Synthesis and thermal decomposition of potassium tetraamidoboranealuminate,K[Al(NH2BH3)4]

A new potassium tetraamidoboranealuminate, K[Al(NH₂BH₃)₄], has been synthesized by a mechanochemical reaction between KAlH₄ and NH₃BH₃. The compound, K[Al(NH₂BH₃)₄], crystallizes in a triclinic unit cell with space group symmetry P?1. The crystal structure consists of [K(NH₂BH₃)₆]^5? octahedra which facilitate the bridging between K⁺ in 1D chains, while also bridging K⁺ to Al³⁺ to connect the 1D chains in a 3D network. Thermal analysis reveals that K[Al(NH₂BH₃)₄] decomposes in two exothermic steps at T ～ 94 and 138 °C and releases primarily hydrogen. The total gas release amounts to ～6.0 wt% H₂. The decomposition products are investigated ex situ by powder X-ray diffraction, infrared spectroscopy, and ¹¹B and ²⁷Al NMR and identified as KBH₄ and amorphous phases, possibly BN₃, N₂BH, and/or NBH₂ whereas aluminum is found in four-, five-, and six-fold coordination. Unfortunately, the decomposed sample shows no hydrogen absorption at T = 260 °C and p(H₂) = 110 bar.     

Dynamic forecasting of individual cow milk yield in automatic milking systems

Accurate forecasting of dairy cow milk yield is useful to dairy farmers, both in relation to financial planning and for detection of deviating yield patterns, which can be an indicator of mastitis and other diseases. In this study we developed a dynamic linear model (DLM) designed to forecast milk yields of individual cows per milking, as they are milked in milking robots. The DLM implements a Wood's function to account for the expected total daily milk yield. It further implements a second-degree polynomial function to account for the effect of the time intervals between milkings on the proportion of the expected total daily milk yield. By combining these 2 functions in a dynamic framework, the DLM was able to continuously forecast the amount of milk to be produced in a given milking. Data from 169,774 milkings on 5 different farms in 2 different countries were used in this study. A separate farm-specific implementation of the DLM was made for each of the 5 farms. To determine which factors would influence the forecast accuracy, the standardized forecast errors of the DLM were described with a linear mixed effects model (lme). This lme included lactation stage (early, middle, or late), somatic cell count (SCC) level (nonelevated or elevated), and whether or not the proper farm-specific version of the DLM was used. The standardized forecast errors of the DLM were only affected by SCC level and interactions between SCC level and lactation stage. Therefore, we concluded that the implementation of Wood's function combined with a second-degree polynomial is useful for dynamic modeling of milk yield in milking robots, and that this model has potential to be used as part of a mastitis detection system.     

A multiscale approach to network event identification using geolocated twitter data

The large volume of data associated with social networks hinders the unaided user from interpreting network content in real time. This problem is compounded by the fact that there are limited tools available for enabling robust visual social network exploration. We present a network activity visualization using a novel aggregation glyph called the clyph. The clyph intuitively combines spatial, temporal, and quantity data about multiple network events. We also present several case studies where major network events were easily identified using clyphs, establishing them as a powerful aid for network users and owners.     

Effect of initial joint position on nerve-cuff recordings of muscleafferents in rabbits

The objective was to characterize nerve-cuff recordings of muscle afferents to joint rotation over a large part of the physiological joint range. This information is needed to develop control strategies for functional electrical stimulation (FES) systems using muscle afferent signals for sensory feedback. Five acute rabbit experiments were performed. Tripolar cuff electrodes were implanted around the tibial and peroneal divisions of the sciatic nerve in the rabbit's left leg. The electroneurograms (ENG) were recorded during passive ankle rotation, using a ramp-and-hold profile starting at seven different joint positions (excursion=5°, velocity=10°/s, initial positions 60°, 70°, 80°, 90°, 100°, 110°, and 120°). The amplitude of the afferent activity was dependent on the initial joint position. The steady-state sensitivity of both nerve responses increased with increasing joint flexion, whereas the dynamic sensitivity increased initially but then decreased. The results indicate that recordings of the muscle afferents may provide reliable information over only a part of the physiological joint range, Despite this limitation, muscle afferent activity may be useful for motion feedback if the movement to be controlled is within a narrow joint range such as postural sway     

Energy demand in the Norwegian building stock: Scenarios on potential reduction

A model has been developed for studying the effect of three hypothetical approaches in reducing electricity and energy demand in the Norwegian building stock: wide diffusion of thermal carriers, heat pumps and conservation measures, respectively. Combinations of these are also considered. The model has a demand side perspective, considers both residential and service sectors, and calculates energy flows from net to delivered energy. Energy demand is given by the product of activity and intensity matrices. The activity levels are defined for the stock and the new construction, renovation and demolition flows. The intensity properties are defined in archetypes, and are the result of different energy class and heating carriers share options. The scenarios are shaped by combining the activity flows with different archetypes. The results show that adopting conservation measures on a large scale does allow reducing both electricity and total energy demand from present day levels while the building stock keeps growing. The results also highlight the importance of making a clear distinction between the assumptions on intensity and activity levels.     

