The identification of the domestic waste collection system associated with the least operative musculoskeletal disorders using human resource absence data

With increasing pressures around public sector costs, UK Local Authorities (LAs) and waste collection companies, are under pressure to reduce absence rates due to ill health. The identification of the ‘safest’ method of waste collection in the UK has been largely unresolved with many different types of waste and recycling receptacles used and deemed acceptable. The purpose of the study was to investigate the relationships between domestic waste collection methods and absence due to Musculoskeletal Disorders (MSDs) through the comparison of absence rates for different activity. Studies based upon ergonomic theory had suggested the use of wheeled bins is better than the use of boxes, but this has not been tested empirically. Absence data was obtained from 15 LAs who allocated a more detailed activity role to their records, allowing for activity absence rates to be calculated. The outputs were collated and analysed using SPSS to identify statistically significant relationships between types of waste collection services. The results confirm that wheeled bins are associated with less proxy measures of MSD than boxes, baskets and sacks with even lower absence rates associated with 1100 litre capacity bins, when handled by two workers. Findings also indicates that there is a level where MSD absence interventions are unlikely to be sustainable. In conclusion these findings should help LAs better understand some critical factors regarding waste collection strategies and MSD absence and inform HSE enforcement strategies. Employers should interrogate their own ill health data and seek to move to systems that create less MSDs

Chimpanzees do not take into account what others can hear in a competitive situation

Chimpanzees (Pan troglodytes) know what others can and cannot see in a competitive situation. Does this reflect a general understanding the perceptions of others? In a study by Hare et al. (2000) pairs of chimpanzees competed over two pieces of food. Subordinate individuals preferred to approach food that was behind a barrier that the dominant could not see, suggesting that chimpanzees can take the visual perspective of others. We extended this paradigm to the auditory modality to investigate whether chimpanzees are sensitive to whether a competitor can hear food rewards being hidden. Results suggested that the chimpanzees did not take what the competitor had heard into account, despite being able to locate the hiding place themselves by the noise

Towards optimal 1.5° and 2 °C emission pathways for individual countries: A Finland case study

© 2019 Nationally Determined Contributions (NDCs) submitted so far under the Paris Agreement are not in line with its long-term temperature goal. To bridge this gap, countries are required to provide regular updates and enhancements of their long-term targets and strategies, based on scientific assessments. The goal of this paper is to demonstrate a policy-support approach for evaluating NDCs and guiding enhanced ambition. The approach rests on deriving national targets in line with the Paris Agreement by downscaling regional results of Integrated Assessment Models (IAMs) to the country level. The method of downscaling relies on a reduced complexity IAM: SIAMESE (Simplified Integrated Assessment Model with Energy System Emulator). We apply the approach to an EU28 member state – Finland – with the aim of providing useful insights for policy makers to consider cost-effective mitigation options. Results over the historical period confirm that our approach is valid when national policies are similar to those across the larger IAM region, but must include country-specific circumstances. Strengths and limitations of the approach are discussed. We assess the remaining carbon budget and analyse the different implications of 2 °C and 1.5 °C global warming limits for the emissions pathway and energy mix in Finland over the 21st century

How Polarized Have We Become? A Multimodal Classification of Trump Followers and Clinton Followers

Polarization in American politics has been extensively documented and analyzed for decades, and the phenomenon became all the more apparent during the 2016 presidential election, where Trump and Clinton depicted two radically different pictures of America. Inspired by this gaping polarization and the extensive utilization of Twitter during the 2016 presidential campaign, in this paper we take the first step in measuring polarization in social media and we attempt to predict individuals' Twitter following behavior through analyzing ones' everyday tweets, profile images and posted pictures. As such, we treat polarization as a classification problem and study to what extent Trump followers and Clinton followers on Twitter can be distinguished, which in turn serves as a metric of polarization in general. We apply LSTM to processing tweet features and we extract visual features using the VGG neural network. Integrating these two sets of features boosts the overall performance. We are able to achieve an accuracy of 69%, suggesting that the high degree of polarization recorded in the literature has started to manifest itself in social media as well.Comment: 16 pages, SocInfo 2017, 9th International Conference on Social Informatic

