gebhart/patrepeval huggingface dataset:
Cauda Equina Repair in the Rat: Part 1. Stimulus-Evoked EMG for Identifying Spinal Nerves Innervating Intrinsic Tail Muscles (2009)

Cauda equina injuries may produce severe leg and pelvic floor dysfunction, for which no effective treatments exist. We are developing a rat cauda equina injury model to allow nerve root identification and surgical repair. One possible difficulty in implementing any repair strategy after trauma in humans involves the correct identification of proximal and distal ends of nerve roots separated by the injury. Two series of studies were carried out. In Series 1, we electrically stimulated segmental contributors to the dorsal and ventral caudales nerves in order to characterize the recruitment patterns of muscles controlling rat tail movements. In Series 2, we attempted to identify individual nerve roots forming the cauda equina by both level of origin and function (i.e., dorsal or ventral), based solely upon the recruitment patterns in response to electrical stimulation. For Series 1 studies, electrical stimulation of the segmental contributors showed that all nerve roots-from the sixth lumbar to the first coccygeal-contributed to recruitment of muscles found at the base of the tail. Intrinsic tail muscles lying more distally in the tail showed a more root-specific pattern of innervation. For Series 2, the rate of successful identification of an unknown nerve root as being ventral was very high (>95%), and only somewhat lower (approximately 80%) for dorsal roots. Correctly identifying the level of origin of that root was more difficult, but for ventral roots this rate still exceeded 90%. Using the rat cauda equina model, we have shown that stimulus-evoked EMG can be used to identify ventral nerve roots innervating tail muscles with a high degree of accuracy. These findings support the feasibility of using this conceptual approach for identifying and repairing damaged human cauda equina nerve roots based on stimulus-evoked recruitment of muscles in the leg and pelvic floor.
Autonomous retrosynthesis of nanoscale structures via spectral shape matching (2022)

Synthesizing complex nanostructures and assemblies in experiments involves careful tuning of design factors to obtain a suitable set of reaction conditions. In this paper, we study the application of Bayesian optimization (BO) to achieve autonomous retrosynthesis of a specific nanoparticle or nano-assembly structure, shape, and size starting from a set of reagents selected a priori. We formulate the BO as a shape matching problem given target spectra as a structural proxy with a goal to minimize the shape discrepancy. The proposed framework is grounded in analyzing the spectra as belonging to function spaces and a Riemannian metric defined on them. The metric decomposes spectral similarity into amplitude and phase components and provides a near convex function to optimize as opposed to nearly flat functions produced from the commonly used mean squared error (MSE). Applying the framework to both experimental and simulated spectra, we demonstrate the advantage of shape matching over MSE and other generic functional distance measures.
Serial Systemic Injections of Endotoxin (LPS) Elicit Neuroprotective Spinal Cord Microglia through IL-1-Dependent Cross Talk with Endothelial Cells (2020)

