gebhart/patrepeval huggingface dataset:
Modulation of airway inflammation and resistance in mice by a nicotinic receptor agonist (2005)

Nicotinic agonists, including 1,1-dimethyl-4-phenylpiperazinium (DMPP), have anti-inflammatory properties and in some instances smooth muscle relaxing effects. Since inflammation and airway smooth muscle contraction are two major components of asthma, the present authors investigated the effects of DMPP on airway inflammation and airway resistance in a mouse model of asthma. Mice were sensitised and challenged with ovalbumin (OVA) and treated either intraperitoneally or intranasally with DMPP. The effect of DMPP was tested on airway inflammation, airway resistance and on the increase of intracellular calcium in bronchial smooth muscle cells. DMPP given either during sensitisation, OVA challenges or throughout the protocol prevented lung inflammation and decreased the serum level of OVA specific immunoglobulin E. DMPP administration reduced the number of total cells, lymphocytes and eosinophils in the bronchoalveolar lavage (BAL) fluid. Intranasal DMPP administration was as effective as dexamethasone (DEXA) in reducing total cell count and eosinophil counts in BAL fluid. DMPP, but not DEXA, reduced tissue inflammation. Intranasal DMPP, given 10 min before the test, reduced airway responsiveness to metacholine. DMPP also reduced the increase in intracellular calcium in response to bradykinin. In conclusion, these results show that 1,1-dimethyl-4-phenylpiperazinium reduces lung inflammation and prevents airway hyperresponsiveness in the mouse model of asthma.
Feature Isolation for Hypothesis Testing in Retinal Imaging: An Ischemic Stroke Prediction Case Study (2019)

Ischemic stroke is a leading cause of death and long-term disability that is difficult to predict reliably. Retinal fundus photography has been proposed for stroke risk assessment, due to its non-invasiveness and the similarity between retinal and cerebral microcirculations, with past studies claiming a correlation between venular caliber and stroke risk. However, it may be that other retinal features are more appropriate. In this paper, extensive experiments with deep learning on six retinal datasets are described. Feature isolation involving segmented vascular tree images is applied to establish the effectiveness of vessel caliber and shape alone for stroke classification, and dataset ablation is applied to investigate model generalizability on unseen sources. The results suggest that vessel caliber and shape could be indicative of ischemic stroke, and sourcespecific features could influence model performance.
FAUST: A framework for algorithm understanding and sonification testing (1997)

Presented at the 4th International Conference on Auditory Display (ICAD), Palo Alto, California, November 2-5, 1997.
DC-40 GHz amplifier for high-speed optical communications designed with the real frequency technique (2004)

Synchronous optical network (SONET/SDH) requirements for 40 Gbps links impose transmitter drivers to provide a high and linear voltage swing to the modulator from a few kilohertz to 40 GHz. This paper presents a two stage DC-40 GHz GaAs P-HEMT amplifier including a level shift part for DC-coupling. The design synthesis method uses the real frequency technique.
Global internet roaming with ROAMIP (2000)

Reachability and session continuity represent two distinct services that global mobility protocols should provide. Reachability is the possibility for Internet hosts to initiate sessions to mobile users. Session continuity refers to mechanisms that ensure that active transport or application layer sessions are not broken due to mobility. We present ROAMIP, a global mobility architecture that uses application layer solutions for global reachability and reuses transparent Mobile IP tunnelling mechanisms to ensure session continuity. ROAMIP eliminates long triangular routes, yet it is compatible with mobility unaware correspondent hosts. It is applicable to IPv6 as well as IPv4 networks. The ROAMIP architecture naturally lends itself to easy, gradual deployment and can reuse existing Mobile IP or SIP message formats. We conclude the paper by showing example traces from an experimental implementation.
High performance SiC MOSFET module for industrial applications (2016)

A novel 1.7kV, 500A low inductance half-bridge module has been developed for fast-switching SiC devices. The module has a maximum temperature rating of 175°C. There are 12 GE SiC MOSFET chips per switch and the MOSFET's body diode is utilized as the freewheeling diode. The module's typical on-resistance is 3.8mOhms at 25°C and 5.8mOhms at 175°C. Internal loop inductance measured from DC input terminals is 4.5nH, approximately 75% lower than that of a standard IGBT module. When connected to a low inductance busbars, the module can be switched in 50ns without excessive voltage and current overshoots. Double pulse inductive switching losses at VDS=1000V, Id=450A and TJ=150°C are: EON=21.5mJ, EOFF=16.5mJ and EREC=6mJ. The losses are at least ten times lower when compared to a similarly rated IGBT module, highlighting the SiC advantage for higher switching frequency applications. Short circuit testing was performed, demonstrating good ruggedness albeit the need for a fast protection circuit.
Performance of hollow concrete block masonry walls retrofitted with steel‐fiber and microsilica admixed plaster (2018)

