Rotavirus infections and climate variability in Dhaka, Bangladesh: a time-series analysis.

Attempts to explain the clear seasonality of rotavirus infections have been made by relating disease incidence to climate factors; however, few studies have disentangled the effects of weather from other factors that might cause seasonality. We investigated the relationships between hospital visits for rotavirus diarrhoea and temperature, humidity and river level, in Dhaka, Bangladesh, using time-series analysis adjusting for other confounding seasonal factors. There was strong evidence for an increase in rotavirus diarrhoea at high temperatures, by 40.2% for each 1 degrees C increase above a threshold (29 degrees C). Relative humidity had a linear inverse relationship with the number of cases of rotavirus diarrhoea. River level, above a threshold (4.8 m), was associated with an increase in cases of rotavirus diarrhoea, by 5.5% per 10-cm river-level rise. Our findings provide evidence that factors associated with high temperature, low humidity and high river-level increase the incidence of rotavirus diarrhoea in Dhaka

Movers and shakers: Granular damping in microgravity

The response of an oscillating granular damper to an initial perturbation is studied using experiments performed in microgravity and granular dynamics mulations. High-speed video and image processing techniques are used to extract experimental data. An inelastic hard sphere model is developed to perform simulations and the results are in excellent agreement with the experiments. The granular damper behaves like a frictional damper and a linear decay of the amplitude is bserved. This is true even for the simulation model, where friction forces are absent. A simple expression is developed which predicts the optimal damping conditions for a given amplitude and is independent of the oscillation frequency and particle inelasticities.Comment: 9 pages, 9 figure

Branch Module for an Inductive Voltage Adder for Driving Kicker Magnets with a Short Circuit Termination

For driving kicker magnets terminated in a short circuit, a branch module for an inductive voltage adder has been designed and assembled. The module has been designed for a maximum charging voltage of 1.2 kV and an output current of 200 A considering the current doubling due to the short circuit termination. It features three consecutive modes of operation: energy injection, freewheeling, and energy extraction. Therefore, the topology of the branch module consists of two independently controlled SiC MOSFET switches and one diode switch. In order not to extend the field rise time of the kicker magnet significantly beyond the magnet fill time, the pulse must have a fast rise time. Hence, the switch for energy injection is driven by a gate boosting driver featuring a half bridge of GaN HEMTs and a driving voltage of 80 V. Measurements of the drain source voltage of this switch showed a fall time of 2.7 ns at a voltage of 600 V resulting in a voltage rise time of 5.4 ns at the output terminated with a resistive load. To meet both the rise time and current requirements, a parallel configuration of four SiC MOSFETs was implemented

The tarantula toxin GxTx detains K+ channel gating charges in their resting conformation.

Allosteric ligands modulate protein activity by altering the energy landscape of conformational space in ligand-protein complexes. Here we investigate how ligand binding to a K+ channel's voltage sensor allosterically modulates opening of its K+-conductive pore. The tarantula venom peptide guangxitoxin-1E (GxTx) binds to the voltage sensors of the rat voltage-gated K+ (Kv) channel Kv2.1 and acts as a partial inverse agonist. When bound to GxTx, Kv2.1 activates more slowly, deactivates more rapidly, and requires more positive voltage to reach the same K+-conductance as the unbound channel. Further, activation kinetics are more sigmoidal, indicating that multiple conformational changes coupled to opening are modulated. Single-channel current amplitudes reveal that each channel opens to full conductance when GxTx is bound. Inhibition of Kv2.1 channels by GxTx results from decreased open probability due to increased occurrence of long-lived closed states; the time constant of the final pore opening step itself is not impacted by GxTx. When intracellular potential is less than 0 mV, GxTx traps the gating charges on Kv2.1's voltage sensors in their most intracellular position. Gating charges translocate at positive voltages, however, indicating that GxTx stabilizes the most intracellular conformation of the voltage sensors (their resting conformation). Kinetic modeling suggests a modulatory mechanism: GxTx reduces the probability of voltage sensors activating, giving the pore opening step less frequent opportunities to occur. This mechanism results in K+-conductance activation kinetics that are voltage-dependent, even if pore opening (the rate-limiting step) has no inherent voltage dependence. We conclude that GxTx stabilizes voltage sensors in a resting conformation, and inhibits K+ currents by limiting opportunities for the channel pore to open, but has little, if any, direct effect on the microscopic kinetics of pore opening. The impact of GxTx on channel gating suggests that Kv2.1's pore opening step does not involve movement of its voltage sensors

Sub-Nanosecond Switching of HV SiC MOS Transistors for Impact Ionisation Triggering

