Seizure clusters in drug-resistant focal epilepsy.

We investigated clinical factors associated with seizure clustering in patients with drug-resistant focal epilepsy and any association between seizure clustering and outcome after surgery. We performed a retrospective study including patients with a diagnosis of drug-resistant focal epilepsy who underwent epilepsy surgery. Patients were prospectively registered in a database from 1986 until 2015. Seizure cluster was defined as two or more seizures occurring within 2 days. Potential risk factors for seizure clustering were assessed. To investigate any potential association between seizure clusters and seizure outcome after surgery, time to event analysis was used to produce a Kaplan-Meier estimate of seizure recurrence. We studied 764 patients. Seizure clusters were reported in 23.6% of patients with temporal lobe epilepsy (TLE) and 16.9% of extratemporal patients (p = 0.2). We could not identify any significant clinical factors associated with seizure clustering. Among patients with TLE, those who had history of seizure clusters fared better after surgery (p \u3c 0.01). We found that seizure clusters relate to prognosis after temporal lobe surgery in drug-resistant TLE. These data may provide added value for surgical prognostication when combined with other data types. A better understanding of the neurobiology underlying seizure clusters is needed

Fast and accurate con-eigenvalue algorithm for optimal rational approximations

The need to compute small con-eigenvalues and the associated con-eigenvectors of positive-definite Cauchy matrices naturally arises when constructing rational approximations with a (near) optimally small $L^{\infty}$ error. Specifically, given a rational function with $n$ poles in the unit disk, a rational approximation with $m\ll n$ poles in the unit disk may be obtained from the $m$th con-eigenvector of an $n\times n$ Cauchy matrix, where the associated con-eigenvalue $\lambda_{m}>0$ gives the approximation error in the $L^{\infty}$ norm. Unfortunately, standard algorithms do not accurately compute small con-eigenvalues (and the associated con-eigenvectors) and, in particular, yield few or no correct digits for con-eigenvalues smaller than the machine roundoff. We develop a fast and accurate algorithm for computing con-eigenvalues and con-eigenvectors of positive-definite Cauchy matrices, yielding even the tiniest con-eigenvalues with high relative accuracy. The algorithm computes the $m$th con-eigenvalue in $\mathcal{O}(m^{2}n)$ operations and, since the con-eigenvalues of positive-definite Cauchy matrices decay exponentially fast, we obtain (near) optimal rational approximations in $\mathcal{O}(n(\log\delta^{-1})^{2})$ operations, where $\delta$ is the approximation error in the $L^{\infty}$ norm. We derive error bounds demonstrating high relative accuracy of the computed con-eigenvalues and the high accuracy of the unit con-eigenvectors. We also provide examples of using the algorithm to compute (near) optimal rational approximations of functions with singularities and sharp transitions, where approximation errors close to machine precision are obtained. Finally, we present numerical tests on random (complex-valued) Cauchy matrices to show that the algorithm computes all the con-eigenvalues and con-eigenvectors with nearly full precision

A new role for exhaled nitric oxide as a functional marker of peripheral airway caliber changes: a theoretical study

Though considered as an inflammation marker, exhaled nitric oxide (FENO) was shown to be sensitive to airway caliber changes to such an extent that it might be considered as a marker of them. It is thus important to understand how these changes and their localization mechanically affect the total NO flux penetrating the airway lumen (JawNO), hence FENO, independently from any inflammatory status change. A new model was used which simulates NO production, consumption and diffusion inside the airway epithelium wall, then, NO excretion through the epithelial wall into the airway lumen and, finally, its axial transport by diffusion and convection in the airway lumen. This model may also consider the presence of a mucus layer coating the epithelial wall. Simulations were performed that showed the great sensitivity of JawNO to peripheral airways caliber changes. Moreover, FENO showed distinct behaviors depending on the location of the caliber change. Considering a bronchodilation, absence of FENO change was associated with dilation of central airways, FENO increase with dilation up to pre-acinar small airways, and FENO decrease with intra-acinar dilation due to amplification of the back-diffusion flux. The presence of a mucus layer was also shown to play a significant role in FENO changes. Altogether, the present work provides theoretical evidences that specific FENO changes in acute situations are linked to specifically located airway caliber changes in the lung periphery. This opens the way for a new role for FENO as a functional marker of peripheral airway caliber change

