gebhart/patrepeval huggingface dataset:
Human Norovirus Evolution in a Chronically Infected Host (2017)

Typically, human noroviruses cause symptoms of acute gastroenteritis for 2 to 4 days. Often, the virions are shed in stool for several days after the symptoms recede, which in turn can lead to further contamination and transmission. Moreover, a number of reports have considered that chronic norovirus infections, i.e., lasting months and years, might even function as reservoirs for the generation of novel strains that can escape the herd immunity or have modified binding interactions with histo-blood group antigens (HBGAs). In this study, we analyzed noroviruses isolated from a patient who has presented a chronic infection for more than 6 years. We found that the isolated capsid sequences clustered into two main genetic types (termed A and B), despite a plethora of capsid quasi-sequences. Furthermore, the two genetic types corresponded well with distinct antigenicities. On the other hand, we showed that numerous amino acid substitutions on the capsid surface of genetic types A and B did not alter the HBGA binding profiles. However, divergent binding profiles for types A and B were observed with human milk oligosaccharides (HMOs), which structurally mimic HBGAs and may act as natural antivirals. Importantly, the isolated capsid sequences only had approximately 90% amino acid identity with other known sequences, which suggested that transmission of these chronic noroviruses could be limited. <b>IMPORTANCE</b> The norovirus genogroup II genotype 4 (GII.4) variants have approximately 5% divergence in capsid amino acid identity and have dominated over the past decade. The precise reason(s) for the GII.4 emergence and persistence in the human population is still unknown, but some studies have suggested that chronically infected patients might generate novel variants that can cause new epidemics. We examined GII.4 noroviruses isolated from an immunocompromised patient with a long-term infection. Numerous norovirus capsid quasi-species were isolated during the 13-month study. The capsid quasi-species clustered into two genetic and antigenic types. However, the HBGA binding profiles were similar between the two antigenic clusters, indicating that the amino acid substitutions did not alter the HBGA binding interactions. The isolated sequences represented two new GII.4 variants, but similar sequences were not found in the database. These results indicated that chronically infected patients might not generate novel noroviruses that cause outbreaks.
DeepFovea (2019)

In order to provide an immersive visual experience, modern displays require head mounting, high image resolution, low latency, as well as high refresh rate. This poses a challenging computational problem. On the other hand, the human visual system can consume only a tiny fraction of this video stream due to the drastic acuity loss in the peripheral vision. Foveated rendering and compression can save computations by reducing the image quality in the peripheral vision. However, this can cause noticeable artifacts in the periphery, or, if done conservatively, would provide only modest savings. In this work, we explore a novel foveated reconstruction method that employs the recent advances in generative adversarial neural networks. We reconstruct a plausible peripheral video from a small fraction of pixels provided every frame. The reconstruction is done by finding the closest matching video to this sparse input stream of pixels on the learned manifold of natural videos. Our method is more efficient than the state-of-the-art foveated rendering, while providing the visual experience with no noticeable quality degradation. We conducted a user study to validate our reconstruction method and compare it against existing foveated rendering and video compression techniques. Our method is fast enough to drive gaze-contingent head-mounted displays in real time on modern hardware. We plan to publish the trained network to establish a new quality bar for foveated rendering and compression as well as encourage follow-up research.
Algal Carbon Dioxide Concentrating Mechanisms (2011)

