gebhart/patrepeval huggingface dataset:
Detection ofn:mPhase Locking from Noisy Data: Application to Magnetoencephalography (1998)

We use the concept of phase synchronization for the analysis of noisy nonstationary bivariate data. Phase synchronization is understood in a statistical sense as an existence of preferred values of the phase difference, and two techniques are proposed for a reliable detection of synchronous epochs. These methods are applied to magnetoencephalograms and records of muscle activity of a Parkinsonian patient. We reveal that the temporal evolution of the peripheral tremor rhythms directly reflects the time course of the synchronization of abnormal activity between cortical motor areas.
The He(I) photoelectron spectra of methylenecyclopropene derivatives. Correlation with electrochemical oxidation (1988)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTThe He(I) photoelectron spectra of methylenecyclopropene derivatives. Correlation with electrochemical oxidationT. Koenig, Tim Curtiss, Rolf Winter, Kevin Ashley, Qiu Mei, Peter J. Stang, Stanley Pons, Simon J. Buckland, Brian Halton, and Debra RolisonCite this: J. Org. Chem. 1988, 53, 16, 3735–3738Publication Date (Print):August 1, 1988Publication History Published online1 May 2002Published inissue 1 August 1988https://pubs.acs.org/doi/10.1021/jo00251a013https://doi.org/10.1021/jo00251a013research-articleACS PublicationsRequest reuse permissionsArticle Views68Altmetric-Citations10LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts
Hemodynamic Responses to Angiotensin I in Normal Volunteers and the Antagonism by the Angiotensin-Converting Enzyme Inhibitor Cilazapril (1987)

According to classic pharmacologic theory, agonist/antagonist competition can be used to quantify an antagonist's potency by measurement of agonist dose-response curves in the presence of varying doses of the antagonist. We used this principle to characterize the interaction between angiotensin I (AI) and the angiotensin-converting enzyme (ACE) inhibitor cilazapril in humans. In addition, by comparing the effects of AI and angiotensin II before and after administration of a 30-mg dose of cilazapril, we could show the specific AI antagonism of the ACE inhibitor in humans. To obtain the antagonist's dose-response curves, six healthy male volunteers received five single oral doses of cilazapril, 0.5-8.0 mg. Enalapril, 10 mg, and captopril, 12.5 mg, served as positive controls and placebo as the negative control. Dose-response curves following intravenous infusions of AI were established 4 h after oral ingestion of the ACE inhibitors. Noninvasively measured systolic and diastolic blood pressures and total peripheral resistance assessed AI effects. Cilazapril dose dependently shifted the AI dose-response curve rightward, with 1.0 mg inducing a twofold shift. Enalapril and captopril appear less potent, on a milligram basis, in antagonizing AI effects 4 h after drug intake. The methodology could be a useful tool for a rational testing and comparison of ACE inhibitors in clinical pharmacology.
Is time on cardiopulmonary bypass during cardiac surgery associated with acute kidney injury requiring dialysis? (2011)

It is commonly accepted that the longer the time on extracorporeal cardiopulmonary bypass (CPB), the higher is the likelihood of developing acute renal failure requiring dialysis (ARF-D). Nonetheless, previous works elicited conflicting evidence. We investigated the relationship between CPB duration and ARF-D occurrence. Data were extracted from a large observational study. All factors independently associated with ARF-D were detected. Overall, 11,092 case record forms were analyzed. At the univariate analyses, time on CBP was associated with an increase in the ARF-D risk (odds ratio of fifth vs. first quintile of CBP time: 3.84; 95% confidence interval: 2.58-5.7; P < 0.001). However, after adjusting for confounders, the association between time on CBP and ARF-D lost its statistical significance. In this large dataset, CBP time did not predict ARF-D occurrence. These results might suggest that an accurate risk assessment might be more important than time on CPB in determining ARF-D occurrence.
An improved molecularly imprinted polymer film for recognition of amino acids (2002)

Abstract A highly selective imprinted film was produced from a formic acid solution of nylon. Amino acids were used as template molecules and spin cast films typically of the order of 1 μm, but as thin as 500 nm, were routinely prepared. The films were shown to be specific to the identity and chirality of the template amino acid, and were shown to be effective after as many as five cycles of template extraction and reintroduction. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 3611–3615, 2002
A narrative review of the potential role of microaspiration and a dysregulated aerodigestive microbiome in lung disease (2021)

