Miracle-dz/UniFAR-FTUs huggingface dataset:
Association between asthma control test, pulmonary function tests and non-specific bronchial hyperresponsiveness in assessing the level of asthma control.

INTRODUCTION Global Initiative for Asthma (GINA) reports emphasize the use of validated and simple tools in order to assess the level of asthma control, as the Asthma Control Test (ACT). However, an ACT does not include assessment of airway inflammation, which is better reflected when measuring nonspecific bronchial hyperresponsiveness (BHR). The authors aimed to find out if the level of asthma control quantified by an ACT correlates with BHR and pulmonary function tests. MATERIAL AND METHODS 118 asthmatics participated in the study. All patients completed an ACT. The scores of the ACTs were compared with pulmonary function tests and BHR assessed with the methacholine challenge test and expressed as a provocative concentration of methacholine, inducing a 20% decline in the FEV1 (PC20 M in mg/ml). RESULTS Patients with controlled asthma amounted to 52 (44%) while those with uncontrolled asthma amounted to 66 (56%). In patients with controlled asthma (ACT score ≥ 20) the mean geometric value of PC20M was 2.72 mg/ml (range from 0.25 to > 8.0), whereas 0.94 mg/ml (range from 0.28 to 8.0) (p = 0.02) was observed in patients with uncontrolled asthma (ACT score < 20). Almost 64% (21/33) of uncontrolled asthmatics achieved normal lung function (FEV1 > 80% pred. value) while 19% (5/26) patients with controlled asthma presented an FEV1 < 80% predicted value. Asthma duration in years in controlled asthmatics was significantly shorter than in uncontrolled patients (6.2 ± 8.9 vs. 12.0 ± 11.4, p = 0.005) CONCLUSION: In determining the most accurate level of asthma control it is reasonable to use an ACT in conjunction with BHR, which provides more accurate assessment of bronchial inflammation than ventilatory parameters alone.
A Bayesian Approach to Quantifying the Effects of Mass Poultry Vaccination upon the Spatial and Temporal Dynamics of H5N1 in Northern Vietnam

Outbreaks of H5N1 in poultry in Vietnam continue to threaten the livelihoods of those reliant on poultry production whilst simultaneously posing a severe public health risk given the high mortality associated with human infection. Authorities have invested significant resources in order to control these outbreaks. Of particular interest is the decision, following a second wave of outbreaks, to move from a “stamping out” approach to the implementation of a nationwide mass vaccination campaign. Outbreaks which occurred around this shift in policy provide a unique opportunity to evaluate the relative effectiveness of these approaches and to help other countries make informed judgements when developing control strategies. Here we use Bayesian Markov Chain Monte Carlo (MCMC) data augmentation techniques to derive the first quantitative estimates of the impact of the vaccination campaign on the spread of outbreaks of H5N1 in northern Vietnam. We find a substantial decrease in the transmissibility of infection between communes following vaccination. This was coupled with a significant increase in the time from infection to detection of the outbreak. Using a cladistic approach we estimated that, according to the posterior mean effect of pruning the reconstructed epidemic tree, two thirds of the outbreaks in 2007 could be attributed to this decrease in the rate of reporting. The net impact of these two effects was a less intense but longer-lasting wave and, whilst not sufficient to prevent the sustained spread of outbreaks, an overall reduction in the likelihood of the transmission of infection between communes. These findings highlight the need for more effectively targeted surveillance in order to help ensure that the effective coverage achieved by mass vaccination is converted into a reduction in the likelihood of outbreaks occurring which is sufficient to control the spread of H5N1 in Vietnam.
Domain-Driven Development: the SmartTools Software Factory

