gebhart/patrepeval huggingface dataset:
Methods and Graphical Tools for Exploratory Data Analysis of Artificial Olfaction Experiments (2012)

Visualization and initial examination of the Electronic Nose data is one of the most important parts of the data analysis cycle. This aspect of data investigation should ideally be performed iteratively together with data collection in order to optimize experimental protocols and final results. Once exploration has been completed, a complete supervised data analysis on a full dataset can be run, leading to prediction and thereby to e-nose performance evaluation. Exploratory Data Analysis (EDA) comprises three tasks: checking the quality of the data, calculating summary statistics, and producing plots of the data to get a feel of their structure. Graphical visualization of data allows checking for instrumental malfunctioning, discovering human errors, removing outliers, understanding the influence of experimental parameters, verifying the ability of the machine in discriminating the examined samples, and eventually formulating new hypotheses. A number of different techniques have been developed for data visualization, including multivariate statistical analysis, non-linear mapping, and clustering techniques. This chapter will present an overview of methods, tools, and software for EDA of artificial olfaction experiments. These will cover visualization and data mining tools for both raw and preprocessed data, such as: histograms, scatter plots, feature and box plots, Principal Component Analysis (PCA), Cluster Analysis (CA), and Cluster Validity (CV). Some case studies that demonstrate the application of the methods to specific chemical sensing problems will be illustrated.
Neural assembly generation by selective connection weight updating (2010)

In this paper, a neural network model, which learns symbols is introduced. VSF-Network (Vibration Synchronizing Function Network) is a hybrid neural network combining a chaos neural network with a hierarchical network. It has an ability for a incremental learning of patters by abstracting input data. VSF-Network finds unknown elements in data based on clusters generated by chaos neurons. VSF-Network generates sub-networks while it learns new patterns based on the information about the clusters. When a combination of learned patterns is presented, VSF-network recognizes them by combining its sub-networks. In this paper, an incremental learning model to examine the dynamics of VSF-network is introduced. The performances of the incremental learning by VSF-network are shown through the two tasks and the discussion about the combination form of the sub-networks generated by VSF-Network.
Concolic testing for deep neural networks (2018)

Concolic testing combines program execution and symbolic analysis to explore the execution paths of a software program. In this paper, we develop the first concolic testing approach for Deep Neural Networks (DNNs). More specifically, we utilise quantified linear arithmetic over rationals to express test requirements that have been studied in the literature, and then develop a coherent method to perform concolic testing with the aim of better coverage. Our experimental results show the effectiveness of the concolic testing approach in both achieving high coverage and finding adversarial examples.
Synthesizing high-performance compliant stroke amplification systems for MEMS (2002)

We have recently designed, fabricated, demonstrated a new class of compliant stroke amplification mechanisms that are exceptionally well suited for MEMS applications. Manufactured in Sandia's advanced 5-level surface micromachining technology known as SUMMiT-V, these computer generated structures provide high work and area efficiency in designs that are highly compatible with the fabrication process. The actual devices display outstanding yield, robustness, endurance, and resistance to surface adhesion effects during the final release process. One device has been driven to a 20-/spl mu/m output displacement at resonance for more than 10/sup 10/ cycles with no apparent fatigue. This paper focuses on the unique methodology employed to design and analyze these compliant stroke amplification systems. The same approach, however, can be used to design many other compliant structures for fabrication in a MEMS technology. Compliance in design leads to creation of jointless, no-assembly, monolithic mechanical device.
Recent Advances: the Cytochrome P450 Enzymes (1995)

Successful application of information on cytochrome P450 to prevent drug interactions and improve the therapeutic risk: benefit ratio can occur only if we know which enzyme is responsible for the metabolism of a drug. Until recently, this information was not usually available when new drugs reached the market. It is not enough to know the fraction of a dose metabolized versus excreted unchanged or the metabolic pathways by which a compound is degraded. Studies conducted during drug development must identify the enzyme or enzymes involved in the metabolism of new drugs. In addition, the ability of new drugs to inhibit or induce the activity of the key P450 enzymes must be known if we are to take full advantage of our current knowledge of how the cytochrome P450 system works.
Noninvasive measurements of transmural myocardial metabolites using 3-D 31P NMR spectroscopy (2001)