Abstract: When initiated the human microbiome project did not include the lungs and airways in its sampling sites, indicating an under appreciation of the role of the human lung microbiome in health and disease. This paradigm has recently changed through the use of culture independent methods to characterise the human lung microbiome. The original thinking, that the normal lung was essentially sterile, had previously been challenged by findings of microaspiration in normal volunteers and in patients with decreased levels of consciousness. The sterile lung was also questioned by findings of clinically occult infection markers in lung allograft recipients. What is arguably a “rediscovery” of the importance of the human lung microbiome may still underappreciate physiological and patho-physiological inter-relationships between organ systems, studied in separate research disciplines. In particular, microaspiration may be an important, direct mechanism through which the lung microbiome is modulated. As well as aspiration related to gastro-oesophageal reflux and microaspiration the authors feel that the importance of dysphagia in chronic lung disease, will be increasingly recognised in frailty related microbiome exchange between the oropharynx into the lung. This review therefore discusses interconnections in the human microbiome, with a focus on the potential for aerodigestive pathophysiology and microaspiration. Potential connections with human lung disease are discussed and contextualised within a developing literature. This review therefore highlights much needed new targets for translational intervention in lung pathophysiology and underlies the importance of a mixed disciplinary team approach for the future.
Graph Theory Based Approach to Users Grouping and Downlink Scheduling in FDD Massive MIMO (2017)

Massive MIMO is considered as one of the key enablers of the next generation 5G networks.With a high number of antennas at the BS, both spectral and energy efficiencies can be improved. Unfortunately, the downlink channel estimation overhead scales linearly with the number of antenna. This does not create complications in Time Division Duplex (TDD) systems since the channel estimate of the uplink direction can be directly utilized for link adaptation in the downlink direction. However, this channel reciprocity is unfeasible for the Frequency Division Duplex (FDD) systems where different physical transmission channels are existent for the uplink and downlink. In the aim of reducing the amount of Channel State Information (CSI) feedback for FDD systems, the promising method of two stage beamforming transmission was introduced. The performance of this transmission scheme is however highly influenced by the users grouping and selection mechanisms. In this paper, we first introduce a new similarity measure coupled with a novel clustering technique to achieve the appropriate users partitioning. We also use graph theory to develop a low complexity groups scheduling scheme that outperforms currently existing methods in both sum-rate and throughput fairness. This performance gain is demonstrated through computer simulations.
Current Therapies and Emerging Targets for the Treatment of Diabetes (2001)

Concurrent with the spread of the western lifestyle, the prevalence of all types of diabetes is on the rise in the world's population. The number of diabetics is increasing by 4-5% per year with an estimated 40-45% of individual's over the age of 65 years having either type II diabetes or impaired glucose tolerance. Since the signs of diabetes are not immediately obvious, diagnosis can be preceded by an extended period of impaired glucose tolerance resulting in the prevalence of beta-cell dysfunction and macrovascular complications. In addition to increased medical vigilance, diabetes is being combatted through aggressive treatment directed at lowering circulating blood glucose and inhibiting postprandial hyperglycemic spikes. Current strategies to treat diabetes include reducing insulin resistance using glitazones, supplementing insulin supplies with exogenous insulin, increasing endogenous insulin production with sulfonylureas and meglitinides, reducing hepatic glucose production through biguanides, and limiting postprandial glucose absorption with alpha-glucosidase inhibitors. In all of these areas, new generations of small molecules are being investigated which exhibit improved efficacy and safety profiles. Promising biological targets are also emerging such as (1) insulin sensitizers including protein tyrosine phosphatase-1B (PTP-1B) and glycogen synthase kinase 3 (GSK3), (2) inhibitors of gluconeogenesis like pyruvate dehydrogenase kinase (PDH) inhibitors, (3) lipolysis inhibitors, (4) fat oxidation including carnitine palmitoyltransferase (CPT) I and II inhibitors, and (5) energy expenditure by means of beta 3-adrenoceptor agonists. Also important are alternative routes of glucose disposal such as Na+-glucose cotransporter (SGLT) inhibitors, combination therapies, and the treatment of diabetic complications (eg. retinopathy, nephropathy, and neuropathy). With may new opportunities for drug discovery, the prospects are excellent for development of innovative therapies to effectively manage diabetes and prevent its long term complications. This review highlights recent (1997-2000) advances in diabetes therapy and research with an emphasis on small molecule drug design (275 references).
Decoupling of Distributed Consensus, Failure Detection and Agreement in SDN Control Plane (2020)