With the increasing dependency on the Internet and the proliferation of new component and distributive technologies, the design and implementation of complex applications must take into account standards, code distribution, deployment of components and reuse of business logic. To cope with these changes, applications need to be more open, adaptable and capable of evolving. To accommodate to these new challenges, this paper presents a new development approach based on generators associated with domain-specific languages, each of the latter related to one possible concern useful when building an application. It relies on Generative Programming, Component Programming and Aspect-Oriented Programming. A software factory, called SmartTools, has been developed using this new approach. The main results are i) to build software of better quality and to enable rapid development due to Generative Programming and, ii) to facilitate insertion of new facets and the portability of applications to new technologies or platforms due to business logic and technology separation. Key-words: Software Factory, Domain-Driven Development, Generative Programming, Component Programming, Aspect-Oriented Programming ∗ INRIA Sophia-Antipolis 2004, route des Lucioles BP93 F-06902 Sophia-Antipolis cedex France Didier.Parigot@inria.fr † University College London Computer science department Adastral Park Martlesham IP5 3RE UK Carine.Courbis@bt.com Developpements diriges par les modeles : La fabrique logicielle SmartTools Resume : Avec l’emergence de l’Internet et la proliferation des technologies de composants, la conception et l’execution d’applications complexes doivent prendre en compte les standards, les aspects de distribution de code, de deploiement des composants, et de reutilisation. Pour faire face a ces changements, les applications doivent etre plus ouvertes, adaptables et etre capables d’evoluer rapidement. Pour s’adapter a ces nouveaux defis, cet article presente une nouvelle approche de developpement logicielle basee sur l’utilisation de generateurs associes et de langages metiers chacun dedie a une preoccupation utile pour la construction d’une application. Cette approche relie la programmation generative, la programmation par composants et la programmation par aspects. Une usine logicielle, appelee SmartTools, a ete developpee en utilisant cette nouvelle approche. Les resultats principaux sont i) une meilleure qualite du logiciel et un developpement rapide dus a la programmation generative et ii) une facilite d’ajout de nouvelles fonctionnalites et d’adaptation a de nouvelles technologies ou environnements dus a la separation entre le code metier et les technologies d’implementations. Mots-cles : Fabrique Logicielle, Developpement dirige par les Modeles, Programmation Generative, Programmation par Composants, Programmation par Aspects Domain-Driven Development 3
Predicting molecules--more realism, please!

The body of computations of molecules for which there is as yet no experimental evidence is growing very rapidly. This is simply wonderful—as a marker of the reliability of theory, and, sociologically, in creating a tense and fruitful balance between theory and synthesis in chemistry. Claims of “stability,” implicit and explicit, are made for the calculated molecules; we have been as guilty of this as others. We would like to suggest that literature reports of these claims be qualified, and that the computations performed be described in a circumspect way.
Experimental and clinical study of lactulose in obstructive jaundice

The role of lactulose in preventing endotoxaemia in obstructive jaundice has been investigated. A prospective study was performed on 24 consecutive patients with obstructive jaundice undergoing surgery. Twelve patients were given oral lactulose before operation and were compared with twelve controls. Endotoxaemia was reduced in peroperative portal (P < 0·05) and postoperative systemic (P < 0·05) blood samples in the lactulose treated group, and a significant fall (P < 0·05) occurred in the postoperative 24 h creatinine clearances in controls compared with the lactulose treated group. Results from animal experiments in which oral lactulose reduced endotoxin related mortality in obstructive jaundice (P < 0·05), and the in vitro demonstration of a direct anti‐endotoxic action of lactulose suggest that its beneficial action is due in part to an inactivation of endotoxin.
Optimal Use of Plant Stanol Ester in the Management of Hypercholesterolemia

Plant stanol ester is a natural compound which is used as a cholesterol-lowering ingredient in functional foods and food supplements. The safety and efficacy of plant stanol ester have been confirmed in more than 70 published clinical studies and the ingredient is a well-established and widely recommended dietary measure to reduce serum cholesterol. Daily intake of 2 g plant stanols as plant stanol ester lowers LDL-cholesterol by 10%, on average. In Europe, foods with added plant stanol ester have been on the market for 20 years, and today such products are also available in many Asian and American countries. Despite the well-documented efficacy, the full potential in cholesterol reduction may not be reached if plant stanol ester is not used according to recommendations. This review therefore concentrates on the optimal use of plant stanol ester as part of dietary management of hypercholesterolemia. For optimal cholesterol lowering aiming at a lower risk of cardiovascular disease, plant stanol ester should be used daily, in sufficient amounts, with a meal and in combination with other recommended dietary changes.
Oncolytic Viruses: Do They Have a Role in Anti-Cancer Therapy?

