87 research outputs found

    Model-predicted ammonia emission from two broiler houses with different rearing systems

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    Ammonia (NH3) emissions from broiler production can affect human and animal health and may cause acidification and eutrophication of the surrounding environment. This study aimed to estimate ammonia emissions from broiler litter in two systems of forced ventilation, the tunnel ventilation (TV) and the dark house (DH). The experiment was carried out on eight commercial broiler houses, and the age of the birds (day, d), pH and litter temperature were recorded. Broilers were reared on built-up wood shaving litter using an average flock density of 14 bird m–2. Temperature and relative humidity inside the broiler houses were recorded in the morning during the grow-out period. A factorial experimental design was adopted, with two types of houses, four replicates and two flocks with two replicates each. A deterministic model was used to predict ammonia emissions using the litter pH and temperature, and the day of grow-out. The highest litter temperature and pH were found at 42 d of growth in both housing systems. Mean ambient air temperature and relative humidity did not differ in either system. Mean model predicted ammonia emission was higher in the DH rearing system (5200 mg NH3 m−2h−1 at 42 d) than in the TV system (2700 mg NH3m−2 h−1 at 42 d). TV presented the lowest mean litter temperature and pH at 42 d of growth. In the last week of the broilers’ grow-out cycle, estimated ammonia emissions inside DH reached 5700 mg m−2h−1 in one of the flocks. Ammonia emissions were higher inside DH, and they did not differ between flocks. Assuming a broiler market weight in Brazil of close to 2 kg, ammonia emissions were equivalent to 12 g NH3 bird-marketed−1. Model-predicted ammonia emissions provided comprehensible estimations and might be used in abatement strategies for NH3 emission

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

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    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

    A cytogenetic study of 74 nasopharyngeal carcinoma biopsies.

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    Annals of the Academy of Medicine Singapore205597-60

    Therapeutic potential of antifungal plant and insect defensins

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    To defend themselves against invading fungal pathogens, plants and insects largely depend on the production of a wide array of antifungal molecules, including antimicrobial peptides such as defensins. Interestingly, plant and insect defensins display antimicrobial activity not only against plant and insect pathogens but also against human fungal pathogens, including Candida spp. and Aspergillus spp. This review focuses on these defensins as novel leads for antifungal therapeutics. Their mode of action, involving interaction with fungus-specific sphingolipids, and heterologous expression, required for cost-effective production, are major assets for development of plant and insect defensins as antifungal leads. Studies evaluating their in vivo antifungal efficacy demonstrate their therapeutic potential
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