Microglia are dynamic immunosurveillance cells in the CNS. Whether microglia are protective or pathologic is context dependent; the outcome varies as a function of time relative to the stimulus, activation state of neighboring cells in the microenvironment or within progression of a particular disease. Although brain microglia can be "primed" using bacterial lipopolysaccharide (LPS)/endotoxin, it is unknown whether LPS delivered systemically can also induce neuroprotective microglia in the spinal cord. Here, we show that serial systemic injections of LPS (1 mg/kg, i.p., daily) for 4 consecutive days (LPSx4) consistently elicit a reactive spinal cord microglia response marked by dramatic morphologic changes, increased production of IL-1, and enhanced proliferation without triggering leukocyte recruitment or overt neuropathology. Following LPSx4, reactive microglia frequently contact spinal cord endothelial cells. Targeted ablation or selective expression of IL-1 and IL-1 receptor (IL-1R) in either microglia or endothelia reveal that IL-1-dependent signaling between these cells mediates microglia activation. Using a mouse model of ischemic spinal cord injury in male and female mice, we show that preoperative LPSx4 provides complete protection from ischemia-induced neuron loss and hindlimb paralysis. Neuroprotection is partly reversed by either pharmacological elimination of microglia or selective removal of IL-1R in microglia or endothelia. These data indicate that spinal cord microglia are amenable to therapeutic reprogramming via systemic manipulation and that this potential can be harnessed to protect the spinal cord from injury.<b>SIGNIFICANCE STATEMENT</b> Data in this report indicate that a neuroprotective spinal cord microglia response can be triggered by daily systemic injections of LPS over a period of 4 d (LPSx4). The LPSx4 regimen induces morphologic transformation and enhances proliferation of spinal cord microglia without causing neuropathology. Using advanced transgenic mouse technology, we show that IL-1-dependent microglia-endothelia cross talk is necessary for eliciting this spinal cord microglia phenotype and also for conferring optimal protection to spinal motor neurons from ischemic spinal cord injury (ISCI). Collectively, these novel data show that it is possible to consistently elicit spinal cord microglia via systemic delivery of inflammogens to achieve a therapeutically effective neuroprotective response against ISCI.
SNR analysis of crosstalk and filtering effects in an amplified multichannel direct-detection dense-WDM system (1992)

An SNR analysis is presented for multichannel dense-WDM (wavelength-division-multiplexed) networks using optical amplifiers and optical filters. By using Lorentzian approximations for the amplified spontaneous emission and the optical and electrical bandwidths, simple expressions are derived for the relevant noise sources and crosstalk and filtering effects. Guidelines are stated for choosing appropriate optical filter widths and channel spacings to reduce power penalties. For any experimental system easily measurable quantities can be inserted into the analytical solutions to obtain close approximations for minimizing SNR degradation due to filtering and crosstalk.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>
Chemically Polished Quartz (1977)

Abstract : Etching in a saturated solution of ammonium bifluoride is shown to be capable of producing chemically polished AT-cut quartz surfaces over a broad range of conditions. The quality of chemical polish depends primarily on the surface finish prior to etching, the depth of etch and the quality of quartz used. The speed of polishing depends primarily on the temperature of the etching bath. In an 88 degree C etching bath, starting with 3 micrometers lapped blanks, chemically polished blanks with a surface roughness of 0.1 micrometer and a roughness angle of 1 degree can be produced in 15 minutes. Starting with a finer surface finish can produce a smoother chemically polished surface. Chemically polished blanks are shown to be extremely strong. Fundamental mode 20 MHz resonators made with chemically polished natural quartz blanks showed no Q degradation with increasing depth of etch.
Faculty Opinions recommendation of ssHMM: extracting intuitive sequence-structure motifs from high-throughput RNA-binding protein data. (2017)

) play an important role in RNA post-transcriptional regulation and recognize target RNAs via sequence-structure motifs. The extent to which RNA structure influences protein binding in the presence or absence of a sequence motif is still poorly understood. Existing RNA motif finders either take the structure of the RNA only partially into account, or employ models which are not directly interpretable as sequence-structure motifs. We developed ssHMM, an RNA motif finder based on a hidden Markov model (HMM) and Gibbs sampling which fully captures the relationship between RNA sequence and secondary structure preference of a given RBP. Compared to previous methods which output separate logos for sequence and structure, it directly produces a combined sequence-structure motif when trained on a large set of sequences. ssHMM's model is visualized intuitively as a graph and facilitates biological interpretation. ssHMM can be used to find novel bona fide sequence-structure motifs of uncharacterized RBPs, such as the one presented here for the YY1 protein. ssHMM reaches a high motif recovery rate on synthetic data, it recovers known RBP motifs from CLIP-Seq data, and scales linearly on the input size, being considerably faster than MEMERIS and RNAcontext on large datasets while being on par with GraphProt. It is freely available on Github and as a Docker image.
Formation of alkylsiloxane self-assembled monolayers on Si3N4 (1999)