A completely noninvasive three-dimensional (3-D) static magnetic field magnitude spatially localized (31)P spectroscopy technique has been developed and applied to study the in vivo canine myocardium at 9.4 T. The technique incorporates both Fourier series windows and selective Fourier transform methods utilizing all three orthogonal gradients for 3-D phase encoding. The number of data acquisitions for each phase-encoding step was weighted according to the Fourier coefficients to define cylindrical voxels. Spatially localized (31)P spectra can be generated for voxels of desired location within the field of view as a postprocessing step. The quality of localization was first demonstrated by using a three-compartment phantom. The technique was then applied to in vivo canine models and yielded (31)P cardiac spectra with an excellent signal-to-noise ratio. The in vivo validation experiments, using an implanted 2-phosphoenolpyruvate-containing marker, demonstrated that the technique is capable of measuring at least two transmural layers of left ventricular myocardium representing the subepicardium and subendocardium.
Deep Neural Network based Body Movement Cancellation for Doppler Radar Vital Sign Detection (2019)

This paper presents a novel technique of cancelling random body movement (BM) in Doppler radar noncontact vital sign detection based on deep neural network (DNN). Respiration motions with different frequencies and different phase offsets are synthesized and mixed with simulated BMs to train the DNN model. Neither hardware modification nor extra hardware complexity is needed. The proposed DNN based method can separate the stable respiration motion from the signal mixture of respiration and BM without prior information from the BM. Experimental results show that the proposed DNN based method allows a single radar sensor to successfully reconstruct stable respiration motions without BM disturbance.
Fast, Reversible Lithium Storage with a Sulfur/Long‐Chain‐Polysulfide Redox Couple (2013)

The cathodic reactions in Li-S batteries can be divided into two steps. Firstly, elemental sulfur is transformed into long-chain polysulfides (S8 ↔ Li2S4), which are highly soluble in the electrolyte. Next, long-chain polysulfides undergo nucleation reaction and convert into solid-state Li2S2 and Li2S (Li2S4 ↔ Li2S) by slow processes. As a result, the second-step of the electrochemical reaction hinders the high-rate application of Li-S batteries. In this report, the kinetics of the sulfur/long-chain-polysulfide redox couple (theoretical capacity=419 mA h g(-1)) are experimentally demonstrated to be very fast in the Li-S system. A Li-S cell with a blended carbon interlayer retains excellent cycle stability and possesses a high percentage of active material utilization over 250 cycles at high C rates. The meso-/micropores in the interlayer are responsible for accommodating the shuttling polysulfides and offering sufficient electrolyte accessibility. Therefore, utilizing the sulfur/long-chain polysulfide redox couple with an efficient interlayer configuration in Li-S batteries may be a promising choice for high-power applications.
Silicides as new electrode/heater for compact integration of phase change memory with CMOS (2010)

We report the first demonstration of phase change memory cells utilizing nickel monosilicide (NiSi) or platinum monosilicide (PtSi) as the bottom electrode or heater material. This work enables the integration of PCRAM directly on the silicided drain regions of MOSFETs, allowing compact integration with reduced process complexity and cost. Low reset current of 0.8 mA was achieved for contact dimensions of ~ 1 μm. Electrical and simulation results demonstrate the feasibility of employing silicides as a bottom electrode/heater in a PCRAM.
Thermodynamic Analysis of Enantioselectivity of HaloalkaneDehalogenase DbjA and its Variants DbjA and DbjA+H139A towardsBrominated Esters and substituted Bromoalkanes (2008)

Poster prezentovaný Mgr. Radkou Chaloupkovou na konfereneci Protein Design and Evolution for Biocatalysis ve Spanelsku.
Anti-Angiogenic Therapeutic Drugs for Treatment of Human Cancer (2008)