Centralized Software Defined Networking (SDN) controllers and Network Management Systems (NMS) introduce the issue of controller as a single-point of failure (SPOF). The SPOF correspondingly motivated the introduction of distributed controllers, with replicas assigned into clusters of controller instances replicated for purpose of enabling high availability. The replication of the controller state relies on distributed consensus and state synchronization for correct operation. Recent works have, however, demonstrated issues with this approach. False positives in failure detectors deployed in replicas may result in oscillating leadership and control plane unavailability.In this paper, we first elaborate the problematic scenario. We resolve the related issues by decoupling failure detector from the underlying signaling methodology and by introducing event agreement as a necessary component of the proposed design. The effectiveness of the proposed model is validated using an exemplary implementation and demonstration in the problematic scenario. We present an analytic model to describe the worst-case delay required to reliably agree on replica failures. The effectiveness of the analytic formulation is confirmed empirically using varied cluster configurations in an emulated environment. Finally, we discuss the impact of each component of our design on the replica failure- and recovery-detection delay, as well as on the imposed communication overhead.
Desensitisation of oxytocin receptors with labour-onset in isolated human myometrium (2008)

We evaluated the impact of implementing automated hepatitis C (HCV) opt-out screening in the emergency department of an urban, academic medical center with high HCV prevalence, in the context of a longstanding HCV opt-in screening model. We compared nine-month periods before and after implementation. HCV testing increased by 502%, and active HCV infection identification increased by 212%. Settings where there is great opportunity for HCV diagnosis, such as emergency department settings, should consider opt-out HCV screening models. (<i>Am J Public Health</i>. 2024;114(11):1228-1231. https://doi.org/10.2105/AJPH.2024.307783).
A neural network predicting the amplitude of the N2pc in individual EEG datasets (2021)

<i>Objective.</i>The N2pc is a small amplitude transient interhemispheric voltage asymmetry used in cognitive neuroscience to investigate subject's allocation of selective visuo-spatial attention. N2pc is typically estimated by averaging the sweeps of the electroencephalographic (EEG) signal but, in absence of explicit normative indications, the number of sweeps is often based on arbitrariness or personal experience. With the final aim of reducing duration and cost of experimental protocols, here we developed a new approach to reliably predict N2pc amplitude from a minimal EEG dataset.<i>Approach.</i>First, features predictive of N2pc amplitude were identified in the time-frequency domain. Then, an artificial neural network (NN) was trained to predict N2pc mean amplitude at the individual level. By resorting to simulated data, accuracy of the NN was assessed by computing the mean squared error (MSE) and the amplitude discretization error (ADE) and compared to the standard time averaging (TA) technique. The NN was then tested against two real datasets consisting of 14 and 12 subjects, respectively.<i>Main result.</i>In simulated scenarios entailing different number of sweeps (between 10 and 100), the MSE obtained with the proposed method resulted, on average, 1/5 of that obtained with the TA technique. Implementation on real EEG datasets showed that N2pc amplitude could be reliably predicted with as few as 40 EEG sweeps per cell of the experimental design.<i>Significance.</i>The developed approach allows to reduce duration and cost of experiments involving the N2pc, for instance in studies investigating attention deficits in pathological subjects.
Markov Approximation for Combinatorial Network Optimization (2013)

Many important network design problems are fundamentally combinatorial optimization problems. A large number of such problems, however, cannot readily be tackled by distributed algorithms. The Markov approximation framework studied in this paper is a general technique for synthesizing distributed algorithms. We show that when using the log-sum-exp function to approximate the optimal value of any combinatorial problem, we end up with a solution that can be interpreted as the stationary probability distribution of a class of time-reversible Markov chains. Selected Markov chains among this class yield distributed algorithms that solve the log-sum-exp approximated combinatorial network optimization problem. By examining three applications, we illustrate that the Markov approximation technique not only provides fresh perspectives to existing distributed solutions, but also provides clues leading to the construction of new distributed algorithms in various domains with provable performance. We believe the Markov approximation techniques will find applications in many other network optimization problems.
Electron Beam Driven Disordering in Small Particles (1996)

Small metal particles in the range of a few nanometers in diameter are seen to progressively disorder when the 100 keV electron beam of a Scanning Transmission Electron Microscope (STEM) is held stationary on the particle. The diffraction pattern of the individual particle is seen to progress from an initial array of indexable diffraction spots to a mixture of diffraction spots and amorphous-like rings and finally to rings with no persistent diffraction spots. After the electron beam is removed, the particles will recrystallize after minutes or hours. Only particles below a critical size are seen to fully disorder. We have observed this in Platinum, Palladium, Rhodium, and Iridium and based on our model of disordering process believe it is a universal effect. It has also been observed with a Platinum Ruthenium alloy. We discuss the mechanism of this disordering and the structure of the resulting disordering particle for the case of Platinum clusters.
Development of an FIA method with on-line microwave-assisted saponification of vitamin A to retinol and direct in-line spectrophotometric determination (1995)

