568 research outputs found
Introduction – Regional Monitoring Programs
There is increasing interest in the initiation of regional or statewide monitoring programs that are less extensive than national efforts such as the Breeding Bird Survey. A number of regional programs have been in existence for a decade or more, so the papers in this section represented an effort to bring together the collective experience of the people who had developed these programs, and to hear about the benefits and drawbacks of their particular designs. Speakers reviewed why they felt there was a need for a regional monitoring effort, examined the designs and response variables associated with their regional monitoring program, presented the short- and longer-term results from the program, discussed the logistic and scientific successes and failures of each program, and presented recommendations for those who might be interested in starting their own regional monitoring program. Below, we provide a brief overview of some important points that emerged from this session, and how these regional efforts might be included as integral parts of broader national monitoring efforts that seem to be emerging
Using Spatial Models To Map Bird Distributions Along The Madison River
The Avian Science Center developed predictive maps of species distributions for the Madison River based on newly available riverine system data from the National Wetlands Inventory (NWI) and the Natural Heritage Program’s Landscape Integrity Model. We used a maximum entropy model (MaxEnt) to predict species distributions using species occurrence locations collected from 2003-2010. Models performed well for 13 species, demonstrating that available environmental data layers, including NWI, can be used to successfully predict species distributions along the Madison River for a number of important riparian bird species. These models allow fine-scale mapping of habitat suitability for riparian birds, which fills gaps in current data on species distributions, and can be used to prioritize riparian conservation and restoration projects
Bird Populations in Logged and Unlogged Western Larch/Douglas-fir Forest in Northwestern Montana
Of 32 species of abundant breeding birds, populations of 10 species differed significantly between small cutting units and adjacent uncut forest. Foliage foragers and tree gleaners were less abundant in cutting units, while flycatching species and ground foragers were more common there. Of nesting guilds, conifer tree nesters were least abundant in cutting units, and ground nesters were more common there. Results suggest that bird management should consider diverse community-level habitat needs and that if maintenance of tree-dependent species is important, broadleaf trees and snags of all species should be retained
Maintaining Bird Diversity in Western Larch/Douglas-fir Forests
Bird occurrences were evaluated under four stand conditions in western larch/Douglas-fir forests: clearcut, partial cut, unlogged (fragmented), and contiguous forest. Frequencies were noted for foraging guilds, tree gleaners, flycatchers, nesting guilds, tree drillers, and primary cavity nesters. Managers should consider a diversity of habitat conditions if maintaining habitat for bird species is an objective
On-treatment follow-up in real-world studies of direct oral anticoagulants in atrial fibrillation: Association with treatment effects.
Background
Numerous observational studies support the safety and effectiveness of the direct oral anticoagulants (DOAC) for stroke prevention in atrial fibrillation (AF), but these data are often limited to short duration of follow-up. We aimed to assess the length of on-treatment follow-up in the accumulated real-world evidence and the relationship between follow-up duration and estimates of DOAC effectiveness and safety.
Methods
We searched the literature for observational studies reporting comparative effectiveness and safety outcomes of DOACs versus warfarin. In random-effects meta-analyses, we assessed associations of specific DOACs vs warfarin for stroke/systematic embolism (SE) and major bleeding. In meta-regression analyses, we assessed the correlation between the reported on-treatment follow-up with the effect sizes for stroke/SE and major bleeding outcomes.
Results
In 45 eligible observational studies, the average on-treatment follow-up was <1 year for all DOACs. In meta-analyses, all DOACs showed significantly lower risks of stroke/SE, but only dabigatran and apixaban showed lower risks for major bleeding compared to warfarin. There was no correlation between follow-up duration and magnitude of stroke/SE reduction for any of the DOACs. Longer follow-up correlated with greater major bleeding reduction for dabigatran (p = 0.006) and rivaroxaban (p = 0.033) as compared to warfarin, but it correlated with smaller major bleeding reduction for apixaban (p = 0.004).
Conclusions
The numerous studies of DOAC effectiveness and safety in the routine AF practice pertain to short treatment follow-up. Study follow-up correlates significantly with DOAC-specific vs warfarin associations for major bleeding
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Effect of certain blood enzymes and cellular constituents on growth in different genetic groups of sheep
In the present study, five breeds of ewes and their lambs were
utilized. The breeds used were: Border Cheviot, Dorset Horn, Columbia,
Suffolk and Willamette. In all, 31 ewes and 42 lambs were involved.