Oncolytic viruses are replication competent, tumor selective and lyse cancer cells. Their potential for anti-cancer therapy is based upon the concept that selective intratumoral replication will produce a potent anti-tumor effect and possibly bystander or remote cell killing, whilst minimizing normal tissue toxicity. Viruses may be naturally oncolytic or be engineered for oncolytic activity, and possess a host of different mechanisms to provide tumor selectivity. Clinical use of live replicating viruses is associated with a unique set of safety issues. Clinical experience has so far provided evidence of limited efficacy and a favourable toxicity profile. The interaction with the host immune system is complex. An anti-viral immune response may limit efficacy by rapidly clearing the virus. However, virally-induced cell lysis releases tumor associated antigens in a ‘dangerous’ context, and limited evidence suggests that this can lead to the generation of a specific anti-tumor immune response. Combination therapy with chemotherapy or radiotherapy represents a promising avenue for ongoing translation of oncolytic viruses into clinical practice. Obstacles to therapy include highly effective non-specific host mechanisms to clear virus following systemic delivery, immune-mediated clearance, and intratumoral barriers limiting virus spread. A number of novel strategies are now under investigation to overcome these barriers. This review provides an overview of the potential role of oncolytic viruses, highlighting recent progress towards developing effective therapy and asks if they are a realistic therapeutic option at this stage.
A Discrete Wavelet Transform Compression Technique Used in Underwater Sensor Network ( UWSN ) for Energy Efficiency

The underwater sensors are used in various activity monitoring, data sensing or other similar applications. The underwater sensors works in the dense medium than the air, which increases the possibility of higher data drop rates etc. The higher data drop rate decreases the efficiency of the Underwater Wireless Sensor Networks (UWSN), because high volumes of data drop causes higher number of missing values, which directly affects the statistical calculations. In this paper, the model has been proposed for the data compression of the sensor data in the underwater applications. The proposed model is offered with the discrete wavelet transform (DWT) method of compression. The DWT method decomposes the data into multiple coefficients. One coefficient is known as the approximation coefficient, which is the approximation of the original data, and the original data can be produced by using the reverse DWT process. The proposed model has been evaluated on the basis of network load, data loss, and power consumption etc. The experimental results have shown the effectiveness of the proposed model. Key wordsData compression, Electromagnetic signal compression, Signal decomposition, Wavelet compression, Underwater sensor
The dome of silence : sexual harassment and abuse in sport

This book frames the issue of sexual harassment and abuse in sports within the context of existing research on sexual violence and within the ethic of care, a direction the authors believe sport organizations should adopt. This book investigates sexual violence in sport and examines its underlying values. This is carried out in the context of contemporary experiences of a number of athletes. Issues covered include the emphasis on competition, compulsory heterosexuality, and patriotism.
Decreased numerical density of CA3 hippocampal mossy fiber synapses in schizophrenia

