gebhart/patrepeval huggingface dataset:
Antibiotic action revealed by real-time imaging of the mycobacterial membrane (2022)

Abstract The current understanding of mycobacterial cell envelope remodeling in response to antibiotics is limited. Chemical tools that report on phenotypic changes with minimal cell wall perturbation are critical to understanding such time-dependent processes. We employed a fluorogenic chemical probe to image how antibiotics perturb mycobacterial cell envelope assembly in real-time. Time-lapse microscopy revealed that differential antibiotic treatment elicited unique cellular phenotypes, providing a platform for simultaneously monitoring cell envelope construction and remodeling responses. Our data show that rifampicin, which does not directly inhibit cell wall biosynthesis, affords a readily detected mycomembrane phenotype. The fluorogenic probe revealed the production of extracellular vesicles in response to antibiotics, and analyses of these vesicles indicate that antibiotic treatment elicits the release of agents that attenuate macrophage activation.
Practical Memory Deduplication Attacks In Sandboxed Javascript (2015)

Page deduplication is a mechanism to reduce the memory footprint of a system. Identical physical pages are identified across borders of virtual machines and programs and merged by the operating system or the hypervisor. However, this enables side-channel information leakage through cache or memory access time. Therefore, it is considered harmful in public clouds today, but it is still considered safe to use in a private environment, i.e., private clouds, personal computers, and smartphones. We present the first memory-disclosure attack in sandboxed Javascript which exploits page deduplication. Unlike previous attacks, our attack does not require the victim to execute an adversary’s program, but simply to open a website which contains the adversary’s Javascript code. We are not only able to determine which applications are running, but also specific user activities, for instance, whether the user has specific websites currently opened. The attack works on servers, personal computers and smartphones, and across the borders of virtual machines.
Input Selection for Performance, Stabilizability, and Controllability of Structured Linear Descriptor Systems (2018)

Networked systems are often controlled by selecting a subset of nodes to act as inputs, which then control the remaining network nodes via local interactions. In this paper, we investigate the problem of selecting input nodes in order to control structured linear descriptor systems, which contain free parameters that can take any value as well as fixed parameters that take a known, fixed value. This class of system generalizes standard models of networked systems, which typically assume that all parameters are either fixed or free. We develop a framework for joint selection to ensure controllability, stabilizability via output feedback, and performance, by mapping conditions for controllability and stabilizability to matroid constraints on the set of input nodes. We propose polynomial-time algorithms with provable optimality bounds when the performance metrics under consideration are submodular. Our results are illustrated through a numerical study.
Early-stage performance modeling and its application for integrated embedded control software design (2004)

Most of current embedded control software (ECSW) development techniques deal only with performance specifications during the early software design phase and delay the modeling and analysis until the detail design has been completed. In this paper, we propose a new approach to modeling and analysis of the performance of the designed ECSW without knowing the platform configuration and the software deployment. The functional model is assumed --- as is commonly the case in practice --- to be constructed by integrating existing (reusable) software components. The performance of components and connections in the model are modeled using annotated requirements and virtual resource demands. Our algorithm then computes the system performance such as end-to-end delays of transactions and workloads by traversing the model. The results can be applied to the platform design and runtime architecture generation. To demonstrate the usefulness of the proposed method in real world applications, we present the analysis of automotive vehicle-to-vehicle control software as an example.
DataSeries (2009)

Structured serial data is used in many scientific fields; such data sets consist of a series of records, and are typically written once, read many times, chronologically ordered, and read sequentially. In this paper we introduce DataSeries, an on-disk format, run-time library and set of tools for storing and analyzing structured serial data. We identify six key properties of a system to store and analyze this type of data, and describe how DataSeries was designed to provide these properties. We quantify the benefits of DataSeries through several experiments. In particular, we demonstrate that DataSeries exceeds the performance of common trace formats by at least a factor of two.
A Review of the Effect of Processing Variables on the Fabrication of Electrospun Nanofibers for Drug Delivery Applications (2013)

