Miracle-dz/UniFAR-FTUs huggingface dataset:
CoVaccine HT™ adjuvant potentiates robust immune responses to recombinant SARS-CoV-2 Spike S1 immunisation

The current COVID-19 pandemic has claimed hundreds of thousands of lives and its causative agent, SARS-CoV-2, has infected millions, globally. The highly contagious nature of this respiratory virus has spurred massive global efforts to develop vaccines at record speeds. In addition to enhanced immunogen delivery, adjuvants may greatly impact protective efficacy of a SARS-CoV-2 vaccine. To investigate adjuvant suitability, we formulated protein subunit vaccines consisting of the recombinant S1 domain of SARS-CoV-2 Spike protein alone or in combination with either CoVaccine HT™ or Alhydrogel. CoVaccine HT™ induced high titres of antigen-binding IgG after a single dose, facilitated affinity maturation and class switching to a greater extent than Alhydrogel and elicited potent cell-mediated immunity as well as virus neutralising antibody titres. Data presented here suggests that adjuvantation with CoVaccine HT™ can rapidly induce a comprehensive and protective immune response to SARS-CoV-2.
Impact of Highly Active Antiretroviral Therapy on Anemia and Relationship Between Anemia and Survival in a Large Cohort of HIV-Infected Women: Women’s Interagency HIV Study

BackgroundAnemia is common in HIV-infected individuals and may be associated with decreased survival. ObjectiveTo ascertain the impact of highly active antiretroviral therapy (HAART) on anemia and the relationship between anemia and overall survival in HIV-infected women. MethodsA prospective multicenter study of HIV-1 infection in women. Visits occurred every 6 months, including a standardized history, physical examination, and comprehensive laboratory evaluation. The setting was a university-affiliated clinic at 6 sites in the United States. Participants were 2056 HIV-infected women from the Women’s Interagency HIV Study (WIHS). The outcome measure was anemia, defined as hemoglobin (Hb) <12 g/dL. Survival analysis was based on overall mortality during the follow-up period. ResultsAmong HIV-infected women who were not anemic at baseline, 47% became anemic by 3.5 years of follow-up. On multivariate analysis, the use of HAART was associated with resolution of anemia even when used for only 6 months (odds ratio [OR] = 1.45; P < 0.05). In the multivariate model, a CD4 cell count <200 cells/μL (OR = 0.56; P < 0.001); HIV-1 RNA level ≥50,000 copies/mL (OR = 0.65; P < 0.001), and mean corpuscular volume (MCV) value <80 fL (OR = 0.40; P < 0.001) were also associated with an inability to correct anemia. Similarly, use of HAART for 12 months or more was associated with a protective effect against development of anemia (OR = 0.71; P < 0.001). Among HIV-infected women, anemia was independently associated with decreased survival (hazard ratio [HR] = 2.58; P < 0.001). Other factors associated with decreased survival included a CD4 cell count <200 cells/μL (HR = 5.83; P < 0.001), HIV-1 RNA level ≥50,000 copies/mL (HR = 2.12; P < 0.001), and clinical diagnosis of AIDS (HR = 2.83; P < 0.001). ConclusionsAnemia is an independent risk factor for decreased survival among HIV-infected women. HAART therapy for as little as 6 months is associated with resolution of anemia.
Genomic data suggest parallel dental 1 vestigialization within the xenarthran 2 radiation 3

