Year patterns of climate impact on wheat yields

Rainfall, temperature, and solar radiation are important climate factors, which determine crop growth, development and yield from instantaneous to decadal scales. We propose to identify year patterns of climate impact on yield on the basis of rain and non-rain weather. There are inter-related impacts of climatic factors on crop production within a specific pattern. Historical wheat yield data in Queensland during 1889-2004 were used. The influence of meteorological conditions on wheat yields was derived from statistical yield data which were detrended by 9-year-smoothing averages to remove the effects of technological improvements on wheat yields over time. Climate affects crop growth and development differently over different growth stages. Therefore, we considered the climate effects at both vegetative and reproductive stages (before and after flowering date, respectively) on yield. Cluster analysis was employed to identify the year patterns of climate impact. Five patterns were significantly classified. Precipitation during the vegetative stage was the dominant and beneficial factor for wheat yields while increasing maximum temperature had a negative influence. Crop yields were strongly dependent on solar radiation under normal rainfall conditions. As the effect of rainfall on soil water is relatively long-lasting, its beneficial effect in vegetative stage was higher than its effect during the reproductive stage. The Agricultural Production Systems sIMulator (APSIM) was evaluated using long-term historical data to determine whether the model could reasonably simulate effects of climate factors for each year pattern. The model provided good estimates of wheat yield when conditions resulted in medium yield levels, however, in extremely low or high yield years, corresponding to extremely low or high precipitation in the vegetative stage, the model tended to underestimate or overestimate. Under high growing season precipitation, simulations responded more favourably to reproductive stage rainfall than measured yields. © 2013 Royal Meteorological Society

The relationship between the systemic inflammatory response, tumour proliferative activity, T-lymphocytic and macrophage infiltration, microvessel density and survival in patients with primary operable breast cancer

The significance of the inter-relationship between tumour and host local/systemic inflammatory responses in primary operable invasive breast cancer is limited. The inter-relationship between the systemic inflammatory response (pre-operative white cell count, C-reactive protein and albumin concentrations), standard clinicopathological factors, tumour T-lymphocytic (CD4+ and CD8+) and macrophage (CD68+) infiltration, proliferative (Ki-67) index and microvessel density (CD34+) was examined using immunohistochemistry and slide-counting techniques, and their prognostic values were examined in 168 patients with potentially curative resection of early-stage invasive breast cancer. Increased tumour grade and proliferative activity were associated with greater tumour T-lymphocyte (P<0.05) and macrophage (P<0.05) infiltration and microvessel density (P<0.01). The median follow-up of survivors was 72 months. During this period, 31 patients died; 18 died of their cancer. On univariate analysis, increased lymph-node involvement (P<0.01), negative hormonal receptor (P<0.10), lower albumin concentrations (P<0.01), increased tumour proliferation (P<0.05), increased tumour microvessel density (P<0.05), the extent of locoregional control (P<0.0001) and limited systemic treatment (Pless than or equal to0.01) were associated with cancer-specific survival. On multivariate analysis of these significant covariates, albumin (HR 4.77, 95% CI 1.35–16.85, P=0.015), locoregional treatment (HR 3.64, 95% CI 1.04–12.72, P=0.043) and systemic treatment (HR 2.29, 95% CI 1.23–4.27, P=0.009) were significant independent predictors of cancer-specific survival. Among tumour-based inflammatory factors, only tumour microvessel density (P<0.05) was independently associated with poorer cancer-specific survival. The host inflammatory responses are closely associated with poor tumour differentiation, proliferation and malignant disease progression in breast cancer

Absolute quantitation of DNA methylation of 28 candidate genes in prostate cancer using pyrosequencing

