WILL FARMERS USE SAFER PESTICIDES?

Virtually all technology adoption studies are conducted ex post, yet policy makers often need to assess the likely level of adoption before the technology is introduced. This study uses data from a contingent valuation survey of Michigan corn growers to assess what factors would influence the adoption of two safer corn herbicides, one that is not carcinogenic and one that does not leach. Results indicate that price, risk perception, and sources of pest control information are all important. This suggests that public policies designed to change perceptions and improve information dissemination may encourage voluntary use of more environmentally friendly technologies.atrazine, cancer risk, contingent valuation, herbicides, nitrate leaching, public policy, technology adoption, Crop Production/Industries,

Key benefits of enterprise resource planning adoption within small family businesses : a conceptual framework

This research mainly focused on the perceived benefits of ERP adoption for Small Family Businesses (SFB). In doing so, it explores some of the key benefits of an ERP system for SMEs. Through the exploration of the literature, a framework is constructed classifying the ERP benefits to SFBs, in that they are different to other businesses where ERP systems have historically been implemented. The literature also helps establish that there are some differences in how ERP benefits SFBs owed to the family ownership and management of business that brings about unique characteristics. Finally, this research concludes that adopting an ERP system within a SFB environment could assist in them achieving their main goals by improving business performance and better managerial control. It could also aid the achievement of SFB’s succession goals. It is, however, unclear how the ERP system can manage the tacit family and business knowledge relied upon by SFBs for their survival

A search for solar neutrons on a long duration balloon flight

The EOSCOR 3 detector, designed to measure the flux of solar neutrons, was flown on a long duration RACOON balloon flight from Australia during Jan. through Feb, 1983. The Circum-global flight lasted 22 days. No major solar activity occurred during the flight and thus only an upper limit to the solar flare neutrons flux is given. The atmospheric neutron response is compared with that obtained on earlier flights from Palestine, Texas

A New Verified Compiler Backend for CakeML

We have developed and mechanically verified a new compiler backend for CakeML. Our new compiler features a sequence of intermediate languages that allows it to incrementally compile away high-level features and enables verification at the right levels of semantic detail. In this way, it resembles mainstream (unverified) compilers for strict functional languages. The compiler supports efficient curried multi-argument functions, configurable data representations, exceptions that unwind the call stack, register allocation, and more. The compiler targets several architectures: x86-64, ARMv6, ARMv8, MIPS-64, and RISC-V. In this paper, we present the overall structure of the compiler, including its 12 intermediate languages, and explain how everything fits together. We focus particularly on the interaction between the verification of the register allocator and the garbage collector, and memory representations. The entire development has been carried out within the HOL4 theorem prover.Engineering and Physical Sciences Research Counci

Cross Pixel Optical Flow Similarity for Self-Supervised Learning

We propose a novel method for learning convolutional neural image representations without manual supervision. We use motion cues in the form of optical flow, to supervise representations of static images. The obvious approach of training a network to predict flow from a single image can be needlessly difficult due to intrinsic ambiguities in this prediction task. We instead propose a much simpler learning goal: embed pixels such that the similarity between their embeddings matches that between their optical flow vectors. At test time, the learned deep network can be used without access to video or flow information and transferred to tasks such as image classification, detection, and segmentation. Our method, which significantly simplifies previous attempts at using motion for self-supervision, achieves state-of-the-art results in self-supervision using motion cues, competitive results for self-supervision in general, and is overall state of the art in self-supervised pretraining for semantic image segmentation, as demonstrated on standard benchmarks

Redshift determination in the X-ray band of gamma-ray bursts

If gamma-ray bursts originate in dense stellar forming regions, the interstellar material can imprint detectable absorption features on the observed X-ray spectrum. Such features can be detected by existing and planned X-ray satellites, as long as the X-ray afterglow is observed after a few minutes from the burst. If the column density of the interstellar material exceeds ~10^{23} cm^{-2} there exists the possibility to detect the K_alpha fluorescent iron line, which should be visible for more than one year, long after the X-ray afterglow continuum has faded away. Detection of these X-ray features will make possible the determination of the redshift of gamma-ray bursts even when their optical afterglow is severely dimmed by extinction.Comment: 15 pages with 5 figures. Submitted to Ap