The recent influx of genomic data has provided greater insights into the molecular basis for 19 regressive evolution, or vestigialization, through gene loss and pseudogenization. As such, the 20 analysis of gene degradation patterns has the potential to provide insights into the 21 evolutionary history of regressed anatomical traits. We specifically applied these principles to 22 the xenarthran radiation (anteaters, sloths, armadillos), which is characterized by taxa with a 23 gradation in regressed dental phenotypes. Whether the pattern among extant xenarthrans is 24 due to an ancient and gradual decay of dental morphology or occurred repeatedly in parallel is 25 unknown. We tested these competing hypotheses by examining 11 core dental genes in most 26 living species of Xenarthra, characterizing shared inactivating mutations and patterns of relaxed 27 selection during their radiation. Here we report evidence of independent and distinct events of 28 dental gene loss in the major xenarthran subclades. First, we found strong evidence of 29 complete enamel loss in the common ancestor of sloths and anteaters, suggested by the 30 inactivation of five enamel-associated genes ( AMELX , AMTN , MMP20 , ENAM, ACP4 ). Next, 31 whereas dental regression appears to have halted in sloths, presumably a critical event that 32 ultimately permitted adaptation to an herbivorous lifestyle, anteaters continued losing genes 33 on the path towards complete tooth loss. Echoes of this event are recorded in the genomes of 34 all living anteaters, being marked by a 2-bp deletion in a gene critical for dentinogenesis ( DSPP ) 35 and a putative shared 1-bp insertion in a gene linked to tooth retention ( ODAPH ). By contrast, 36 in the two major armadillo clades, genes pertaining to the dento-gingival junction and 37 amelogenesis appear to have been independently inactivated prior to losing all or some 38 enamel. These genomic data provide evidence for multiple pathways and rates of anatomical 39 regression, and underscore the utility of using pseudogenes to reconstruct evolutionary history 40 when fossils are sparse. 41
Learning to Generate 5’ UTR Sequences for Optimized Ribosome Load and Gene Expression

The 5’ untranslated region (5’ UTR) of the messenger RNA plays a crucial role in the translatability and stability of a molecule. Thus, it is an important component in the design of synthetic biological circuits for high and stable expression of intermediate proteins. Several UTR sequences are patented and used frequently in laboratories. We present a novel model UTRGAN, a Generative Adversarial Network (GAN)-based model designed to generate 5’ UTR sequences coupled with an optimization procedure to ensure a target property such as high expression for a target gene sequence or high ribosome load. We rigorously analyze and show that the model can generate sequences that mimic various properties of natural UTR sequences. Then, we show that the optimization procedure yields sequences that are expected to yield 32% higher expression (up to 7-fold) on a set of target genes and 12% higher ribosome load on average on a set of generated 5’ UTRs (up to 90% for the best 5’ UTR), compared to the initially generated UTR sequences. We also demonstrate that when there is a single target gene of interest, the expected expression increases by 55% on average and up to 100% for certain genes (up to 15-fold for the best 5’ UTR).
System and software architecture reconciliation

Large, complex systems today are increasingly software‐intensive. As a result, it is commonly essential that system development methods strongly facilitate good software development, even where to do so departs from traditional systems engineering practice. Unfortunately, the traditional state of the practice in systems engineering and system architecture descriptions are often not well suited to support complex software developments. For example, traditional systems engineering practice is to take a function‐first approach to definition, while software architectures are typically driven from the external interfaces inward, and are more often data‐based than function‐based. Moreover, the most successful very large system architectures typically take a strongly layered approach, with deliberate selection of convergence layers, a concept not typically found in traditional systems engineering practice. Each of these issues can be addressed through understanding of the elements of a good software architecture, appropriate ordering of systems engineering activities, and modeling methods extended to encompass layered system descriptions. While the example here is specific to software‐intensive systems, the methods applied can be extended to other types of domain integration. © 2006 Syst Eng 9: 146–159, 2006
Crustal Anisotropy of Hudson Bay from Ambient-Noise Tomography

Summary The Hudson Bay basin is more than 1000 km wide and contains up to 2 km of Paleozoic sedimentary rocks that overlie Archean and Proterozoic crust of the Trans-Hudson orogen and adjacent cratonic regions (Eaton and Darbyshire, 2009). Twenty-one months of continuous ambient-noise recordings have been acquired from 37 broadband seismograph stations that encircle Hudson Bay. These stations are part of the Hudson Bay Lithospheric Experiment (HuBLE), an international project that is currently operating more than 40 broadband seismograph stations around the periphery of the Bay with the aim of improving our knowledge of crustal structure of the basin and underlying orogen, as well as to image the thick mantle root beneath the Canadian Shield. Using well-established data processing methods (Bensen et al., 2007) that included trend-removal, one-bit normalization and instrument-response correction, we obtained 591 inter-station group velocity dispersion curves from the amplitude-envelope of average daily cross-correlation functions (Lin et al., 2007). Data from these curves in the period range of 5-40 s provide the input for a tomographic inversion procedure developed for surfacewave analysis. We follow the inversion procedure described by Deschamps et al. (2008), which yields azimuthal anisotropy parameters in addition to an isotropic crustal velocity model. In principle, ambient-noise tomography has an advantage over two-station analysis of surface waves from earthquakes, in that a larger number of paths are typically available to perform tomographic inversion. In practice, however, dispersion curves obtained from ambient-noise analysis are less well resolved than those obtained from surface waves, which add uncertainty to the inversion. In addition to the tectonic interpretation of crustal anisotropic fabrics beneath Hudson Bay, a focus of this preliminary study is to assess the reliability of ambient-noise tomography approach where seismic anisotropy is considered as part of the inversion.
STRESS ANALYSIS AND OPTIMIZATION OF CRANK SHAFT USING CAE TOOLS