The blood constituents which were determined for the ewes and
lambs were: acid and alkaline phosphatase, hematocrit, hemoglobin and
red and white blood cell numbers.
Blood samples were taken and analyzed for each ewe and lamb, at
two-week intervals, from the ninth or tenth day of lactation until
approximately 94 days subsequent to lambing. At 100 days of age the
lambs were scored for conformation and condition. Then the lambs were
slaughtered and a sample of each carcass was cooked and submitted to a
taste panel to obtain scores for tenderness and preference.
Acid phosphatase levels of activity were approximately three times
higher for lambs than for ewes at 10 days following lambing, and two
times higher than the level for ewes for the entire testing period.
Highly significant breed and period differences were observed for acid phosphatase levels in lambs. No breed differences for this enzyme were
noted in ewes.
Alkaline phosphatase levels of activity were higher in lambs than
in ewes throughout the testing period. The average alkaline phosphatase
value for lambs was 8.07 units compared to 2.96 units for the
ewes. The average alkaline phosphatase value of lambs was highest at
10 days (11.00 units) and lowest at 80 days (6.36 units). Alkaline
phosphatase levels were affected statistically (P<.01) by breed, sex
and period, and ewe values were affected (P<.01) by breed, period and
type of birth.
Hematocrit values were only slightly higher in lambs than in ewes.
At the first testing period the ewe values slightly exceeded the lamb
values, but from the second period until the end of the test the lamb
values were higher than the ewe values. Highly significant (P<.01)
differences were found in ewes according to breed and period, whereas,
lamb hematocrit values differed according to age of dam and period
(P<.01).
Hemoglobin levels followed a pattern similar to that found for
hematocrit in lambs and ewes. Hemoglobin values for lambs and ewes
reached the highest level at 24 days subsequent to lambing. Hemoglobin
levels differed significantly (P<.01) in ewes according to breed and
period, and in lambs according to period (P<.01) and sex (P<.05).
Average red blood cell counts were higher for ewes (9,690,000)
than for lambs (8,920,000) at 10 days subsequent to lambing, but by
94 days the average ewe red blood count was 8,440,000 compared to
10,680,000 for lambs. No breed differences could be found in red blood cell numbers for ewes or lambs. However, period and birth type
differences were observed in lambs.
White blood cell numbers were slightly more than one thousand
lower for lambs than for ewes at 10 days following lambing. The lamb
values were still lower than the ewe values at 24 days, but by 38 days
the lamb values exceeded the ewe values. White blood cell numbers
differed significantly (P<.01) for ewes according to breed and according
to breed, birth type and period for lambs. A slight sex difference
in white blood cell numbers was observed in lambs.
The Columbia lambs had the lowest conformation and condition
scores of any of the breeds. The Border Cheviots and the Willamettes
had the highest scores for conformation and condition, respectively.
However, the Columbias had the highest preference and tenderness
scores of any of the breeds, while the Border Cheviots had the lowest
preference and tenderness scores of any of the breeds.
The breeds ranked in the following order for average weight gains
of lambs: Willamettes, Suffolks, Columbias, Dorest Horns and Border
Cheviots. Body weight of lambs differed significantly (P<.01) according
to breed, birth type and period and (P<.05) according to sex.
