Miracle-dz/UniFAR-FTUs huggingface dataset:
Prophylactic Herpes Simplex Virus 2 (HSV-2) Vaccines Adjuvanted with Stable Emulsion and Toll-Like Receptor 9 Agonist Induce a Robust HSV-2-Specific Cell-Mediated Immune Response, Protect against Symptomatic Disease, and Reduce the Latent Viral Reservoir

ABSTRACT Several prophylactic vaccines targeting herpes simplex virus 2 (HSV-2) have failed in the clinic to demonstrate sustained depression of viral shedding or protection from recurrences. Although these vaccines have generated high titers of neutralizing antibodies (NAbs), their induction of robust CD8 T cells has largely been unreported, even though evidence for the importance of HSV-2 antigen-specific CD8 T cells is mounting in animal models and in translational studies involving subjects with active HSV-2-specific immune responses. We developed a subunit vaccine composed of the NAb targets gD and gB and the novel T cell antigen and tegument protein UL40, and we compared this vaccine to a whole-inactivated-virus vaccine (formaldehyde-inactivated HSV-2 [FI-HSV-2]). We evaluated different formulations in combination with several Th1-inducing Toll-like receptor (TLR) agonists in vivo. In mice, the TLR9 agonist cytosine-phosphate-guanine (CpG) oligodeoxynucleotide formulated in a squalene-based oil-in-water emulsion promoted most robust, functional HSV-2 antigen-specific CD8 T cell responses and high titers of neutralizing antibodies, demonstrating its superiority to vaccines adjuvanted by monophosphoryl lipid A (MPL)-alum. We further established that FI-HSV-2 alone or in combination with adjuvants as well as adjuvanted subunit vaccines were successful in the induction of NAbs and T cell responses in guinea pigs. These immunological responses were coincident with a suppression of vaginal HSV-2 shedding, low lesion scores, and a reduction in latent HSV-2 DNA in dorsal root ganglia to undetectable levels. These data support the further preclinical and clinical development of prophylactic HSV-2 vaccines that contain appropriate antigen and adjuvant components responsible for programming elevated CD8 T cell responses. IMPORTANCE Millions of people worldwide are infected with herpes simplex virus 2 (HSV-2), and to date, an efficacious prophylactic vaccine has not met the rigors of clinical trials. Attempts to develop a vaccine have focused primarily on glycoproteins necessary for HSV-2 entry as target antigens and to which the dominant neutralizing antibody response is directed during natural infection. Individuals with asymptomatic infection have exhibited T cell responses against specific HSV-2 antigens not observed in symptomatic individuals. We describe for the first time the immunogenicity profile in animal models of UL40, a novel HSV-2 T cell antigen that has been correlated with asymptomatic HSV-2 disease. Additionally, vaccine candidates adjuvanted by a robust formulation of the CpG oligonucleotide delivered in emulsion were superior to unadjuvanted or MPL-alum-adjuvanted formulations at eliciting a robust cell-mediated immune response and blocking the establishment of a latent viral reservoir in the guinea pig challenge model of HSV-2 infection.
From Eyes to Face Synthesis: a New Approach for Human-Centered Smart Surveillance

With the popularity of surveillance cameras and the development of deep learning, significant progress has been made in the field of smart surveillance. Face recognition is one of the most important yet challenging tasks in human-centered smart surveillance, especially in public security, criminal investigation and anti-terrorism, and so on. Although, the state-of-the-art algorithms for face recognition have achieved dramatically improved results and have been widely applied in authentication scenario, the occlusion problem on face is still one of the critical issues for personal identification in smart surveillance, especially in the occasion of terrorist searching and identification. To address this issue, this paper proposed a new approach for eyes-to-face synthesis and personal identification for human-centered smart surveillance. An end-to-end network based on conditional generative adversarial networks (GAN) is designed to generate the face information based only on the available data of eyes region. To obtain photorealistic faces and identity-preserving information, a synthesis loss function based on feature loss, GAN loss, and total variation loss is proposed to guide the training process. Both the subject and objective experimental results demonstrated that the proposed method can preserve the identity based on eyes-only data, and provide a potential solution for the identification of person even in the case of face occlusion.
DPC-Net: Deep Pose Correction for Visual Localization