Crankshaft is one of the most important parts in internal combustion engine, which converts the reciprocating displacement of the piston to a rotary motion with a four link mechanism.The objective of this paper was to suggest the optimum design parameter of the existing crankshaft by changing the design variables like journal diameter, crankpin diameter, fillets and counterweights etc. Here crankshaft of a four cylinder diesel engine was taken as case study. In the present paper, model of crankshaft was designed in the ANSYS Workbench and then Finite Element Analysis was carried out under the same loading conditions. Here, static analysis was done to find the maximum deformation and maximum stress point. Apart from this strain, shear stress and total deformation contours are also plotted. The results obtained are compared with the existing results and the crankshaft with optimum design was selected.
Journal of Cerebral Blood Flow and Metabolism Exercise-induced Changes in Local Cerebral Glucose Utilization in the Rat

In exercise, little is known about local cere­ bral glucose utilization (LCGU), which is an index of functional neurogenic activity. We measured LCGU in resting and running (=85% of maximum O2 uptake) rats (n = 7 in both groups) previously equipped with a tail artery catheter. LCGU was measured quantitatively from 2-deoxY-D-[1-14C]glucose autoradiographs. During exer­ cise, total cerebral glucose utilization (TCGU) increased by 38% (p < 0.005). LCGU increased (p < 0.05) in areas involved in motor function (motor cortex 39%, cerebel­ lum = 110%, basal ganglia =30%, substantia nigra =37%, and in the following nuclei: subthalamic 47%, posterior hypothalamic 74%, red 61%, ambiguus 43%, pontine 61 %), areas involved in sensory function (somatosensory 27%, auditory 32%, and visual cortex 42%, thalamus =75%, and in the following nuclei: Darkschewitsch 22%, cochlear 51%, vestibular 30%, superior olive 23%, cu-Pronounced motor, sensory, and autonomic ad­ aptation is known to occur in response to both static and dynamic exercise. Such changes must be thought to evoke marked regional changes in cere­ bral functional activity, but little is known about the effect of exercise on regional cerebral blood flow and in particular on regional cerebral metabolism, which are both indexes of the functional activity of regional neurons (Sokoloff, 1991, 1992). Results from investigations on cerebral blood flow during dynamic exercise are conflicting. Thus, in response to dynamic exercise, cerebral blood flow measure­ ments using the 133Xe washout technique, which 729 neate 115%), areas involved in autonomic function (dor­ sal raphe nucleus 30%, and areas in the hypothalamus =35%, amygdala =35%, and hippocampus 29%), and in white matter of the corpus callosum (36%) and cerebel­ lum (52%). LCGU did not change with exercise in pre­ frontal and frontal cortex, cingulum, inferior olive, nu­ cleus of solitary tract and median raphe, lateral septal and interpenduncular nuclei, or in areas of the hippocampus, amygdala, and hypothalamus. Glucose utilization did not decrease during exercise in any of the studied cerebral regions. In summary, heavy dynamic exercise increases TCGU and evokes marked differential changes in LCGU. The findings provide clues to the cerebral areas that par­ ticipate in the large motor, sensory, and autonomic adap­ tation occurring in exercise. Key Words: Autoradiogra­ phy-Brain glucose metabolism-2-Deoxyglucose. primarily measures cortical blood flow, have shown increased flow (Herholz et aI., 1987; Thomas et aI., 1989) or no change in flow (Globus et aI., 1983). The radioactive microsphere method shows no change in …
What to expect from dynamical modelling of galactic haloes.

