On-farm Campylobacter and Escherichia coli in commercial broiler chickens: Re-used bedding does not influence Campylobacter emergence and levels across sequential farming cycles

Limitations in quality bedding material have resulted in the growing need to re-use litter during broiler farming in some countries, which can be of concern from a food-safety perspective. The aim of this study was to compare the Campylobacter levels in ceca and litter across three litter treatments under commercial farming conditions. The litter treatments were (a) the use of new litter after each farming cycle; (b) an Australian partial litter re-use practice; and (c) a full litter re-use practice. The study was carried out on two farms over two years (Farm 1, from 2009–2010 and Farm 2, from 2010–2011), across three sheds (35,000 to 40,000 chickens/shed) on each farm, adopting three different litter treatments across six commercial cycles. A random sampling design was adopted to test litter and ceca for Campylobacter and Escherichia coli, prior to commercial first thin-out and final pick-up. Campylobacter levels varied little across litter practices and farming cycles on each farm and were in the range of log 8.0–9.0 CFU/g in ceca and log 4.0–6.0 MPN/g for litter. Similarly the E. coli in ceca were ∼log 7.0 CFU/g. At first thin-out and final pick-up, the statistical analysis for both litter and ceca showed that the three-way interaction (treatments by farms by times) was highly significant (P < 0.01), indicating that the patterns of Campylobacter emergence/presence across time vary between the farms, cycles and pickups. The emergence and levels of both organisms were not influenced by litter treatments across the six farming cycles on both farms. Either C. jejuni or C. coli could be the dominant species across litter and ceca, and this phenomenon could not be attributed to specific litter treatments. Irrespective of the litter treatments in place, cycle 2 on Farm 2 remained campylobacter-free. These outcomes suggest that litter treatments did not directly influence the time of emergence and levels of Campylobacter and E. coli during commercial farming.

Fast algorithms for frequent episode discovery in event sequences

In this paper we consider the process of discovering frequent episodes in event sequences. The most computationally intensive part of this process is that of counting the frequencies of a set of candidate episodes. We present two new frequency counting algorithms for speeding up this part. These, referred to as non-overlapping and non-inteleaved frequency counts, are based on directly counting suitable subsets of the occurrences of an episode. Hence they are different from the frequency counts of Mannila et al [1], where they count the number of windows in which the episode occurs. Our new frequency counts offer a speed-up factor of 7 or more on real and synthetic datasets. We also show how the new frequency counts can be used when the events in episodes have time-durations as well.

Generalized frequent episodes in Event Sequences

Discovering patterns in temporal data is an important task in Data Mining. A successful method for this was proposed by Mannila et al. [1] in 1997. In their framework, mining for temporal patterns in a database of sequences of events is done by discovering the so called frequent episodes. These episodes characterize interesting collections of events occurring relatively close to each other in some partial order. However, in this framework(and in many others for finding patterns in event sequences), the ordering of events in an event sequence is the only allowed temporal information. But there are many applications where the events are not instantaneous; they have time durations. Interesting episodesthat we want to discover may need to contain information regarding event durations etc. In this paper we extend Mannila et al.’s framework to tackle such issues. In our generalized formulation, episodes are defined so that much more temporal information about events can be incorporated into the structure of an episode. This significantly enhances the expressive capability of the rules that can be discovered in the frequent episode framework. We also present algorithms for discovering such generalized frequent episodes.

Pattern-growth based frequent serial episode discovery

Frequent episode discovery is a popular framework for pattern discovery from sequential data. It has found many applications in domains like alarm management in telecommunication networks, fault analysis in the manufacturing plants, predicting user behavior in web click streams and so on. In this paper, we address the discovery of serial episodes. In the episodes context, there have been multiple ways to quantify the frequency of an episode. Most of the current algorithms for episode discovery under various frequencies are apriori-based level-wise methods. These methods essentially perform a breadth-first search of the pattern space. However currently there are no depth-first based methods of pattern discovery in the frequent episode framework under many of the frequency definitions. In this paper, we try to bridge this gap. We provide new depth-first based algorithms for serial episode discovery under non-overlapped and total frequencies. Under non-overlapped frequency, we present algorithms that can take care of span constraint and gap constraint on episode occurrences. Under total frequency we present an algorithm that can handle span constraint. We provide proofs of correctness for the proposed algorithms. We demonstrate the effectiveness of the proposed algorithms by extensive simulations. We also give detailed run-time comparisons with the existing apriori-based methods and illustrate scenarios under which the proposed pattern-growth algorithms perform better than their apriori counterparts. (C) 2013 Elsevier B.V. All rights reserved.