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Aberrant DNA methylation plays a pivotal role in carcinogenesis and its mapping is likely to provide biomarkers for improved diagnostic and risk assessment in prostate cancer (PCa). We quantified and compared absolute methylation levels among 28 candidate genes in 48 PCa and 29 benign prostate hyperplasia (BPH) samples using the pyrosequencing (PSQ) method to identify genes with diagnostic and prognostic potential. RARB, HIN1, BCL2, GSTP1, CCND2, EGFR5, APC, RASSF1A, MDR1, NKX2-5, CDH13, DPYS, PTGS2, EDNRB, MAL, PDLIM4, HLAa, ESR1 and TIG1 were highly methylated in PCa compared to BPH (p < 0.001), while SERPINB5, CDH1, TWIST1, DAPK1, THRB, MCAM, SLIT2, CDKN2a and SFN were not. RARB methylation above 21% completely distinguished PCa from BPH. Separation based on methylation level of SFN, SLIT2 and SERPINB5 distinguished low and high Gleason score cancers, e.g. SFN and SERPINB5 together correctly classified 81% and 77% of high and low Gleason score cancers respectively. Several genes including CDH1 previously reported as methylation markers in PCa were not confirmed in our study. Increasing age was positively associated with gene methylation (p < 0.0001). Accurate quantitative measurement of gene methylation in PCa appears promising and further validation of genes like RARB, HIN1, BCL2, APC and GSTP1 is warranted for diagnostic potential and SFN, SLIT2 and SERPINB5 for prognostic potential

Frequency tracking by method of least squares combined with channel estimation for OFDM over mobile wireless channels

[[abstract]]To track frequency offset and time-varying channel in orthogonal frequency division multiplexing (OFDM) systems over mobile wireless channels, a common technique is, based on one OFDM training block sample, to apply the maximum-likelihood (ML) algorithm to perform joint frequency tracking and channel estimation employing some adaptive iteration processes. The major drawback of such joint estimation techniques is the local extrema problem arising from the highly nonlinear nature of the log-likelihood function. This makes the joint estimation process very difficult and complicated, and many a time the results are not very satisfactory if the algorithm is not well designed. In this study, rather than using the ML algorithm, we shall apply the method of least squares (LS) for frequency tracking utilizing repeated OFDM training blocks. As will be seen, by using such an LS approach, the frequency offset estimation requires no channel knowledge. The channel state can be estimated separately after the LS frequency offset correction. This not only circumvents the local extrema complication, but also obviates the need for the lengthy adaptive iteration process of joint estimation thus greatly simplifies the entire estimation process. Most importantly, our technique can achieve excellent estimation performance as compared to the usual ML algorithms.[[incitationindex]]SCI[[booktype]]紙

Flavor conversion of cosmic neutrinos from hidden jets

High energy cosmic neutrino fluxes can be produced inside relativistic jets under the envelopes of collapsing stars. In the energy range E ~ (0.3 - 1e5) GeV, flavor conversion of these neutrinos is modified by various matter effects inside the star and the Earth. We present a comprehensive (both analytic and numerical) description of the flavor conversion of these neutrinos which includes: (i) oscillations inside jets, (ii) flavor-to-mass state transitions in an envelope, (iii) loss of coherence on the way to observer, and (iv) oscillations of the mass states inside the Earth. We show that conversion has several new features which are not realized in other objects, in particular interference effects ("L- and H- wiggles") induced by the adiabaticity violation. The neutrino-neutrino scattering inside jet and inelastic neutrino interactions in the envelope may produce some additional features at E > 1e4 GeV. We study dependence of the probabilities and flavor ratios in the matter-affected region on angles theta13 and theta23, on the CP-phase delta, as well as on the initial flavor content and density profile of the star. We show that measurements of the energy dependence of the flavor ratios will, in principle, allow to determine independently the neutrino and astrophysical parameters.Comment: 56 pages, 19 figures. Minor changes. Accepted by JHEP

Different atmospheric moisture divergence responses to extreme and moderate El Niños

On seasonal and inter-annual time scales, vertically integrated moisture divergence provides a useful measure of the tropical atmospheric hydrological cycle. It reflects the combined dynamical and thermodynamical effects, and is not subject to the limitations that afflict observations of evaporation minus precipitation. An empirical orthogonal function (EOF) analysis of the tropical Pacific moisture divergence fields calculated from the ERA-Interim reanalysis reveals the dominant effects of the El Niño-Southern Oscillation (ENSO) on inter-annual time scales. Two EOFs are necessary to capture the ENSO signature, and regression relationships between their Principal Components and indices of equatorial Pacific sea surface temperature (SST) demonstrate that the transition from strong La Niña through to extreme El Niño events is not a linear one. The largest deviation from linearity is for the strongest El Niños, and we interpret that this arises at least partly because the EOF analysis cannot easily separate different patterns of responses that are not orthogonal to each other. To overcome the orthogonality constraints, a self-organizing map (SOM) analysis of the same moisture divergence fields was performed. The SOM analysis captures the range of responses to ENSO, including the distinction between the moderate and strong El Niños identified by the EOF analysis. The work demonstrates the potential for the application of SOM to large scale climatic analysis, by virtue of its easier interpretation, relaxation of orthogonality constraints and its versatility for serving as an alternative classification method. Both the EOF and SOM analyses suggest a classification of “moderate” and “extreme” El Niños by their differences in the magnitudes of the hydrological cycle responses, spatial patterns and evolutionary paths. Classification from the moisture divergence point of view shows consistency with results based on other physical variables such as SST

