gebhart/patrepeval huggingface dataset:
Composed sketch framework for quantiles and cardinality queries over big data streams (2017)

Quantiles and Cardinality queries are important tools to analyze statistical information from big data streams. Due to the features of the streams, such as huge volume and high velocity, it is a challenging problem to quickly provide responses for the two types of queries using constrained space over big data streams. In this paper, we propose a composed sketch framework, which can support both quantiles queries and cardinality queries over the data streams. We introduce cardinality estimators into a baseline q-digest structure and propose unified sketch merging and query processing operations. Our approach can support these two types of queries simultaneously. We conduct detailed theoretical and experimental analysis in terms of query accuracy and query response time. The analytical and experimental results show that our approach can obtain accurate estimates quicker than traditional method and system in big data streams environments, and it just produces less than 0.8‰ storage overhead in TB-scale real-world data sets.
Malathion Exposure and the Incidence of Cancer in the Agricultural Health Study (2007)

Malathion is the most common organophosphate insecticide applied in the United States, and while some studies suggest that it may be clastogenic, its carcinogenicity has not been demonstrated in rodents. However, malathion has been associated with non-Hodgkin's lymphoma in several epidemiologic studies. The authors investigated associations between malathion exposure and cancer among 19,717 pesticide applicators enrolled in the Agricultural Health Study between 1993 and 1997. Information on lifetime years and days per year of use and intensity of malathion exposure was obtained with self-administered questionnaires prior to the onset of any cancer. The average follow-up time was 7.5 years (1993-2002). Rate ratios and 95% confidence intervals were calculated using Poisson regression, adjusting for potential confounders. Overall, lifetime days of malathion use (top tertile of exposure, >39 days) was not associated with all cancers combined (rate ratio = 0.97, 95% confidence interval: 0.81, 1.15). The risk of non-Hodgkin's lymphoma was not associated with malathion use, although the number of cases was small. The risk of melanoma with more than 39 lifetime exposure-days was 0.39 (95% confidence interval: 0.14, 1.03). In summary, malathion exposure was not clearly associated with cancer at any of the sites examined. Although the rate ratios for melanoma were reduced, small numbers and lack of experimental evidence suggest that the observed reductions may have arisen by chance.
A Review of Vibration-based Structural Health Monitoring with Special Emphasis on Composite Materials (2006)

Structural health monitoring and damage detection techniques are tools of great importance namely in the offshore, civil, mechanical and aeronautical engineering communities, either due to safety reasons or to the economical benefits it may bring.The need for detecting damage in complex structures has led to the development of a vast amount of techniques, in particular those based upon structural vibration analysis.In the present article, some of the latest advances in Structural Health Monitoring and Damage Detection have been covered, with an emphasis on composite structures, given the fact that this kind of materials have currently a wide range of engineering applications.
Exploiting Concepts In Videos For Video Event Detection (2021)

Constructing end-to-end NLP systems requires the processing of many types of linguistic information prior to solving the desired end task. A common approach to this problem is to construct a pipeline, one component for each task, with each system's output becoming input for the next. This approach poses two problems. First, errors propagate, and, much like the childhood game of "telephone", combining systems in this manner can lead to unintelligible outcomes. Second, each component task requires annotated training data to act as supervision for training the model. These annotations are often expensive and time-consuming to produce, may differ from each other in genre and style, and may not match the intended application. In this dissertation we present a general framework for constructing and reasoning on joint graphical model formulations of NLP problems. Individual models are composed using weighted Boolean logic constraints, and inference is performed using belief propagation. The systems we develop are composed of two parts: one a representation of syntax, the other a desired end task (semantic role labeling, named entity recognition, or relation extraction). By modeling these problems jointly, both models are trained in a single, integrated process, with uncertainty propagated between them. This mitigates the accumulation of errors typical of pipelined approaches. Additionally we propose a novel marginalization-based training method in which the error signal from end task annotations is used to guide the induction of a constrained latent syntactic representation. This allows training in the absence of syntactic training data, where the latent syntactic structure is instead optimized to best support the end task predictions. We find that across many NLP tasks this training method offers performance comparable to fully supervised training of each individual component, and in some instances improves upon it by learning latent structures which are more appropriate for the task.
Challenges in gigapixel multiscale image formation (2012)