Abstract Photosynthetic microorganisms like cyanobacteria and many eukaryotic algae acclimate to a limited availability of carbon dioxide (CO 2 ) in their environment by inducing a process called the carbon dioxide concentrating mechanism. This process uses an active inorganic carbon (C i ; CO 2 and/or HCO 3 − ) uptake system that leads to the internal accumulation of C i to levels significantly higher than extracellular levels. Carbonic anhydrase activity converts much of the accumulated hydrogen carbonate to CO 2 , concentrating this substrate around Rubisco and thereby optimising photosynthetic efficiency even under low CO 2 conditions. The efficiency of the process is further improved by the sequestration of Rubisco into specialised structures like the cyanobacterial carboxysome or the pyrenoid in eukaryotic algae. The carbon dioxide concentrating mechanism enhances carbon dioxide fixation and growth in algae. With the increasing demands for sustainable energy sources, algae with efficient carbon dioxide concentrating mechanisms are attractive models for biotechnological and transgenic applications for biofuel and biomass production. Key Concepts: The carbon dioxide concentrating mechanism helps photosynthetic algae optimise photosynthesis under limiting CO 2 conditions. Rubisco uses both carbon dioxide and oxygen as substrates. Rubisco is localised in the carboxysome in cyanobacteria and the pyrenoid in the green alga, Chlamydomonas reinhardtii. The charged hydrogen carbonate needs transporters to enter the cell and cross organellar membranes. Carbonic anhydrase is an efficient enzyme that carries out the reversible interconversion of carbon dioxide and hydrogen carbonate and this reaction proceeds at a much faster rate than the uncatalysed reaction. At higher pH levels most of the inorganic carbon is in the form of hydrogen carbonate. Most algae with carbon dioxide concentrating mechanisms can take up both carbon dioxide and hydrogen carbonate. Carbon dioxide can diffuse out of the cell so algae trap carbon dioxide in the form of the charged hydrogen carbonate anion. Algae are used for large‐scale biomass production and are currently being explored as sources of bio‐fuel.
Kombinatorische Synthese niedermolekularer organischer Verbindungen (1996)

Abstract Innerhalb weniger Jahre hat sich die kombinatorische Synthese von einer Laborkuriosität zu einer ernstzunehmenden Methode in der Wirkstofforschung entwickelt. Die rasanten Fortschritte der Molekularbiologie und die daraus resultierende Möglichkeit, die Wirksamkeit neuer Substanzen extrem effizient bestimmen zu können, haben zu einem Paradigmenwechsel bei der Synthese von Testsubstanzen geführt: Neben der konventionellen Vorgehensweise, eine Substanz nach der anderen zu synthetisieren, gewinnen zunehmend Methoden an Bedeutung, mit denen es gelingt, viele Substanzen mit definierter Struktur gleichzeitig herzustellen. Eine kombinatorische Synthese ist dadurch gekennzeichnet, daß in einer Synthesestufe nicht nur mit einem Synthesebaustein, sondern mit vielen – parallel oder in Mischung – umgesetzt wird. In jeder Stufe werden alle möglichen Kombinationen gebildet, so daß aus nur wenigen Bausteinen eine große Zahl an Produkten, eine „Verbindungsbibliothek”︁, entsteht. Aufbauend auf den Arbeiten zur Synthese von Peptidbibliotheken wurden verschiedene Methoden zur kombinatorischen Synthese niedermolekularer organischer Verbindungen entwickelt: Durch hochautomatisierte Parallelsynthese werden Einzelsubstanzen hergestellt, und spezielle Techniken ermöglichen die gezielte Synthese definiert zusammengesetzter Mischungen. Verbindungen mit unterschiedlichsten Strukturen sind mittlerweile durch kombinatorische Synthesen zugänglich, wobei die Größe der erhaltenen Bibliotheken von wenigen Einzelverbindungen bis hin zu vielen tausend Substanzen in Mischungen reicht. Der vorliegende Beitrag gibt eine Übersicht über die bislang beschriebenen kombinatorischen Synthesen niedermolekularer organischer Verbindungen, unabhängig davon, ob diese in Lösung oder an fester Phase durchgeführt wurden. Weiterhin werden die Techniken zur Identifizierung aktiver Verbindungen in Mischungen sowie Möglichkeiten der Automatisierung der Synthese und der Verwaltung der anfallenden großen Datenmengen vorgestellt. Ferner wird ein Überblick über auf diesem Gebiet aktive Venture‐Firmen gegeben. Der abschließende Ausblick versucht, die zukünftige Entwicklung in diesem exponentiell wachsenden Arbeitsgebiet sowie die Auswirkungen dieses „neuen Denkens”︁ auf andere Bereiche der Chemie aufzuzeigen.
Precious Metal Catalysts Supported on Ceramic and Metal Monolithic Structures for the Hydrogen Economy (2007)