Electrospinning is a fast emerging technique for producing ultrafine fibers by utilizing electrostatic repulsive forces. The technique has gathered much attention due to the emergence of nanotechnology that sparked worldwide research interest in nanomaterials for their preparation and application in biomedicine and drug delivery. Electrospinning is a simple, adaptable, cost‐effective, and versatile technique for producing nanofibers. For effective and efficient use of the technique,several processing parameters need to be optimized for fabricating polymeric nanofibers. The nanofiber morphology, size, porosity, surface area, and topography can be refined by varying these parameters. Such flexibility and diversity in nanofiber fabrication by electrospinning has broadened the horizons for widespread application of nanofibers in the areas of drug and gene delivery, wound dressing, and tissue engineering. Drug‐loaded electrospun nanofibers have been used in implants, transdermal systems, wound dressings, and as devices for aiding the prevention of postsurgical abdominal adhesions and infection. They show great promise for use in drug delivery provided that one can confidently control the processing variables during fabrication. This paper provides a concise incursion into the application of electrospun nanofibers in drug delivery and cites pertinent processing parameters that may influence the performance of the nanofibers when applied to drug delivery.
Local inversion of transient shear wave propagation for elasticity and viscosity mapping in soft tissues : theoretical and experimental analysis (2005)

Observation of transient shear-wave propagation in soft tissue is of great interest for the study of tissue viscoelastic properties. Previously, we introduced a technique, supersonic shear imaging (SSI), able to generate transient shear waves using the acoustic radiation force and to image their propagation in soft tissues in real time. Inversion methods were used to recover elasticity from the shear-wave propagation. We now present a precise and robust inversion algorithm taking into account not only elastic, but also viscous, properties of soft tissues. Based on a Voigt model, this algorithm is designed to provided quantitative and local estimation of soft tissue elasticity and viscosity. The influence of viscosity on transient shear waves is modeled and analyzed using a 3D analytical formulation of the mechanical Green's function in a viscoelastic medium. The spatial and temporal shape of experimental shear waves induced in soft tissues using SSI can only be accurately modeled by taking into account tissue shear viscosity. The respective influences of viscosity, elasticity or diffraction on the shear wave shape are carefully studied and discriminated. Taking advantage of the previous modeling, a local inverse problem permitting the recovery of shear elasticity and viscosity is presented and validated using the Green's function based simulation tool. The role of viscosity on the accuracy of the elasticity estimation is studied. The influence of out of plane shear propagation on the inversion algorithm is discussed. In media exhibiting shear viscoelasticity heterogeneities, finite differences simulations are used to study the spatial resolution of the algorithm and its sensitivity to signal-to-noise ratio. Experiments on calibrated tissue-mimicking phantoms having different viscoelastic properties are presented, validating the simulation results.
Utility of Diffusion Tensor Imaging Tractography in Evaluating Motor Examination and Functional Outcomes in Patients with Surgically Resected Deep Intracranial Cavernous Malformations: A Preliminary Model (2019)

Introduction: Resection of deep intracranial CMs (CMs) is associated with risk of neurological deterioration and uncertainty regarding clinical outcomes.
Analytical Expressions for the Mutual Coupling of Loop Antennas Valid From the RF to Optical Regimes (2017)

Arrays of circular loop antennas are commonly employed at radio frequencies for communications and geophysical sensing, while also holding enormous potential in the optical regime for applications such as solar energy harvesting. Exact analytical expressions exist for predicting the mutual coupling between a variety of antennas, including dipoles and slots. However, due to the complexity of the integrals involved, analytical expressions for evaluating the coupling between loop antennas have not been previously available. This paper presents straightforward analytical expressions for efficient calculation of the coupling between two circular loops at arbitrary locations. The theory is extended to the optical regime by taking into account the dispersion and loss of the material comprising the loop antenna. These analytical expressions provide insight into the physics underlying the mutual coupling phenomenon. Along with the approximate analytical expressions, a useful pseudo-analytical representation is developed which is more exact, especially in the near-field regime, and can be easily and efficiently evaluated in MATLAB via numerical integration. It is shown that full-wave simulations for a two-element array of nanoloops can take up to six hours, while the corresponding analytical and pseudo-analytical implementations derived here take less than a minute.
EZH2 inhibition remodels the inflammatory senescence-associated secretory phenotype to potentiate pancreatic cancer immune surveillance (2022)