One of the proposed benefits of targeted therapies is reduced toxicity and improved quality of life. The approval of a new broad family of molecularly targeted anticancer drugs represents one of the most significant recent advances in clinical oncology. The growth of solid tumors is dependent on their capacity to acquire a blood supply. Much effort has been directed towards the development of drugs that disrupt or normalize this process for cancer therapy. Some tumors also contain vasculogenic mimicry channels consisting of cancer cells and their extracellular matrix. In solid tumors, vasculogenic mimicry has been found to be strongly correlated with advanced-stage disease and poor outcome. In this review article, we summarize the clinical use of small molecules and therapeutic antibodies as angiogenesis inhibitors and their toxic side effects. We discuss vasculogenic mimicry of solid tumors and describe strategies for identifying putative tumor vascular targets. We end by discussing the future prospects for the clinical use of vascular targeting in treatment of cancer.
A Simple DNA Extraction Method for PCR‐based Detection of Xanthomonas campestris pv. pelargonii in Geraniums (1997)

Abstract A simple method for PCR‐based plant clinical diagnosis of bacterial blight of geraniums caused by Xanthomonas campestris pv. pelargonii is described. The method entails maceration of infected tissues in water or 10mM Tris‐ HCI, pH 8.0 buffer, followed by treatment of the macerate with a commercially‐available extraction matrix (GeneReleaser TM ) in which nucleic acid is released by brief microwave heating. Nucleic acid prepared in this manner served directly as template for PCR amplification with primers targeting a sequence in the genome of the bacterium. Using this protocol, it was possible to quickly identify X. campestris pv. pelargonii in infected geraniums, whereas amplification products were not obtained with nucleic acid preparations from noninfected plants, or from plants infected with the bacterial pathogens, Corynebacterium fascians or Pseudomonas cichorii .
Endosomal Escape of Polymeric Gene Delivery Complexes Is Not Always Enhanced by Polymers Buffering at Low pH (2003)

One of the crucial steps in gene delivery with cationic polymers is the escape of the polymer/DNA complexes ("polyplexes") from the endosome. A possible way to enhance endosomal escape is the use of cationic polymers with a pKa around or slightly below physiological pH ("proton sponge"). We synthesized a new polymer with two tertiary amine groups in each monomeric unit [poly(2-methyl-acrylic acid 2-[(2-(dimethylamino)-ethyl)-methyl-amino]-ethyl ester), abbreviated as pDAMA]. One pKa of the monomer is approximately 9, providing cationic charge at physiological pH, and thus DNA binding properties, the other is approximately 5 and provides endosomal buffering capacity. Using dynamic light scattering and zeta potential measurements, it was shown that pDAMA is able to condense DNA in small particles with a surface charge depending on the polymer/DNA ratio. pDAMA has a substantial lower toxicity than other polymeric transfectants, but in vitro, the transfection activity of the pDAMA-based polyplexes was very low. The addition of a membrane disruptive peptide to pDAMA-based polyplexes considerably increased the transfection efficiency without adversely affecting the cytotoxicity of the system. This indicates that the pDAMA-based polyplexes alone are not able to mediate escape from the endosomes via the proton sponge mechanism. Our observations imply that the proton sponge hypothesis is not generally applicable for polymers with buffering capacity at low pH and gives rise to a reconsideration of this hypothesis.
Estudo de levantamento de tendências de mercado e competências para o futuro do sector agroindustrial (2011)

A relevância e pertinência deste Estudo está na capacidade de transformar a liderança intelectual em liderança de mercado, transformando a previsão em realidade, saindo à frente dos concorrentes na “estrada” para o futuro. Nos dias de hoje, o valor do conhecimento é essencial, sendo este o principal factor crítico de sucesso da nossa sociedade. Para lá de todas as conceptualizações e definições que a informação e a sociedade da informação e do conhecimento em que vivemos possam ter, certo é que a sua utilização e importância são inquestionáveis. Gerir o Conhecimento e as Competências assume uma importância crescente num contexto de competitividade e concorrência sem precedentes. O foco estratégico de qualquer empresa deverá estar centrado nas competências que estão por detrás do seu core business, que accionam as suas mais-valias no mercado. Gerir os recursos e o conhecimento, de modo a que estes sejam instrumentos seguros das empresas para fazer face às necessidades e expectativas do mercado são as pedras e toque para o sucesso empresarial na nova sociedade.
Genetic susceptibility to obesity and diet intakes: association and interaction analyses in the Malmö Diet and Cancer Study (2013)