Video Representation Learning by Recognizing Temporal Transformations

We introduce a novel self-supervised learning approach to learn representations of videos that are responsive to changes in the motion dynamics. Our representations can be learned from data without human annotation and provide a substantial boost to the training of neural networks on small labeled data sets for tasks such as action recognition, which require to accurately distinguish the motion of objects. We promote an accurate learning of motion without human annotation by training a neural network to discriminate a video sequence from its temporally transformed versions. To learn to distinguish non-trivial motions, the design of the transformations is based on two principles: 1) To define clusters of motions based on time warps of different magnitude; 2) To ensure that the discrimination is feasible only by observing and analyzing as many image frames as possible. Thus, we introduce the following transformations: forward-backward playback, random frame skipping, and uniform frame skipping. Our experiments show that networks trained with the proposed method yield representations with improved transfer performance for action recognition on UCF101 and HMDB51.Comment: ECCV 202

Extracting inner‐heliosphere solar wind speed information from Heliospheric Imager observations

We present evidence that variability in the STEREO‐A Heliospheric Imager (HI) data is correlated with in situ solar wind speed estimates from WIND, STEREO‐A, and STEREO‐B. For 2008–2012, we compute the variability in HI differenced images in a plane‐of‐sky shell between 20 to 22.5 solar radii and, for a range of position angles, compare daily means of HI variability and in situ solar wind speed estimates. We show that the HI variability data and in situ solar wind speeds have similar temporal autocorrelation functions. Carrington rotation periodicities are well documented for in situ solar wind speeds, but, to our knowledge, this is the first time they have been presented in statistics computed from HI images. In situ solar wind speeds from STEREO‐A, STEREO‐B, and WIND are all are correlated with the HI variability, with a lag that varies in a manner consistent with the longitudinal separation of the in situ monitor and the HI instrument. Unlike many approaches to processing HI observations, our method requires no manual feature tracking; it is automated, is quick to compute, and does not suffer the subjective biases associated with manual classifications. These results suggest we could possibly estimate solar wind speeds in the low heliosphere directly from HI observations. This motivates further investigation, as this could be a significant asset to the space weather forecasting community; it might provide an independent observational constraint on heliospheric solar wind forecasts, through, for example, data assimilation. Finally, these results are another argument for the potential utility of including a HI on an operational space weather mission

A Critical Appraisal and Evaluation of Modern PDFs

We review the present status of the determination of parton distribution functions (PDFs) in the light of the precision requirements for the LHC in Run 2 and other future hadron colliders. We provide brief reviews of all currently available PDF sets and use them to compute cross sections for a number of benchmark processes, including Higgs boson production in gluon-gluon fusion at the LHC. We show that the differences in the predictions obtained with the various PDFs are due to particular theory assumptions made in the fits of those PDFs. We discuss PDF uncertainties in the kinematic region covered by the LHC and on averaging procedures for PDFs, such as advocated by the PDF4LHC15 sets, and provide recommendations for the usage of PDF sets for theory predictions at the LHC.Comment: 70 pages pdflatex, 19 figures, 17 tables; final versio

Two-photon quantum walks in an elliptical direct-write waveguide array

Integrated optics provides an ideal test bed for the emulation of quantum systems via continuous-time quantum walks. Here we study the evolution of two-photon states in an elliptic array of waveguides. We characterise the photonic chip via coherent-light tomography and use the results to predict distinct differences between temporally indistinguishable and distinguishable two-photon inputs which we then compare with experimental observations. Our work highlights the feasibility for emulation of coherent quantum phenomena in three-dimensional waveguide structures.Comment: 8 pages, 7 figure