ABSTRACT T cell-activating immunotherapies that produce durable and even curative responses in some malignancies have failed in pancreatic ductal adenocarcinoma (PDAC) due to rampant immune suppression and poor tumor immunogenicity. We and others have demonstrated that induction of cellular senescence and its accompanying senescence-associated secretory phenotype (SASP) can be an effective approach to activate not only T cell but also cytotoxic Natural Killer (NK) cell-mediated anti-tumor immunity. Here we found that the pancreas tumor microenvironment (TME) suppresses NK and T cell surveillance following therapy-induced senescence through EZH2-mediated repression of pro-inflammatory SASP genes. Genetic or pharmacological inhibition of EZH2 or its methyltransferase activity stimulated the production of pro-inflammatory SASP chemokines CCL2 and CXCL9/10 that led to enhanced NK and T cell infiltration and tumor eradication in preclinical PDAC mouse models. EZH2 activity was also associated with suppression of SASP-associated inflammatory chemokines and cytotoxic lymphocyte immunity and reduced overall survival in a PDAC patient cohort. These results demonstrate that EZH2 mediates epigenetic repression of the pro-inflammatory SASP in the pancreas TME, and that EZH2 blockade in combination with senescence-inducing therapies could be a powerful means to potentiate NK and T cell surveillance in PDAC to achieve immune-mediated tumor control.
Stereochemistry of Glutamate Receptor Agonist Efficacy:  Engineering a Dual-Specificity AMPA/Kainate Receptor, (2006)

ADVERTISEMENT RETURN TO ISSUEPREVAddition/CorrectionStereochemistry of Glutamate Receptor Agonist Efficacy: Engineering a Dual-Specificity AMPA/Kainate Receptor,Dean R. Madden, Qing Cheng, Shalita Thiran, Shanti Rajan, Frank Rigo, Kari Keinänen, Stefan Reinelt, Herbert Zimmermann, and Vasanthi JayaramanCite this: Biochemistry 2006, 45, 10, 3472Publication Date (Web):February 18, 2006Publication History Published online18 February 2006Published inissue 1 March 2006https://doi.org/10.1021/bi0680025Copyright © 2006 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views215Altmetric-Citations1LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (5 KB) Get e-Alerts Get e-Alerts
ChemInform Abstract: Preparation and Reactions of Tantalum Alkylidene Complexes Containing Bulky Phenoxide or Thiolate Ligands. Controlling Ring‐Opening Metathesis Polymerization Activity and Mechanism Through Choice of Anionic Ligand. (1988)

Abstract The alkylidene‐Ta complexes (III) are prepared according to the scheme.
Efficient Semantic Segmentation using Gradual Grouping (2018)

Deep CNNs for semantic segmentation have high memory and run time requirements. Various approaches have been proposed to make CNNs efficient like grouped, shuffled, depth-wise separable convolutions. We study the effectiveness of these techniques on a real-time semantic segmentation architecture like ERFNet for improving run time by over 5X. We apply these techniques to CNN layers partially or fully and evaluate the testing accuracies on Cityscapes dataset. We obtain accuracy vs parameters/FLOPs trade offs, giving accuracy scores for models that can run under specified runtime budgets. We further propose a novel training procedure which starts out with a dense convolution but gradually evolves towards a grouped convolution. We show that our proposed training method and efficient architecture design can improve accuracies by over 8% with depth wise separable convolutions applied on the encoder of ERFNet and attaching a light weight decoder. This results in a model which has a 5X improvement in FLOPs while only suffering a 4% degradation in accuracy with respect to ERFNet.
An all-MOSFET 69 ppm/°C Wide Range Programmable Current Reference with PV Insensitive Temperature Compensation (2022)

The paper proposes an all-MOSFET wide range programmable current reference with PV insensitive temperature compensation. Temperature insensitivity in the current is achieved by mutual compensation of temperature characteristics of carrier mobility, threshold voltage, and a novel temperature-dependent voltage bias. It is implemented in a standard 180 nm mixed-mode CMOS technology and uses only standard <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$V_{TH}$</tex> MOSFETs operating in the subthreshold region without requiring any resistors. A unit reference current of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$2.8\ \mu A$</tex> is generated with a minimum and average Temperature Coefficient (TC) of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$109.3\ \text{ppm}/^{\circ}C$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$117.5\ \text{ppm}/^{\circ}C$</tex> respectively, for temperature range of −20 °C to 100 °C across process corners. Average line sensitivity (LS) of 0.7 %/V is achieved across all process corners in the supply range of 1.2 V to 3 V. The circuit offers a wide range programmable current from <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$106\ \mu\mathrm{A}$</tex> to 1.586 mA using a 4-bit input with the best and average TC of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$93.2\ \text{ppm}/^{\circ}C$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$111.2\ \text{ppm}/^{\circ}C$</tex> respectively. The circuit is operated at 1.8 V. Further, a nano-ampere current reference is generated without additional circuitry, achieving a minimum and average TC of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$69.1\ \text{ppm}/^{\circ}C$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$80.3\ \text{ppm}/^{\circ}C$</tex> respectively, with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$3.1\ \mu\mathrm{W}$</tex> power consumption, 0.54 %/V LS for 1.2 V to 3 V and an area of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$0.0185\ mm^{2}$</tex> . Micro-ampere reference has a power consumption of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$11.67\ \mu W$</tex> .
A virus-specific CD8 + T cell immunodominance hierarchy determined by antigen dose and precursor frequencies (2006)