We present new results from the image formation team on the AWARE Wide-Field project. We will report on new strategies prompted by new challenges encountered in experiments with two prototype AWARE Wide-Field systems.
Towards metal–organic framework based field effect chemical sensors: UiO-66-NH<sub>2</sub> for nerve agent detection (2016)

We present a highly sensitive gas detection approach for the infamous 'nerve agent' group of alkyl phosphonate compounds. Signal transduction is achieved by monitoring the work function shift of metal-organic framework UiO-66-NH<sub>2</sub> coated electrodes upon exposure to ppb-level concentrations of a target simulant. Using the Kelvin probe technique, we demonstrate the potential of electrically insulating MOFs for integration in field effect devices such as ChemFETs: a three orders of magnitude improvement over previous work function-based detection of nerve agent simulants. Moreover, the signal is fully reversible both in dry and humid conditions, down to low ppb concentrations. Comprehensive investigation of the interactions that lead towards this high sensitivity points towards a series of confined interactions between the analyte and the pore interior of UiO-66-NH<sub>2</sub>.
Electrostatic Linear Actuator (1990)

Electrically charged helices attract or repel each other. Proposed electrostatic linear actuator made with intertwined dual helices, which holds charge-bearing surfaces. Dual-helix configuration provides relatively large unbroken facing charged surfaces (relatively large electrostatic force) within small volume. Inner helix slides axially in outer helix in response to voltages applied to conductors. Spiral form also makes components more rigid. Actuator conceived to have few moving parts and to be operable after long intervals of inactivity.
The role of CD8<sup>+</sup> T cells in the initiation of insulin‐dependent diabetes mellitus (1996)

While it is generally accepted that T cells are critical for the development of diabetes in the non-obese diabetic (NOD) mouse, the precise functions of the CD4+ and CD8+ subsets remain ill-defined. Transfer experiments have provided evidence that CD4+ cells are the disease initiators, provoking massive mononuclear leukocyte infiltration into the pancreatic islets, while CD8+ cells play an effector role, responsible for the final destruction of islet beta cells. It was surprising, then, to find that NOD mice carrying a null mutation at the beta 2-microglobulin (beta 2-mu) locus, and thereby lacking major histocompatibility complex class I molecules and CD8+ T cells, developed neither insulitis nor diabetes. Here, we argue that the absence of insulitis in these animals results from their lack of CD8+ cells because islet infiltration is also absent when NOD mice are treated with an anti-CD8 monoclonal antibody (mAb) at a young age. Interestingly, the anti-CD8 effect is only observed when the mAb is injected during a discrete age window--2 to 5 weeks after birth. Transfer experiments indicate that the lack of CD8+ cells during this period somehow alters the phenotype of CD4+ cells, preventing them from expressing their insulitis potential. This is not because they are generally immuno-incompetent nor because they are generally more prone to differentiating into cells with Th2 characteristics. Given that neither the beta 2-mu mutation nor anti-CD8 treatment affect insulitis in a T cell receptor transgenic (tg) mouse strain with a CD4+ T cell repertoire highly skewed for an anti-islet cell reactivity, the most straight-forward interpretation of these observations is that CD8+ cells are required for effective priming and expansion of autoreactive CD4+ cells.
Surgical Outcomes in Patients With Extratemporal Epilepsy and Subtle or Normal Magnetic Resonance Imaging Findings (2013)

Among patients with medically refractory MRI nonlesional extratemporal epilepsy, detailed evaluation and subsequent resection leads to seizure freedom in 42% of patients at 2 years.
Autonomous UAV Navigation for Active Perception of Targets in Uncertain and Cluttered Environments (2020)