The structure of alkylsiloxane self-assembled monolayers formed on HF-treated Si3N4 has been studied using x-ray photoelectron spectroscopy, high-resolution electron energy-loss spectroscopy, and contact angle analysis. It is shown that the monolayers are similar in quality to those formed on oxidized silicon, despite the fact that upon etching in HF, the Si3N4 surface contains only 0.2 ML of oxygen. In contrast, on NH4F-treated Si(100) surfaces with similar quantities of oxygen, high-quality monolayers cannot be formed. We argue that these results point to the importance of a water layer in monolayer formation.
Allergy medical care network: A new model of care for specialties (2014)

In 2005 the Althaia Foundation Allergy Department performed its daily activity in the Hospital Sant Joan de Deu of Manresa. Given the increasing demand for allergy care, the department's performance was analysed and a strategic plan (SP) for 2005–2010 was designed. The main objective of the study was to assess the impact of the application of the SP on the department's operations and organisational level in terms of profitability, productivity and quality of care. Descriptive, retrospective study which evaluated the operation of the allergy department. The baseline situation was analysed and the SP was designed. Indicators were set to perform a comparative analysis after application of the SP. The indicators showed an increase in medical care activity (first visits, 34%; successive visits, 29%; day hospital treatments, 51%), high rates of resolution, reduced waiting lists. Economic analysis indicated an increase in direct costs justified by increased activity and territory attended. Cost optimisation was explained by improved patient accessibility, minimised absenteeism in the workplace and improved cost per visit. After application of the SP a networking system was established for the allergy speciality that has expanded the territory for which it provides care, increased total activity and the ability to resolve patients, optimised human resources, improved quality of care and streamlined medical costs.
Sigma-delta modulation based wafer-level testing for TFT-LCD source driver ICs (2011)

Output variation testing of TFT-LCD source driver ICs is very expensive and time-consuming due to the large amount of analog output channels and levels to measure. This paper presents a low-cost on-scribe-line BIST technique for wafer-level source driver IC testing. Based on the BIST structure and the sigma-delta modulation principle, we propose a two-stage test flow and construct a generalized test cost function to find the optimal test setup parameters.
Evolution of the Composition of a Selected Bitter Camembert Cheese during Ripening:  Release and Migration of Taste-Active Compounds (2001)

The aim of this study was to add to the understanding of changes in taste that occur during the ripening of a bitter Camembert cheese by the evolution of its composition. Physicochemical analyses were performed on rind, under-rind, and center portions of a Camembert cheese selected for its intense bitterness. At each of the six steps of ripening studied organic acids, sugars, total nitrogen, soluble nitrogen, phosphotungstic acid soluble nitrogen, non-protein nitrogen, Na, K, Ca, Mg, Pi, Cl, and biogenic amines were quantified in each portion. Changes in cheese composition seemed to mainly result from the development of Penicillium camemberti on the cheese outer layer. Migration phenomena and the release of potentially taste-active compounds allowed for the evolution of saltiness, sourness, and bitterness throughout ripening to be better understood. Apart from taste-active compounds, the impact of the cheese matrix on its taste development is discussed.
Silicon-on-insulator electro-optically tunable waveguide-coupled microdisk resonators with selectively integrated p-i-n diodes (2005)

We report silicon-on-insulator electro-optically tunable microdisk resonators with selectively integrated p-i-n diodes. Using free-carrier plasma dispersion effect, we show that the whispering-gallery modes can be blueshifted by 0.4 nm upon I-V forward bias.
Expression of Angiogenic and Vasculogenic Factors in Human Lymphedematous Tissue (2011)

Lymphedematous tissue does not exhibit upregulation of angiogenesis or vasculogenesis. Neovascularization is unlikely to be involved in the pathogenesis of this disease.
The effects of high concentration tooth whitening bleaches on microleakage of Class V composite restorations. (2008)

Bleaching with the materials tested had no influence on microleakage of Filtek Z250 composite bonded with Scotchbond 1.
Application of a distributed data mining approach to network intrusion detection (2002)

