bias occurs in a lowstakes FL reading test when the test becomes objectively challenging for students. Our data also suggest that concerns about unsuccessful text comprehension play a central role in the elevation of anxiety in a low-stakes test situation.
Sedna: A Memory Based Key-Value Storage System for Realtime Processing in Cloud

Comparing with the traditional disk based distributed storage system, RAM based storage has been proven to be an effective way to accelerate real time applications processing speed. In this paper, we propose a memory based distributed Cloud storage system called Sedna. Managing 'big data' across lots of commodity servers, Sedna provides high scalability, simple effective data access APIs with data consistency and persistency, and a new trigger based APIs for real time applications. To guarantee the scalability with low latency, we design and implement a hierarchical structure to manage huge size data center which is simple and effective. Except the high speed provided by memory based storage, Sedna absorbs advantages from state-of-art cloud programming frameworks, and gives programmers a new way to write massive data real time applications. These data read/write triggers APIs are necessary but are missing parts of modern distributed storage system. Experiments and examples show Sedna achieve comparable speed to widely-used distributed cache system, and provide a more efficient way to use distributed storage.
Cortical thickness and resting-state cardiac function across the lifespan: A cross-sectional pooled mega-analysis.

Understanding the association between autonomic nervous system [ANS] function and brain morphology across the lifespan provides important insights into neurovisceral mechanisms underlying health and disease. Resting-state ANS activity, indexed by measures of heart rate [HR] and its variability [HRV] has been associated with brain morphology, particularly cortical thickness [CT]. While findings have been mixed regarding the anatomical distribution and direction of the associations, these inconsistencies may be due to sex and age differences in HR/HRV and CT. Previous studies have been limited by small sample sizes, which impede the assessment of sex differences and aging effects on the association between ANS function and CT. To overcome these limitations, 20 groups worldwide contributed data collected under similar protocols of CT assessment and HR/HRV recording to be pooled in a mega-analysis (N = 1,218 (50.5% female), mean age 36.7 years (range: 12-87)). Findings suggest a decline in HRV as well as CT with increasing age. CT, particularly in the orbitofrontal cortex, explained additional variance in HRV, beyond the effects of aging. This pattern of results may suggest that the decline in HRV with increasing age is related to a decline in orbitofrontal CT. These effects were independent of sex and specific to HRV; with no significant association between CT and HR. Greater CT across the adult lifespan may be vital for the maintenance of healthy cardiac regulation via the ANS-or greater cardiac vagal activity as indirectly reflected in HRV may slow brain atrophy. Findings reveal an important association between CT and cardiac parasympathetic activity with implications for healthy aging and longevity that should be studied further in longitudinal research.
A Simple SQP Algorithm for Constrained Finite Minimax Problems

A simple sequential quadratic programming method is proposed to solve the constrained minimax problem. At each iteration, through introducing an auxiliary variable, the descent direction is given by solving only one quadratic programming. By solving a corresponding quadratic programming, a high-order revised direction is obtained, which can avoid the Maratos effect. Furthermore, under some mild conditions, the global and superlinear convergence of the algorithm is achieved. Finally, some numerical results reported show that the algorithm in this paper is successful.
Are V1 Simple Cells Optimized for Visual Occlusions? A Comparative Study

Simple cells in primary visual cortex were famously found to respond to low-level image components such as edges. Sparse coding and independent component analysis (ICA) emerged as the standard computational models for simple cell coding because they linked their receptive fields to the statistics of visual stimuli. However, a salient feature of image statistics, occlusions of image components, is not considered by these models. Here we ask if occlusions have an effect on the predicted shapes of simple cell receptive fields. We use a comparative approach to answer this question and investigate two models for simple cells: a standard linear model and an occlusive model. For both models we simultaneously estimate optimal receptive fields, sparsity and stimulus noise. The two models are identical except for their component superposition assumption. We find the image encoding and receptive fields predicted by the models to differ significantly. While both models predict many Gabor-like fields, the occlusive model predicts a much sparser encoding and high percentages of ‘globular’ receptive fields. This relatively new center-surround type of simple cell response is observed since reverse correlation is used in experimental studies. While high percentages of ‘globular’ fields can be obtained using specific choices of sparsity and overcompleteness in linear sparse coding, no or only low proportions are reported in the vast majority of studies on linear models (including all ICA models). Likewise, for the here investigated linear model and optimal sparsity, only low proportions of ‘globular’ fields are observed. In comparison, the occlusive model robustly infers high proportions and can match the experimentally observed high proportions of ‘globular’ fields well. Our computational study, therefore, suggests that ‘globular’ fields may be evidence for an optimal encoding of visual occlusions in primary visual cortex.
PPARγ2Pro12Ala Polymorphism and Human Health

The nuclear hormone receptor peroxisome proliferator activated receptor gamma (PPARγ) is an important transcription factor regulating adipocyte differentiation, lipid and glucose homeostasis, and insulin sensitivity. Numerous genetic mutations of PPARγ have been identified and these mutations positively or negatively regulate insulin sensitivity. Among these, a relatively common polymorphism of PPARγ, Pro12Ala of PPARγ2, the isoform expressed only in adipose tissue has been shown to be associated with lower body mass index, enhanced insulin sensitivity, and resistance to the risk of type 2 diabetes in human subjects carrying this mutation. Subsequent studies in different ethnic populations, however, have revealed conflicting results, suggesting a complex interaction between the PPARγ2 Pro12Ala polymorphism and environmental factors such as the ratio of dietary unsaturated fatty acids to saturated fatty acids and/or between the PPARγ2 Pro12Ala polymorphism and genetic factors such as polymorphic mutations in other genes. In addition, this polymorphic mutation in PPARγ2 is associated with other aspects of human diseases, including cancers, polycystic ovary syndrome, Alzheimer disease and aging. This review will highlight findings from recent studies.