Immunodominance hierarchies are a substantial, but poorly understood, characteristic of CD8(+) T cell-mediated immunity. Factors influencing the differential responses to the influenza A virus nucleoprotein (NP(366-374)) and acid polymerase (PA(224-233)) peptides presented by H2D(b) have been analyzed by disabling (N5--> Q substitution) these peptides in their native configuration, then expressing them in the viral neuraminidase protein. This strategy of shifting epitopes within the same viral context resulted in an apparent equalization of D(b)NP(366) [epitope consisting of viral nucleoprotein (NP) amino acid residues 366-374 complexed with the H2D(b) MHC class I glycoprotein] and D(b)PA(224) (H2D(b)+PA(224-233)) epitope abundance after direct infection in vitro and induced reproducible changes in the magnitude of the D(b)NP(366)- and D(b)PA(224)-specific T cell subsets generated after infection of mice. Comparison of D(b)NP(366)- and D(b) PA(224)-specific CD8(+) T cell responses induced from the native configuration and from the viral neuraminidase stalk demonstrated that the size of both primary and secondary responses is influenced by relative epitope levels and that, at least after secondary challenge, the magnitude of responses is also determined by CD8(+) T cell precursor frequency. Thus, this immunodominance hierarchy is a direct function of antigen dose and T cell numbers.
HyperCubeMap (2015)

Advertising activity on SNS has grown rapidly and is now a billion dollar business. In the SNS advertising model, the SNS serves as the advertising agent, and takes the advantage of network diffusion to attract advertisers and charges for the cascading impressions. The optimal ad allocation task is to choose the ad allocation plan that maximizes the revenue. Each user has different diffusion ability, limited daily impressions and the advertisers have various bidding prices and budget concerns. A feasible plan that obeys the constraints is difficult to find. The solution of this problem lies in the space of N |Ads|× |user|, which makes direct optimization unattractive. In this paper, we study SNS advertising business models, formulate the SNS ad allocation problem and show their connections with hyperbolic embedding. We develop a new embedding algorithm Hyper Cube Map that allows for dimension reduction. Our proposed method reduces the dimensionality of the original problem significantly, runs two to four orders of magnitude faster, and reaches 95% of the optimum.
Quantitative time-course metabolomics in human red blood cells reveal the temperature dependence of human metabolic networks (2017)

The temperature dependence of biological processes has been studied at the levels of individual biochemical reactions and organism physiology (<i>e.g.</i> basal metabolic rates) but has not been examined at the metabolic network level. Here, we used a systems biology approach to characterize the temperature dependence of the human red blood cell (RBC) metabolic network between 4 and 37 °C through absolutely quantified exo- and endometabolomics data. We used an Arrhenius-type model (<i>Q</i><sub>10</sub>) to describe how the rate of a biochemical process changes with every 10 °C change in temperature. Multivariate statistical analysis of the metabolomics data revealed that the same metabolic network-level trends previously reported for RBCs at 4 °C were conserved but accelerated with increasing temperature. We calculated a median <i>Q</i><sub>10</sub> coefficient of 2.89 ± 1.03, within the expected range of 2-3 for biological processes, for 48 individual metabolite concentrations. We then integrated these metabolomics measurements into a cell-scale metabolic model to study pathway usage, calculating a median <i>Q</i><sub>10</sub> coefficient of 2.73 ± 0.75 for 35 reaction fluxes. The relative fluxes through glycolysis and nucleotide metabolism pathways were consistent across the studied temperature range despite the non-uniform distributions of <i>Q</i><sub>10</sub> coefficients of individual metabolites and reaction fluxes. Together, these results indicate that the rate of change of network-level responses to temperature differences in RBC metabolism is consistent between 4 and 37 °C. More broadly, we provide a baseline characterization of a biochemical network given no transcriptional or translational regulation that can be used to explore the temperature dependence of metabolism.