Gene-environment interactions need to be studied to better understand the obesity. We aimed at determining whether genetic susceptibility to obesity associates with diet intake levels and whether diet intakes modify the genetic susceptibility. In 29,480 subjects of the population-based Malmö Diet and Cancer Study (MDCS), we first assessed association between 16 genome-wide association studies identified obesity-related single-nucleotide polymorphisms (SNPs) with body mass index (BMI) and associated traits. We then conducted association analyses between a genetic risk score (GRS) comprising of 13 replicated SNPs and the individual SNPs, and relative dietary intakes of fat, carbohydrates, protein, fiber and total energy intake, as well as interaction analyses on BMI and associated traits among 26,107 nondiabetic MDCS participants. GRS associated strongly with increased BMI (P = 3.6 × 10(-34)), fat mass (P = 6.3 × 10(-28)) and fat-free mass (P = 1.3 × 10(-24)). Higher GRS associated with lower total energy intake (P = 0.001) and higher intake of fiber (P = 2.3 × 10(-4)). No significant interactions were observed between GRS and the studied dietary intakes on BMI or related traits. Of the individual SNPs, after correcting for multiple comparisons, NEGR1 rs2815752 associated with diet intakes and BDNF rs4923461 showed interaction with protein intake on BMI. In conclusion, our study does not provide evidence for a major role for macronutrient-, fiber- or total energy intake levels in modifying genetic susceptibility to obesity measured as GRS. However, our data suggest that the number of risk alleles as well as some of the individual obesity loci may have a role in regulation of food and energy intake and that some individual loci may interact with diet.
Introduction to the research topic: the role of physical fitness on cardiovascular responses to stress (2014)

[EN] This e-book is the culmination of countless hours of meticulous&#13;\nwork by global scientists. We would like to thank the researchers&#13;\nfor their great contributions to this hot topic. The combination&#13;\nof these studies reflects the importance of the topic amongst&#13;\nresearchers and practitioners and the wide interest from numer-&#13;\nous laboratories around the world. The contributions include&#13;\na variety of formats including five original investigations, three&#13;\nreview articles, one opinion article and a hypothesis and the-&#13;\nory article. Notably, these contributions included both human&#13;\nand animal models that encompassed a range of techniques from&#13;\nmolecular mechanisms to real life interventions thus reinforcing&#13;\nthe translational approach for the understanding of cardiovascu-&#13;\nlar responses to stress.
Characterization of platinum(II) complexes exhibiting inhibitory activity against the 20S proteasome (2020)

Proteasome inhibitors are useful for biochemical research and clinical treatment. In our previous study, we reported that the 4N-coordinated platinum complexes with anthracenyl ring and heterocycle exhibited proteasome-inhibitory activity. In the present study, the structure-activity relationships and characterization of these complexes were determined for the elucidation of the role of aromatic ligands. Lineweaver-Burk analysis revealed that the chemical structure of heterocycles affects the binding mode of platinum complexes. Platinum complexes with anthracenyl ring and pyridine showed competitive inhibition, although platinum complexes with anthracenyl ring and phenanthroline showed non-competitive inhibition. The structure-activity relationships demonstrated that anthracenyl moiety plays a crucial role in proteasome-inhibitory activity. The platinum complexes with naphthyl or phenyl rings exhibited lower inhibitory activities than the platinum complex with anthracenyl ring. The reactivity with N-acetylcysteine varied according to the chemical structure of complexes.
Our Man in Chernobyl (2004)

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.
The Bayesian Elastic Net: Classifying Multi-Task Gene-Expression Data (2009)