Prandtl-Meyer flow tables for parahydrogen at total temperatures from 30K to 290K and for nitrogen at total temperatures from 100K to 300K at total pressures from 1 ATM to 10 ATM

The dependency of Mach number on the Prandtl-Meyer function was numerically determined by iterating the Prandtl-Meyer function and applying the Muller method to converge on the Mach number for flows in cryogenic parahydrogen and nitrogen at various total pressures and total temperatures. The results are compared with the ideal diatomic gas values and are presented in tabular form

Tables of isentropic expansions of parahydrogen and related transport properties for total temperatures from 25 K to 300 K and for total pressures from 1 ATM to 10 ATM

The isentropic expansions of parahydrogen at various total pressures and total temperatures were numerically determined by iterating Mach number and by using a modified interval halving method. The calculated isentropic values and related properties are presented in tabulated form

A Decentralized Parallelization-in-Time Approach with Parareal

With steadily increasing parallelism for high-performance architectures, simulations requiring a good strong scalability are prone to be limited in scalability with standard spatial-decomposition strategies at a certain amount of parallel processors. This can be a show-stopper if the simulation results have to be computed with wallclock time restrictions (e.g.\,for weather forecasts) or as fast as possible (e.g. for urgent computing). Here, the time-dimension is the only one left for parallelization and we focus on Parareal as one particular parallelization-in-time method. We discuss a software approach for making Parareal parallelization transparent for application developers, hence allowing fast prototyping for Parareal. Further, we introduce a decentralized Parareal which results in autonomous simulation instances which only require communicating with the previous and next simulation instances, hence with strong locality for communication. This concept is evaluated by a prototypical solver for the rotational shallow-water equations which we use as a representative black-box solver

SLIDES: The EFD Program: Addressing Environmental Issues and Increasing Environmental Awareness

Presenter: Rich Haut, Houston Advanced Research Center 8 slide

SLIDES: Environmentally Friendly Drilling Systems Program

Presenter: Rich Haut, Houston Advanced Research Center 6 slide

Investigation of DNA methylation turnover in pluripotency and early differentiation

Throughout embryonic development, cells undergo a series of lineage decisions, accompanied by morphological and functional changes, culminating in the formation of a complete organism. This intricate process is orchestrated by a complex interplay of diverse genetic and epigenetic mechanisms, including DNA methylation. After major changes shaping the somatic DNA methylome in the pre-implantation embryo, this modification remains globally stable, with local alterations occurring in a tissue-specific manner, often associated with putative genetic regulatory elements. However, in human pluripotent stem cells (hPSCs), thousands of highly methylated regions are targeted by DNA demethylases (TETs), whose local demethylation activity is counteracted by de novo methyltransferases (DNMT3s), resulting in a delicate balance referred to as DNA methylation turnover. What is the molecular mechanism and its functional role during pluripotency and developmental progression remains elusive. In my doctoral work, I combined experimental and analytical approaches to investigate the emergence and regulation of DNA methylation turnover during human pluripotency and early differentiation. I revealed that this dynamic mechanism substantially occurs at regions that undergo demethylation during in vitro three germ-layer differentiation, but that it is also active at genomic loci linked to mature lineage decisions. Importantly, I described the establishment of de novo DNA methylation turnover in transient progenitor populations for the first time, suggesting an extended regulative role of the DNA methylation turnover beyond pluripotency. Furthermore, I provide functional evidence that pluripotency-associated DNA methylation turnover regions have enhancer activity in differentiated cells, implying a potential functional regulatory role of the turnover. Regarding transposable elements, my analysis confirms that the DNA methylation turnover is highly target-specific. In particular, I reveal that the evolutionary young ERV1 LTR7up1/2 and the hominoid-specific ERVK LTR5-Hs subfamilies of the long terminal repeat (LTR) retrotransposons are prominently targeted by the DNA methylation turnover in hPSCs. Interestingly, specifically these subfamilies were previously shown to be bound by pluripotency factors, including NANOG, providing a possible underlying mechanism behind the turnover during pluripotency. Lastly, I generated various genetically modified hPSCs lines to experimentally dissect the functional role of TETs and DNMT3s at turnover targets. Thus, my work provides a valuable toolkit and an unexplored analytical angle into the target-specific regulation of DNA methylation turnover, emphasizing its potential role for human cell differentiation during embryonic development