Beyond the standard work model? Varieties of flexible working time in European economies

Working time has been among the first aspect of the employment relation to be the object of intense regulation at the national and supra-national level. This standard regulation of working time comprised a number of elements: full-time hours, rigid working schedules, strong employers’ control and clear boundaries around working time In spite of general claims about the erosion of this model, few studies have investigated this process in a comparative and empirical perspective. The aim of this paper is to investigate the diversity of working time arrangements in European economies by applying latent class analysis to data
from the European Working Conditions Survey (EWCS). This analysis shows the existence of six different types of working time organization highlighting five cross-national patterns: multiple flexibilities, extended flexibility, standard, rigid and fragmented time.

Overconfidence, sexual health awareness and sexual health risk among young female users of sexual health clinics

This study explored the patterning of young people’s sexual health competence, and how this relates to sexual health outcomes. A survey of 381 young people attending two sexual health clinics in Northern Ireland was carried out between 2009 and 2010. Latent profile analysis of self-rated decision making, self-rated sexual health knowledge, and knowledge of sexually transmitted disease questionnaire scores was used to determine typologies of sexual health competence. Analysis revealed three categories of sexual health competence and explored their association with other behaviours and social characteristics. Young people’s subjective opinion of their sexual health competency, when not matched with a corresponding knowledge of sexual health, could place people at an increased risk of poor sexual health outcomes. Greater levels of peer pressure to have sex and early sexual debut were associated with poorer sexual health knowledge. This finding warrants further investigation, as the importance of self-perceived competence for sexual health screening and education programmes are considerable.

Turbo-smt: Accelerating coupled sparse matrix-tensor factorizations by 200x

How can we correlate the neural activity in the human brain as it responds to typed words, with properties of these terms (like ‘edible’, ‘fits in hand’)? In short, we want to find latent variables, that jointly explain both the brain activity, as well as the behavioral responses. This is one of many settings of the Coupled Matrix-Tensor Factorization (CMTF) problem.

Can we accelerate any CMTF solver, so that it runs within a few minutes instead of tens of hours to a day, while maintaining good accuracy? We introduce Turbo-SMT, a meta-method capable of doing exactly that: it boosts the performance of any CMTF algorithm, by up to 200x, along with an up to 65 fold increase in sparsity, with comparable accuracy to the baseline.

We apply Turbo-SMT to BrainQ, a dataset consisting of a (nouns, brain voxels, human subjects) tensor and a (nouns, properties) matrix, with coupling along the nouns dimension. Turbo-SMT is able to find meaningful latent variables, as well as to predict brain activity with competitive accuracy.

Rapid detection of health-care-associated bloodstream infection in critical care using multipathogen real-time polymerase chain reaction technology: a diagnostic accuracy study and systematic review

Background: There is growing interest in the potential utility of real-time polymerase chain reaction (PCR) in diagnosing bloodstream infection by detecting pathogen deoxyribonucleic acid (DNA) in blood samples within a few hours. SeptiFast (Roche Diagnostics GmBH, Mannheim, Germany) is a multipathogen probe-based system targeting ribosomal DNA sequences of bacteria and fungi. It detects and identifies the commonest pathogens causing bloodstream infection. As background to this study, we report a systematic review of Phase III diagnostic accuracy studies of SeptiFast, which reveals uncertainty about its likely clinical utility based on widespread evidence of deficiencies in study design and reporting with a high risk of bias. 

Objective: Determine the accuracy of SeptiFast real-time PCR for the detection of health-care-associated bloodstream infection, against standard microbiological culture. 

Design: Prospective multicentre Phase III clinical diagnostic accuracy study using the standards for the reporting of diagnostic accuracy studies criteria. 

Setting: Critical care departments within NHS hospitals in the north-west of England. 

Participants: Adult patients requiring blood culture (BC) when developing new signs of systemic inflammation. 

Main outcome measures: SeptiFast real-time PCR results at species/genus level compared with microbiological culture in association with independent adjudication of infection. Metrics of diagnostic accuracy were derived including sensitivity, specificity, likelihood ratios and predictive values, with their 95% confidence intervals (CIs). Latent class analysis was used to explore the diagnostic performance of culture as a reference standard. 