The use of Small Unmanned Aerial Vehicles (sUAVs) has grown exponentially owing to an increasing number of autonomous capabilities. Automated functions include the return to home at critical energy levels, collision avoidance, take-off and landing, and target tracking. However, sUAVs applications in real-world and time-critical scenarios, such as Search and Rescue (SAR) is still limited. In SAR applications, the overarching aim of autonomous sUAV navigation is the quick localisation, identification and quantification of victims to prioritise emergency response in affected zones. Traditionally, sUAV pilots are exposed to prolonged use of visual systems to interact with the environment, which causes fatigue and sensory overloads. Nevertheless, the search for victims onboard a sUAV is challenging because of noise in the data, low image resolution, illumination conditions, and partial (or full) occlusion between the victims and surrounding structures. This paper presents an autonomous Sequential Decision Process (SDP) for sUAV navigation that incorporates target detection uncertainty from vision-based cameras. The SDP is modelled as a Partially Observable Markov Decision Process (POMDP) and solved online using the Adaptive Belief Tree (ABT) algorithm. In particular, a detailed model of target detection uncertainty from deep learning-based models is shown. The presented formulation is tested under Software in the Loop (SITL) through Gazebo, Robot Operating System (ROS), and PX4 firmware. A Hardware in the Loop (HITL) implementation is also presented using an Intel Myriad Vision Processing Unit (VPU) device and ROS. Tests are conducted in a simulated SAR GPS-denied scenario, aimed to find a person at different levels of location and pose uncertainty.
Electric signalling controls wound healing, cell proliferation and division, and nerve regeneration. (2004)

In this project we designed four different level of electrotaxis experiment from <i>in vitro</i> and <i>in vivo</i>, from single cell monolayer cells then further to stratified multiple layers of cells, to prove that cell directional migration, wound healing and nerve regeneration are all controlled by endogenous electric field. Using single cell model and monolayer scratch wound model <i>in vitro</i>, we demonstrated the electrotactic response of directional cell migration and wound healing were all controlled by physiological EF. Using a three dimensional stratified cornea epithelium wound model <i> ex vivo</i>, we further proved that electric signals could modulate the directional cell migration in a wound. We then used an <i>in vivo</i> rat corneal model, which generates its own endogenous EF, to show that the direction of nerve growth, the rate of epithelial wound healing and the orientation of the cell division in wound healing were all controlled by the wound-induced engenous EF. Wounding the cornea generates endogenous EFs in the plane of the epithelial sheet because the transcorneal potential difference (TCPD); +40mb internally positive) collapses at the wound edge, but is maintained at normal levels 0.5 mm back from the wound. We manipulated the endogenous EF this creates using clinically proved drugs with differing actions. The wound-induced EF controlled the orientation of cell division; most epithelial cells divided with a cleavage plane parallel to the wound edge and perpendicular to the EF vector. Increasing or decreasing the EF pharmacological, respectively increased or decreased the extent of oriented cell division. IN addition, cells closest to the wound edge where the EF was highest, were oriented most strongly by the EF. Remarkably, an endogenous EF also enhanced the frequency of cell division. This also was regulated by enhancing or suppressing the EF pharmacologically. Since the endogenous EF also regulated the wound healing rate, it may act as one control of the interplay between cell migration and cell division during healing.
Octarellin VI: Using Rosetta to Design a Putative Artificial (β/α)8 Protein (2013)