We present a novel method to fuse the power of deep networks with the computational efficiency of geometric and probabilistic localization algorithms. In contrast to other methods that completely replace a classical visual estimator with a deep network, we propose an approach that uses a convolutional neural network to learn difficult-to-model corrections to the estimator from ground-truth training data. To this end, we derive a novel loss function for learning $ \mathrm{SE}(3)$ corrections based on a matrix Lie groups approach, with a natural formulation for balancing translation and rotation errors. We use this loss to train a deep pose correction network (DPC-Net) that predicts corrections for a particular estimator, sensor and environment. Using the KITTI odometry dataset, we demonstrate significant improvements to the accuracy of a computationally-efficient sparse stereo visual odometry pipeline, that render it as accurate as a modern computationally-intensive dense estimator. Further, we show how DPC-Net can be used to mitigate the effect of poorly calibrated lens distortion parameters.
An Exponential-Rayleigh Model for RSS-Based Device-Free Localization and Tracking

A common technical difficulty in device-free localization and tracking (DFLT) with a wireless sensor network is that the change of the received signal strength (RSS) of the link often becomes more unpredictable due to the multipath interferences. This challenge can lead to unsatisfactory or even unstable DFLT performance. This work focuses on developing a new RSS model, called Exponential-Rayleigh (ER) model, for addressing this challenge. Based on data from our extensive experiments, we first develop the ER model of the received signal strength. This model consists of two parts: the large-scale exponential attenuation part and the small-scale Rayleigh enhancement part. The new consideration on using the Rayleigh model is to depict the target-induced multipath components. We then explore the use of the ER model with a particle filter in the context of multi-target localization and tracking. Finally, we experimentally demonstrate that our ER model outperforms the existing models. The experimental results highlight the advantages of using the Rayleigh model in mitigating the multipath interferences thus improving the DFLT performance.
Learning Unsupervised Learning Rules

A major goal of unsupervised learning is to discover data representations that are useful for subsequent tasks, without access to supervised labels during training. Typically, this goal is approached by minimizing a surrogate objective, such as the negative log likelihood of a generative model, with the hope that representations useful for subsequent tasks will arise as a side effect. In this work, we propose instead to directly target a later desired task by meta-learning an unsupervised learning rule, which leads to representations useful for that task. Here, our desired task (meta-objective) is the performance of the representation on semi-supervised classification, and we meta-learn an algorithm -- an unsupervised weight update rule -- that produces representations that perform well under this meta-objective. Additionally, we constrain our unsupervised update rule to a be a biologically-motivated, neuron-local function, which enables it to generalize to novel neural network architectures. We show that the meta-learned update rule produces useful features and sometimes outperforms existing unsupervised learning techniques. We show that the meta-learned unsupervised update rule generalizes to train networks with different widths, depths, and nonlinearities. It also generalizes to train on data with randomly permuted input dimensions and even generalizes from image datasets to a text task.
Gait generation for powered Hip-Ankle-Linkage-Orthosis

A hip-knee-ankle-foot orthotic system called `HALO'(Hip and Ankle Linked Orthosis) for paraplegic walking has been developed in our previous study. Each ankle joint of the HALO system is linked with a medial single joint via a wire which allows both feet of the orthosis to stay always parallel to the floor during walking and assists swinging the leg. The tests of the HALO system demonstrated that it allows smoother walking and easy don/doff. In order to improve further the characteristics of the previous design, we started a new project called pHALO aiming at further reducing of the energy expenditure during walking. As a difference from the previous solution where ankle joints were restrained, the new solution will incorporate two actuators to control the ankle joints angles. As an intermediate step from the development of the pHALO system, in this study we added to the existing system a feedback PI controller to control the ankle joint angle of the right foot in the push-off phase and conducted an experiment to evaluate the effect of the new design on the walking patterns and energy efficiency. The results showed longer stride length, faster gait speed, smaller variation of the CoG, and less energy consumption.
Design of a Dual Quantization Electromechanical Sigma–Delta Modulator MEMS Vibratory Wheel Gyroscope