Results: Of 1006 new patient episodes of systemic inflammation in 853 patients, 922 (92%) met the inclusion criteria and provided sufficient information for analysis. Index test assay failure occurred on 69 (7%) occasions. Adult patients had been exposed to a median of 8 days (interquartile range 4–16 days) of hospital care, had high levels of organ support activities and recent antibiotic exposure. SeptiFast real-time PCR, when compared with culture-proven bloodstream infection at species/genus level, had better specificity (85.8%, 95% CI 83.3% to 88.1%) than sensitivity (50%, 95% CI 39.1% to 60.8%). When compared with pooled diagnostic metrics derived from our systematic review, our clinical study revealed lower test accuracy of SeptiFast real-time PCR, mainly as a result of low diagnostic sensitivity. There was a low prevalence of BC-proven pathogens in these patients (9.2%, 95% CI 7.4% to 11.2%) such that the post-test probabilities of both a positive (26.3%, 95% CI 19.8% to 33.7%) and a negative SeptiFast test (5.6%, 95% CI 4.1% to 7.4%) indicate the potential limitations of this technology in the diagnosis of bloodstream infection. However, latent class analysis indicates that BC has a low sensitivity, questioning its relevance as a reference test in this setting. Using this analysis approach, the sensitivity of the SeptiFast test was low but also appeared significantly better than BC. Blood samples identified as positive by either culture or SeptiFast real-time PCR were associated with a high probability (> 95%) of infection, indicating higher diagnostic rule-in utility than was apparent using conventional analyses of diagnostic accuracy. 

Conclusion: SeptiFast real-time PCR on blood samples may have rapid rule-in utility for the diagnosis of health-care-associated bloodstream infection but the lack of sensitivity is a significant limiting factor. Innovations aimed at improved diagnostic sensitivity of real-time PCR in this setting are urgently required. Future work recommendations include technology developments to improve the efficiency of pathogen DNA extraction and the capacity to detect a much broader range of pathogens and drug resistance genes and the application of new statistical approaches able to more reliably assess test performance in situation where the reference standard (e.g. blood culture in the setting of high antimicrobial use) is prone to error.

Utilisation of a novel ProteaseTag™ activity immunoassay for the specific measurement of neutrophil elastase in patients with Cystic Fibrosis

Neutrophil elastase (NE), a biomarker of infection and inflammation, correlates with the severity of several respiratory diseases including cystic fibrosis (CF) however, its detection and quantification in biological samples is confounded by a lack of robust methodologies. Standard assays using chromogenic or fluorogenic substrates are not specific when added to complex samples containing multiple proteolytic and hydrolytic enzymes, resulting in an over-estimation of the target protease. ELISA systems measure total protein levels which can be a mixture of latent, active and protease-inhibitor complexes. We have therefore developed a novel immunoassay (NE-Tag ELISA), incorporating an activity dependent ProteaseTag™ and a specific antibody step, which is selective and specific for the capture of active NE. The objective of this study was to clinically validate NE-Tag ELISA for the detection of active NE in sputum from CF patients. Sputum (n=45) was recovered from CF patients hospitalised for acute exacerbation. Sol was recovered and analysed for NE activity using the NE-Tag ELISA and two fluorogenic substrate-based assays [1. Suc-AAPV-AMC (Sigma) and 2. InnozymeTM Immunocapture assay (Calbiochem)]. NE activity between assays and with a range of clinical parameters was correlated.A highly significant correlation was shown between assays. NE activity (NE-Tag) further correlated appropriately with clinical parameters: inversely with FEV1 (p = 0.036) and positively with CRP (p = 0.035), neutrophils and total white cell counts (p < 0.001). The InnozymeTM assay showed similar correlations with the clinical parameters (with the exception of CRP). No correlations with any of the clinical parameters were observed when NE was measured using the standard fluorogenic substrate.

Multiloop robust H∞ control design based on the dynamic PLS approach to chemical processes

In this paper, a multiloop robust control strategy is proposed based on H∞ control and a partial least squares (PLS) model (H∞_PLS) for multivariable chemical processes. It is developed especially for multivariable systems in ill-conditioned plants and non-square systems. The advantage of PLS is to extract the strongest relationship between the input and the output variables in the reduced space of the latent variable model rather than in the original space of the highly dimensional variables. Without conventional decouplers, the dynamic PLS framework automatically decomposes the MIMO process into multiple single-loop systems in the PLS subspace so that the controller design can be simplified. Since plant/model mismatch is almost inevitable in practical applications, to enhance the robustness of this control system, the controllers based on the H∞ mixed sensitivity problem are designed in the PLS latent subspace. The feasibility and the effectiveness of the proposed approach are illustrated by the simulation results of a distillation column and a mixing tank process. Comparisons between H∞_PLS control and conventional individual control (either H∞ control or PLS control only) are also made

Shape stabilised phase change materials based on a high melt viscosity HDPE and paraffin waxes