Many dynamical models of the Milky Way halo require assumptions that the distribution function of a tracer population should be independent of time (i.e. a steady-state distribution function) and that the underlying potential is spherical. We study the limitations of such modelling by applying a general dynamical model with minimal assumptions to a large sample of galactic haloes from cosmological N-body and hydrodynamical simulations. Using dark matter particles as dynamical tracers, we find that the systematic uncertainties in the measured mass and concentration parameters typically have an amplitude of 25–40 per cent. When stars are used as tracers, however, the systematic uncertainties can be as large as a factor of 2–3. The systematic uncertainties are not reduced by increasing the tracer sample size and vary stochastically from halo to halo. These systematic uncertainties are mostly driven by underestimated statistical noise caused by correlated phase-space structures that violate the steady-state assumption. The number of independent phase-space structures inferred from the uncertainty level sets a limiting sample size beyond which a further increase no longer significantly improves the accuracy of dynamical inferences. The systematic uncertainty level is determined by the halo merger history, the shape and environment of the halo. Our conclusions apply generally to any spherical steady-state model.
SOFIA-EXES Mid-IR Observations of Emission from the Extended Atmosphere of Betelgeuse

We present a NASA-DLR SOFIA-Echelon Cross Echelle Spectrograph (EXES) and NASA Infrared Telescope Facility-Texas Echelon Cross Echelle Spectrograph (TEXES) mid-IR spectral study of forbidden Fe ii transitions in the early-type M supergiants, Betelgeuse (α Ori: M2 Iab) and Antares (α Sco: M1 Iab + B3 V). With EXES, we spectrally resolve the ground term [Fe ii] 25.99 μm ( : K) emission from Betelgeuse. We find a small centroid blueshift of 1.9 ± 0.4 that is a significant fraction (20%) of the current epoch wind speed, with a FWHM of 14.3 ± 0.1 . The TEXES observations of [Fe ii] 17.94 μm ( : K) show a broader FWHM of 19.1 ± 0.2 , consistent with previous observations, and a small redshift of 1.6 ± 0.6 with respect to the adopted stellar center-of-mass velocity of . To produce [Fe ii] 25.99 μm blueshifts of 20% wind speed requires that the emission arises closer to the star than existing thermal models for α Ori’s circumstellar envelope predict. This implies a more rapid wind cooling to below 500 K within ( mas, dist = 200 pc) of the star, where the wind has also reached a significant fraction of the maximum wind speed. The line width is consistent with the turbulence in the outflow being close to the hydrogen sound speed. EXES observations of [Fe ii] 22.90 μm ( : K) reveal no emission from either star. These findings confirm the dominance of cool plasma in the mixed region where hot chromospheric plasma emits copiously in the UV, and they also constrain the wind heating produced by the poorly understood mechanisms that drive stellar outflows from these low variability and weak-dust signature stars.
Numerical Test of Finite-Difference Form of Primitive Equations for Barotropic Case

We derived a finite-difference scheme of primitive equations for the staggered coordinate system as well as for the ordinary one. This scheme is supposedly reasonable from the standpoint of compatibility with the system of original differential equations. We also formulated computational boundary conditions with a great care. In order to test the usefulness of this computation scheme, the forecastings of wave motions in a channel with the balance Barotropic model and with the non-balance barotropic model of the atmosphere were attempted. The finite-difference form we used was computationally stable for both models and caused no trouble in 48-hour forecast of the height field which was given mathematically at the initial time. The budget of energy within the forecasting domain could be estimated accurately. Besides, the results of the forecasting agree well with what can be expected theoretically from the model atmosphere. Since the numerical test of the finite-difference form gave fairly satisfactory result in the forecasting of simple pattern, we tried to apply the scheme for the non-balance model to the barotropic forecasting of 500-mb height over the northern hemisphere. There occurred no trouble in this case, either.
Transmutation maps: modeling, structural properties, estimation and applications