Statistical significance of episodes with general partial orders

Frequent episode discovery is one of the methods used for temporal pattern discovery in sequential data. An episode is a partially ordered set of nodes with each node associated with an event type. For more than a decade, algorithms existed for episode discovery only when the associated partial order is total (serial episode) or trivial (parallel episode). Recently, the literature has seen algorithms for discovering episodes with general partial orders. In frequent pattern mining, the threshold beyond which a pattern is inferred to be interesting is typically user-defined and arbitrary. One way of addressing this issue in the pattern mining literature has been based on the framework of statistical hypothesis testing. This paper presents a method of assessing statistical significance of episode patterns with general partial orders. A method is proposed to calculate thresholds, on the non-overlapped frequency, beyond which an episode pattern would be inferred to be statistically significant. The method is first explained for the case of injective episodes with general partial orders. An injective episode is one where event-types are not allowed to repeat. Later it is pointed out how the method can be extended to the class of all episodes. The significance threshold calculations for general partial order episodes proposed here also generalize the existing significance results for serial episodes. Through simulations studies, the usefulness of these statistical thresholds in pruning uninteresting patterns is illustrated. (C) 2014 Elsevier Inc. All rights reserved.

Migration patterns of young Pacific bluefin tuna (Thunnus orientalis) determined with archival tags

We investigated the migration and behavior of young Pacific bluefin tuna (Thunnus orientalis) using archival tags that measure environmental variables, record them in memory, and estimate daily geographical locations using measured light levels. Swimming depth, ambient water temperature, and feeding are described in a companion paper. Errors of the tag location estimates that could be checked were –0.54° ±0.75° (mean ±SD) in longitude and –0.12° ±3.06° in latitude. Latitude, estimated automatically by the tag, was problematic, but latitude, estimated by comparing recorded sea-surface temperatures with a map of sea-surface temperature, was satisfactory. We concluded that the archival tag is a reliable tool for estimating location on a scale of about one degree, which is sufficient for a bluefin tuna migration study. After release, tagged fish showed a normal swimming behavioral pattern within one day and normal feeding frequency within one month. In addition, fish with an archival tag maintained weight-at-length similar to that of wild fish; however, their growth rate was less than that of wild fish. Of 166 fish released in the East China Sea with implanted archival tags, 30 were recovered, including one that migrated across the Pacific Ocean. Migration of young Pacific bluefin tuna appears to consist of two phases: a residency phase comprising more than 80% of all days, and a traveling phase. An individual young Pacific bluefin tuna was observed to cover 7600 km in one traveling phase that lasted more than two months (part of this phase was a trans-Pacific migration completed within two months). Many features of behavior in the traveling phase were similar to those in the residency phase; however the temperature difference between viscera and ambient temperature was larger, feeding was slightly more frequent, and dives to deeper water were more frequent.

Generalized Methods for Discovering Frequent Poly-Regions in DNA

The problem of discovering frequent poly-regions (i.e. regions of high occurrence of a set of items or patterns of a given alphabet) in a sequence is studied, and three efficient approaches are proposed to solve it. The first one is entropy-based and applies a recursive segmentation technique that produces a set of candidate segments which may potentially lead to a poly-region. The key idea of the second approach is the use of a set of sliding windows over the sequence. Each sliding window covers a sequence segment and keeps a set of statistics that mainly include the number of occurrences of each item or pattern in that segment. Combining these statistics efficiently yields the complete set of poly-regions in the given sequence. The third approach applies a technique based on the majority vote, achieving linear running time with a minimal number of false negatives. After identifying the poly-regions, the sequence is converted to a sequence of labeled intervals (each one corresponding to a poly-region). An efficient algorithm for mining frequent arrangements of intervals is applied to the converted sequence to discover frequently occurring arrangements of poly-regions in different parts of DNA, including coding regions. The proposed algorithms are tested on various DNA sequences producing results of significant biological meaning.

Constraint-based Mining of Frequent Arrangements of Temporal Intervals

The problem of discovering frequent arrangements of temporal intervals is studied. It is assumed that the database consists of sequences of events, where an event occurs during a time-interval. The goal is to mine temporal arrangements of event intervals that appear frequently in the database. The motivation of this work is the observation that in practice most events are not instantaneous but occur over a period of time and different events may occur concurrently. Thus, there are many practical applications that require mining such temporal correlations between intervals including the linguistic analysis of annotated data from American Sign Language as well as network and biological data. Two efficient methods to find frequent arrangements of temporal intervals are described; the first one is tree-based and uses depth first search to mine the set of frequent arrangements, whereas the second one is prefix-based. The above methods apply efficient pruning techniques that include a set of constraints consisting of regular expressions and gap constraints that add user-controlled focus into the mining process. Moreover, based on the extracted patterns a standard method for mining association rules is employed that applies different interestingness measures to evaluate the significance of the discovered patterns and rules. The performance of the proposed algorithms is evaluated and compared with other approaches on real (American Sign Language annotations and network data) and large synthetic datasets.

