A study of the time course of fructose-2, 6-bisphosphate production in a septic mouse model.

Where sepsis occurs in the post-surgical period, mortality rates tend to be high. In sepsis, metabolism is grossly disrupted with glucose becoming the preferred fuel for energy provision even where ketogenesis has been promoted

Introduction

What are the strategies, modalities and aspirations of island-based, stateless nationalist and regionalist parties in the twenty-first century? Political independence is now easier to achieve, even by the smallest of territories; yet, it is not so likely to be pursued with any vigour by the world's various persisting sub-national (and mainly island) jurisdictions. Theirs is a pursuit of different expressions of sub-national autonomy, stopping short of independence. And yet, a number of independence referenda are scheduled, including one looming in Scotland in autumn 2014

A different appetite for sovereignty? Independence movements in subnational island jurisdictions

Local autonomy in a subnational jurisdiction is more likely to be gained, secured or enhanced where there are palpable movements or political parties agitating for independence in these smaller territories. A closer look at the fortunes, operations and dynamics of independence parties from subnational island jurisdictions can offer some interesting insights on the appetite for sovereignty and independence, but also the lack thereof, in the twenty-first century.peer-reviewe

Highly selective population of spin-orbit levels in electronic autoionization of O₂

The dynamics of electronic autoionization in O2 has been studied using a new apparatus which combines a free-jet supersonic expansion with synchrotron radiation. Ions and electrons were analyzed by a double time-of-flight spectrometer. The spin-orbit sublevels of the 3Πu (v=0 and 2) Rydberg states in O2 were selectively excited and the resulting O+2 final states were determined by time-of-flight photoelectron spectros copy. A strong variation of the 2Π1/2g :2Π3/2g branching ratio was observed. This variation results from the selection of a single continuum wave function in the autoionization process

Pulsed-field ionization threshold photoelectron spectroscopy with coherent extreme ultraviolet radiation: A comparison of CO and N_2

Single‐photon zero‐kinetic‐energy pulsed‐field‐ionization spectra have been measured for the v^+=0 and 1 levels of CO^+ (X  ^2Σ^+) and the v^+=0 level of N_2^+ (X  ^2Σ_g^+) by coherent XUV radiation. In spite of similarities in the electronic structure of CO and N_2, the measured ion spectra show dramatically different intensities for the Q branches. These threshold spectra are interpreted on the basis of ab initio calculations of the ion rotational distributions. Agreement between the calculated and measured spectra is very encouraging. Improved values for the ionization potentials of CO (113 025.6 and 115 211.2±1.5 cm^(−1) for v^+=0 and 1, respectively) are reported and the unusual dynamics favoring ΔN<0 transitions are discussed. The CO spectra show quite different behavior for the ΔN<0 transitions for v^+=0 and v^+=1 bands, which is interpreted in terms of the relative importance of rotational autoionization in the two bands

A convolutional neural network based deep learning methodology for recognition of partial discharge patterns from high voltage cables

It is a great challenge to differentiate partial discharge (PD) induced by different types of insulation defects in high-voltage cables. Some types of PD signals have very similar characteristics and are specifically difficult to differentiate, even for the most experienced specialists. To overcome the challenge, a convolutional neural network (CNN)-based deep learning methodology for PD pattern recognition is presented in this paper. First, PD testing for five types of artificial defects in ethylene-propylene-rubber cables is carried out in high voltage laboratory to generate signals containing PD data. Second, 3500 sets of PD transient pulses are extracted, and then 33 kinds of PD features are established. The third stage applies a CNN to the data; typical CNN architecture and the key factors which affect the CNN-based pattern recognition accuracy are described. Factors discussed include the number of the network layers, convolutional kernel size, activation function, and pooling method. This paper presents a flowchart of the CNN-based PD pattern recognition method and an evaluation with 3500 sets of PD samples. Finally, the CNN-based pattern recognition results are shown and the proposed method is compared with two more traditional analysis methods, i.e., support vector machine (SVM) and back propagation neural network (BPNN). The results show that the proposed CNN method has higher pattern recognition accuracy than SVM and BPNN, and that the novel method is especially effective for PD type recognition in cases of signals of high similarity, which is applicable for industrial applications