Using concepts of shoot growth and architecture to understand and predict responses of peach trees to pruning

International audienceOne definition of horticulture is "the art of cultivating garden plants" and pruning is a horticultural practice that is traditionally approached as more of an art than a science. This is largely because of the complexity of tree growth and development and a lack of general understanding and appreciation about the processes involved in governing shoot and tree growth and development. However recent tree architectural studies have provided systematic analyses of the shoot growth and statistical and dynamic simulation models have been developed that predict tree development and responses to pruning based on scientific concepts. These concepts include apical dominance (and its subcomponents; correlative inhibition, apical control and shoot epinasty); prolepsis and syllepsis; preformation and neoformation; epicormic shoot formation and plastochron (leaf emergence rates). In this paper we will discuss how many of these concepts can be combined with hidden semi-Markov chain models of shoot bud fates and a simulation model of source-sink interactions in peach trees (L-PEACH) to understand and predict natural development of peach trees and their responses to pruning. The results of these modeling efforts help explain the architectural and physiological basis of several common, empirically-based pruning systems used in California. These concepts also provide an understanding of the limitations of relying primarily on the use of pruning to control size of trees growing on commonly used invigorating rootstocks. This research demonstrates how computer simulation modeling can be used to test and analyze interactions between environmental factors and management practices in determining patterns of tree growth and development

The neuropsychology of obsessive-compulsive personality disorder : a new analysis

Background: Obsessive compulsive personality disorder (OCPD) is characterized by perfectionism, need for control, and cognitive rigidity. Currently, little neuropsychological data exist on this condition, though emerging evidence does suggest that disorders marked by compulsivity, including obsessive-compulsive disorder (OCD), are associated with impairment in cognitive flexibility and executive planning on neurocognitive tasks.Aim: The current study investigated the neurocognitive profile in a nonclinical community-based sample of people fulfilling diagnostic criteria for OCPD in the absence of major psychiatric comorbidity.Method: Twenty-one nonclinical subjects who fulfilled Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for OCPD were compared with 15 healthy controls on selected clinical and neurocognitive tasks. OCPD was measured using the Compulsive Personality Assessment Scale (CPAS). Participants completed tests from the Cambridge Automated Neuropsychological Test Battery including tests of set shifting (Intra-Extra Dimensional [IED] Set Shifting) executive planning (Stockings of Cambridge [SOC]), and decision making (Cambridge Gamble Task [CGT]).Results: The OCPD group made significantly more IED-ED shift errors and total shift errors, and also showed longer mean initial thinking time on the SOC at moderate levels of difficulty. No differences emerged on the CGT.Conclusions: Nonclinical cases of OCPD showed significant cognitive inflexibility coupled with executive planning deficits, whereas decision-making remained intact. This profile of impairment overlaps with that of OCD and implies that common neuropsychological changes affect individuals with these disorders.Peer reviewe

Collaborative Training With a More Experienced Partner: Remediating Low Pretraining Self-Efficacy in Complex Skill Acquisition

Objective: This study examined the effectiveness of collaborative training for individuals with low pretraining self-efficacy versus individuals with high pretraining selfefficacy regarding the acquisition of a complex skill that involved strong cognitive and psychomotor demands. Background: Despite support for collaborative learning from the educational literature and the similarities between collaborative learning and interventions designed to remediate low self-efficacy, no research has addressed how selfefficacy and collaborative learning interact in contexts concerning complex skills and human-machine interactions. Method: One hundred fifty-five young male adults trained either individually or collaboratively with a more experienced partner on a complex computer task that simulated the demands of a dynamic aviation environment. Participants also completed a task-specific measure of self-efficacy before, during, and after training. Results: Collaborative training enhanced skill acquisition significantly more for individuals with low pretraining self-efficacy than for individuals with high pretraining self-efficacy. However, collaborative training did not bring the skill acquisition levels of those persons with low pretraining self-efficacy to the levels found for persons with high pretraining self-efficacy. Moreover, tests of mediation suggested that collaborative training may have enhanced appropriate skill development strategies without actually raising self-efficacy. Conclusion: Although collaborative training can facilitate the skill acquisition process for trainees with low self-efficacy, future research is needed that examines how the negative effects of low pretraining self-efficacy on complex skill acquisition can be more fully remediated. Application: The differential effects of collaborative training as a function of self-efficacy highlight the importance of person analysis and tailoring training to meet differing trainee needs.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Interannual population dynamics of the green spruce aphid Elatobium abietinum (Walker) in France

The hypothesis that similar processes govern interannual dynamics of green spruce aphid in the UK and France, is generally supported by the application of a general discrete model. A simple model based on relatively few parameters was able to closely characterise interannual population dynamics from completely independent aerial and arboreal samples of aphids. Long term field population estimates of the green spruce aphid Elatobium abietinum (Walker) in France have provided the opportunity to select and evaluate the generality of a model which was developed in the UK to explain the year‐to‐year variations in peak abundance of the aphid. Aims The objective was to observe the influence of the local climates and disturbing climate factors on the population densities of the insect in two regions of France. Methods The model uses climate variables and aphid population data from regular samples in the two regions that were investigated. A general discrete model was used to predict aphid population densities. Results The model performed well in tracking the interannual patterns of population but was less likely to predict absolute population density. Conclusion To improve predictions, further account would need to be taken of additional site‐specific climate variables and the strength of overcompensating density dependence. Nevertheless it is clear that broadly similar processes are at work in the population dynamics of this insect across its biogeographical range

Developing the Active Communities Tool to Implement the Community Guide's Built Environment Recommendation for Increasing Physical Activity

Physical activity is higher in communities that include supportive features for walking and bicycling. In 2016, the Community Preventive Services Task Force released a systematic review of built environment approaches to increase physical activity. The results of the review recommended approaches that combine interventions to improve pedestrian and bicycle transportation systems with land use and environmental design strategies. Because the recommendation was multifaceted, the Centers for Disease Control and Prevention determined that communities could benefit from an assessment tool to address the breadth of the Task Force recommendations. The purpose of this article is to describe the systematic approach used to develop the Active Communities Tool. First, we created and refined a logic model and community theory of change for tool development. Second, we reviewed existing community-based tools and abstracted key elements (item domains, advantages, disadvantages, updates, costs, permissions to use, and psychometrics) from 42 tools. The review indicated that no tool encompassed the breadth of the Community Guide recommendations for communities. Third, we developed a new tool and pilot tested its use with 9 diverse teams with public health and planning expertise. Final revisions followed from pilot team and expert input. The Active Communities Tool comprises 6 modules addressing all 8 interventions recommended by the Task Force. The tool is designed to help cross-sector teams create an action plan for improving community built environments that promote physical activity and may help to monitor progress toward achieving community conditions known to promote physical activity

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Common variants near MC4R are associated with fat mass, weight and risk of obesity.

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits