Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of Human Leukocyte Antigen DRB1*15 and DRB1*15:01 Polymorphisms with Response to Immunosuppressive Therapy in Patients with Aplastic Anemia: A Meta-Analysis

This study aimed to review and quantitatively analyze (1) the association of aplastic anemia (AA) with human leukocyte antigen (HLA)-DRB1*15 and HLA-DRB1*15:01 polymorphisms and (2) the association of HLA-DRB1*15 and HLA-DRB1*15:01 polymorphisms with response to immunosuppressive therapy (IST) in AA. Published studies have reported conflicting and heterogeneous results regarding the association of HLA-DRB1*15 and HLA-DRB1*15:01 polymorphisms with response to IST in AA. The PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, Chinese BioMedical Literature, Wangfang and Chinese Social Sciences Citation Index databases were searched. All relevant publications were searched through December 2015. Odds ratio (OR), risk ratio (RR), and 95% confidence intervals (CI) for the comparison between case–control or cohort studies were evaluated. Finally, 24 articles were identified. For HLA-DRB1*15 and HLA-DRB1*15:01, the OR (95% CI) was 2.24(1.33–3.77), P < 0.01 and 2.50(1.73–3.62), P < 0.01, respectively; and the overall pooled RR was 1.72 (1.30–2.29), P < 0.01 and 1.59 (1.29–1.96), P < 0.01, respectively. Statistical evidence showed no publication bias (P > 0.05). Sensitivity analyses revealed that the results were statistically robust. The meta-analysis suggested that HLA-DRB1*15 and HLA-DRB1*15:01 polymorphisms might be associated with increased AA risk in Asians. IST might be more effective in HLA-DRB1*15+ and HLA-DRB1*15:01+ Asian patients with AA than in HLA-DRB1*15− and HLA-DRB1*15:01− Asian patients with AA. Future studies with adequate methodological quality on gene–gene and gene–environment interactions and gene treatment may yield valid results.
Evaluation of atmospheric correction using bi-temporal hyperspectral images

Atmospheric correction of hyperspectral image data is frequently a requirement for using remote sensing to understand and quantify various phenomena that take place on the Earth. This is particularly true when the analysis requires the use of spectral reflectance. Although sophisticated models exist that can be used to perform atmospheric correction, evaluating the performance of these procedures is non-trivial. In this study, two atmospheric correction programs, FLAASH (based on MODTRAN 4), and TAFKAA_6S (based on 6S), were applied to a pair of images of the same area but collected six weeks apart. The results of the two atmospheric correction procedures are analyzed based on the expected stability of pseudo-invariant features (PIFs). Although both procedures performed rather well in terms of removing atmospheric absorption features in the infrared region, the analysis identified some anomalous behaviors as well, the most important of which appears to be related to the bidirectional reflectance distribut.
Efficient Separation of Ethanol–Methanol and Ethanol–Water Mixtures Using ZIF-8 Supported on a Hierarchical Porous Mixed-Oxide Substrate

This work reports a new approach for the synthesis of a zeolitic imidazolate framework (ZIF-8) composite. It employs the direct growth of the crystalline ZIF-8 on a mixed-metal oxide support TiO2–SiO2 (TSO), which mimics the porous structure of Populus nigra. Using the natural leaf as a template, the TSO support was prepared using a sol–gel method. The growth of the ZIF-8 layer on the TSO support was carried out by the seeds and second growth method. This method facilitates the homogeneous dispersion of ZIF-8 crystals at the surface of the TSO composite. The ZIF-8@TSO composite adsorbs methanol selectively, mainly due to the hierarchical porous structure of the mixed oxide support. As compared with the as-synthesized ZIF-8, a 50% methanol uptake is achieved in the ZIF-8@TSO composite, with only 25 wt % ZIF-8 loading. IAST simulations show that the ZIF-8@TSO composite has a preferential adsorption toward methanol when using an equimolar methanol–ethanol mixture. An opposite behavior is observed for the as-synthesized ZIF-8. The results show that combining MOFs and mixed-oxide supports with bioinspired structures opens opportunities for synthesizing new materials with unique and enhanced adsorption and separation properties.
Recharge et paléorecharge d'une nappe libre en milieu sahélien (Niger oriental) : approches géochimique et hydrodynamique