This paper presents a dual quantization lateral-axis capacitive electromechanical sigma–delta modulator (EM-<inline-formula> <tex-math notation="LaTeX">$\Sigma \Delta {\mathrm{ M}}$ </tex-math></inline-formula>) vibratory wheel gyroscope under mode-matched condition. A symmetric wheel gyroscope structure was designed, fabricated, and wafer-level packaged under vacuum. The EM-<inline-formula> <tex-math notation="LaTeX">$\Sigma \Delta {\mathrm{ M}}$ </tex-math></inline-formula> interface loop adopts a fourth-order multifeedback and local resonator <inline-formula> <tex-math notation="LaTeX">$\Sigma \Delta {\mathrm{ M}}$ </tex-math></inline-formula> noise shaping structure, taking advantage of single-bit and multibit quantization in a single-loop modulator. To evaluate the influence of quantization noise, various numbers of bits of the multibit quantizator were compared and the optimal number of bits was calculated. The interface circuit system was implemented in hardware based on a low-noise front-end application-specified integrated circuit and a back-end discrete-time EM-<inline-formula> <tex-math notation="LaTeX">$\Sigma \Delta {\mathrm{ M}}$ </tex-math></inline-formula> realized in a field-programmable gate array chip. The system clock was generated using a self-clocking scheme, which allows interfacing to gyroscope with a wide range of drive frequencies. Experimental evaluation indicated that the digital gyroscope system achieved a scale factor of 2073LSB(4.1 mV)/deg/s, with a nonlinearity of 0.046%, a noise floor of 3.1 m°/s/<inline-formula> <tex-math notation="LaTeX">$\surd $ </tex-math></inline-formula>Hz within a bandwidth of 100 Hz, and a bias instability of 1.3 deg/hr. [2017-0081]
Characterizing the Performance of Concurrent Virtualized Network Functions with OVS-DPDK, FD.IO VPP and SR-IOV

The virtualization of network functions is promising significant cost reductions for network operators. Running multiple network functions on a standard x86 server instead of dedicated appliances can increase the utilization of the underlying hardware,while reducing the maintenance and management costs of such functions. However, total cost of ownership calculations are typically a function of the attainable network throughput, which in a virtualized system is highly dependent on the overall system architecture - in particular the input/output (I/O) path. In this paper we investigate the attainable performance of an x86 host running multiple virtualized network functions (VNFs) under different I/O architectures: OVS-DPDK, SR-IOV, and FD.io VPP. Running multiple VNFs in parallel on a standard x86 host is a common use-case for cloud-based networking services. We show that the system throughput in a multi-VNF environment differs significantly from deployments where only a single VNF is running on a server.
Visual Analysis of Inclusion Dynamics in Two-Phase Flow

In single-phase flow visualization, research focuses on the analysis of vector field properties. In two-phase flow, in contrast, analysis of the phase components is typically of major interest. So far, visualization research of two-phase flow concentrated on proper interface reconstruction and the analysis thereof. In this paper, we present a novel visualization technique that enables the investigation of complex two-phase flow phenomena with respect to the physics of breakup and coalescence of inclusions. On the one hand, we adapt dimensionless quantities for a localized analysis of phase instability and breakup, and provide detailed inspection of breakup dynamics with emphasis on oscillation and its interplay with rotational motion. On the other hand, we present a parametric tightly linked space-time visualization approach for an effective interactive representation of the overall dynamics. We demonstrate the utility of our approach using several two-phase CFD datasets.
Impact of pre-transplant bone marrow plasma cell percentage on post-transplant response and survival in newly diagnosed multiple myeloma