Shape stabilised phase change materials (SSPCMs) based on a high density poly(ethylene)(hv-HDPE) with high (H-PW, Tm = 56–58 °C) and low (L-PW, Tm = 18–23 °C) melting point paraffin waxes were readily prepared using twin-screw extrusion. The thermo-physical properties of these materials were assessed using a combination of techniques and their suitability for latent heat thermal energy storage (LHTES) assessed. The melt processing temperature (160 °C) of the HDPE used was well below the onset of thermal decomposition of H-PW (220 °C), but above that for L-PW (130 °C), although the decomposition process extended over a range of 120 °C and the residence time of L-PW in the extruder was <30 s. The SSPCMs prepared had latent heats up to 89 J/g and the enthalpy values for H-PW in the respective blends decreased with increasing H-PW loading, as a consequence of co-crystallisation of H-PW and hv-HDPE. Static and dynamic mechanical analysis confirmed both waxes have a plasticisation effect on this HDPE. Irrespective of the mode of deformation (tension, flexural, compression) modulus and stress decreased with increased wax loading in the blend, but the H-PW blends were mechanically superior to those with L-PW.

The Determinants of Brownfields Redevelopment in England

This paper uses discrete choice models, supported by GIS data, to analyse the National Land Use Database, a register of more than 21,000 English brownfields - previously used sites with or without contamination that are currently unused or underused. Using spatial discrete choice models, including the first application of a spatial probit latent class model with class-specific neighbourhood effects, we find evidence of large local differences in the determinants of brownfields redevelopment in England and that the reuse decisions of adjacent sites affect the reuse of a site. We also find that sites with a history of industrial activities, large sites, and sites that are located in the poorest and bleakest areas of cities and regions of England are more difficult to redevelop. In particular, we find that the probability of reusing a brownfield increases by up to 8.5% for a site privately owned compared to a site publicly owned and between 15% - 30% if a site is located in London compared to the North West of England. We suggest that local tailored policies are more suitable than regional or national policies to boost the reuse of brownfield sites.

Scoup-SMT: Scalable Coupled Sparse Matrix-Tensor Factorization

How can we correlate neural activity in the human brain as it responds to words, with behavioral data expressed as answers to questions about these same words? In short, we want to find latent variables, that explain both the brain activity, as well as the behavioral responses. We show that this is an instance of the Coupled Matrix-Tensor Factorization (CMTF) problem. We propose Scoup-SMT, a novel, fast, and parallel algorithm that solves the CMTF problem and produces a sparse latent low-rank subspace of the data. In our experiments, we find that Scoup-SMT is 50-100 times faster than a state-of-the-art algorithm for CMTF, along with a 5 fold increase in sparsity. Moreover, we extend Scoup-SMT to handle missing data without degradation of performance. We apply Scoup-SMT to BrainQ, a dataset consisting of a (nouns, brain voxels, human subjects) tensor and a (nouns, properties) matrix, with coupling along the nouns dimension. Scoup-SMT is able to find meaningful latent variables, as well as to predict brain activity with competitive accuracy. Finally, we demonstrate the generality of Scoup-SMT, by applying it on a Facebook dataset (users, friends, wall-postings); there, Scoup-SMT spots spammer-like anomalies.

Development of a Novel Assay for the Detection of Active Neutrophil Elastase in Patients with Chronic Obstructive Pulmonary Disease

Neutrophil elastase (NE), a biomarker of infection and inflammation, correlates with the severity of several respiratory diseases including chronic obstructive pulmonary disease (COPD). However, it’s detection and quantification in biological samples is confounded by a lack of reliable and robust methodologies. Standard assays using chromogenic or fluorogenic substrates are not specific when added to complex clinical samples containing multiple proteolytic and hydrolytic enzymes which have the ability to hydrolyse the substrate, thereby resulting in an over-estimation of the target protease. Furthermore, ELISA systems measure total protease levels which can be a mixture of latent, active and protease-inhibitor complexes. Therefore, we have developed a novel immunoassay (ProteaseTag™ Active NE Immunoassay) which is selective and specific for the capture of active NE in sputum and Bronchoalveolar Lavage (BAL) in patients with COPD. The objective of this study was to clinically validate ProteaseTag™ Active NE Ultra Immunoassay for the detection of NE in sputum from COPD patients. 20 matched sputum sol samples were collected from 10 COPD patients (M=6, F=4; 73 ± 6 years) during stable and exacerbation phases. Samples were assayed for NE activity utilising both ProteaseTag™ Active NE Ultra Immunoassay and a fluorogenic substrate-based kinetic activity assay. Both assays detected elevated levels of NE in the majority of patients (n=7) during an exacerbation (mean=217.2 μg/ml ±296.6) compared to their stable phase (mean=92.37 μg/ml ±259.8). However, statistical analysis did not show this difference to be significant (p=0.07, ProteaseTag™ Active NE Ultra Immunoassay; p=0.06 kinetic assay), most likely due to the low study number. A highly significant correlation was found between the 2 assay types (p≤0.0001, r=0.996). NE as a primary efficacy endpoint in clinical trials or as a marker of inflammation within the clinic has been hampered by the lack of a robust and simple to use assay. ProteaseTag™ Active NE Immunoassay specifically measures only active NE in clinical samples, is quick and easy to use (< 3 hours) and has no dependency on a kinetic readout. ProteaseTag™ technology is currently being transferred to a lateral flow device for use at Point of Care.