Cette these porte sur la caracterisation de l'hydrogeologie de la nappe libre du Niger oriental, premiere ressource en eau dans ce milieu sahelien marque par une forte variabilite spatio-temporelle. Une centaine d'echantillon ont ete preleves de 1997 a 2003 pour une etude geochimique (ions majeurs, 18O, 2H , 13C, 14C) couplee a un modele hydrodynamique. La recharge est active au sud et discontinue quelle que soit la source : (i) la riviere Komadougou Yobe, (ii) le lac Tchad et (iii) les pluies au sein de l'erg ancien du Manga. L'enrichissement systematique en 18O et 2H des eaux souterraines montre l'impact significatif de l'evaporation sur la recharge sous ce climat semi-aride. Les âges 14C indiquent la presence d'eaux fossiles sur l'ensemble de la region, datant de l'optimum holocene. Ces eaux presentent les plus faibles valeurs en 18O de la nappe, signe d'une paleo-recharge rapide et intense. En parallele, les valeurs 13C suggerent le developpement d'une vegetation adaptee a un climat plus humide (type C3) et apportent de nouveaux indices d'un paleo-lac Tchad recouvrant la plaine du Kadzell. La modelisation de la depression piezometrique du Kadzell a ete calee et validee a partir des mesures piezometriques disponibles depuis 1960. Le modele montre la necessite d'une evapotranspiration dominante sur la plaine et de faibles permeabilites pour reproduire la depression piezometrique. Il confirme les resultats isotopiques avec une recharge uniquement laterale avec 50% des apports depuis la riviere et seulement 7% depuis le lac. Par ailleurs, le regime transitoire montre l'impact limite sur la nappe libre des secheresses majeures(1970-80) malgre l'assechement prolonge du lac.
Mussel farming on the east coast of India

﻿At Kovalam bay (Madras) rafts made of casuarina poles have been used to suspend mussel seed transplanted ropes for culture. An average growth of mussel at the rate of 12.8 mm per month is reported. Harvestable size of 75 mm is reported to have been reached in 3 J months time. However similar experiments done at Kakinada (Andhra Coast) and Ennore (north of Madras) did not yield conclusive results.
Feature-driven emergence of model graphs for object recognition and categorization

An important requirement for the expression of cognitive structures is the ability to form mental objects by rapidly binding together constituent parts. In this sense, one may conceive the brain’s data structure to have the form of graphs whose nodes are labeled with elementary features. These provide a versatile data format with the ability to render the structure of any mental object. Because of the multitude of possible object variations the graphs are required to be dynamic. Upon presentation of an image a so-called model graph should rapidly emerge by binding together memorized subgraphs derived from earlier learning examples driven by the image features. In this model, the richness and flexibility of the mind is made possible by a combinatorial game of immense complexity. Consequently, emergence of model graphs is a laborious task which, in computer vision, has most often been disregarded in favor of employing model graphs tailored to specific object categories like faces in frontal pose. Invariant recognition or categorization of arbitrary objects, however, demands dynamic graphs. In this work we propose a form of graph dynamics, which proceeds in three steps. In the first step position-invariant feature detectors, which decide whether a feature is present in an image, are set up from training images. For processing arbitrary objects, these features are small regular graphs, termed parquet graphs, whose nodes are attributed with Gabor amplitudes. Through combination of these classifiers into a linear discriminant that conforms to Linsker’s infomax principle a weighted majority voting scheme is implemented. The network is well suited to quickly rule out most irrelevant matches and only leaves the ambiguous cases, so-called model candidates, to be processed in a third step using a rudimentary version of elastic graph matching, a standard correspondence-based technique for face and object recognition. To further differentiate between model candidates with similar features it is asserted that the features be in similar spatial arrangement for the model to be selected. Model graphs are constructed dynamically
Exploring the electrophysiological correlates of the default ‐ mode network with intracerebral EEG