Initially, we use the quadratic transmutation maps to compose a new probability model: the transmuted log-logistic distribution. Transmutation maps are a convenient way of constructing new distributions, in particular survival ones. It comprises the functional composition of the cumulative distribution function of one distribution with the inverse cumulative distribution (quantil) function of another. Its comprehensive description of properties, such as moments, quantiles, order statistics etc., along with its survival study and the classical and Bayesian estimation methods, are also part of this work. Focusing on analysis of survival, the study included two practical situations commonly found: the presence of regression variables, through the transmuted log-logistic regression model, and the presence of right censorship. In a second moment, searching for a more exible model than the transmuted, we present its generalization, the transmuted distributions of cubic rank. Using the methodology presented in this rst generalization, two models were considered to compose the new cubic transmuted distributions: the log-logistic and Weibull models. Faced with problems presented in the transmutated class of quadratic and cubic orders (such as the restricted parametric space of the transmutation parameter λ), we propose in this work, a new family of distribution. This family, which we call e-transmuted or e-extended, is as simple as the transmuted model, because it includes a single parameter to the base model, but more exible than the class of transmuted models, once the transmuted is a particular case of the proposed family. In addition, the nem family presents important properties such as, orthogonality between the baseline model parameters and the e-transmutation parameter, along with unrestricted parametric space for the ω e-transmutation parameter, which is de ned on the real line. Simulation studies and real data applications were performed for all proposed models and generalizations.
Volume instabilities in capillary flow of pure SBR and SBR compounds

The flow instabilities of pure styrene-butadiene-rubber (SBR) and SBR compounds filled with silica were characterized using capillary rheometry. Above a critical shear stress, volume defects develop, leading to products of unacceptable quality. Unlike other polymers (polystyrene and low density polyethylene), the onset of these defects is concomitant with a transition from no slip (or weak slip) to strong slip conditions. Volume instabilities are affected by the silica content and the type of additive (coating or coupling agents) present in the compounds. A method based on image analysis is proposed to quantify volume defects, which can help to compare the different compounds in terms of extrusion quality.
Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Graphs

Graph neural networks (GNN) have shown great success in learning from graph-structured data. They are widely used in various applications, such as recommendation, fraud detection, and search. In these domains, the graphs are typically large, containing hundreds of millions or billions of nodes. To tackle this challenge, we develop DistDGLv2, a system that extends DistDGL for training GNNs in a mini-batch fashion, using distributed hybrid CPU/GPU training to scale to large graphs. DistDGLv2 places graph data in distributed CPU memory and performs mini-batch computation in GPUs. Dist-DGLv2 distributes the graph and its associated data (initial features) across the machines and uses this distribution to derive a computational decomposition by following an owner-compute rule. DistDGLv2 follows a synchronous training approach and allows ego-networks forming mini-batches to include non-local nodes. To minimize the overheads associated with distributed computations, DistDGLv2 uses a multi-level graph partitioning algorithm with min-edge cut along with multiple balancing constraints. This localizes computation in both machine level and GPU level and statically balance the computations. DistDGLv2 deploys an asynchronous mini-batch generation pipeline that makes all computation and data access asynchronous to fully utilize all hardware (CPU, GPU, network, PCIe). The combination allows DistDGLv2 to train high-quality models while achieving high parallel ef-ﬁciency and memory scalability. We demonstrate DistDGLv2 on various GNN workloads. Our results show that DistDGLv2 achieves 2 − 3 × speedup over DistDGL and 18 × speedup over Euler. It takes only 5 − 10 seconds to complete an epoch on graphs with 100s millions of nodes on
Classifying Graphs as Images with Convolutional Neural Networks

The task of graph classification is currently dominated by graph kernels, which, while powerful, scale poorly to large graphs and datasets. Convolutional Neural Networks (CNNs) offer a very appealing alternative. However, feeding graphs to CNNs is not trivial. To address this challenge, many sophisticated extensions of CNNs have recently been proposed. In this paper, we show that a classical 2D CNN architecture designed for images can also be used for graph processing in a completely off-the-shelf manner; the only prerequisite being to encode graphs as stacks of two-dimensional histograms of their node embeddings. Despite its simplicity, our method proves very competitive to state-of-the-art graph kernels, and even outperforms them by a wide margin on some datasets.