The CA3 region of the hippocampus is unique in its connectivity, its role in cognitive maintenance, and its great vulnerability in schizophrenia. The down regulation of the expression and binding activity of glutamate receptors was revealed in the CA3 hippocampal region and may be attributed to cognitive disturbances in schizophrenia. Our previous study demonstrated that only schizophrenics with predominantly positive (but not predominantly negative) symptoms had smaller‐sized branched spines (thorny excrescences) of CA3 pyramidal neurons and fewer synaptic contacts formed by dentate mossy fiber terminals (MFT‐synapses). In the present study, we used an unbiased stereological physical dissector method to verify whether the numerical density of MFT‐synapses is altered in schizophrenia. A morphometric study was performed in 10 normal controls and eight age‐matched cases with chronic schizophrenia, including five cases with predominantly positive and three with predominantly negative symptoms. Schizophrenic cases had a significantly reduced numerical density of MFT‐synapses (−25%, P < 0.01) compared with the control group. The decrease was similar in schizophrenic subgroups with predominantly positive and predominantly negative symptoms. No effects of postmortem delay, age, duration of disease, and neuroleptic exposure were found. Taken together with our previous results, the data suggest that the decrease of numerical density of MFT‐synapses may be the result of different mechanisms in schizophrenics with predominantly positive and predominantly negative symptoms. Synapse 61:615–621, 2007. © 2007 Wiley‐Liss, Inc.
Analysis of least congested path routing in WDM lightwave networks

Analyzes an adaptive routing rule in a WDM lightwave network. Each switching node in the network may have a number of wavelength converters which can be used to resolve wavelength conflicts in multi-hop paths. The authors found that without any wavelength converters, the wavelength conflict possesses an inherent blocking to alternate route traffic and that the use of wavelength converter to resolve wavelength conflicts does not give any significant reduction of blocking probability. <<ETX>>
Fuzzy Rule-Based Reinforcement Learning for Load Balancing Techniques in Enterprise LTE Femtocells

Mobile-broadband traffic has experienced a large increase over the past few years. Femtocells are envisioned to cope with such a demand of capacity in indoor environments. Since those small cells are low-cost nodes, a thorough deployment is not typically performed, particularly in enterprise scenarios. As a result, the matching between traffic demand and network resources is rarely optimal. In this paper, several load balancing techniques based on self-tuning of femtocell parameters are designed to solve localized congestion problems. In particular, these techniques are implemented by fuzzy logic controllers (FLC) and fuzzy rule-based reinforcement learning systems (FRLSs). Performance assessment is carried out in a dynamic system-level simulator. Results show that the combination of FLC and FRLS produces an increase in performance that is significantly higher than if techniques are implemented alone. Both the response time and the final value of performance indicators are improved.
Breathe, walk and chew : the neural challenge

This volume investigates the implications of how our brain directs our movements on decision-making. An extensive body of knowledge in chapters from international experts is presented as well as integrative group reports discussing new directions for future research. The understanding of how people make decisions is of central interest to experts working in fields such as psychology, economics, movement science, cognitive neuroscience, neuroinformatics, robotics, and sport science. For the first time the current volume provides a multidisciplinary overview of how action and cognition are integrated in the planning of and decisions about action. * Offers intense, focused, and genuine interdisciplinary perspective * Conveys state-of-the-art and outlines future research directions on the hot topic of mind and motion (or embodied cognition) * Includes contributions from psychologists, neuroscientists, movement scientists, economists, and others
A hierarchical training and identification method using Gaussian process models for face recognition in videos

In a video based face identification task, a sequence of frames can be utilized to identify the subject in the video. The information extracted from frames can provide samples of the subject in different head poses and facial expressions and under various lighting conditions which enriches the training process. However, some of these frames may not be useful for identification due to noise from various sources (such as occlusion, low resolution, and face tracking errors). It is important to reduce the effect of noisy samples by designing a representation structure that is capable of alleviating the noise in each sequence, complemented by developing a recognition procedure that rejects the wrong decisions affected by noise. In this paper we propose a sequence representation called Ensemble of Abstract Sequence Representatives (EASR) that is aimed at reducing the effect of noisy frames in a sequence. EASRs are used to guide the sampling process in a learning scheme called specialization - generalization which is used to train an ensemble of binary Gaussian Process (GP) models. Identification is done using: (i) the similarity between the EASRs of the gallery and probe images, and (ii) the label provided by the ensemble of GP classifier models. Evaluation of our approach on three publicly available benchmark datasets demonstrates significantly better performance compared to the state-of-the-art.
Beyond Holistic Descriptors, Keypoints, and Fixed Patches: Multiscale Superpixel Grids for Place Recognition in Changing Environments