quest to fully elucidate the function of intrinsic brain networks also requires a solid understanding of the link between neuroimaging findings and their electrophysiological underpinnings. In this paper we provide perspectives on the necessity, feasibility , and limitations of tackling the electrophysiological properties of DMN dynamics. We will discuss the utility and limitations of non-invasive electrophysiological techniques such as electroen-cephalography (EEG) and magnetoencephalography (MEG) in this endeavor. Most importantly, we will focus on the potential of direct electrophysiological recordings in humans to unravel the spectral and temporal properties of task-related changes of population activity in DMN structures. A parallel stream of research in humans has revealed that blood-oxygenation level-dependent (BOLD) signal increases are tightly coupled with task-related power increases in the high-frequency range (broad-band gamma, 50–150 Hz) of the intracranial EEG signal (Mukamel et al., 2005; Lachaux et al., 2007a; Nir et al., 2007). It is therefore tempting to ask whether task-related BOLD deactivations, typical for DMN areas, are in turn associated with suppressions of high gamma power. While human studies of gamma power increases are abundant (e., little is known about task-related gamma power suppression. Intracerebral studies from our group were the first to provide direct evidence in humans for task-related decreases of broad-band gamma (>50 Hz) power during performance of attention-demanding cognitive tasks (Lachaux et al.
The digital bee brain : integrating and managing neurons in a common 3 D reference system

for the precise composition of multiple reconstructions would be an atlas of the whole brain that contains a large number of landmarks for warping different brains into one reference (e.g., Toga and Mazziotta, 2002). We developed and tested the suitability of this approach by creating a standard atlas of the bee brain (the honeybee standard brain: HSB, Brandt et al., 2005). The HSB atlas can be used to successfully reconstruct components of a neural network from separately acquired neurons and to visualize their spatial relations. To create digital standard insect brains, two standardization methods have been employed: (1) The iterative shape method (ISA), which eliminates individual shape variability (Rohlfing et al., 2001; Brandt et al., 2005; Kvello et al., 2009). (2) The virtual insect brain (VIB) protocol, which allows a comparative volume analysis of brain neuropils, developmental studies, and studies on neuronal plasticity and genetic differences (Rein et al., 2002; Kurylas et al., 2008; el Jundi et al., 2009). We favored the ISA standard, which is derived by averaging across multiple individual brains. Analyses of other procedures, for example, selecting an individual representative brain, have shown that the averaging procedure is best suited to the registration of neurons collected from different brains (Kurylas et al., 2008). IntroductIon Analysis of the structure of neural networks requires the selective staining of the participating neurons, their three-dimensional (3D) reconstruction, and the integration of these reconstructions into a common reference frame, an anatomical atlas. Insects have rather small brains that can be captured in full using confocal microscope imaging. Unsurprisingly, significant advances have been made in attempts to create digital atlases of whole insect brains (see the other contributions to this special issue). Neurons that participate in neural networks are normally stained in separate preparations. Even if double or triple staining is performed in one brain, a whole network can only be reconstructed using data collected from multiple preparations. An ideal frame The digital bee brain: integrating and managing neurons in a common 3D reference system
Investigation of hydroacoustic flow-monitoring alternatives at the Sacramento River at Freeport, California: results of the 2002-2004 pilot study

The Sacramento River at Freeport is a tidally affected channel approximately 620 feet wide located at the northern boundary of the Sacramento—San Joaquin River Delta, California. In 1978, an acoustic velocity meter was installed at Freeport to monitor the flow. The acoustic velocity meter was calibrated successfully and has been used continuously since that time. Although the calibration has been extremely stable, an increasing number of maintenance problems prompted a search for alternatives to monitor discharge at this location. Two sideward-looking acoustic Doppler velocity meters were tested in a pilot study from 2002–2004: a short-range system and a long-range system. The pilot study was conducted over a wide range of hydrologic conditions and both sidewardlooking acoustic Doppler velocity meters have performed well at this location and have been calibrated successfully. As of February 2004, the short-range system had a robust calibration and a higher data-recovery rate, therefore, it was selected as the primary replacement of the acoustic velocity meter, with the long-range system providing real-time data redundancy to minimize data loss.
Design and Experimental Analysis of an Optical Fiber Coupling System for a Ground-based Telescope with Adaptive Optics