In very many situations the collection of data from distributed hosts for its subsequent use to generate an intrusion detection profile may not be technically feasible (e.g., due to data size or network security transfer protocols). This situation is especially evident for data intensive intrusion profile generation (e.g., inducing profiles via data mining techniques). An alternative solution is to build a network profile by applying distributed data analysis methods (e.g., agent based computing). Such an approach is described in this paper. Global profiles are built using a Distributed Data Mining approach that integrates inductive generalization and Agent based computing. In this approach, classification rules are learned via tree induction from distributed data to be used as intrusion profiles. Agents, in a collaborative fashion, generate partial trees and communicate the temporary results among them in the form of indices to the data records. The process is terminated when a final tree is induced. This communication mechanism does not involve any data transfers, and in addition, a compression approach is used to reduce the communication bandwidth of data index transfers.
Indecisive Classifier (2005)

Nearest neighbor classification expects the class conditional probabilities to be locally constant. The assumption becomes invalid in high dimension due to the curse-of-dimensionality. Severe bias can be introduced under this condition when using nearest neighbor rule. We propose an adaptive nearest neighbor classification method "indecisive classifier" to minimize bias and variance by avoiding decision making in some hard-decision region. As a result, better classification performance can be expected in some scenario such as video based face recognition.
Implementation of personalized situation-aware service (2005)

New service concepts of sharing contexts with support for communication on wireless networks are beginning to emerge for mobile devices with diverse embedded sensors. In order to promote services based on sharing contexts in mobile devices, this paper introduces the MoCE (Mobile Context Explorer) architecture. MoCE was designed to support context-based services with context sharing on wireless networks in UTOPIA (Ubiquitous computing TOwn Project: Intelligent context Awareness). The major purpose of this research is to provide a situation-aware environment, known as U-Town, by using sensors and mobile devices currently available to the public. The paper next introduces U-Theme Park service, which is one service in the U-Town environment. U-Theme Park uses MoCE to realize a personalized environment from various sensors.
Oxidative Gold Catalysis Meets Photochemistry – Synthesis of Benzo[a]fluorenones from Diynes (2014)

Abstract Diynes bearing one terminal and one triarylmethyl‐substituted alkyne were converted into complex benzofluorenone derivatives via a one‐pot process involving a gold‐catalyzed step followed by a photocyclization/oxidation. In the first step an N ‐oxide was used to position‐selectively generate an α‐oxo carbenoid at the terminal alkyne which after a regioselective 1,6‐carbene transfer along the tethered tritylalkyne and a subsequent aryl 1,2‐shift furnished tetraphenylethylene‐like derivatives. These intermediates were successfully transformed to fluorenones via oxidative photocyclization. magnified image
Design of Giant Magnetostrictive Actuator for fuel injector (2008)

This paper presents a basic research on giant magnetostrictive actuator (GMA) for fuel injector. An injector is a pilot operational valve with position servomechanism, which enables to control injection rate freely with input current into the actuator. Based on the combination of finite element analysis and experiment, a prototype of GMA is successfully made as well as the test platform. The injector is actuated by a GMA which outputs displacement of 38.3 mum within 0.03s. The result shows that the analysis of finite element computation meets well with the experimental research. It has a significant guidance meaning for the design and application of GMA based on giant magnetostrictive material (GMM). And this actuator can be also used for active vibration reduction.
Multiple Reaction Monitoring-Ion Pair Finder: A Systematic Approach To Transform Nontargeted Mode to Pseudotargeted Mode for Metabolomics Study Based on Liquid Chromatography–Mass Spectrometry (2015)

Pseudotargeted metabolic profiling is a novel strategy combining the advantages of both targeted and untargeted methods. The strategy obtains metabolites and their product ions from quadrupole time-of-flight (Q-TOF) MS by information-dependent acquisition (IDA) and then picks targeted ion pairs and measures them on a triple-quadrupole MS by multiple reaction monitoring (MRM). The picking of ion pairs from thousands of candidates is the most time-consuming step of the pseudotargeted strategy. Herein, a systematic and automated approach and software (MRM-Ion Pair Finder) were developed to acquire characteristic MRM ion pairs by precursor ions alignment, MS(2) spectrum extraction and reduction, characteristic product ion selection, and ion fusion. To test the reliability of the approach, a mixture of 15 metabolite standards was first analyzed; the representative ion pairs were correctly picked out. Then, pooled serum samples were further studied, and the results were confirmed by the manual selection. Finally, a comparison with a commercial peak alignment software was performed, and a good characteristic ion coverage of metabolites was obtained. As a proof of concept, the proposed approach was applied to a metabolomics study of liver cancer; 854 metabolite ion pairs were defined in the positive ion mode from serum. Our approach provides a high throughput method which is reliable to acquire MRM ion pairs for pseudotargeted metabolomics with improved metabolite coverage and facilitate more reliable biomarkers discoveries.
A novel diffusion tensor imaging-based computer-aided diagnostic system for early diagnosis of autism. (2014)

Autism spectrum disorders (ASDs) denote a significant growing public health concern. Currently, one in 68 children has been diagnosed with ASDs in the United States, and most children are diagnosed after the age of four, despite the fact that ASDs can be identified as early as age two. The ultimate goal of this thesis is to develop a computer-aided diagnosis (CAD) system for the accurate and early diagnosis of ASDs using diffusion tensor imaging (DTI). This CAD system consists of three main steps. First, the brain tissues are segmented based on three image descriptors: a visual appearance model that has the ability to model a large dimensional feature space, a shape model that is adapted during the segmentation process using first- and second-order visual appearance features, and a spatially invariant second-order homogeneity descriptor. Secondly, discriminatory features are extracted from the segmented brains. Cortex shape variability is assessed using shape construction methods, and white matter integrity is further examined through connectivity analysis. Finally, the diagnostic capabilities of these extracted features are investigated. The accuracy of the presented CAD system has been tested on 25 infants with a high risk of developing ASDs. The preliminary diagnostic results are promising in identifying autistic from control patients.
Power Grid Security Improvement by Remedial Action Schemes Using Vulnerability Assessment Based on Fault Chains and Power Flow (2018)

The risk of large-scale blackouts and cascading failures in power grids can be due to vulnerable transmission lines and lack of proper remediation techniques after recognizing the first failure. In this paper, we assess the vulnerability of a system using fault chain theory and a power flow-based method, and calculate the probability of large-scale blackout. Further, we consider a Remedial Action Scheme (RAS) to reduce the vulnerability of the system and to harden the critical components against intentional attacks. To identify the most critical lines more efficiently, a new vulnerability index is presented. The effectiveness of the new index and the impact of the applied RAS is illustrated on the IEEE 14-bus test system.
Study of mercury(II) binding to thiol-modified ordered mesoporous silicas by analytical and electrochemical analyses: influence of the pore structure and the functionalization process (2006)

Congrès du 05 au 07 août 2006
Superior Mechanical Properties of Nanostructured Light Metallic Materials and Their Innovation Potential (2015)

This chapter reviews the recent advances in the area of severe plastic deformation (SPD)-processed nanostructured (NS) light metals and alloys, and highlights the modern trends in research. The SPD techniques developed for grain refinement in metals have attracted great attention due to their ability to produce significant grain refinement in bulk metallic samples, which can be used for various engineering applications. The chapter outlines five main strategies to increase the strength of light metals: solid solution strengthening, precipitation strengthening, dislocation strengthening, grain size hardening, and crystallographic texture strengthening. It provides a brief overview of the fatigue properties observed in the NS light metals. The chapter discusses the current industrial applications of the NS light metals and their innovation potential. Commercialization of NS light metals is associated with three potential advantages: the superior properties of NS light metals, their efficient fabrication, and the possibility to produce cutting-edge products from these materials.