Abstract We evaluated 1070 patients with newly diagnosed multiple myeloma, who completed a single line of induction therapy followed by autologous stem cell transplantation. Patients with pre-transplant <5% BMPC had a threefold likelihood of achieving stringent complete response (sCR) after transplant compared to those with BMPC ≥5% (45.6% vs. 16.3%; p < 0.0001). The median progression-free survival and overall survival from transplant for patients with pre-transplant BMPC <5% and ≥5% was 30.8 and 115.2 months compared to 20.8 and 74.1 months, respectively (p < 0.0001 for both comparisons). The effect of pre-transplant BMPC was most pronounced in patients achieving complete response or very good partial response after transplant. In conclusion, pre-transplant BMPC <5% is an important prognostic marker of long-term survival after transplant and should be routinely incorporated into pre-transplant risk stratification.
Popular is cheaper: curtailing memory costs in interactive analytics engines

This paper targets the growing area of interactive data analytics engines. We present a system called Getafix that intelligently decides replication levels and replica placement for data segments, in a way that is responsive to changing popularity of data access by incoming queries. We present an optimal solution to the static version of the problem, achieving minimality in both makespan and replication factor. Based on this intuition we build the Getafix system to handle queries and segments arriving in real time. We integrated Getafix into Druid, a modern open-source interactive data analytics engine. We present experimental results using workloads from Yahoo! 's production Druid cluster. Compared to existing work, Getafix achieves comparable query latency (both average and tail), while using 1.45--2.15 x less memory in a private cloud. In a public cloud, for a 100 TB hot dataset size, Getafix can cut dollar costs by as much as 10 million annually with negligible performance impact.
Structure of Nanocrystalline Nickel Prepared by Powder Metallurgy

Nanocrystaline nickel was prepared by selective leaching technology. Consequently, the powder was compacted by spark plasma sintering method. This process is suitable due to its high heating rates, which leads to relatively low thermal exposition of compacted material. The dependence of structure of compacted material on preparation conditions is described in this paper.
Factors associated with risk of malnutrition in the elderly in south-eastern Brazil.

OBJECTIVE The aim of this study was to evaluate the prevalence of malnutrition risk and its association with socioeconomic, behavioral, and health characteristics in the community-dwelling elderly. METHODS A cross-sectional study with individuals aged ≥ 60 years. Nutritional status was evaluated using the Mini Nutritional Assessment. Socioeconomic, behavioral, and health information was also collected from all participants. The association between each variable and the risk of malnutrition was calculated and adjusted using Poisson hierarchical regression. RESULTS The initial sample consisted of 3,101 elderly people, of whom 28.3% (95%CI 25.3 - 31.4%) were at risk of malnutrition. The multivariate analysis showed that the risk of malnutrition was significantly higher in women without formal education, who did not live with a partner, and identified as black-skinned. The risk of malnutrition was twice as high in individuals with no family income as compared to those who earned at least three minimum wages. Smokers were also more likely to be at risk of malnutrition than individuals who had never smoked. Participants suffering from kidney, respiratory or heart disease were at higher risk of malnutrition than those with no history of such illnesses. CONCLUSION These findings could be used to help in the development of health policies and in the establishment of adequate programs aimed at reducing the risk of malnutrition in this population.
Intergenerational social mobility and leisure-time physical activity in adulthood: a systematic review