Astronomy photonics has opened up a new era for the application of astronomical optical instruments. The fiber coupling system serves as the crucial link between the telescope and photonic devices. This paper explores a beam shaping method that utilizes a coupled lens to enhance the efficiency of coupling light into an optical single mode fiber. Compared to directly coupling the telescope beam into the fiber, this approach offers improved coupling efficiency and greater adjustment tolerance. The laboratory-based optical fiber coupling system described in this study comprises an imaging component with an F/50 ratio and a fiber coupling component. Theoretical analysis indicates that optimal coupling efficiency is achieved when the diameter of the focusing spot, limited by diffraction, matches the fiber core size. Any axial error, position error, or tip-tilt error between the lens and the fiber will reduce the coupling efficiency. Experimental results confirm that the coupling system achieves an efficiency of approximately 70%, which is close to the theoretical limit of 78%. These findings underscore the effectiveness of the fiber coupling method.
Automatic fi tting of spiking neuron models to electrophysiological recordings

There are several important diffi culties in this model fi tting problem. Firstly, because of the threshold property, the mapping from a time-varying signal to spike trains is generally discontinuous in spiking models (Brette, 2004). Besides, the fi tness criterion we used (the gamma coincidence factor used in the INCF competition; Jolivet et al., 2008) is discrete, because it is a function of the number of coincidences within a predefi ned temporal window. These facts prevent us from using optimization methods based on gradients (e.g. conjugated gradient descent). Secondly, a single evaluation of the criterion for a given set of parameter values involves the simulation of a neuron model over a very long time. For example, recordings in challenges A and B of the 2009 INCF competition last 60 s, sampled at 10 kHz, totalling 600,000 values of the input signal. Thus, evaluating the fi tness criterion for any spiking model involves several millions of operations. Thirdly, not only the parameter values are unknown, but there are also many candidate models. In particular, it is not unreasonable to think that different neuron types may be best fi t by different phenomenological models. Therefore, the optimization tools should be fl exible enough to allow testing different models. To address these issues, we developed a model fi tting toolbox for the spiking neural network Brian (Goodman and Brette, 2009). Brian is a simulator written in Python that lets the user defi ne a model by directly providing its equations in mathematical form (including threshold condition and reset operations). Using an interpreted language such as Python comes at a cost, because the interpretation overhead can slow down the simulations, but this problem can be solved by vectorizing all operations when the network model includes many neurons. It turns out that the same strategy applies to programming GPUs, which are most effi cient when all processors execute the same operation (the Single Instruction, Multiple Data (SIMD) model of parallel programming). Therefore, we developed several vectoriza-tion techniques for spiking model optimization (see Vectorization
Application of Optical Techniques in the Characterization of Thermal Stability and Environmental Degradation in High Temperature Superconductors

The possibility of applying non-destructive techniques is important in the characterization of different problems that are associated with the use of high temperature superconducting materials in diverse technological applications. In this context, optical characterization techniques are being implemented in the analysis of several properties of solid materials due to their non-destructive nature. In particular, in some optical techniques the sample is illuminated with a coherent light and the recorded images present a granularity. This granularity is called speckle and its origin comes from the interference of the light scattered by the different points of the surface (Goodman, 1975b; Andrés et al., 2008). In consequence, any change taking place in the surface is immediately transferred to the speckle. Some speckle techniques that use digital recording have been developed. In this work, we present the applicability of Digital Speckle Pattern Interferometry (DSPI) and Digital Speckle Photography (DSP) in the study of two important problems associated with high temperature superconducting materials: the thermal stability and the environmental degradation (Recuero et al., 2005a; Angurel et al., 2006). Thermal stability is a great challenge in the development of applications. In comparison with low-Tc superconductors, thermal properties of High Temperature Superconductors combine higher specific heat values and lower thermal conductivity ones. With these properties, the normal zone propagation velocities in these materials are several orders of magnitude lower than in the classical superconductors (Wang et al., 2007). Due to these properties, usually a hot spot appears in these materials and an important heat amount is generated leading to local temperature increases. Several stabilizing strategies have been used in order to facilitate heat dissipation in higher volumes and to reduce the possibility of local thermal degradation of the material. In addition, a great amount of work is being performed in order to obtain information about quench generation and propagation in High
Vesicular Stomatitis Virus-Based Vaccines Provide Cross-Protection against Andes and Sin Nombre Viruses

