Anatomical and molecular properties of long descending propriospinal neurons in mice

Long descending propriospinal neurons (LDPNs) are interneurons that form direct connections between cervical and lumbar spinal circuits. LDPNs are involved in interlimb coordination and are important mediators of functional recovery after spinal cord injury (SCI). Much of what we know about LDPNs comes from a range of species, however, the increased use of transgenic mouse lines to better define neuronal populations calls for a more complete characterisation of LDPNs in mice. In this study, we examined the cell body location, inhibitory neurotransmitter phenotype, developmental provenance, morphology and synaptic inputs of mouse LDPNs throughout the cervical and upper thoracic spinal cord. LDPNs were retrogradely labelled from the lumbar spinal cord to map cell body locations throughout the cervical and upper thoracic segments. Ipsilateral LDPNs were distributed throughout the dorsal, intermediate and ventral grey matter as well as the lateral spinal nucleus and lateral cervical nucleus. In contrast, contralateral LDPNs were more densely concentrated in the ventromedial grey matter. Retrograde labelling in GlyT2GFP and GAD67GFP mice showed the majority of inhibitory LDPNs project either ipsilaterally or adjacent to the midline. Additionally, we used several transgenic mouse lines to define the developmental provenance of LDPNs and found that V2b positive neurons form a subset of ipsilaterally projecting LDPNs. Finally, a population of Neurobiotin (NB) labelled LDPNs were assessed in detail to examine morphology and plot the spatial distribution of contacts from a variety of neurochemically distinct axon terminals. These results provide important baseline data in mice for future work on their role in locomotion and recovery from SCI

Outsmart supply dips in renewable energy

Integrating intermittent renewable-energy supplies into existing electricity grids in a stable way will depend on artificial intelligence. Such a system could process massive volumes of consumption data and adjust power usage almost instantly, giving real-time control over supply and demand. Domestic consumers would be rewarded (with cheaper bills) for shifting their energy demand at short notice when the grid has a power imbalance, as is already the case for large industrial consumers and grid-scale storage systems. Smart meters that collect household consumption data would enable this process. By 2020, the United Kingdom aims to have such meters in 26 million homes and the European Union has a target of 200 million. These meters would contain microcontroller devices that communicate wirelessly with the grid. The meter could then momentarily dim lighting or switch off electric heaters, for example, without discomforting the occupiers. The efficiency of this process will depend on demand predictions for individual consumers, which involves using large amounts of data to model people's energy constraints and preferences over time. Embedded artificial intelligence will analyse and model these consumption data, enabling the grid response to occur within seconds

Toward a comprehensive system for constructing compartmental epidemic models

Compartmental models are valuable tools for investigating infectious diseases. Researchers building such models typically begin with a simple structure where compartments correspond to individuals with different epidemiological statuses, e.g., the classic SIR model which splits the population into susceptible, infected, and recovered compartments. However, as more information about a specific pathogen is discovered, or as a means to investigate the effects of heterogeneities, it becomes useful to stratify models further -- for example by age, geographic location, or pathogen strain. The operation of constructing stratified compartmental models from a pair of simpler models resembles the Cartesian product used in graph theory, but several key differences complicate matters. In this article we give explicit mathematical definitions for several so-called ``model products'' and provide examples where each is suitable. We also provide examples of model stratification where no existing model product will generate the desired result

Rubidium in Metal-Deficient Disk and Halo Stars

We report the first extensive study of stellar Rb abundances. High-resolution spectra have been used to determine, or set upper limits on, the abundances of this heavy element and the associated elements Y, Zr, and Ba in 44 dwarfs and giants with metallicities spanning the range -2.0 <[Fe/H] < 0.0. In metal-deficient stars Rb is systematically overabundant relative to Fe; we find an average [Rb/Fe] of +0.21 for the 32 stars with [Fe/H] < -0.5 and measured Rb. This behavior contrasts with that of Y, Zr, and Ba, which, with the exception of three new CH stars (HD 23439A and B and BD +5 3640), are consistently slightly deficient relative to Fe in the same stars; excluding the three CH stars, we find the stars with [Fe/H] < -0.5 have average [Y/Fe], [Zr/Fe], and [Ba/Fe] of --0.19 (24 stars), --0.12 (28 stars), and --0.06 (29 stars), respectively. The different behavior of Rb on the one hand and Y, Zr, and Ba on the other can be attributed in part to the fact that in the Sun and in these stars Rb has a large r-process component while Y, Zr, and Ba are mostly s-process elements with only small r-process components. In addition, the Rb s-process abundance is dependent on the neutron density at the s-processing site. Published observations of Rb in s-process enriched red giants indicate a higher neutron density in the metal-poor giants. These observations imply a higher s-process abundance for Rb in metal-poor stars. The calculated combination of the Rb r-process abundance, as estimated for the stellar Eu abundances, and the s-process abundance as estimated for red giants accounts satisfactorily for the observed run of [Rb/Fe] with [Fe/H].Comment: 23 pages, 5 tables, 7 figure

An inflammation based score can optimize the selection of patients with advanced cancer considered for early phase clinical trials.