Utilisation of a novel ProteaseTag™ activity immunoassay for the specific measurement of neutrophil elastase in BAL from children with cystic fibrosis

Introduction: Neutrophil elastase (NE) is a serine protease implicated in the pathogenesis of several respiratory diseases including cystic fibrosis (CF). The presence of free NE in BAL is a predictor of subsequent bronchiectasis in children with CF (Sly et al, 2013, NEJM 368: 1963-1970). Furthermore, children with higher levels of sputum NE activity (NEa) tend to experience a more rapid decline in FEV1 over time even after adjusting for age, gender and baseline FEV1 (Sagel et al, 2012, AJRCCM 186: 857-865). Its detection and quantification in biological samples is however confounded by a lack of robust methodologies. Standard assays using chromogenic or fluorogenic substrates are not specific when added to complex samples containing multiple proteolytic and hydrolytic enzymes. ELISA systems measure total protein levels which can be a mixture of latent, active and protease-inhibitor complexes. We have therefore developed a novel assay (ProteaseTag™ Active NE Immunoassay), which couples an activity dependent NE-Tag with a specific antibody step, resulting in an assay which is both selective and specific for NEa. Aims: To clinically validate ProteaseTag™ Active NE for the detection of free NEa in BAL from children with CF. Methods: A total of 95 paediatric BAL samples [CF (n=76; 44M, 32F) non-CF (n=19; 12M, 7F)] collected through the Study of Host Immunity and Early Lung Disease in CF (SHIELD CF) were analysed for NEa using ProteaseTag™ Active NE (ProAxsis Ltd) and a fluorogenic substrate-based assay utilising Suc-AAPV-AMC (Sigma). IL-8 was measured by ELISA (R&D Systems). Results were analysed to show comparisons in free NEa between CF and non-CF samples alongside correlations with a range of clinical parameters. Results: NEa measured by ProteaseTag™ Active NE correlated significantly with age (r=0.3, p=0.01) and highly significantly with both IL-8 (r=0.4, p=<0.0001) and the absolute neutrophil count (ANC) (r=0.4, p=<0.0001). These correlations were not observed when NEa was measured by the substrate assay even though a significant correlation was found between the two assays (r=0.8, p<0.0001). A trend towards significance was found between NEa in the CF and non-CF groups when measured by ProteaseTag™ Active NE (p=0.07). Highly significant differences were found with the other inflammatory parameters between the 2 groups (IL-8: p=0.0002 and ANC: p=0.006). Conclusion: NEa as a primary efficacy endpoint in clinical trials or as a marker of inflammation within the clinic has been hampered by the lack of a robust and simple to use assay. ProteaseTag™ Active NE has been shown to be a specific and superior tool in the measurement of NEa in paediatric CF BAL samples (supporting data from previous studies using adult CF expectorated samples). The technology is currently being transferred to a lateral flow device for use at Point of Care. Acknowledgements: This work was supported by the National Children’s Research Centre, Dublin (SHIELD CF) and grants from the Medical Research Council and Cystic Fibrosis Foundation Therapeutics.

Step by step: reconstruction of terrestrial animal movement paths by dead-reckoning

BACKGROUND: Research on wild animal ecology is increasingly employing GPS telemetry in order to determine animal movement. However, GPS systems record position intermittently, providing no information on latent position or track tortuosity. High frequency GPS have high power requirements, which necessitates large batteries (often effectively precluding their use on small animals) or reduced deployment duration. Dead-reckoning is an alternative approach which has the potential to 'fill in the gaps' between less resolute forms of telemetry without incurring the power costs. However, although this method has been used in aquatic environments, no explicit demonstration of terrestrial dead-reckoning has been presented.

RESULTS: We perform a simple validation experiment to assess the rate of error accumulation in terrestrial dead-reckoning. In addition, examples of successful implementation of dead-reckoning are given using data from the domestic dog Canus lupus, horse Equus ferus, cow Bos taurus and wild badger Meles meles.

CONCLUSIONS: This study documents how terrestrial dead-reckoning can be undertaken, describing derivation of heading from tri-axial accelerometer and tri-axial magnetometer data, correction for hard and soft iron distortions on the magnetometer output, and presenting a novel correction procedure to marry dead-reckoned paths to ground-truthed positions. This study is the first explicit demonstration of terrestrial dead-reckoning, which provides a workable method of deriving the paths of animals on a step-by-step scale. The wider implications of this method for the understanding of animal movement ecology are discussed.