None of the variables studied seemed to be highly related to
growth rate in lambs
Vader: A parsimonious rule-based model for sentiment analysis of social media text
Abstract The inherent nature of social media content poses serious challenges to practical applications of sentiment analysis. We present VADER, a simple rule-based model for general sentiment analysis, and compare its effectiveness to eleven typical state-of-practice benchmarks including LIWC, ANEW, the General Inquirer, SentiWordNet, and machine learning oriented techniques relying on Naive Bayes, Maximum Entropy, and Support Vector Machine (SVM) algorithms. Using a combination of qualitative and quantitative methods, we first construct and empirically validate a goldstandard list of lexical features (along with their associated sentiment intensity measures) which are specifically attuned to sentiment in microblog-like contexts. We then combine these lexical features with consideration for five general rules that embody grammatical and syntactical conventions for expressing and emphasizing sentiment intensity. Interestingly, using our parsimonious rule-based model to assess the sentiment of tweets, we find that VADER outperforms individual human raters (F1 Classification Accuracy = 0.96 and 0.84, respectively), and generalizes more favorably across contexts than any of our benchmarks
An Army of Me: Sockpuppets in Online Discussion Communities
In online discussion communities, users can interact and share information
and opinions on a wide variety of topics. However, some users may create
multiple identities, or sockpuppets, and engage in undesired behavior by
deceiving others or manipulating discussions. In this work, we study
sockpuppetry across nine discussion communities, and show that sockpuppets
differ from ordinary users in terms of their posting behavior, linguistic
traits, as well as social network structure. Sockpuppets tend to start fewer
discussions, write shorter posts, use more personal pronouns such as "I", and
have more clustered ego-networks. Further, pairs of sockpuppets controlled by
the same individual are more likely to interact on the same discussion at the
same time than pairs of ordinary users. Our analysis suggests a taxonomy of
deceptive behavior in discussion communities. Pairs of sockpuppets can vary in
their deceptiveness, i.e., whether they pretend to be different users, or their
supportiveness, i.e., if they support arguments of other sockpuppets controlled
by the same user. We apply these findings to a series of prediction tasks,
notably, to identify whether a pair of accounts belongs to the same underlying
user or not. Altogether, this work presents a data-driven view of deception in
online discussion communities and paves the way towards the automatic detection
of sockpuppets.Comment: 26th International World Wide Web conference 2017 (WWW 2017
User Intent Prediction in Information-seeking Conversations
Conversational assistants are being progressively adopted by the general
population. However, they are not capable of handling complicated
information-seeking tasks that involve multiple turns of information exchange.
Due to the limited communication bandwidth in conversational search, it is
important for conversational assistants to accurately detect and predict user
intent in information-seeking conversations. In this paper, we investigate two
aspects of user intent prediction in an information-seeking setting. First, we
extract features based on the content, structural, and sentiment
characteristics of a given utterance, and use classic machine learning methods
to perform user intent prediction. We then conduct an in-depth feature
importance analysis to identify key features in this prediction task. We find
that structural features contribute most to the prediction performance. Given
this finding, we construct neural classifiers to incorporate context
information and achieve better performance without feature engineering. Our
findings can provide insights into the important factors and effective methods
of user intent prediction in information-seeking conversations.Comment: Accepted to CHIIR 201
ACCOMMODATING MIXED-SEVERITY FIRE TO RESTORE AND MAINTAIN ECOSYSTEM INTEGRITY WITH A FOCUS ON THE SIERRA NEVADA OF CALIFORNIA, USA
Existing fire policy encourages the maintenance of ecosystem integrity in fire management, yet this is difficult to implement on lands managed for competing economic, human safety, and air quality concerns. We discuss a fire management approach in the mid-elevations of the Sierra Nevada, California, USA, that may exemplify similar challenges in other fire-adapted regions of the western USA. We also discuss how managing for pyrodiversity through mixed-severity fires can promote ecosystem integrity in Sierran mixed conifer and ponderosa pine (Pinus ponderosa Laws) forests. To illustrate, we show how coarse-filter (landscape-level) and complementary fine-filter (species-level) approaches can enhance forest management and conservation biology objectives as related to wildfire management. At the coarse-filter level, pyrodiverse mixed-severity fires provide landscape heterogeneity. Species and ecosystem characteristics associated with pyrodiversity can be maintained or enhanced by accommodating moderately severe fires, which hasten restoration by recreating a complex vegetation mosaic otherwise at risk from suppression. At the fine-filter level, managers can select focal species and species of conservation concern based on the degree to which those species depend on fire and accommodate their specific conservation needs. The black-backed woodpecker (Picoides arcticus [Swainson, 1832]) is an ideal focal species for monitoring the ecological integrity of forests restored through mixed-severity fire, and the California spotted owl (Strix occidentalis occidentalis [Xantus de Vesey, 1860]) is a species of conservation concern that uses post-fire habitat mosaics and is particularly vulnerable to logging. We suggest a comprehensive approach that integrates wildland fire for ecosystem integrity and species viability with strategic deployment of fire suppression and ecologically based restoration of pyrodiverse landscapes. Our approach would accomplish fire management goals while simultaneously maintaining biodiversity
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