The validity of a latent class typology of adolescent drinking patterns

Objectives: This study examined the validity of a latent class typology of adolescent drinking based on four alcohol dimensions; frequency of drinking, quantity consumed, frequency of binge drinking and the number of alcohol related problems encountered. Method: Data used were from the 1970 British Cohort Study sixteen-year-old follow-up. Partial or complete responses to the selected alcohol measures were provided by 6,516 cohort members. The data were collected via a series of postal questionnaires. Results: A five class LCA typology was constructed. Around 12% of the sample were classified as �hazardous drinkers� reporting frequent drinking, high levels of alcohol consumed, frequent binge drinking and multiple alcohol related problems. Multinomial logistic regression, with multiple imputation for missing data, was used to assess the covariates of adolescent drinking patterns. Hazardous drinking was associated with being white, being male, having heavy drinking parents (in particular fathers), smoking, illicit drug use, and minor and violent offending behaviour. Non-significant associations were found between drinking patterns and general mental health and attention deficient disorder. Conclusion: The latent class typology exhibited concurrent validity in terms of its ability to distinguish respondents across a number of alcohol and non-alcohol indicators. Notwithstanding a number of limitations, latent class analysis offers an alternative data reduction method for the construction of drinking typologies that addresses known weaknesses inherent in more tradition classification methods.

Distinct patterns of peripheral HIV-1-specific interferon- gamma responses in exposed HIV-1-seronegative individuals.

It is unclear how human immunodeficiency virus (HIV) type 1–specific immune responses in exposed seronegative (ESN) individuals differ from those in HIV-1–infected subjects. By use of overlapping peptides spanning Gag, Tat, Nef, Vif, Vpr, and Vpu, peripheral blood mononuclear cells from ESN individuals, their seropositive (SP) partners, and unexposed seronegative control subjects were screened for interferon-? production. Responses were more frequent (95.7% vs. 20%), of a higher magnitude (9-fold), and of wider breadth (median number of peptides recognized, 18 vs. 2.5) in SP than in ESN individuals. Peptides recognized by ESN individuals were less frequently recognized by their SP partners. SP subjects infrequently recognized peptides from Vif, and such responses were subdominant; among ESN individuals, this HIV-1 protein was most frequently recognized. Immunodominant peptides recognized by SP subjects tended to be from relatively conserved regions, whereas peptides recognized by ESN individuals were associated with slow disease progression.

Ecological coherence in marine reserve network design: an empirical evaluation of sequential site selection using genetic structure

Ecological coherence is a multifaceted conservation objective that includes some potentially conflicting concepts. These concepts include the extent to which the network maximises diversity (including genetic diversity) and the extent to which protected areas interact with non-reserve locations. To examine the consequences of different selection criteria, the preferred location to complement protected sites was examined using samples taken from four locations around each of two marine protected areas: Strangford Lough and Lough Hyne, Ireland. Three different measures of genetic distance were used: FST, Dest and a measure of allelic dissimilarity, along with a direct assessment of the total number of alleles in different candidate networks. Standardized site scores were used for comparisons across methods and selection criteria. The average score for Castlehaven, a site relatively close to Lough Hyne, was highest, implying that this site would capture the most genetic diversity while ensuring highest degree of interaction between protected and unprotected sites. Patterns around Strangford Lough were more ambiguous, potentially reflecting the weaker genetic structure around this protected area in comparison to Lough Hyne. Similar patterns were found across species with different dispersal capacities, indicating that methods based on genetic distance could be used to help maximise ecological coherence in reserve networks. ⺠Ecological coherence is a key component of marine protected area network design. ⺠Coherence contains a number of competing concepts. ⺠Genetic information from field populations can help guide assessments of coherence. ⺠Average choice across different concepts of coherence was consistent among species. ⺠Measures can be combined to compare the coherence of different network designs.

Parallel patterns + Macro Data Flow for multi-core programming

Data flow techniques have been around since the early '70s when they were used in compilers for sequential languages. Shortly after their introduction they were also consideredas a possible model for parallel computing, although the impact here was limited. Recently, however, data flow has been identified as a candidate for efficient implementation of various programming models on multi-core architectures. In most cases, however, the burden of determining data flow "macro" instructions is left to the programmer, while the compiler/run time system manages only the efficient scheduling of these instructions. We discuss a structured parallel programming approach supporting automatic compilation of programs to macro data flow and we show experimental results demonstrating the feasibility of the approach and the efficiency of the resulting "object" code on different classes of state-of-the-art multi-core architectures. The experimental results use different base mechanisms to implement the macro data flow run time support, from plain pthreads with condition variables to more modern and effective lock- and fence-free parallel frameworks. Experimental results comparing efficiency of the proposed approach with those achieved using other, more classical, parallel frameworks are also presented. © 2012 IEEE.