Pulse generators with multi kV/kA pulses are necessary for the particle accelerator environment for beam transfer magnets. Traditionally these generators are using thyratrons - until recently the only switches capable of switching such pulses within tens of ns. There is a strong demand to replace thyratrons with semiconductor switches to avoid their future obsolescence. Very promising candidates are components from the family of fast ionization dynistors triggered by impact ionization. Their sub-nanosecond switching time and extreme current densities can provide performances superior to that of thyratrons. Recent investigations showed that impact ionization triggering is feasible also in cheap industrial thyristors. The main issue is the generation of triggering pulses with slew rates in the multi kV/ns region and with the required output current for charging the parasitic capacitance of the thyristor. We present an approach of generating > 1 kV/ns pulses by ultra-boosted gate driving of HV SiC MOS transistors. We found that the MOS lifetime under these extreme triggering conditions can still reach more than 10⁸ pulses, enough for kicker generator applications

Strong-coupling effects in the relaxation dynamics of ultracold neutral plasmas

We describe a hybrid molecular dynamics approach for the description of ultracold neutral plasmas, based on an adiabatic treatment of the electron gas and a full molecular dynamics simulation of the ions, which allows us to follow the long-time evolution of the plasma including the effect of the strongly coupled ion motion. The plasma shows a rather complex relaxation behavior, connected with temporal as well as spatial oscillations of the ion temperature. Furthermore, additional laser cooling of the ions during the plasma evolution drastically modifies the expansion dynamics, so that crystallization of the ion component can occur in this nonequilibrium system, leading to lattice-like structures or even long-range order resulting in concentric shells

DEFAULT MODE NETWORK AND WORKING MEMORY NETWORK DURING AN FMRI WORKING MEMORY TASK: DIFFERENCES AND CORRELATIONS WITH BEHAVIORAL PERFORMANCE

INTRODUCTION Previous neuroimaging studies have shown that working memory load has marked effects on regional neural activation[1-5]. However, the mechanism through which working memory load modulates brain connectivity is still unclear. During a working memory task, two of the most involved networks are the default mode network (DMN) and the working memory network (WMN)[6-7]: the selective focus on these networks can be useful in better understanding the load effects. Spatial independent component analysis (ICA)[8] has becomes a reliable technique to investigate the networks involved during an fMRI task, as it extracts spatiotemporal patterns of neural activity maximizing spatial independence. A specific study, conducted with ICA, investigating on how the load and phase of a working memory task are related with the activation and response time, is nowadays lacking. The aim of this work is to use the time course of DMN and WMN, selected by means of ICA, for studying: a) how these networks are involved with the complexity of the task and the phase; b) how, in these networks, complexity and phase are correlated with reaction times. METHODS MR Data Acquisition and preprocessing Fifteen young adult healthy and right-handed were involved. The MR protocol consisted of one anatomical sequence 3D T1-weighted MP-RAGE (Voxel size: 1 x 1 x 1 mm) and three functional acquisitions of 15 minutes each performed with a T2*-weighted EPI sequence (TR/TE: 1500/30, In- plane resolution: 3.5x3.5 mm, Thickness: 3.5 mm, Nr of slices: 24, Field of view: 64 x 64 mm). All the images were collected with a Siemens Allegra 3T MR scanner (Siemens, Erlangen, Germany) and a standard head coil. During the fMRI acquisition the subjects performed a delayed spatial working memory paradigm presented with three levels of difficulty. The memory set consisted of one, three or five circles presented randomly in different locations and to the subjects were asked to judge whether or not a given target stimulus had been part of a previous memory stimulus set. Every experiment consisted of 90 working memory trials, 30 per load, divided in three runs. Data were analyzed with Brain Voyager QX. 2.4 (Brain Innovation, Maastricht, The Netherlands). FMRI preprocessing included: 3D head-motion correction, slice-scan time correction, spatial smoothing, temporal high pass filter and linear trend removal. Anatomic 3D data set was inhomogeneities corrected, filtered and transformed into Talairach coordinates and coregistered with the functional information. Independent Component Analysis This analysis was conducted using Brainvoyager QX 2.4. ICA analysis was performed on each subject\u2019s three functional acquisitions. A subsequent total ICA group analysis[9-10] was achieved by an inter- subject ICA group analysis of all the intra-subject ICA group analysis. From the obtained maps were selected two Independent Components (ICs) containing the WMN[1,2]: WMN1 defined by SPL and Precuneus, and WMN2 with DLPFC and IPS (Fig. 1b-c). Also one IC describing the DMN was considered, with PCC, IPL and MPFC (Fig. 1a)[11]. For each run of all the subjects the ICs time course was considered: three time windows of 3TR (4.5s) for each working memory task phase (encode, maintenance and retrieval) were selected taking into account the haemodynamic response by delaying the window of 5 volumes events from the start of every trial. The window time course was corrected for a baseline value. Mean values of the ICs where examined and a subsequent correlation between the mean values and the response time in every trial was estimated. A 3x3 two-way ANOVA on Fisher transformed correlation was conducted to test the variation of loads (load1=less complex, load3=more complex), phases and runs. Figure 1: Networks selected from ICA analysis (transversal view): (a) DMN, (b) WMN1 (c) WMN2. RESULTS Figure 2 exhibits window mean activities and correlations divided for phase and load. DMN mean activity is negative while WMN1-2 mean activities have opposite behaviors regarding the phase, but similar concerning with the complexity (Fig. 2a-c). DMN shows a reduction of the correlation from encode to retrieval, instead of WM1-2 where it grows (Fig. 2d-f). The ANOVA showed significant variation for the phases over all the subjects in WMN1-2, an interaction of the variation of phases and runs in WMN2 and a interaction of phases, runs and loads in DMN. DISCUSSION These findings suggest that working memory networks (WMNs), as isolated by means of IC A, display substantially opposed mean values related to a different areas specialization. WMN1 seems to be more involved in the first part of the mnemonic phase and the amount of this involvement is associated to the trial: the more complicated the task, the higher the activation with respect to baseline. On the other hand, WMN2 increases from the first to the last part of the trial and is probably more involved in the operation of retrieval. In Figure 2e-f it is also shown that in the retrieval there is a stronger correlation between WMN1-2 mean values and the response time probably because this phase is the more complex. DMN exhibits, over all the phases, smaller than zero mean values (due to the task inducted deactivation). In contrast, its correlation has a different trend and increases above zero during the maintenance, probably due to the free thought of this phase. The different behavior of load 3 is probably due to the fact that this type of complexity is totally different from the other two. In conclusion, this study shows that, by means of ICA, it is possible to isolate networks of connected regions and relate their time courses to task phases and behavioral performance. This is a promising approach to advance the understanding of connectivity modulations in several brain networks, including WMNs and DMN