Distributed hydrogen for the hydrogen economy will require new catalysts and processes. Existing large‐scale hydrogen plants can not simply be reduced in size to meet the economic, safety, and frequent duty cycle requirements for applications for fuel cells, hydrogen fueling stations, and industrial uses such as hydrogenation reactions, gas turbine cooling, metal processing, etc 1 Armor, J. 2005. Catalysis for the Hydrogen Economy. Catalysis Letters, 101(3): 4–131. [Crossref] , [Google Scholar] 2 Forsberg, C. 2005. The Hydrogen Economy is Coming: The Question is Where. Chemical Engineering Progress, 101(12): 20–22. [Web of Science ®] , [Google Scholar]. Consequently, there is a need to completely reassess how hydrogen can be made for the emerging hydrogen economy. This article presents some of the technological advantages of precious metal monoliths over traditional base metal particulate catalysts for reforming hydrocarbons, such as natural gas, for the generation of distributed hydrogen.
Survey on Resource Allocation Policy and Job Scheduling Algorithms of Cloud Computing1 (2013)

Cloud computing is the product of the evolution of calculation. It is a new distributed computing model. As more and more people put into the research and applications on cloud computing, the technology of computing becomes more and more widely used. Cloud computing has a huge user group. It has to deal with a large number of tasks. How to make appropriate decisions when allocating hardware resources to the tasks and dispatching the computing tasks to resource pool has become the main issue in cloud computing. This paper is based on the current situation of resource allocation policy and job scheduling algorithms under cloud circumstance. It summarizes some methods to improve the performance, including dynamic resource allocation strategy based on the law of failure, dynamic resource assignment on the basis of credibility, ant colony optimization algorithm for resource allocation, dynamic scheduling algorithm based on threshold, optimized genetic algorithm with dual fitness and improved ant colony algorithm for job scheduling.
Learning-based network path planning for traffic engineering (2018)

Recent advances in traffic engineering offer a series of techniques to address the network problems due to the explosive growth of Internet traffic. In traffic engineering, dynamic path planning is essential for prevalent applications, e.g., load balancing, traffic monitoring and firewall. Application-specific methods can indeed improve the network performance but can hardly be extended to general scenarios. Meanwhile, massive data generated in the current Internet has not been fully exploited, which may convey much valuable knowledge and information to facilitate traffic engineering. In this paper, we propose a learning-based network path planning method under forwarding constraints for finer-grained and effective traffic engineering. We form the path planning problem as the problem of inferring a sequence of nodes in a network path and adapt a sequence-to-sequence model to learn implicit forwarding paths based on empirical network traffic data. To boost the model performance, attention mechanism and beam search are adapted to capture the essential sequential features of the nodes in a path and guarantee the path connectivity. To validate the effectiveness of the derived model, we implement it in Mininet emulator environment and leverage the traffic data generated by both a real-world GEANT network topology and a grid network topology to train and evaluate the model. Experiment results exhibit a high testing accuracy and imply the superiority of our proposal.
Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding (2021)

This paper presents a new Vision Transformer (ViT) architecture Multi-Scale Vision Longformer, which significantly enhances the ViT of [12] for encoding high-resolution images using two techniques. The first is the multi-scale model structure, which provides image encodings at multiple scales with manageable computational cost. The second is the attention mechanism of Vision Long-former, which is a variant of Longformer [3], originally developed for natural language processing, and achieves a linear complexity w.r.t. the number of input tokens. A comprehensive empirical study shows that the new ViT significantly outperforms several strong baselines, including the existing ViT models and their ResNet counterparts, and the Pyramid Vision Transformer from a concurrent work [47], on a range of vision tasks, including image classification, object detection, and segmentation. The models and source code are released at https://github.com/microsoft/vision-longformer.
Multiple states and heat transfer in two-dimensional tilted convection with large aspect ratios (2018)

Multiple stable states exist for two-dimensional tilted convection with large aspect ratios (\ensuremath{\Gamma}\ensuremath{\ge}2). The Nusselt number generally decreases monotonically with increasing tilt angle for large \ensuremath{\Gamma} cases with \ensuremath{\Gamma}\ensuremath{\ge}8.
SARS-CoV-2 immune evasion by the B.1.427/B.1.429 variant of concern (2021)

