The Cornell Turfgrass Hotline: A Pest Management Decision-Making Tool for Extension Staff and Turfgrass Managers

NYS IPM Type: Project ReportThe New York State Integrated Pest Management (IPM) program has established an international reputation for delivering quality programming that results in enhanced management practices focused on reducing pesticide use. To this end, thousands of turfgrass managers are currently using techniques developed and delivered through Cornell based research and extension efforts. Still, there is a majority of turf managers who are unaware, unable or not interested in utilizing the research based information for the purpose of reducing pesticide use

Evaluation of Golf Turf Management Systems with Reduced Chemical Pesticide Inputs

ReportThe goal of this project is to provide information on the costs, feasibility and performance of golf course turf managed with few or no chemical pesticides

Video analysis of dogs with separation-related behaviors

Separation-related behaviors are described as problematic behaviors that occur exclusively in the owner's absence or virtual absence. Diagnosis is generally based on indirect evidence such as elimination or destruction that occurs during owner absence. Questionnaire studies are based on owner perception and might therefore underestimate the actual proportion of dogs with separation problems. The aim of this study was to film dogs with separation-related problems when left home alone and compile objective information on behaviors exhibited. Twenty-three dogs, ranging in age from 5 months to 13 years (2.9 \ub1 22.7 years), were filmed home alone for 20-60 min (49.87 \ub1 12.9 min) after owner departure. Analysis of behaviors on tape showed that dogs spent most of their time vocalizing (22.95 \ub1 12.3% of total observed time) and being oriented to the environment (21 \ub1 20%). Dogs also exhibited panting (14 \ub1 18%), were passive (12 \ub1 27%) and were destroying (6 \ub1 6%) during owner absence. Most dogs displayed signs within less than 10 min after owner departure, such as vocalizing (mean latency 3.25 min) and/or destroying (mean latency 7.13 min). Barking and oriented to the environment tended to decrease (respectively p = 0.08 and p = 0.07) and conversely panting tended to increase over time (p = 0.07). Diagnosis of separation-related problems is traditionally dependant on owner reports. Although owner observation may be informative, direct observation and standardized behavioral measurement of dogs with separation-related problems, before and after treatment, would be the best way to diagnose and to measure behavioral improvement

How big is too big? Critical Shocks for Systemic Failure Cascades

External or internal shocks may lead to the collapse of a system consisting of many agents. If the shock hits only one agent initially and causes it to fail, this can induce a cascade of failures among neighoring agents. Several critical constellations determine whether this cascade remains finite or reaches the size of the system, i.e. leads to systemic risk. We investigate the critical parameters for such cascades in a simple model, where agents are characterized by an individual threshold \theta_i determining their capacity to handle a load \alpha\theta_i with 1-\alpha being their safety margin. If agents fail, they redistribute their load equally to K neighboring agents in a regular network. For three different threshold distributions P(\theta), we derive analytical results for the size of the cascade, X(t), which is regarded as a measure of systemic risk, and the time when it stops. We focus on two different regimes, (i) EEE, an external extreme event where the size of the shock is of the order of the total capacity of the network, and (ii) RIE, a random internal event where the size of the shock is of the order of the capacity of an agent. We find that even for large extreme events that exceed the capacity of the network finite cascades are still possible, if a power-law threshold distribution is assumed. On the other hand, even small random fluctuations may lead to full cascades if critical conditions are met. Most importantly, we demonstrate that the size of the "big" shock is not the problem, as the systemic risk only varies slightly for changes of 10 to 50 percent of the external shock. Systemic risk depends much more on ingredients such as the network topology, the safety margin and the threshold distribution, which gives hints on how to reduce systemic risk.Comment: 23 pages, 7 Figure

Reducing Chemical Use on Golf Course Turf: Redefining IPM

The purpose of this handbook is to provide practical guidance for golf turf managers interested in reducing chemical pesticide and fertilizer use