The computational protein design protocol Rosetta has been applied successfully to a wide variety of protein engineering problems. Here the aim was to test its ability to design de novo a protein adopting the TIM-barrel fold, whose formation requires about twice as many residues as in the largest proteins successfully designed de novo to date. The designed protein, Octarellin VI, contains 216 residues. Its amino acid composition is similar to that of natural TIM-barrel proteins. When produced and purified, it showed a far-UV circular dichroism spectrum characteristic of folded proteins, with α-helical and β-sheet secondary structure. Its stable tertiary structure was confirmed by both tryptophan fluorescence and circular dichroism in the near UV. It proved heat stable up to 70°C. Dynamic light scattering experiments revealed a unique population of particles averaging 4 nm in diameter, in good agreement with our model. Although these data suggest the successful creation of an artificial α/β protein of more than 200 amino acids, Octarellin VI shows an apparent noncooperative chemical unfolding and low solubility.
Multi Composition GeSi Tuneable Concentration Silicon-Germanium Wire Structures for CMOS Photonics (2019)

In this presentation, we report for the first time Rapid Melt Growth SiGe based structures embedded in an SOI platform with constant siGe composition over the length of the SiGe wires. This method is suitable for waveguide integration on the SOI platform which is crucial for multi wavelength operation of Franz Keldysh type modulators.
Determination of particle concentration in the air using a digital SLR camera (2009)

Many researches showed that pollution particles are associated with adverse health effects. These particles are 10 micrometers in diameter or smaller (PM<sub>10</sub>). Now the challenge is to develop a better technique for monitoring the concentration of these particles. In this study, we intend to use a Single Lens Reflex (SLR) camera to determine particle concentration in the air using our own developed algorithm. This algorithm was developed based on the regression analysis of relationship between the measured reflectance and the reflected components from a surface material and the atmosphere. This algorithm is used to convert multispectral image pixel values acquired by this camera into quantitative values of the concentrations of PM<sub>10</sub>. These computed PM<sub>10</sub> concentrations were compared to other standard values measured by a DustTrak<sup>TM</sup> meter. The validated result of the newly develop algorithm produced a high degree of accuracy as indicated by high correlation coefficient (R<sup>2</sup>) and low root-mean-square-error (RMS).
cAMP and IP3 Signaling Pathways in HEK293 Cells Transfected with Canine Olfactory Receptor Genes (2011)

Olfactory receptors (ORs) expressed at the cell surface of olfactory sensory neurons lining the olfactory epithelium are the first actors of events leading to odor perception and recognition. As for other mammalian ORs, few dog OR have been deorphanized, mainly because of the absence of good methodology and the difficulties encountered to express ORs at the cell surface. Within this work, our aim was 1) to deorphanize a large subset of dog OR and 2) to compare the implication of the 2 main pathways, namely the cAMP and inositol 1,4,5-triphosphate (IP3) pathways, in the transduction of the olfactory message. For this, we used 2 independent tests to assess the importance of each of these 2 pathways and analyzed the responses of 47 canine family 6 ORs to a number of aliphatic compounds. We found these ORs globally capable of inducing intracellular calcium elevation through the IP3 pathway as confirmed by the use of specific inhibitors and/or a cAMP increase in response to aldehyde exposure. We showed that the implication of the cAMP or/and IP3 pathway was dependent upon the ligand-receptor combination rather than on one or the other partner. Finally, by exposing OR-expressing cells to the 21 possible pairs of C6-C12 aliphatic aldehydes, we confirmed that some odorant pairs may have an inhibitory or additive effect. Altogether, these results reinforce the notion that odorant receptor subfamilies may constitute functional units and call for a more systematic use of 2 complementary tests interrogating the cAMP and IP3 pathways when deorphanizing ORs.
Detection of Power quality disturbances using discrete wavelet transform (2016)

Recently the electrical Power quality (PQ) has become a main concern for both utilities and customers because the load side on the costumer side gets affected and may get damage. This paper presents a discrete wavelet transform (DWT) based technique for the detection of power system operational events and power quality disturbances associated with these events. The power quality disturbances associated with the power system operation events such as switching on and off the loads, switching on and off the capacitor banks, tripping and reclosing the transmission lines, outage of the generator and utility network has been investigated effectively. The detailed simulation study of power quality disturbances has been carried out in MATLAB/Simulink environment.
C by Example (1992)

From the Publisher:
The newest edition of this revolutionary book-comprehensive coverage with liberal use of program listing call-outs and cross-referencing.
Short chapters make for quick progress and easy learning
Features extensive use of icons, illustrations, and margin notes
Presents complex programming logic in easy-to-understand pseudocode resembling simple sentences
A novel <i>in vitro</i> wound biofilm model used to evaluate low-frequency ultrasonic-assisted wound debridement (2015)

The manufacturer of the ultrasonic-assisted wound debridement device, Söring GmbH, Germany, has supported the ultrasound studies. The funding company had no role in the design, data collection, analysis, review, or approval of the manuscript.
CD47 Enhances <i>In Vivo</i> Functionality of Artificial Antigen-Presenting Cells (2015)

Our data for the first time show that aAPC functionalized with CD47 maintain their stimulatory capacity in vitro and demonstrate enhanced in vivo efficiency. Thus, these next-generation aAPC(CD47+) have a unique potential to enhance the application of the aAPC technology for future immunotherapy approaches.
Heterogeneous IRIS recognition using heterogeneous eigeniris and sparse representation (2014)

When the iris images for training and testing are acquired by different iris image sensors, the recognition rate will be degraded and not as good as the one when both sets of images are acquired by the same image sensors. Such problem is called “heterogeneous iris recognition”. In this paper, we propose two novel patch-based heterogeneous dictionary learning methods using heterogeneous eigeniris and sparse representation which learn the basic atoms in iris textures across different image sensors and build connections between them. After such connections are built, at testing stage, it is possible to hallucinate (synthesize) iris images across different sensors. By matching training images with hallucinated images, the recognition rate can be successfully enhanced. Experimenting with an iris database consisting of 3015 images, we show that the EER is decreased 23.9% relatively by the proposed method using sparse representation, which proves the effectiveness of the proposed image hallucination method.
Liquid Chromatography at Critical Conditions:  Comprehensive Approach to Sequence-Dependent Retention Time Prediction (2006)

An approach to sequence-dependent retention time prediction of peptides based on the concept of liquid chromatography at critical conditions (LCCC) is presented. Within the LCCC approach applied to biopolymers (BioLCCC), the specific retention time corresponds to a particular sequence. In combination with mass spectrometry, this approach provides an efficient tool to solve problems wherein the protein sequencing is essential. In this work, we present a theoretical background of the BioLCCC concept and demonstrate experimentally its feasibility for sequence-dependent LC retention time prediction for peptides. BioLCCC model is based on three notions: (a) a random walk model for a macromolecule chain; (b) an entropy and energy compensation for the macromolecules within the adsorbent pore; and (c) a set of phenomenological parameters for the effective interaction energies of interactions between the amino acid residues and the adsorbent surface. In this work, the phenomenological parameters have been obtained for C18 reversed-phase HPLC. Note, that contrary to alternative additive models for retention time prediction based on summation of the so-called "retention coefficients", the BioLCCC approach takes into account the location of amino acids within the primary structure of a peptide and, thus, allows the identification of the peptides having the same composition of amino acids but differing by their arrangement. As a result, this new approach allows prediction of retention time for any possible amino acid sequence in particular HPLC experiments. In addition, the BioLCCC model lacks of main drawbacks of additive approaches that predict retention time for sequences of limited chain lengths and provide information about amino acid composition only. The proposed BioLCCC approach was characterized experimentally using LTQ FT LC-MS and LC-MS/MS data obtained earlier for Escherichia coli. The HPLC system calibration was performed using peptide retention standards. The results received show a linear correlation between predicted and experimental retention times, with a correlation coefficient, R2, of 0.97 for a peptide standard mixture and 0.9 for E. coli data, respectively, with the standard error below 1 min. The work presents the first description of a BioLCCC approach for high-throughput peptide characterization and preliminary results of its feasibility tests.