Vision-based place recognition in environments subject to severe appearance changes due to day-night cycles, changing weather or seasons is a challenging task. Existing methods typically exploit image sequences, holistic descriptors and/or training data. Each of these approaches limits the practical applicability, e.g., to constant viewpoints for usage of holistic image descriptors. Recently, the combination of local region detectors and descriptors based on convolutional neural networks showed to be a promising approach to overcome these limitations. However, established region detectors, e.g., keypoint detectors, showed severe problems to provide repetitive landmarks despite dramatically changed appearance of the environment. Thus, they are typically replaced by holistic image descriptors or fixedly arranged patches-both known to be sensitive towards viewpoint changes. In this letter, we present a novel local region detector, SP-Grid, that is particularly suited for the combination of severe appearance and viewpoint changes. It is based on multiscale image oversegmentations and is designed to combine the advantages of keypoints and fixed image patches by starting from an initial gridlike arrangement and subsequently adapting to the image content. The grid-like arrangement showed to be beneficial in the presence of severe appearance changes and the adaptation to the image content increases the robustness toward viewpoint changes. The experimental evaluation will show the benefit compared to existing local region detectors and holistic image descriptors.
Exosomes with Immune Modulatory Features Are Present in Human Breast Milk1

Breast milk is a complex liquid with immune-competent cells and soluble proteins that provide immunity to the infant and affect the maturation of the infant’s immune system. Exosomes are nanovesicles (30–100 nm) with an endosome-derived limiting membrane secreted by a diverse range of cell types. Because exosomes carry immunorelevant structures, they are suggested to participate in directing the immune response. We hypothesized that human breast milk contain exosomes, which may be important for the development of the infant’s immune system. We isolated vesicles from the human colostrum and mature breast milk by ultracentrifugations and/or immuno-isolation on paramagnetic beads. We found that the vesicles displayed a typical exosome-like size and morphology as analyzed by electron microscopy. Furthermore, they floated at a density between 1.10 and 1.18 g/ml in a sucrose gradient, corresponding to the known density of exosomes. In addition, MHC classes I and II, CD63, CD81, and CD86 were detected on the vesicles by flow cytometry. Western blot and mass spectrometry further confirmed the presence of several exosome-associated molecules. Functional analysis revealed that the vesicle preparation inhibited anti-CD3-induced IL-2 and IFN-γ production from allogeneic and autologous PBMC. In addition, an increased number of Foxp3+CD4+CD25+ T regulatory cells were observed in PBMC incubated with milk vesicle preparations. We conclude that human breast milk contains exosomes with the capacity to influence immune responses.
In Vitro Study of Oscillatory Growth Dynamics of Camellia Pollen Tubes in Microfluidic Environment

A hallmark of tip-growing cells such as pollen tubes and fungal hyphae is their oscillatory growth dynamics. The multiple aspects of this behavior have been studied to identify the regulatory mechanisms that drive the growth in walled cells. However, the limited temporal and spatial resolution of data acquisition has hitherto prevented more detailed analysis of this growth behavior. To meet this challenge, we employed a microfluidic device that is able to trap pollen grains and to direct the growth of pollen tubes along microchannels filled with liquid growth medium. This enabled us to observe the growth behavior of Camellia pollen tubes without the use of the stabilizer agarose and without risking displacement of the cell during time lapse imaging. Using an acquisition interval of 0.5 s, we demonstrate the existence of primary and secondary peak frequencies in the growth dynamics. The effect of sucrose concentration on the growth dynamics was studied through the shift in these peak frequencies indicating the pollen tube's ability to modulate its growth activity.