Ultra-Fast Generator for Impact Ionization Triggering

Impact ionization triggering can be successfully applied to standard thyristors, thus boosting their dI/dt capability by up to 1000x. This groundbreaking triggering requires applying significant overvoltage on the anode-cathode of thyristor with a slew rate > 1kV/ns. Compact pulse generators based on commercial off-the-shelf (COTS) components would allow the spread of this technology into numerous applications, including fast kicker generators for particle accelerators. In our approach, the beginning of the triggering chain is a HV SiC MOS with an ultra-fast super-boosting gate driver. The super boosting of a 1.7kV rated SiC MOS allows to reduce the MOS rise time by a factor of > 25 (datasheet tr = §I{20}{ns} vs. measured tr 1kV/ns and an amplitude > 1kV. Additional boosting is obtained by a Marx generator with GaAs diodes, reaching an output voltage slew rate > 11kV/ns. The final stage will be a Marx generator with medium size thyristors triggered in impact ionization mode with sufficient voltage and current rating necessary for the triggering of a big thyristor. This paper presents the impact ionization triggering of a small size thyristor

Continuous measurements of greenhouse gases and atmospheric oxygen at the Namib Desert atmospheric observatory

A new coastal background site has been established for observations of greenhouse gases (GHGs) in the central Namib Desert at Gobabeb, Namibia. The location of the site was chosen to provide observations for a data-poor region in the global sampling network for GHGs. Semi-automated continuous measurements of carbon dioxide, methane, nitrous oxide, carbon monoxide, atmospheric oxygen, and basic meteorology are made at a height of 21 m a.g.l., 50 km from the coast at the northern border of the Namib Sand Sea. Atmospheric oxygen is measured with a differential fuel cell analyzer (DFCA). Carbon dioxide and methane are measured with an early-model cavity ring-down spectrometer (CRDS); nitrous oxide and carbon monoxide are measured with an off-axis integrated cavity output spectrometer (OA-ICOS). Instrument-specific water corrections are employed for both the CRDS and OA-ICOS instruments in lieu of drying. The performance and measurement uncertainties are discussed in detail. As the station is located in a remote desert environment, there are some particular challenges, namely fine dust, high diurnal temperature variability, and minimal infrastructure. The gas handling system and calibration scheme were tailored to best fit the conditions of the site. The CRDS and DFCA provide data of acceptable quality when base requirements for operation are met, specifically adequate temperature control in the laboratory and regular supply of electricity. In the case of the OA-ICOS instrument, performance is significantly improved through the implementation of a drift correction through frequent measurements of a reference cylinder

Antecedents of renal disease in aboriginal children (ARDAC study)

The aim of this study was to identify implicit cognitive predictors of aggressive behavior. Specifically, the predictive value of an attentional bias for aggressive stimuli and automatic association of the self and aggression was examined for reactive and proactive aggressive behavior in a non-clinical sample (N = 90). An Emotional Stroop Task was used to measure an attentional bias. With an idiographic Single-Target Implicit Association Test, automatic associations were assessed between words referring to the self (e.g., the participants' name) and words referring to aggression (e.g., fighting). The Taylor Aggression Paradigm (TAP) was used to measure reactive and proactive aggressive behavior. Furthermore, self-reported aggressiveness was assessed with the Reactive Proactive Aggression Questionnaire (RPQ). Results showed that heightened attentional interference for aggressive words significantly predicted more reactive aggression, while lower attentional bias towards aggressive words predicted higher levels of proactive aggression. A stronger self-aggression association resulted in more proactive aggression, but not reactive aggression. Self-reports on aggression did not additionally predict behavioral aggression. This implies that the cognitive tests employed in our study have the potential to discriminate between reactive and proactive aggression