The Supply Of Community Supported Agriculture

Community Supported Agriculture (CSA) has undergone both a rapid increase in growth and interest over the last two decades.  As such, the amount of literature on the subject has also increased.  However, there are few, if any, theoretical models of supply for CSA memberships (shares) that have been developed from CSA farm data.  This paper uses both survey and anecdotal data from the Roxbury Biodynamic Farm, one of the largest CSA in the United States, to present a theory of supply for CSA membership.  Included in the discussion is the consideration that CSA farms are not profit maximizing and that the farmers (i.e. the suppliers) knowingly take on the responsibilities and earnings associated with a CSA

The Demand For Community Supported Agriculture

Community Supported Agriculture (CSA) has undergone both a rapid increase in growth and interest over the last decade.  As such, the amount of literature on the subject has also increased.  However, there are few, if any, theoretical models of demand on CSA that have been developed from membership data. This paper uses both survey and anecdotal data of members of the Roxbury Biodynamic Farm, the second largest CSA in the United States, to present a theory of demand for CSA membership. Included in the discussion is consideration of the evidence that there is a direct relationship between production method and demand, usually a shibboleth in traditional economic analysis. Further exploration considers the possibility that over time participation influences the very nature of demand for CSA membership, and hypothesizes that this dynamic demand is a necessary but insufficient condition for the sustainability of CSA

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Molecular identification of novel intermediate host species of Angiostrongylus vasorum in Greater London

Angiostrongylus vasorum is a parasitic nematode that can cause serious and potentially fatal disease in dogs and other canids. The aim of this study was to determine the intermediate slug species infected in nature by sampling sites in Greater London and Hertfordshire located within a known hyperendemic region. Overall, A. vasorum larvae were recovered from 6/381 slugs (1.6 %) by tissue digestion, and their identity was confirmed by PCR. Infected slugs originated from three different sites in the Greater London area: one in Waltham Forest and two in Bromley. Slugs parasitised by A. vasorum were identified by a combination of external morphological characteristics and molecular techniques and belonged to three different families: the Arionidae, the Milacidae and the Limacidae. This includes two new host records for the parasite: Arion distinctus and Tandonia sowerbyi. This is the first record of A. vasorum in the family Milacidae, indicating that the parasite has a broader intermediate host range than previously recognised

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press