The role of DSM + C to facilitate the integration of renewable energy and low carbon energy technologies

Recent legislation and building regulations have aiming to reduce the energy demands of buildings and include renewable based micro-generation technologies. Due to the variations in energy delivery from these technologies, optimised control over building plant and loads is essential if we are to achieve a good demand-supply match and achieve a reduction in energy demands. This paper reports on research being undertaken as part of the UK EPSRC SuperGen Future Networks programme, specifically relating to the development of algorithms for simulating dynamic demand side control strategies to identify demand-supply matching options when deploying building integrated renewable energy and low carbon technologies. The development of demand side management and control (DSM+c) is a means to improve the dynamic demand-supply match taking account of the available demand side management capacity and time of occurrence. The principle of the developed DSM+c algorithms is to maximise the available control capacity which will enable a better demand-supply match while minimising any impact on users. This paper will demonstrate the application of DSM+c to improve the energy efficiency of a building (e.g. reduced total capacity), restructure the demand pattern via load shifting and switching (e.g. on/off or proportional control) to one more favourable to building integrated renewables. The impact of different control strategies on demand profile restructuring will be demonstrated using simulation to alter the settings of the DSM+c parameters - such as priority, methods and periods - for a given demand profile. The paper will conclude by presenting the outcomes from a case study using the decision support/design tool, MERIT where the developed DSM+c algorithms have been implemented to better facilitate the match between demand and building integrated clean energy supply technologies at the individual multi-familiy building level

MHCII-mediated dialog between group 2 innate lymphoid cells and CD4+ T cells potentiates type 2 immunity and promotes parasitic helminth expulsion

Group 2 innate lymphoid cells (ILC2s) release interleukin-13 (IL-13) during protective immunity to helminth infection and detrimentally during allergy and asthma. Using two mouse models to deplete ILC2s in vivo, we demonstrate that T helper 2 (Th2) cell responses are impaired in the absence of ILC2s. We show that MHCII-expressing ILC2s interact with antigen-specific T cells to instigate a dialog in which IL-2 production from T cells promotes ILC2 proliferation and IL-13 production. Deletion of MHCII renders IL-13-expressing ILC2s incapable of efficiently inducing Nippostrongylus brasiliensis expulsion. Thus, during transition to adaptive T cell-mediated immunity, the ILC2 and T cell crosstalk contributes to their mutual maintenance, expansion and cytokine production. This interaction appears to augment dendritic-cell-induced T cell activation and identifies a previously unappreciated pathway in the regulation of type-2 immunity

Evidence of Color Coherence Effects in W+jets Events from ppbar Collisions at sqrt(s) = 1.8 TeV

We report the results of a study of color coherence effects in ppbar collisions based on data collected by the D0 detector during the 1994-1995 run of the Fermilab Tevatron Collider, at a center of mass energy sqrt(s) = 1.8 TeV. Initial-to-final state color interference effects are studied by examining particle distribution patterns in events with a W boson and at least one jet. The data are compared to Monte Carlo simulations with different color coherence implementations and to an analytic modified-leading-logarithm perturbative calculation based on the local parton-hadron duality hypothesis.Comment: 13 pages, 6 figures. Submitted to Physics Letters

Search for the standard model Higgs boson decaying into two photons in pp collisions at sqrt(s)=7 TeV

A search for a Higgs boson decaying into two photons is described. The analysis is performed using a dataset recorded by the CMS experiment at the LHC from pp collisions at a centre-of-mass energy of 7 TeV, which corresponds to an integrated luminosity of 4.8 inverse femtobarns. Limits are set on the cross section of the standard model Higgs boson decaying to two photons. The expected exclusion limit at 95% confidence level is between 1.4 and 2.4 times the standard model cross section in the mass range between 110 and 150 GeV. The analysis of the data excludes, at 95% confidence level, the standard model Higgs boson decaying into two photons in the mass range 128 to 132 GeV. The largest excess of events above the expected standard model background is observed for a Higgs boson mass hypothesis of 124 GeV with a local significance of 3.1 sigma. The global significance of observing an excess with a local significance greater than 3.1 sigma anywhere in the search range 110-150 GeV is estimated to be 1.8 sigma. More data are required to ascertain the origin of this excess.Comment: Submitted to Physics Letters