A novel variant of concern (VOC) named CAL.20C (B.1.427/B.1.429), which was originally detected in California, carries spike glycoprotein mutations S13I in the signal peptide, W152C in the N-terminal domain (NTD), and L452R in the receptor-binding domain (RBD). Plasma from individuals vaccinated with a Wuhan-1 isolate-based messenger RNA vaccine or from convalescent individuals exhibited neutralizing titers that were reduced 2- to 3.5-fold against the B.1.427/B.1.429 variant relative to wild-type pseudoviruses. The L452R mutation reduced neutralizing activity in 14 of 34 RBD-specific monoclonal antibodies (mAbs). The S13I and W152C mutations resulted in total loss of neutralization for 10 of 10 NTD-specific mAbs because the NTD antigenic supersite was remodeled by a shift of the signal peptide cleavage site and the formation of a new disulfide bond, as revealed by mass spectrometry and structural studies.
MonALISA : A Distributed Monitoring Service Architecture (2003)

The MonALISA (Monitoring Agents in A Large Integrated Services Architecture) system provides a distributed monitoring service. MonALISA is based on a scalable Dynamic Distributed Services Architecture which is designed to meet the needs of physics collaborations for monitoring global Grid systems, and is implemented using JINI/JAVA and WSDL/SOAP technologies. The scalability of the system derives from the use of multithreaded Station Servers to host a variety of loosely coupled self-describing dynamic services, the ability of each service to register itself and then to be discovered and used by any other services, or clients that require such information, and the ability of all services and clients subscribing to a set of events (state changes) in the system to be notified automatically. The framework integrates several existing monitoring tools and procedures to collect parameters describing computational nodes, applications and network performance. It has built-in SNMP support and network-performance monitoring algorithms that enable it to monitor end-to-end network performance as well as the performance and state of site facilities in a Grid. MonALISA is currently running around the clock on the US CMS test Grid as well as an increasing number of other sites. It is also being used to monitor the performance and optimize the interconnections among the reflectors in the VRVS system.
B Cells Contribute to the Antitumor Activity of CpG-Oligodeoxynucleotide in a Mouse Model of Metastatic Lung Carcinoma (2011)

Abstract Rationale CpG-oligodeoxynucleotide (CpG-ODN; CpG), a Toll-like receptor-9 ligand, has been widely studied as a potential antitumor adjuvant. Toll-like receptor-9 is highly expressed on lung carcinoma tissues and some immune cells, such as plasmacytoid dendritic cells and B cells. Objectives The aim of our study was to elucidate the effect of CpG on B cells in a mouse model of lung carcinoma. Methods C57Bl/6j, B cell–deficient, and Nude mice were intravenously implanted with the lung metastatic B16-F10 melanoma cells and killed 3 and 7 days after CpG administration. Measurements and Main Results Administration of CpG increased lung tumor growth in B16-F10–implanted C57BL/6J mice. The genetic absence of B cells strongly facilitated CpG-induced tumor progression. In contrast, the adoptive transfer of CpG-activated B cells induced tumor arrest, associated with a reduced suppressive immune environment due to the lower recruitment of regulatory T cells, myeloid-derived suppressor cells, and CD8+ regulatory T cells along with the reduced expression of suppressive cytokines such as IL-10 and transforming growth factor-β. Furthermore, concomitant with higher production of IFN-γ, the apoptosis rate in the lungs of mice adoptively transferred with CpG-activated B cells was increased. Depletion of mature CD20+ B cells increased the lung tumor burden in CpG-treated C57BL/6J mice and nude mice. Moreover, nude mice had the same lung tumor burden as B cell–deficient mice when mature CD20+ B cells were depleted. Conclusions Our data demonstrate the protective antitumor activity of CpG-activated B cells and shed light on CpG as an antitumor adjuvant for lung cancer therapy.
XCMS Online: A Web-Based Platform to Process Untargeted Metabolomic Data (2012)