Andes virus (ANDV) and Sin Nombre virus (SNV) are the main causative agents responsible for hantavirus cardiopulmonary syndrome (HCPS) in the Americas. HCPS is a severe respiratory disease with a high fatality rate for which there are no approved therapeutics or vaccines available. Some vaccine approaches for HCPS have been tested in preclinical models, but none have been tested in infectious models in regard to their ability to protect against multiple species of HCPS-causing viruses. Here, we utilize recombinant vesicular stomatitis virus-based (VSV) vaccines for Andes virus (ANDV) and Sin Nombre virus (SNV) and assess their ability to provide cross-protection in infectious challenge models. We show that, while both rVSVΔG/ANDVGPC and rVSVΔG/SNVGPC display attenuated growth as compared to wild type VSV, each vaccine is able to induce a cross-reactive antibody response. Both vaccines protected against both homologous and heterologous challenge with ANDV and SNV and prevented HCPS in a lethal ANDV challenge model. This study provides evidence that the development of a single vaccine against HCPS-causing hantaviruses could provide protection against multiple agents.
Traitement des données de sismique de puits acquises en 2007 sur le site de Soultz-sous-Forêts pour la caractérisation de la fracturation du réservoir géothermique

Les donnees de VSP multi-source/multi-offset acquises en 2007 sur le site geothermique de Soultz-sous-Forets sont traitees et analysees. Des geophones places dans les puits GPK3 et GPK4 entre 3 et 5 km de profondeur ont enregistre les ondes sismiques emises par deux vibrateurs places en 24 positions de tir reparties dans un rayon de 5 km autour des puits. Apres correlation des enregistrements avec la source associee a chaque vibrateur, les differentes composantes du champ d'onde sont separees par filtrage en vitesse apparente. La comparaison des resultats obtenus par filtrage median ou dans le domaine FK montre des signaux similaires. Un modele de vitesse est etabli pour pouvoir calculer les temps d'arrivee. Il comporte deux couches sedimentaires sur le socle granitique et des interfaces planes pentees. Le champ d'onde descendant de forte vitesse apparente est interprete comme des reflexions sur des structures subverticales autour des puits. Leur pendage, azimut et extension laterale sont determines en ajustant les temps de trajet observes et calcules par trace de rayons 3D. Les structures a pendage vers l'ouest connues par les observations en forage et la microsismicite sont retrouvees. Une structure antithetique nouvelle est determinee. Nos resultats permettent de completer le modele structural de la fracturation dans le reservoir geothermique.
SAR object classification using the DAE with a modified triplet restriction

Although deep learning methods have made great progress in synthetic aperture radar (SAR)-based remote sensing, lack of training data has often been the major obstacle while they are adopted for SAR automatic target recognition. In this study, a new deep network in the form of a restricted three-branch denoising auto-encoder (DAE) is proposed to take the full advantage of limited training samples. In this model, a modified triplet restriction that combines the semi-hard triplet loss with the intra-class distance penalty is devised to learn discriminative features with a small intra-class divergence and a large inter-class divergence. Besides, the reconstruction distortion is measured between the model outputs and the images filtered by the improved Lee Sigma filter rather than the original inputs to suppress clutter in the background. Furthermore, a batch-based triplet loss, which calculates the modified triplet loss in a batch-based manner, is proposed to tackle the difficulties in implementation and reduce its computation complexity. The simplified version of the three-branch Triplet-DAE is subsequently devised as a one-branch DAE restricted by the batch-based triplet loss. Experimental results with the MSTAR data demonstrate the effectiveness of the proposed method on real SAR images.