Measurement of isolated photon production in pp and PbPb collisions at sqrt(sNN) = 2.76 TeV

Isolated photon production is measured in proton-proton and lead-lead collisions at nucleon-nucleon centre-of-mass energies of 2.76 TeV in the pseudorapidity range |eta|<1.44 and transverse energies ET between 20 and 80 GeV with the CMS detector at the LHC. The measured ET spectra are found to be in good agreement with next-to-leading-order perturbative QCD predictions. The ratio of PbPb to pp isolated photon ET-differential yields, scaled by the number of incoherent nucleon-nucleon collisions, is consistent with unity for all PbPb reaction centralities.Comment: Submitted to Physics Letters

The Complete Chloroplast Genome Sequence of Date Palm (Phoenix dactylifera L.)

BACKGROUND: Date palm (Phoenix dactylifera L.), a member of Arecaceae family, is one of the three major economically important woody palms--the two other palms being oil palm and coconut tree--and its fruit is a staple food among Middle East and North African nations, as well as many other tropical and subtropical regions. Here we report a complete sequence of the data palm chloroplast (cp) genome based on pyrosequencing. METHODOLOGY/PRINCIPAL FINDINGS: After extracting 369,022 cp sequencing reads from our whole-genome-shotgun data, we put together an assembly and validated it with intensive PCR-based verification, coupled with PCR product sequencing. The date palm cp genome is 158,462 bp in length and has a typical quadripartite structure of the large (LSC, 86,198 bp) and small single-copy (SSC, 17,712 bp) regions separated by a pair of inverted repeats (IRs, 27,276 bp). Similar to what has been found among most angiosperms, the date palm cp genome harbors 112 unique genes and 19 duplicated fragments in the IR regions. The junctions between LSC/IRs and SSC/IRs show different features of sequence expansion in evolution. We identified 78 SNPs as major intravarietal polymorphisms within the population of a specific cp genome, most of which were located in genes with vital functions. Based on RNA-sequencing data, we also found 18 polycistronic transcription units and three highly expression-biased genes--atpF, trnA-UGC, and rrn23. CONCLUSIONS: Unlike most monocots, date palm has a typical cp genome similar to that of tobacco--with little rearrangement and gene loss or gain. High-throughput sequencing technology facilitates the identification of intravarietal variations in cp genomes among different cultivars. Moreover, transcriptomic analysis of cp genes provides clues for uncovering regulatory mechanisms of transcription and translation in chloroplasts

Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P&lt;5&times;10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights

Data from a pre-publication independent replication initiative examining ten moral judgement effects

We present the data from a crowdsourced project seeking to replicate findings in independent laboratories before (rather than after) they are published. In this Pre-Publication Independent Replication (PPIR) initiative, 25 research groups attempted to replicate 10 moral judgment effects from a single laboratory's research pipeline of unpublished findings. The 10 effects were investigated using online/lab surveys containing psychological manipulations (vignettes) followed by questionnaires. Results revealed a mix of reliable, unreliable, and culturally moderated findings. Unlike any previous replication project, this dataset includes the data from not only the replications but also from the original studies, creating a unique corpus that researchers can use to better understand reproducibility and irreproducibility in science

The pipeline project: Pre-publication independent replications of a single laboratory's research pipeline

This crowdsourced project introduces a collaborative approach to improving the reproducibility of scientific research, in which findings are replicated in qualified independent laboratories before (rather than after) they are published. Our goal is to establish a non-adversarial replication process with highly informative final results. To illustrate the Pre-Publication Independent Replication (PPIR) approach, 25 research groups conducted replications of all ten moral judgment effects which the last author and his collaborators had “in the pipeline” as of August 2014. Six findings replicated according to all replication criteria, one finding replicated but with a significantly smaller effect size than the original, one finding replicated consistently in the original culture but not outside of it, and two findings failed to find support. In total, 40% of the original findings failed at least one major replication criterion. Potential ways to implement and incentivize pre-publication independent replication on a large scale are discussed