Uncertainty and sensitivity analyses as a validation tool for BWR bundle thermal-hydraulic predictions

In recent years, more realistic safety analyses of nuclear reactors have been based on best estimate (BE) computer codes. The need to validate and refine BE codes that are used in the predictions of relevant reactor safety parameters, led to the organization of international benchmarks based on high quality experimental data. The OECD/NRC BWR full-size fine-mesh bundle test (BFBT) benchmark offers a good opportunity to assess the accuracy of thermal-hydraulic codes in predicting, among other parameters, single and two phase bundle pressure drop, cross-sectional averaged void fraction distributions and critical powers under a wide range of system conditions. The BFBT is based on a multi-rod assembly integral test facility which is able to simulate the high pressure, high temperature fluid conditions found in BWRs through electrically heated rod bundles. Since code accuracy is unavoidably affected by models and experimental uncertainties, an uncertainty analysis is fundamental in order to have a complete validation study. In this paper, statistical uncertainty and sensitivity analyses are used to validate the thermal-hydraulic features of the POLCA-T code, based on a one dimensional model of the following macroscopic BFBT exercises: (1) single and two phase bundle pressure drop, (2) steady-state cross-sectional averaged void fraction, (3) transient cross-sectional averaged void fraction and (4) steady-state critical power tests. The Latin hypercube sampling (LHS) strategy was chosen since it densely stratifies across the range of each uncertain input probability distribution, allowing a much better coverage of the input uncertainties than simple random sampling (SRS). The results show that POLCA-T predictions on pressure drop and void fractions under a wide range of conditions are within the validation limits imposed by the uncertainty analysis, while the accuracy of critical power predictions depends much on the boundary and input conditions.     

Measuring spatial dispersion: exact results on the variance of random spatial distributions

Measuring the spatial distribution of locations of many entities (trees, atoms, economic activities, etc.), and, more precisely, the deviations from purely random configurations, is a powerful method to unravel their underlying interactions. Several coefficients have been developed in the past to quantify the possible deviations. It is important to quantify the variances of the coefficients for random distributions, to ascertain the statistical significance of an empirical deviation. By lack of a proper analytical expression, the significance is usually obtained by simulating many random configurations by Monte Carlo simulations. In the present paper, we present an exact analytical expression for the variance of several spatial coefficients for random distributions, and we rigorously show that these distributions asymptotically follow a Normal law. These two results eliminate the need for cumbersome Monte Carlo simulations. They also allow to understand qualitatively the main factors that may change the variance: number of sites, spatial inhomogeneity, etc.     

A multi-scale model for solute transport in a wavy-walled channel

This paper concerns steady flow and solute uptake in a wavy-walled channel, where the wavelength and amplitude of the wall are comparable to each other but are much shorter than the width of the channel. The problem has two primary asymptotic regions: a core region where the walls appear flat at leading order and a wall region where there is full interaction between advection, diffusion and uptake at the wavy wall. For weak wall uptake, the effective uptake from the core is shown to increase with wall waviness in proportion to surface area, whereas for stronger wall uptake, it is found that the uptake from the core can be reduced as the wall amplitude increases. Conditions are identified under which this approximation is uniformly valid in a full channel flow, accounting for inlet conditions, and a comprehensive survey of the asymptotic distributions of solute both along and across the channel is provided. It is also shown how this multiscale approach can readily be extended to account for channel walls with multiple lengthscales of spatial variation.     

In vivo validation of a blood vector velocity estimator with MR angiography

Conventional Doppler methods for blood velocity estimation only estimate the velocity component along the ultrasound beam direction. This implies that a Doppler angle under examination close to 90° results in unreliable information about the true blood direction and blood velocity. The novel method transverse oscillation (TO), which combines estimates of the axial and the transverse velocity components in the scan plane, makes it possible to estimate the vector velocity of the blood regardless of the Doppler angle. The present study evaluates the TO method with magnetic resonance phase contrast angiography (MRA) by comparing in vivo measurements of stroke volume. Eleven healthy volunteers were included in this prospective study. From the obtained data sets recorded with the 2 modalities, vector velocity sequences were constructed and stroke volume calculated. Angle of insonation was approximately 90° for TO measurements. The correlation between the stroke volume estimated by TO and MRA was 0.91 (p < 0.01) with the equation for the line of regression: MRA = 1.1?TO-0.4. A Bland-Altman plot was additionally constructed where the mean difference was 0.2 ml with limits of agreement at ?1.4 ml and 1.9 ml. The results indicate that reliable vector velocity estimates can be obtained in vivo using the presented angle-independent 2-D vector velocity method. The TO method can be a useful alternative to conventional Doppler systems by avoiding the angle artifact, thus giving quantitative velocity information.