Physicochemical tolerance, habitat use and predation are drivers of patterns of coexistence and exclusion among invasive and resident amphipods

1. Patterns of coexistence and exclusion among resident and invading species in freshwaters may be generated by direct biotic interactions well as by indirect interactions with the broader abiotic and biotic environments. The North American ‘shrimp’ Crangonyx pseudogracilis (Crustacea: Amphipoda) is invasive in Europe where it forms complex patterns of apparent exclusion and coexistence with resident Gammarus spp. amphipods. Using a comprehensive integrated approach, we investigated the potential biotic and interacting abiotic factors driving these distribution patterns.
2. A 2009 of 69 sites revealed that of 56 river sites containing amphipods only 6 contained C. pseudogracilis and these always co-occurred with Gammarus spp.. In contrast, C. pseudogracilis was the only species present in the 12 ponds/reservoirs containing amphipods.
3. Field transplant experiments in ponds and laboratory oxygen tolerance experiments revealed that C. pseudogracilis tolerates physicochemical regimes which Gammarus spp. are incapable of surviving.
4. River microhabitat sampling showed C. pseudogracilis dominating in slower, more pooled and macrophyte-dense patches, while Gammarus spp. were dominant in faster, more riffled areas.
5. Field bioassays indicated that predation of C. pseudogracilis by Gammarus spp. may be frequent in patches of rivers if/when the species meet.
6. River drift sampling revealed that C. pseudogracilis was greatly underrepresented in night/day drift relative to the Gammarus spp.. Laboratory studies showed C. pseudogracilis to be more photophobic and less active than Gammarus spp., both behaviours potentially contributing to low drift prevalence and consequent reduced exposure to shared drift predators.
7. These interacting factors may ultimately contribute to the coexistence, exclusion and relative distributions of C. pseudogracilis and Gammarus spp.. The former is potentially subject to intense predation from the latter if they encounter one another in the same microhabitat. However, with C. pseudogracilis being more physicochemically tolerant and displaying different habitat utilisation patterns than the Gammarus spp. in respect of the benthos and drift, such encounters are probably minimised. Hence C. pseudogracilis can persist in the same sites with the Gammarus spp., albeit in different microhabitats.

A mixed methods study of the work patterns of full-time nurse practitioners in nursing homes

Aims and objectives: The aim of this study was to explore the integration of the nurse practitioner role in Canadian nursing homes to enable its full potential to be realised for resident and family care. The objective was to determine nurse practitioners' patterns of work activities. 

Background: Nurse practitioners were introduced in Canadian nursing homes a decade ago on a pilot basis. In recent years, government and nursing home sector interest in the role has grown along with the need for data to inform planning efforts. 

Design: The study used a sequential mixed methods design using a national survey followed by case studies. 

Methods: A national survey of nurse practitioners included demographic items and the EverCare Nurse Practitioner Role and Activity Scale. Following the survey, case studies were conducted in four nursing homes. Data were collected using individual and focus group interviews, document reviews and field notes. 

Results: Twenty-three of a target population of 26 nurse practitioners responded to the survey, two-thirds of whom provided services in nursing homes with one site and the remainder in nursing homes with as many as four sites. On average, nurse practitioners performed activities in communicator, clinician, care manager/coordinator and coach/educator subscales at least three to four times per week and activities in the collaborator subscale once a week. Of the 43 activities, nurse practitioners performed daily, most were in the clinician and communicator subscales. Case study interviews involved 150 participants. Findings complemented those of the survey and identified additional leadership activities. 

Conclusion: Nurse practitioners undertake a range of primary health care and advanced practice activities which they adapt to meet the unique needs of nursing homes. Relevance to clinical practice: Knowledge of work patterns enables nursing homes to implement the full range of nurse practitioner roles and activities to enhance resident and family care.

Patterns and predictors of help-seeking contacts with health services and general practitioner detection of suicidality prior to suicide: a cohort analysis of suicides occurring over a two-year period

Background: Contact with primary care and psychiatric services prior to suicide may be considerable, presenting
opportunities for intervention. However, there is scant knowledge on the frequency, nature and determinants of
contact.
Method: Retrospective cohort study-an analysis of deaths recorded as suicide by the Northern Ireland Coroner’s
Office linked with data from General Practice patient records over a 2 year period
Results: Eighty-seven per cent of suicides were in contact with General Practice services in the 12 months before
suicide. The frequency of contact with services was considerable, particularly among patients with a common
mental disorder or substance misuse problems. A diagnosis of psychiatric problems was absent in 40 % of suicides.
Excluding suicide attempts, the main predictors of a noted general practitioner concern for patient suicidality are
male gender, frequency of consultations, diagnosis of mental illness and substance misuse.
Conclusions: Despite widespread and frequent contact, a substantial proportion of suicidal people were
undiagnosed and untreated for mental health problems. General Practitioner alertness to suicidality may be too
narrowly focused.