Aim To systematically review the association between intergenerational social mobility and leisure-time physical activity (LTPA) in adulthood, in order to assess all published evidence relating to the hypothesis that adults socially mobile between childhood and adulthood will have different levels of LTPA than those in the same socioeconomic group across life. Methods A systematic review was carried out following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies were identified by searching databases (MEDLINE, Embase, PsycINFO) and reference lists. Eligible studies examined associations between any indicator of social mobility, based on at least one measure of parental socioeconomic position (SEP) and one measure of own adult SEP, and LTPA in adulthood. Results 13 studies comprising a total of 44 000 participants from the UK, Finland, Sweden, Australia, USA and Brazil were included. Participants were aged 16–70 years and were from population-based surveys, occupational cohorts and primary care registries. Most studies (n=9) used occupational class measures to identify social mobility; education (n=4) and income (n=1) were also used. There was consistent evidence in nine of the 13 studies that stable high socioeconomic groups tended to report the highest levels of participation in LTPA and stable low socioeconomic groups the lowest. Upward and downwardly mobile groups participated in LTPA at levels between these stable groups. Conclusions Cumulative exposure to higher SEP in childhood and adulthood was associated with higher LTPA in adulthood. Thus, a potential outcome of policies and interventions which aim to minimise exposure to socioeconomic adversity may be increased LTPA among adults. Trial registration number CRD42016036538.
Bacterial Microbiota of Rice Roots: 16S-Based Taxonomic Profiling of Endophytic and Rhizospheric Diversity, Endophytes Isolation and Simplified Endophytic Community

Rice is currently the most important food crop in the world and we are only just beginning to study the bacterial associated microbiome. It is of importance to perform screenings of the core rice microbiota and also to develop new plant-microbe models and simplified communities for increasing our understanding about the formation and function of its microbiome. In order to begin to address this aspect, we have performed a 16S rDNA taxonomic bacterial profiling of the rhizosphere and endorhizosphere of two high-yield rice cultivars—Pionero 2010 FL and DANAC SD20A—extensively grown in Venezuela in 2014. Fifteen putative bacterial endophytes were then isolated from surface-sterilized roots and further studied in vitro and in planta. We have then performed inoculation of rice seedlings with a simplified community composed by 10 of the isolates and we have tracked them in the course of 30 days in greenhouse cultivation. The results obtained suggest that a set was able to significantly colonize together the rice endorhizospheres, indicating possible cooperation and the ability to form a stable multispecies community. This approach can be useful in the development of microbial solutions for a more sustainable rice production.
EPID dosimetry for pretreatment quality assurance with two commercial systems

This study compares the EPID dosimetry algorithms of two commercial systems for pretreatment QA, and analyzes dosimetric measurements made with each system alongside the results obtained with a standard diode array. 126 IMRT fields are examined with both EPID dosimetry systems (EPIDose by Sun Nuclear Corporation, Melbourne FL, and Portal Dosimetry by Varian Medical Systems, Palo Alto CA) and the diode array, MapCHECK (also by Sun Nuclear Corporation). Twenty‐six VMAT arcs of varying modulation complexity are examined with the EPIDose and MapCHECK systems. Optimization and commissioning testing of the EPIDose physics model is detailed. Each EPID IMRT QA system is tested for sensitivity to critical TPS beam model errors. Absolute dose gamma evaluation (3%, 3 mm, 10% threshold, global normalization to the maximum measured dose) yields similar results (within 1%–2%) for all three dosimetry modalities, except in the case of off‐axis breast tangents. For these off‐axis fields, the Portal Dosimetry system does not adequately model EPID response, though a previously‐published correction algorithm improves performance. Both MapCHECK and EPIDose are found to yield good results for VMAT QA, though limitations are discussed. Both the Portal Dosimetry and EPIDose algorithms, though distinctly different, yield similar results for the majority of clinical IMRT cases, in close agreement with a standard diode array. Portal dose image prediction may overlook errors in beam modeling beyond the calculation of the actual fluence, while MapCHECK and EPIDose include verification of the dose calculation algorithm, albeit in simplified phantom conditions (and with limited data density in the case of the MapCHECK detector). Unlike the commercial Portal Dosimetry package, the EPIDose algorithm (when sufficiently optimized) allows accurate analysis of EPID response for off‐axis, asymmetric fields, and for orthogonal VMAT QA. Other forms of QA are necessary to supplement the limitations of the Portal Vision Dosimetry system. PACS numbers: 87.53. Bn, 87.53. Jw, 87.53. Kn, 87.55. Qr, 87.56. Fc, 87.57. uq