Highly correlated relevant features are frequently encountered in variable-selection problems, with gene-expression analysis an important example. It is desirable to select all of these highly correlated features simultaneously as a group, for better model interpretation and robustness. Further, irrelevant features should be excluded, resulting in a sparse solution (of importance for avoiding over-fitting with limited data). We address the problem of sparse and grouped variable selection by introducing a new Bayesian Elastic Net model. One advantage of the proposed model is that by imposing priors on individual parameters in the Laplace distribution, we reduce the number of tuning parameters to one, as compared with two such parameters in the original Elastic Net. In addition, we extend the new Bayesian Elastic Net model to the problem of probit regression, in order to deal with classification problems with a sparse but correlated set of covariates (features). Extension to multi-task learning is also considered, with inference performed using variational Bayesian analysis. The model is validated by first performing experiments on simulated data and on previously published gene-expression data; in these experiments we also perform comparisons to the original Elastic Net and to Bayesian Lasso. Finally, we present and analyze a new gene-expression data set for the time-evolving properties of influenza, measured using blood samples from human subjects in a recent challenge study.
Fluorescence and phosphorescence lifetime imaging reveals a significant cell nuclear viscosity and refractive index changes upon DNA damage (2023)

Cytoplasmic viscosity is a crucial parameter in determining rates of diffusion-limited reactions. Changes in viscosity are associated with several diseases, whilst nuclear viscosity determines gene integrity, regulation and expression. Yet how drugs including DNA-damaging agents affect viscosity is unknown. We demonstrate the use of a platinum complex, Pt[L]Cl, that localizes efficiently mostly in the nucleus as a probe for nuclear viscosity. The phosphorescence lifetime of Pt[L]Cl is sensitive to viscosity and provides an excellent tool to investigate the impact of DNA damage. We show using Fluorescence Lifetime Imaging (FLIM) that the lifetime of both green and red fluorescent proteins (FP) are also sensitive to changes in cellular viscosity and refractive index. However, Pt[L]Cl proved to be a more sensitive viscosity probe, by virtue of microsecond phosphorescence lifetime versus nanosecond fluorescence lifetime of FP, hence greater sensitivity to bimolecular reactions. DNA damage was inflicted by either a two-photon excitation, one-photon excitation microbeam and X-rays. DNA damage of live cells causes significant increase in the lifetime of either Pt[L]Cl (HeLa cells, 12.5-14.1 µs) or intracellularly expressed mCherry (HEK293 cells, 1.54-1.67 ns), but a decrease in fluorescence lifetime of GFP from 2.65 to 2.29 ns (in V15B cells). These values represent a viscosity change from 8.59 to 20.56 cP as well as significant changes in the refractive index (RI), according to independent calibration. Interestingly DNA damage localized to a submicron region following a laser microbeam induction showed a whole cell viscosity change, with those in the nucleus being greater than the cytoplasm. We also found evidence of a by-stander effect, whereby adjacent un-irradiated cells also showed nuclear viscosity change. Finally, an increase in viscosity following DNA damage was also observed in bacterial cells with an over-expressed mNeonGreen FP, evidenced by the change in its lifetime from 2.8 to 2.4 ns.
An explicit and unconditionally stable FDTD method for 3-D electromagnetic analysis (2013)

In this paper, an explicit and unconditionally stable finite-difference time-domain (FDTD) method is developed for electromagnetic analysis. It is stable for an arbitrarily large time step irrespective of space step, and accurate for a time step solely determined by accuracy. The method retains the strength of the conventional explicit FDTD in avoiding a matrix solution while eliminating the conventional FDTD's shortcoming in time step. Numerical experiments in both 2-D and 3-D simulations have demonstrated its superior performance in stability and efficiency without losing accuracy. The proposed method successfully generates stable and accurate results with a time step 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">13</sup> times larger than that allowed by the conventional FDTD in an example where the time step required by accuracy is 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">13</sup> times larger than that permitted by stability.
InVITe - Towards Intuitive Visualization of Iterations over Text (2016)

With InVITe, we are working towards intuitive visualization to support review of iterative modifications on text documents. In order to accomplish this, we perform simple matching of text snippets between the two versions of text, across a large range of parameter settings. Next, an overview graphic indicating the effect of parameter space on the output allows the user to select those combinations that are of interest. Finally, such selection will display an alluvial diagram with annotations and covering different resolutions. With this tool, co-authors can keep an overview of changes made, both structural and local.