Modeling recursive RNA interference.

An important application of the RNA interference (RNAi) pathway is its use as a small RNA-based regulatory system commonly exploited to suppress expression of target genes to test their function in vivo. In several published experiments, RNAi has been used to inactivate components of the RNAi pathway itself, a procedure termed recursive RNAi in this report. The theoretical basis of recursive RNAi is unclear since the procedure could potentially be self-defeating, and in practice the effectiveness of recursive RNAi in published experiments is highly variable. A mathematical model for recursive RNAi was developed and used to investigate the range of conditions under which the procedure should be effective. The model predicts that the effectiveness of recursive RNAi is strongly dependent on the efficacy of RNAi at knocking down target gene expression. This efficacy is known to vary highly between different cell types, and comparison of the model predictions to published experimental data suggests that variation in RNAi efficacy may be the main cause of discrepancies between published recursive RNAi experiments in different organisms. The model suggests potential ways to optimize the effectiveness of recursive RNAi both for screening of RNAi components as well as for improved temporal control of gene expression in switch off-switch on experiments

Assessment of low-dose cisplatin as a model of nausea and emesis in beagle dogs, potential for repeated administration

Cisplatin is a highly emetogenic cancer chemotherapy agent, which is often used to induce nausea and emesis in animal models. The cytotoxic properties of cisplatin also cause adverse events that negatively impact on animal welfare preventing repeated administration of cisplatin. In this study, we assessed whether a low (subclinical) dose of cisplatin could be utilized as a model of nausea and emesis in the dog while decreasing the severity of adverse events to allow repeated administration. The emetic, nausea-like behavior and potential biomarker response to both the clinical dose (70 mg/m2) and low dose (15 mg/m2) of cisplatin was assessed. Plasma creatinine concentrations and granulocyte counts were used to assess adverse effects on the kidneys and bone marrow, respectively. Nausea-like behavior and emesis was induced by both doses of cisplatin, but the latency to onset was greater in the low-dose group. No significant change in plasma creatinine was detected for either dose groups. Granulocytes were significantly reduced compared with baseline (P = 0.000) following the clinical, but not the low-dose cisplatin group. Tolerability of repeated administration was assessed with 4 administrations of an 18 mg/m2 dose cisplatin. Plasma creatinine did not change significantly. Cumulative effects on the granulocytes occurred, they were significantly decreased (P = 0.03) from baseline at 3 weeks following cisplatin for the 4th administration only. Our results suggest that subclinical doses (15 and 18 mg/m2) of cisplatin induce nausea-like behavior and emesis but have reduced adverse effects compared with the clinical dose allowing for repeated administration in crossover studies

Reinforcement learning or active inference?

This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain

Zigzag-shaped nickel nanowires via organometallic template-free route

In this manuscript, the formation of nickel nanowires (average size: several tens to hundreds of μm long and 1.0-1.5 μm wide) at low temperature is found to be driven by dewetting of liquid organometallic precursors during spin coating process and by self-assembly of Ni clusters. Elaboration of metallic thin films by low temperature deposition technique makes the preparation process compatible with most of the substrates. The use of iron and cobalt precursor shows that the process could be extended to other metallic systems. In this work, AFM and SEM are used to follow the assembly of Ni clusters into straight or zigzag lines. The formation of zigzag structure is specific to the Ni precursor at appropriate preparation parameters. This template free process allows a control of anisotropic structures with homogeneous sizes and angles on standard Si/SiO2 surface