The development of an FIA method offering on-line saponification in a microwave oven of vitamin A to its retinol form with direct in-line ultraviolet detection is described. Comparison with a batch method indicates that the proposed method offers a more rapid, simple, methodology with improved yields in the saponification process. Optimized conditions are described for the FIA method, which gave an LOD of 0.3 mg l–1 for vitamin A as retinol, a precision of between 1 and 3.8%sr, a working calibration range up to 20 ppm and a sample throughput of less than 120 s.
COMT genotype affects brain white matter pathways in attention-deficit/hyperactivity disorder (2014)

Increased dopamine availability may be associated with impaired structural maturation of brain white matter connectivity. This study aimed to derive a comprehensive, whole-brain characterization of large-scale axonal connectivity differences in attention-deficit/hyperactivity disorder (ADHD) associated with catechol-O-methyltransferase gene (COMT) Val158Met polymorphism. Using diffusion tensor imaging, whole-brain tractography, and an imaging connectomics approach, we characterized altered white matter connectivity in youth with ADHD who were COMT Val-homozygous (N = 29) compared with those who were Met-carriers (N = 29). Additionally, we examined whether dopamine transporter gene (DAT1) and dopamine D4 receptor gene (DRD4) polymorphisms were associated with white matter differences. Level of attention was assessed using the continuous performance test before and after an 8-week open-label trial of methylphenidate (MPH). A network of white matter connections linking 18 different brain regions was significantly weakened in youth with ADHD who were COMT Met-carriers compared to those who were Val-homozygous (P < 0.05, family-wise error-corrected). A measure of white matter integrity, fractional anisotropy, was correlated with impaired pretreatment performance in continuous performance test omission errors and response time variability, as well as with improvement in continuous performance test response time variability after MPH treatment. Altered white matter connectivity was exclusively based on COMT genotypes, and was not evident in DAT1 or DRD4. We demonstrated that white matter connectivity in youth with ADHD is associated with COMT Val158Met genotypes. The present findings suggest that different layers of dopamine-related genes and interindividual variability in the genetic polymorphisms should be taken into account when investigating the human connectome.
The Road to Affordable, Large-Scale Silicon Photonics (2013)

Large-scale optical systems in silicon can become a reality by building upon the existing infrastructure. Due to the shifting economics of silicon photonics, some cost-effective fabless silicon products may even emerge over the next several years.
Non-Genetic Generation of Antibody Conjugates Based on Chemoenzymatic Tyrosine Click Chemistry (2021)

The availability of tools to generate homogeneous and stable antibody conjugates without recombinant DNA technology is a valuable asset in fields spanning from <i>in vitro</i> diagnostics to <i>in vivo</i> imaging and therapeutics. We present here a general approach for the conjugation to human IgG1 antibodies, by employing a straightforward two-stage protocol based on antibody deglycosylation followed by tyrosinase-mediated <i>ortho</i>-quinone strain-promoted click chemistry. The technology is validated by the efficient and clean generation of highly potent DAR2 and DAR4 antibody-drug conjugates (ADCs) with cytotoxic payloads MMAE or PBD dimer, and their <i>in vitro</i> evaluation.
A new class of fenonic Markov word models for large vocabulary continuous speech recognition (1991)

A technique for constructing hidden Markov models for the acoustic representation of words is described. The models, built from combinations of acoustically based subword units called fenones, are derived automatically from one or more sample utterances of words. They are more flexible than previously reported fenone-based word models and lead to an improved capability of modeling variations in pronunciation. In addition, their construction is simplified, because it can be done using the well-known forward-backward algorithm for the parameter estimation of hidden Markov models. Experimental results obtained on a 5000-word vocabulary continuous speech recognition task are presented to illustrate some of the benefits associated with the new models. Multonic baseforms resulted in a reduction of 16% in the average error rate obtained for ten speakers.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>
Fabrication of silver nanoparticles with limited size distribution on TiO2 containing zeolites (2014)

Here we present a simple route to produce well-defined photo-reduced silver nanoparticles on TiO2 containing zeolites. We used natural and artificial irradiation sources to study their effect on the particle size distribution. The samples were investigated by electron microscopy, X-ray diffraction, fluorescence microscopy and UV-Vis diffuse reflectance spectroscopy.
On the design of digitally assisted voltage regulators (2015)

This paper presents a digitally assisted low-dropout voltage regulator. In lieu of the analog error amplifier, the proposed structure uses an analog-to-digital converter, a digital-to-analog converter, and a digital processor. It offers flexibility in terms of stability and regulation accuracy. The measurement results verify the performance of the proposed structure.