Background: Adequate organ function and good performance status (PS) are common eligibility criteria for phase I trials. As inflammation is pathogenic and prognostic in cancer we investigated the prognostic performance of inflammation-based indices including the neutrophil (NLR) and platelet to lymphocyte ratio (PLR). Methods: We studied inflammatory scores in 118 unselected referrals. NLR normalization was recalculated at disease reassessment. Each variable was assessed for progression-free (PFS) and overall survival (OS) on uni- and multivariate analyses and tested for 90 days survival (90DS) prediction using receiving operator curves (ROC). Results: We included 118 patients with median OS 4.4 months, 23% PS>1. LDH 65450 and NLR 655 were multivariate predictors of OS (p<0.001). NLR normalization predicted for longer OS (p<0.001) and PFS (p<0.05). PS and NLR ranked as most accurate predictors of both 90DS with area under ROC values of 0.66 and 0.64, and OS with c-score of 0.69 and 0.60. The combination of NLR+PS increased prognostic accuracy to 0.72. The NLR was externally validated in a cohort of 126 subjects. Conclusions: We identified the NLR as a validated and objective index to improve patient selection for experimental therapies, with its normalization following treatment predicting for a survival benefit of 7 months. Prospective validation of the NLR is warranted. Copyright: \ua9 2014 Pinato et al

Data analysis of battery storage systems

Battery energy storage systems can assist distribution network operators (DNOs) to face the challenges raised by the substantial increase in distributed renewable generation. A challenge is that these resources are intermittent and often ‘invisible‘ to the DNO. If not monitored, the aggregate size of small embedded generation resources can cause thermal wearing of distribution assets and voltage excursions, especially in sunny/windy periods with insufficient local demand. Several developers of energy storage solutions, with technologies such as lithium-ion (Li-ion) batteries, offer their products to address peak shaving, frequency and voltage control needs within the network. Once deployed within the energy network batteries experience capacity degradation with usage, these companies will need to incorporate methods from prognostics and health management (PHM) in order to better manage their products. The main deliverable of this project

The extended tails of Palomar 5: A ten degree arc of globular cluster tidal debris

Using wide-field photometric data from the Sloan Digital Sky Survey (SDSS) we recently showed that the Galactic globular cluster Palomar 5 is in the process of being tidally disrupted. Its tidal tails were initially detected in a 2.5 degree wide band along the celestial equator. A new analysis of SDSS data for a larger field now reveals that the tails of Pal 5 have a much larger spatial extent and can be traced over an arc of 10 deg across the sky, corresponding to a projected length of 4 kpc at the distance of the cluster. The number of former cluster stars found in the tails adds up to about 1.2 times the number of stars in the cluster. The radial profile of stellar surface density in the tails follows approximately a power law r^gamma with -1.5 < gamma < -1.2. The stream of debris from Pal 5 is significantly curved, which demonstrates its acceleration by the Galactic potential. The cluster is presently near the apocenter but has repeatedly undergone disk crossings in the inner part of the Galaxy leading to strong tidal shocks. Our results suggest that the observed debris originates mostly from mass loss within the last 2 Gyrs. The cluster is likely to be destroyed after the next disk crossing, which will happen in about 100 Myr. (abridged)Comment: 44 pages, including 14 figures (Figs.1,3 & 14 with decreased resolution), accepted for publication in the Astronomical Journa

A multi-sectoral approach to modelling community energy demand of the built environment

This paper examines the major challenges associated with evaluating energy demand in the residential building sector in an integrated energy system modelling environment. Three established modelling fields are examined to generate a framework for assessing the impact of energy policy: energy system models, building stock models and dynamic building simulation. A set of profound challenges emerge when attempting to integrate such models, due to distinct differences in their intended applications, operational scales, formulations and computational implementations. Detailed discussions are provided on the integration of temporally refined energy demand, based on thermodynamic processes and socio-technical effects which may stem from new policy. A detailed framework is discussed for generating aggregate residential demands, in terms of space heating demand, domestic hot water demand, and lighting, appliance and consumer electronics demand. The framework incorporates a pathway for interpreting the effects of changes in household behaviour resulting from prospective policy measures. When long-term planning exercises are carried out using this framework, the cyclic effects between behavioural change and policy implementation are also considered. This work focused specifically on the United Kingdom energy system, however parallels can be drawn with other countries, in particular those with a mature privatised system, dominated by space heating concerns

Detection of a glitch in the pulsar J1709-4429

We report the detection of a glitch event in the pulsar J1709$-$4429 (also known as B1706$-$44) during regular monitoring observations with the Molonglo Observatory Synthesis Telescope (UTMOST). The glitch was found during timing operations, in which we regularly observe over 400 pulsars with up to daily cadence, while commensally searching for Rotating Radio Transients, pulsars, and FRBs. With a fractional size of $\Delta\nu/\nu \approx 52.4 \times10^{-9}$, the glitch reported here is by far the smallest known for this pulsar, attesting to the efficacy of glitch searches with high cadence using UTMOST.Comment: 3 pages, 1 figur