The weakness of existing unreinforced masonry (URM) wall buildings in resisting lateral loads is a matter of concern, especially in locations exposed to seismic hazards. In order to address this shortcoming, considerable research effort has been dedicated in the last few years on the strengthening techniques of existing URM structures. This paper presents the test results of four hollow concrete block walls, one as control, one using high steel‐fiber reinforced mortar admixed with microsilica (SFR‐MS) mortar in joints and the other two walls plastered with 10 mm thick SFR‐MS mortar on one and both sides of the wall, respectively. The shear capacity, stiffness, cracking patterns and failure modes of the walls were investigated. In addition, a nonlinear finite element simulation of the walls in an ABAQUS environment is presented and results compared with those obtained from the experimental investigations conducted. Modified analytical equations for predicting the shear capacity of masonry walls with plaster is proposed and results compared with the experimental and finite element simulation results of the investigated walls.
Characterizing and Supporting Question Answering in Human-to-Human Communication (2018)

Email continues to be one of the most important means of online communication. People spend a significant amount of time sending, reading, searching and responding to email in order to manage tasks, exchange information, etc. In this paper, we focus on information exchange over enterprise email in the form of questions and answers. We study a large scale publicly available email dataset to characterize information exchange via questions and answers in enterprise email. We augment our analysis with a survey to gain insights on the types of questions exchanged, when and how do people get back to them and whether this behavior is adequately supported by existing email management and search functionality. We leverage this understanding to define the task of extracting question/answer pairs from threaded email conversations. We propose a neural network based approach that matches the question to the answer considering comparisons at different levels of granularity. We also show that we can improve the performance by leveraging external data of question and answer pairs. We test our approach using a manually labeled email data collected using a crowd-sourcing annotation study. Our findings have implications for designing email clients and intelligent agents that support question answering and information lookup in email.
OMA standalone: orthology inference among public and custom genomes and transcriptomes (2019)

Genomes and transcriptomes are now typically sequenced by individual laboratories but analyzing them often remains challenging. One essential step in many analyses lies in identifying orthologs-corresponding genes across multiple species-but this is far from trivial. The Orthologous MAtrix (OMA) database is a leading resource for identifying orthologs among publicly available, complete genomes. Here, we describe the OMA pipeline available as a standalone program for Linux and Mac. When run on a cluster, it has native support for the LSF, SGE, PBS Pro, and Slurm job schedulers and can scale up to thousands of parallel processes. Another key feature of OMA standalone is that users can combine their own data with existing public data by exporting genomes and precomputed alignments from the OMA database, which currently contains over 2100 complete genomes. We compare OMA standalone to other methods in the context of phylogenetic tree inference, by inferring a phylogeny of Lophotrochozoa, a challenging clade within the protostomes. We also discuss other potential applications of OMA standalone, including identifying gene families having undergone duplications/losses in specific clades, and identifying potential drug targets in nonmodel organisms. OMA standalone is available under the permissive open source Mozilla Public License Version 2.0.
Protein drug target activation homogeneity in the face of intra-tumor heterogeneity: implications for precision medicine (2016)

Protein pathway activation mapping of enriched tumor cells obtained from different regions of the same tumor indicated consistency and robustness independent of the region sampled. This suggests a dominant protein pathway network may be activated in a high percentage of the tumor cell population. Given the genomic intra-tumoral variability, our data suggest that protein/phosphoprotein signaling measurements should be integrated with genomic analysis for precision medicine based analysis.
Adoptive Transfer of Colon Cancer Derived Peptide-specific CD8+T Cells in HHD Mice (2004)

Background: 1-8D gene is a member of human 1-8 interferon inducible gene family and is shown to be overexpressed in fresh colon cancer tissues. Three peptides 1-6, 3-5 and 3-7 derived from 1-8D gene were shown to have immunogenicity against colon cancer. Methods: To study tumor immunotherapy of these peptides we established an adoptive transfer model. microglobulin () null mice transgenic for a chimeric HLA-A2.1/ single chain (HHD mice) were immunized with irradiated peptide-loaded RMA-S/HHD/B7.1 transfectants. Spleens were removed after last immunization, and splenocytes were re-stimulated in vitro. Lymphocytes from vaccinated HHD mice were transferred together with IL-2 to the tumor bearing nude mice that were challenged S.C. with the HCT/HHD/B7 colon carcinoma cell line that was found to grow in these mice. Results: Peptide 3-5 was found to be highly effective in CTL activity. Adoptively transferred anti-peptide 3-5 cytolytic T lymphocytes caused significant retardation in tumor growth. Conclusion: This study shows that peptide 3-5 can be the most effective candidate for the vaccine of adoptive immunotherapy against colon cancer.
Microbubble ultrasound super-localization imaging (MUSLI) (2011)

