FARM COMPUTER ADOPTION IN THE GREAT PLAINS

Computers change rapidly, yet the last survey on computer use in agriculture was in 1991. We surveyed Great Plains producers in 1995 and used logit analysis to characterize adopters and non-adopters. About 37% of these producers use computers which is consistent with the general population. We confirmed previous surveys emphasizing the importance of education, age/experience, and other farm characteristics on adoption. However, we also found that education and experience may no longer be a significant influence. Future research and education could focus on when and where computers are most needed, and therefore when adoption is most appropriate.adoption, agriculture, computers, farmers, Great Plains, logit, Farm Management,

The Scarabaeoid Beetles of Maryland (Coleoptera)

This research recognizes 267 species of scarabaeoid beetles occurring in Maryland. We provide a brief overview of the geology, climate, and vegetation of the state. Keys to the families within Scarabaeoidea occurring in Maryland are provided. We also offer an introduction for each family, keys to all taxa, species descriptions, distributions, and distribution maps for all species, months that adults are observed, notes on their natural history, illustrations, and a glossary of terms. Maryland’s species are found in eight families: Lucanidae (7), Passalidae (1), Geotrupidae (17), Trogidae (18), Ochodaeidae (1), Hybosoridae (2), Glaphyridae (1), and Scarabaeidae (220). Published as Bulletin of the University of Nebraska State Museum, Volume 33, Issue Date: 1 March 2023 340 pages, 7 x10 , color illustrations; file size 70 MBhttps://digitalcommons.unl.edu/zeabook/1140/thumbnail.jp

Ecosystem Food Web Lift-the-Flap Pages

In the lesson on which this practical article is based, third grade students constructed a “lift-the-flap” page to explore food webs on the prairie. The moveable papercraft focused student attention on prairie animals’ external structures and how the inferred functions of those structures could support further inferences about the animals’ diets. In general, most students made simple causal connections between an animal’s observable characteristics and the food it would probably eat. Some students were also able to make multi-agent connections to develop a more complex mental model of a food web. Ultimately, the lift-the flap project was engaging to students and motivated them to focus their attention on the characteristics of animals of different ecosystems to infer their probable diets

Science and Engineering Serials: Issues and Challenges in the Electronic Environment

Pricing Issues: The Core Problem. Subscription Price Increases. Fluctuations in the Foreign Exchange Rate. ISI Impact Factors, Journal Quality, and Cost-Effectiveness. Questions of Content, Archiving, and Access.. Conclusion. Reference Notes

A 4D Light-Field Dataset and CNN Architectures for Material Recognition

We introduce a new light-field dataset of materials, and take advantage of the recent success of deep learning to perform material recognition on the 4D light-field. Our dataset contains 12 material categories, each with 100 images taken with a Lytro Illum, from which we extract about 30,000 patches in total. To the best of our knowledge, this is the first mid-size dataset for light-field images. Our main goal is to investigate whether the additional information in a light-field (such as multiple sub-aperture views and view-dependent reflectance effects) can aid material recognition. Since recognition networks have not been trained on 4D images before, we propose and compare several novel CNN architectures to train on light-field images. In our experiments, the best performing CNN architecture achieves a 7% boost compared with 2D image classification (70% to 77%). These results constitute important baselines that can spur further research in the use of CNNs for light-field applications. Upon publication, our dataset also enables other novel applications of light-fields, including object detection, image segmentation and view interpolation.Comment: European Conference on Computer Vision (ECCV) 201

Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (LDAS) and Other Assimilated Hydrological Data at NASA GES DISC

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides science support for several data sets relevant to agriculture and food security, including the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (LDAS), or FLDAS data set. The GES DISC is one of twelve NASA Earth Observing System (EOS) data centers that process, archive, document, and distribute data from Earth science missions and related projects. The GES DISC hosts a wide range of remote sensing and model data, and provides reliable and robust data access and other services to users worldwide. Beyond data archive and access, the GES DISC offers many services to visualize and analyze the data. This presentation provides a summary of the hydrological data available at the GES DISC, along with an overview of related data services. Specifically, the FLDAS data set has been adapted to work with domains, data streams, and monitoring and forecast requirements associated with food security assessment in data-sparse, developing country settings. The FLDAS global monthly data have a 0.1 x 0.1 degree spatial resolution covering the period from January 1982 to present. Global FLDAS monthly anomaly and monthly climatology data are also available at the GES DISC to evaluate how current conditions compare to averages over the FLDAS 35-year period. Several case studies using the FLDAS soil moisture, evapotranspiration, rainfall, runoff, and surface temperature data will be presented

Fully automated segmentation and tracking of the intima media thickness in ultrasound video sequences of the common carotid artery

Abstract—The robust identification and measurement of the intima media thickness (IMT) has a high clinical relevance because it represents one of the most precise predictors used in the assessment of potential future cardiovascular events. To facilitate the analysis of arterial wall thickening in serial clinical investigations, in this paper we have developed a novel fully automatic algorithm for the segmentation, measurement, and tracking of the intima media complex (IMC) in B-mode ultrasound video sequences. The proposed algorithm entails a two-stage image analysis process that initially addresses the segmentation of the IMC in the first frame of the ultrasound video sequence using a model-based approach; in the second step, a novel customized tracking procedure is applied to robustly detect the IMC in the subsequent frames. For the video tracking procedure, we introduce a spatially coherent algorithm called adaptive normalized correlation that prevents the tracking process from converging to wrong arterial interfaces. This represents the main contribution of this paper and was developed to deal with inconsistencies in the appearance of the IMC over the cardiac cycle. The quantitative evaluation has been carried out on 40 ultrasound video sequences of the common carotid artery (CCA) by comparing the results returned by the developed algorithm with respect to ground truth data that has been manually annotated by clinical experts. The measured IMTmean ± standard deviation recorded by the proposed algorithm is 0.60 mm ± 0.10, with a mean coefficient of variation (CV) of 2.05%, whereas the corresponding result obtained for the manually annotated ground truth data is 0.60 mm ± 0.11 with a mean CV equal to 5.60%. The numerical results reported in this paper indicate that the proposed algorithm is able to correctly segment and track the IMC in ultrasound CCA video sequences, and we were encouraged by the stability of our technique when applied to data captured under different imaging conditions. Future clinical studies will focus on the evaluation of patients that are affected by advanced cardiovascular conditions such as focal thickening and arterial plaques

Do We Really Need Another Meeting? The Science of Workplace Meetings

Meetings are routine in organizations, but their value is often questioned by the employees who must sit through them daily. The science of meetings that has emerged as of late provides necessary direction toward improving meetings, but an evaluation of the current state of the science is much needed. In this review, we examine current directions for the psychological science of workplace meetings, with a focus on applying scientific findings about the activities that occur before, during, and after meetings that facilitate success. We conclude with concrete recommendations and a checklist for promoting good meetings, as well as some thoughts on the future of the science of workplace meetings