To what extent are land resource managers preparing for high-end climate change in Scotland?

We explore the individual and institutional conditions and the climate information used to underpin decision-making for adaptation to high-end climate change (HECC) scenarios in a land resource management context. HECC refers to extreme projections with global annual temperature increases of over 4 °C. We analyse whether HECC scenarios are used in the adaptation decision-making of stakeholders who will tackle the potential problem. We also explore whether the adaptation actions being considered are pertinent only to future climate change or whether other drivers and information types are used in decision-making (including non-climate drivers). We also address the role of knowledge uncertainty in adaptation decision-making. Decision-makers perceive HECC as having a low probability of occurrence and so they do not directly account for HECC within existing actions to address climate change. Such actions focus on incremental rather than transformative solutions in which non-climate drivers are at least as important, and in many cases more important, than climate change alone. This reflects the need to accommodate multiple concerns and low risk options (i.e. incremental change). Uncertainty in climate change information is not a significant barrier to decision-making and stakeholders indicated little need for more climate information in support of adaptation decision-making. There is, however, an identified need for more information about the implications of particular sectoral and cross-sectoral impacts under HECC scenarios. The outcomes of this study provide evidence to assist in contextualising climate change information by creating usable, cross-sectoral, decision-centred information

Phase II study of capecitabine and oxaliplatin given prior to and concurrently with preoperative pelvic radiotherapy in patients with locally advanced rectal cancer

This multicentre phase II study evaluated the efficacy and safety of preoperative capecitabine plus oxaliplatin and radiotherapy (RT) in patients with locally advanced rectal cancer (T3/T4 rectal adenocarcinoma with or without nodal involvement). Treatment consisted of one cycle of XELOX (capecitabine 1000 mg m−2 bid on days 1–14 and oxaliplatin 130 mg m−2 on day 1), followed by RT (1.8 Gy fractions 5 days per week for 5 weeks) plus CAPOX (capecitabine 825 mg m−2 bid on days 22–35 and 43–56, and oxaliplatin 50 mg m−2 on days 22, 29, 43 and 50). Surgery was recommended 5 weeks after completion of chemoradiotherapy. The primary end point was pathological complete tumour response (pCR). Sixty patients were enrolled. In the intent-to-treat population, the pCR rate was 23% (95% CI: 13–36%). 58 patients underwent surgery; R0 resection was achieved in 57 (98%) patients, including all 5 patients with T4 tumours. Sphincter preservation was achieved in 49 (84%) patients. Tumour and/or nodal downstaging was observed in 39 (65%) patients. The most common grade 3/4 adverse events were diarrhoea (20%) and lymphocytopaenia (43%). Preoperative capecitabine, oxaliplatin and RT achieved encouraging rates of pCR, R0 resection, sphincter preservation and tumour downstaging in patients with locally advanced rectal cancer

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Non-Centered Spike-Triggered Covariance Analysis Reveals Neurotrophin-3 as a Developmental Regulator of Receptive Field Properties of ON-OFF Retinal Ganglion Cells

The functional separation of ON and OFF pathways, one of the fundamental features of the visual system, starts in the retina. During postnatal development, some retinal ganglion cells (RGCs) whose dendrites arborize in both ON and OFF sublaminae of the inner plexiform layer transform into RGCs with dendrites that monostratify in either the ON or OFF sublamina, acquiring final dendritic morphology in a subtype-dependent manner. Little is known about how the receptive field (RF) properties of ON, OFF, and ON-OFF RGCs mature during this time because of the lack of a reliable and efficient method to classify RGCs into these subtypes. To address this deficiency, we developed an innovative variant of Spike Triggered Covariance (STC) analysis, which we term Spike Triggered Covariance – Non-Centered (STC-NC) analysis. Using a multi-electrode array (MEA), we recorded the responses of a large population of mouse RGCs to a Gaussian white noise stimulus. As expected, the Spike-Triggered Average (STA) fails to identify responses driven by symmetric static nonlinearities such as those that underlie ON-OFF center RGC behavior. The STC-NC technique, in contrast, provides an efficient means to identify ON-OFF responses and quantify their RF center sizes accurately. Using this new tool, we find that RGCs gradually develop sensitivity to focal stimulation after eye opening, that the percentage of ON-OFF center cells decreases with age, and that RF centers of ON and ON-OFF cells become smaller. Importantly, we demonstrate for the first time that neurotrophin-3 (NT-3) regulates the development of physiological properties of ON-OFF center RGCs. Overexpression of NT-3 leads to the precocious maturation of RGC responsiveness and accelerates the developmental decrease of RF center size in ON-OFF cells. In summary, our study introduces STC-NC analysis which successfully identifies subtype RGCs and demonstrates how RF development relates to a neurotrophic driver in the retina

Corporate image and reputation as drivers of customer loyalty

ABSTRACT: Prior research suggests that corporate image and reputation can contribute to relationship marketing and customer loyalty. However, little empirical evidence support the influence of these constructs on customer loyalty. This study investigates the influence of corporate image ?comprised of functional and emotional aspects? and reputation on customer loyalty. A structural equation model is developed to test the research hypotheses. The study was tested using data collected from a sample of Spanish consumers in a service setting. Results show that functional and emotional image have a positive influence on corporate reputation. Similarly, corporate reputation has a positive influence on customer loyalty. This study may help managers use their resources more effectively by focusing on corporate image and reputation as the greatest strategic assets to enhance customer loyalty

A survey of visualization tools for biological network analysis

The analysis and interpretation of relationships between biological molecules, networks and concepts is becoming a major bottleneck in systems biology. Very often the pure amount of data and their heterogeneity provides a challenge for the visualization of the data. There are a wide variety of graph representations available, which most often map the data on 2D graphs to visualize biological interactions. These methods are applicable to a wide range of problems, nevertheless many of them reach a limit in terms of user friendliness when thousands of nodes and connections have to be analyzed and visualized. In this study we are reviewing visualization tools that are currently available for visualization of biological networks mainly invented in the latest past years. We comment on the functionality, the limitations and the specific strengths of these tools, and how these tools could be further developed in the direction of data integration and information sharing