Spectroscopy of geo-neutrinos from 2056 days of Borexino data

We report an improved geo-neutrino measurement with Borexino from 2056 days of data taking. The present exposure is $(5.5\pm0.3)\times10^{31}$ proton$\times$yr. Assuming a chondritic Th/U mass ratio of 3.9, we obtain $23.7 ^{+6.5}_{-5.7} (stat) ^{+0.9}_{-0.6} (sys)$ geo-neutrino events. The null observation of geo-neutrinos with Borexino alone has a probability of $3.6 \times 10^{-9}$ (5.9$\sigma$). A geo-neutrino signal from the mantle is obtained at 98\% C.L. The radiogenic heat production for U and Th from the present best-fit result is restricted to the range 23-36 TW, taking into account the uncertainty on the distribution of heat producing elements inside the Earth.Comment: 4 pages, 4 figure

Final results of Borexino Phase-I on low energy solar neutrino spectroscopy

Borexino has been running since May 2007 at the LNGS with the primary goal of detecting solar neutrinos. The detector, a large, unsegmented liquid scintillator calorimeter characterized by unprecedented low levels of intrinsic radioactivity, is optimized for the study of the lower energy part of the spectrum. During the Phase-I (2007-2010) Borexino first detected and then precisely measured the flux of the 7Be solar neutrinos, ruled out any significant day-night asymmetry of their interaction rate, made the first direct observation of the pep neutrinos, and set the tightest upper limit on the flux of CNO neutrinos. In this paper we discuss the signal signature and provide a comprehensive description of the backgrounds, quantify their event rates, describe the methods for their identification, selection or subtraction, and describe data analysis. Key features are an extensive in situ calibration program using radioactive sources, the detailed modeling of the detector response, the ability to define an innermost fiducial volume with extremely low background via software cuts, and the excellent pulse-shape discrimination capability of the scintillator that allows particle identification. We report a measurement of the annual modulation of the 7 Be neutrino interaction rate. The period, the amplitude, and the phase of the observed modulation are consistent with the solar origin of these events, and the absence of their annual modulation is rejected with higher than 99% C.L. The physics implications of phase-I results in the context of the neutrino oscillation physics and solar models are presented

Measurement of neutrino flux from the primary proton--proton fusion process in the Sun with Borexino detector

Neutrino produced in a chain of nuclear reactions in the Sun starting from the fusion of two protons, for the first time has been detected in a real-time detector in spectrometric mode. The unique properties of the Borexino detector provided an oppurtunity to disentangle pp-neutrino spectrum from the background components. A comparison of the total neutrino flux from the Sun with Solar luminosity in photons provides a test of the stability of the Sun on the 10$^{5}$ years time scale, and sets a strong limit on the power production in the unknown energy sources in the Sun of no more than 4\% of the total energy production at 90\% C.L.Comment: 15 pages, 2 tables, 3 figure

Autonomous Investigations over WS2_2 and Au{111} with Scanning Probe Microscopy

Individual atomic defects in 2D materials impact their macroscopic functionality. Correlating the interplay is challenging, however, intelligent hyperspectral scanning tunneling spectroscopy (STS) mapping provides a feasible solution to this technically difficult and time consuming problem. Here, dense spectroscopic volume is collected autonomously via Gaussian process regression, where convolutional neural networks are used in tandem for spectral identification. Acquired data enable defect segmentation, and a workflow is provided for machine-driven decision making during experimentation with capability for user customization. We provide a means towards autonomous experimentation for the benefit of both enhanced reproducibility and user-accessibility. Hyperspectral investigations on WS$_2$ sulfur vacancy sites are explored, which is combined with local density of states confirmation on the Au{111} herringbone reconstruction. Chalcogen vacancies, pristine WS$_2$, Au face-centered cubic, and Au hexagonal close packed regions are examined and detected by machine learning methods to demonstrate the potential of artificial intelligence for hyperspectral STS mapping.Comment: Updates from final journal publicatio