When distinct sources are generated in a region of interest, their location can be mapped with a resolution beyond the diffraction limit. Such distinct sources can be generated during ultrafast imaging of clouds of clinical contrast agents at the appropriate acoustic pressures. This paper describes experiments on the resolution limit, in-vitro localization of microbubbles and the demonstration that ultrafast events are present in-vivo. Mapping distinct events could yield images of vasculature at the micrometer scale.
Identification of Nitric Oxide Donors by Biomimetic HTS Application (2005)

Metalloporphyrin catalyzed biomimetic oxidation was used for the identification of nitric oxide (NO) donors with diverse chemical structure. Methodology was validated by testing known NO donors. Efficient automation of the test allowed us to investigate a subset of our corporate library. Several hits identified in this campaign were validated in both the chemical and also microsomal model that revealed all hits to be active in the biological system, as well. One of the hits showed comparable activity to V-PYRRO/NO, the prototypic liver selective NO donor.
Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation (2022)

Federated learning (FL) is a distributed machine learning technique that enables collaborative model training while avoiding explicit data sharing. The inherent privacy-preserving property of FL algorithms makes them especially attractive to the medical field. However, in case of heterogeneous client data distributions, standard FL methods are unstable and require intensive hyperparameter tuning to achieve optimal performance. Conventional hyperparameter optimization algorithms are impractical in real-world FL applications as they involve numerous training trials, which are often not affordable with limited compute budgets. In this work, we propose an efficient reinforcement learning (RL)-based federated hyperparameter optimization algorithm, termed Auto-FedRL, in which an online RL agent can dynamically adjust hyperparameters of each client based on the current training progress. Extensive experiments are conducted to investigate different search strategies and RL agents. The effectiveness of the proposed method is validated on a heterogeneous data split of the CIFAR-10 dataset as well as two real-world medical image segmentation datasets for COVID-19 lesion segmentation in chest CT and pancreas segmentation in abdominal CT.
Study into a Small-Scale Water-Driven Domestic Heat Pump: Design and Performance Analysis (1996)

A heal pump of domestic capacity and applicable for a water-powered system is studied. A design of the necessary parts is carried out, and realization of the heat pump system is achieved. In realization of the system, output power of a small-scale water turbine is considered, and an electrical motor requiring similar power is employed. The estimation of capital cost and payback period is not included in the study.
Osteoarthritic Knee Brace: A Multiple Brace Analysis In Vivo Three-Dimensional Determination of the Effectiveness of the (2005)

This information is current as of December 15, 2005 Reprints and Permissions Permissions] link. article, or locate the article citation on jbjs.org and click on the [Reprints andClick here to order reprints or request permission to use material from thisPublisher Information www.jbjs.org 20 Pickering Street, Needham, MA 02492-3157The Journal of Bone and Joint SurgeryDownloaded from www.ejbjs.org
Time-gated luminescence imaging for background free in vivo tracking of single circulating tumor cells (2020)

Fluorescence imaging is severely limited by the background and autofluorescence of tissues for in vivo detection of circulating tumor cells (CTCs). Time-gated luminescence (TGL) imaging, in combination with luminescent probes that possess hundreds of microsecond emission lifetimes, can be used to effectively suppress this background, which has predominantly nanosecond lifetimes. This Letter demonstrates the feasibility of TGL imaging using luminescent probes for the in vivo real time imaging and tracking of single CTCs circulating freely in the blood vessels with higher accuracy given by substantially higher signal-to-noise ratio. The luminescent probe used in this Letter was a commercial <i>E</i><i>u</i><sup>3+</sup> chelate (EuC) nanosphere with a super-long lifetime of near 800 µs, which enabled TGL imaging to achieve background-free detection with ∼5 times higher SNR versus steady state. Phantom and in vivo mouse studies indicated that EuC labeled tumor cells moving in medium or bloodstream at the speed of 1-2 mm/s could be captured in real time.
Reconstruction from truncated projections in cone-beam CT using an efficient 1D filtering (2013)

In X-ray imaging, a reduction of the field of view (FOV) is proportional to a reduction in radiation dose. The resulting truncation, however, is incompatible with conventional tomographic reconstruction algorithms. This problem has been studied extensively. Very recently, a novel method for region of interest (ROI) reconstruction from truncated projections with neither the use of prior knowledge nor explicit extrapolation has been published, named Approximated Truncation Robust Algorithm for Computed Tomography (ATRACT). It is based on a decomposition of the standard ramp filter into a 2D Laplace filtering (local operation) and a 2D Radon-based filtering step (non-local operation). The 2D Radon-based filtering that involves many interpolations complicates the filtering procedure in ATRACT, which essentially limits its practicality. In this paper, an optimization for this shortcoming is presented. That is to apply ATRACT in one dimension, which implies that we decompose the standard ramp filter into the 1D Laplace filter and a 1D convolutionbased filter. The convolution kernel was determined numerically by computing the 1D impulse response of the standard ramp filtering coupled with the second order anti-derivative operation. The proposed algorithm was evaluated by using a reconstruction benchmark test, a real phantom and a clinical data set in terms of spatial resolution, computational efficiency as well as robustness of correction quality. The evaluation outcomes were encouraging. The proposed algorithm showed improvement in computational performance with respect to the 2D ATRACT algorithm and furthermore maintained reconstructions of high accuracy in presence of data truncation.
TTY phone (2008)

Seeking to enable direct and equal access for the Deaf to emergency call centers, we analyze the current state of the emergency phone system in the United States and elsewhere in the world. Leveraging teletypewriter (TTY) technology mandated by the Americans with Disabilities Act of 1990 to be installed in all emergency call centers in the United States, we developed software that emulates a TTY on a smart phone. We present an Instant Messaging style interface for mobile phones that uses the existing emergency infrastructure and allows Deaf users to communicate directly with emergency operators.
Proteasomal complex regulation by heat‐shock proteins in cancer (2013)

Proteasome mediated protein degradation is a major component of the cellular machinery that maintains the protein homeostasis. The disruption of the proteasomal function induces proteotoxic stress and activates the cellular heat shock response. There are two distinct proteasomal degradation pathways, the ubiquitin dependent proteasome pathway mediated by the 26S proteasomes and the ‐ubiquitin independent proteasomal degradation pathway mediated by the 20S proteasome. The cross talk between the chaperone and ubiquitin system has been highly explored and characterized, however little is known on the direct regulation of heat shock proteins on proteasomal integrity and function in mammalian cells. In this work we try to set the framework to examine the regulatory roles that Hsps might have in regulating proteasomal complex function and integrity. By using high throughput protein‐protein interaction assays and masspectrometry we examine the association of cellular proteins specifically chaperones to the proteasomal machinery following proteotoxic stresses. Our work examines the regulatory role of Hsps in maintaining protein homeostasis by directly regulating the proteasomal complex function and how this interplay contributes to cancer cell proliferation.
A comparative evaluation of supervised and unsupervised representation learning approaches for anaplastic medulloblastoma differentiation (2015)

Learning data representations directly from the data itself is an approach that has shown great success in different pattern recognition problems, outperforming state-of-the-art feature extraction schemes for different tasks in computer vision, speech recognition and natural language processing. Representation learning applies unsupervised and supervised machine learning methods to large amounts of data to find building-blocks that better represent the information in it. Digitized histopathology images represents a very good testbed for representation learning since it involves large amounts of high complex, visual data. This paper presents a comparative evaluation of different supervised and unsupervised representation learning architectures to specifically address open questions on what type of learning architectures (deep or shallow), type of learning (unsupervised or supervised) is optimal. In this paper we limit ourselves to addressing these questions in the context of distinguishing between anaplastic and non-anaplastic medulloblastomas from routine haematoxylin and eosin stained images. The unsupervised approaches evaluated were sparse autoencoders and topographic reconstruct independent component analysis, and the supervised approach was convolutional neural networks. Experimental results show that shallow architectures with more neurons are better than deeper architectures without taking into account local space invariances and that topographic constraints provide useful invariant features in scale and rotations for efficient tumor differentiation.
Dynamic wettability of polyethylene glycol-modified poly(dimethylsiloxane) surfaces in an aqueous/organic two-phase system (2017)

We herein report the preparation of a surface that behaves in a hydrophobic manner but does not undergo protein adsorption in an aqueous/organic two-phase system. We found that polyethylene-glycol (PEG)-modified poly(dimethylsiloxane) (PDMS) exhibits hydrophobic properties when the surface is immersed in an organic solution, while the PEG moiety prevents protein adsorption on the PDMS surface in an aqueous solution at high protein concentrations due to the dynamic behaviour of the PEG moiety. As such, we demonstrated the in-well droplet formation of an aqueous solution containing a high protein concentration. In addition, to demonstrate the feasibility of this method in single cell analyses, a droplet array of a liquid medium containing 10% fetal bovine serum and HeLa cells was formed. The preparation of a droplet array using our PDMS-PEG surface to promote in-well droplet formation avoided the use of flow control equipment and complicated microstructures. We therefore expect that the dynamic wettability of our reported surface will be applicable in single cell and biochemical analyses, such as protein characterisation using crystallography or immunoassays.