Recently, interest in untargeted metabolomics has become prevalent in the general scientific community among an increasing number of investigators. The majority of these investigators, however, do not have the bioinformatic expertise that has been required to process metabolomic data by using command-line driven software programs. Here we introduce a novel platform to process untargeted metabolomic data that uses an intuitive graphical interface and does not require installation or technical expertise. This platform, called XCMS Online, is a web-based version of the widely used XCMS software that allows users to easily upload and process liquid chromatography/mass spectrometry data with only a few mouse clicks. XCMS Online provides a solution for the complete untargeted metabolomic workflow including feature detection, retention time correction, alignment, annotation, statistical analysis, and data visualization. Results can be browsed online in an interactive, customizable table showing statistics, chromatograms, and putative METLIN identities for each metabolite. Additionally, all results and images can be downloaded as zip files for offline analysis and publication. XCMS Online is available at https://xcmsonline.scripps.edu.
The Research Context (1999)

Our purpose here is to describe and discuss the research context, to set the scene for understanding both our own experiences as women researchers in higher education and to provide a background for you to think about your aims, aspirations and skills. Although the experiences of women going into a research career are varied, they can be understood as structured by common features of the context within which they carry out research. What is evident from our experience and other literature on the subject is that women develop strategies to cope with, and overcome, the difficulties they may face. Some of these will be discussed later in the book. Our intention is not to suggest that the obstacles we face are insurmountable or indeed that the culture of higher education and research prohibits creative and flexible ways of working. It is our view that these structures are both constraining and enabling, that women are often able to find a path through the obstacles and develop research that is both creative and innovative.
Color Consistency and Local Contrast Enhancement for a Mobile Image-Based Change Detection System (2017)

Mobile change detection systems allow for acquiring image sequences on a route of interest at different time points and display changes on a monitor. For the display of color images, a processing approach is required to enhance details, to reduce lightness/color inconsistencies along each image sequence as well as between corresponding image sequences due to the different illumination conditions, and to determine colors with natural appearance. We have developed a real-time local/global color processing approach for local contrast enhancement and lightness/color consistency, which processes images of the different sequences independently. Our approach combines the center/surround Retinex model and the Gray World hypothesis using a nonlinear color processing function. We propose an extended gain/offset scheme for Retinex to reduce the halo effect on shadow boundaries, and we employ stacked integral images (SII) for efficient Gaussian convolution. By applying the gain/offset function before the color processing function, we avoid color inversion issues, compared to the original scheme. Our combined Retinex/Gray World approach has been successfully applied to pairs of image sequences acquired on outdoor routes for change detection, and an experimental comparison with previous Retinex-based approaches has been carried out.
Association of Engrailed homeoproteins with vesicles presenting caveolae-like properties (1997)

We report here that the homeoproteins Engrailed-1 and Engrailed-2 are present in specific non-nuclear subcellular compartments. Using electron microscopy, we observed that chick-Engrailed-2 expressed in COS-7 cells associates with membrane fractions that are characterized as caveolae. This characterization is based on morphological, biochemical and immunological criteria such as, in particular, the absence of clathrin coat and the presence of caveolin and cholera toxin-binding sites. These data are fully confirmed by subcellular fractionation experiments, which demonstrate that transfected chick-Engrailed-2 is present in low density membrane fractions that are resistant to Triton X-100, enriched in caveolin and solubilized by the addition of a cholesterol-binding detergent, a set of properties highly characteristic of caveolae. The association of Engrailed-2 with specific membrane fractions observed after transfection in COS-7 cells is also observed for endogenous Engrailed-1 and Engrailed-2 expressed at late embryonic stages in the cerebellum and posterior mesencephalon of the rodent. Indeed, the two proteins are present in membrane fractions that bear all the characteristics of microdomains or caveolae-like domains, i.e. Triton X-100 resistance, saponin solubilization, low density on sucrose gradients, enrichment in glycosphingolipid GM1, absence of transmembrane Neural Cell Adhesion Molecule, presence of the glypiated (GPI-anchored) glycoprotein F3/F11 and of the acylated growth-associated protein GAP-43. Finally we demonstrate that part of the membrane-associated Engrailed, either expressed in COS-7 cells or endogenously present in neural tissues, is not accessible to proteolytic enzymes unless the membranes have been permeabilized with detergent. This study suggests that, in addition to their well-known presence in the nucleus, Engrailed proteins are also associated with caveolae-like vesicles that are primarily transported anterogradely into the axon, and that they can get access to a compartment compatible with secretion.