Analytic calculation of radio emission from parametrized extensive air showers:A tool to extract shower parameters

The radio intensity and polarization footprint of a cosmic-ray induced extensive air shower is determined by the time-dependent structure of the current distribution residing in the plasma cloud at the shower front. In turn, the time dependence of the integrated charge-current distribution in the plasma cloud, the longitudinal shower structure, is determined by interesting physics which one would like to extract, such as the location and multiplicity of the primary cosmic-ray collision or the values of electric fields in the atmosphere during thunderstorms. To extract the structure of a shower from its footprint requires solving a complicated inverse problem. For this purposewe have developed a code that semianalytically calculates the radio footprint of an extensive air shower given an arbitrary longitudinal structure. This code can be used in an optimization procedure to extract the optimal longitudinal shower structure given a radio footprint. On the basis of air-shower universality we propose a simple parametrization of the structure of the plasma cloud. This parametrization is based on the results of Monte Carlo shower simulations. Deriving the parametrization also teaches which aspects of the plasma cloud are important for understanding the features seen in the radio-emission footprint. The calculated radio footprints are compared with microscopic CoREAS simulations

Meta-Tracker: Fast and Robust Online Adaptation for Visual Object Trackers

This paper improves state-of-the-art visual object trackers that use online adaptation. Our core contribution is an offline meta-learning-based method to adjust the initial deep networks used in online adaptation-based tracking. The meta learning is driven by the goal of deep networks that can quickly be adapted to robustly model a particular target in future frames. Ideally the resulting models focus on features that are useful for future frames, and avoid overfitting to background clutter, small parts of the target, or noise. By enforcing a small number of update iterations during meta-learning, the resulting networks train significantly faster. We demonstrate this approach on top of the high performance tracking approaches: tracking-by-detection based MDNet and the correlation based CREST. Experimental results on standard benchmarks, OTB2015 and VOT2016, show that our meta-learned versions of both trackers improve speed, accuracy, and robustness.Comment: Code: https://github.com/silverbottlep/meta_tracker

Airborne multiwavelength High Spectral Resolution Lidar (HSRL-2) observations during TCAP 2012 : Vertical profiles of optical and microphysical properties of a smoke/urban haze plume over the northeastern coast of the US

© Author(s) 2014. This work is distributed under the Creative Commons Attribution 3.0 License.We present measurements acquired by the world's first airborne 3 backscatter (β) + 2 extinction (α) High Spectral Resolution Lidar (HSRL-2). HSRL-2 measures particle backscatter coefficients at 355, 532, and 1064 nm, and particle extinction coefficients at 355 and 532 nm. The instrument has been developed by the NASA Langley Research Center. The instrument was operated during Phase 1 of the Department of Energy (DOE) Two-Column Aerosol Project (TCAP) in July 2012. We observed pollution outflow from the northeastern coast of the US out over the western Atlantic Ocean. Lidar ratios were 50-60 sr at 355 nm and 60-70 sr at 532 nm. Extinction-related Ångström exponents were on average 1.2-1.7, indicating comparably small particles. Our novel automated, unsupervised data inversion algorithm retrieved particle effective radii of approximately 0.2 μm, which is in agreement with the large Ångström exponents. We find good agreement with particle size parameters obtained from coincident in situ measurements carried out with the DOE Gulfstream-1 aircraft.Peer reviewedFinal Published versio

Ultra-Slow Discharges That Precede Lightning Initiation

We report on ultra-slowly propagating discharge events with speeds in the range 1-13 km/s, much lower than any known lightning process. The propagation speeds of these discharges are orders of magnitude slower than leader or streamer speeds, but faster than the ion drift speed. For one particular event, a lightning leader forms about 40 ms later within 50 m of the discharge, likely within the same high field region. A second slow event forms 9 ms prior to the initiation, and leads into the negative leader. Most slow events appear to not be directly involved with lightning initiation. This suggests that the classic streamer cascade model of initiation is not always a definitive process. In this work we describe these discharge events displaying unique behavior, their relation to common lightning discharges, and their implications for lightning initiation

Culture and PCR detection of Haemophilus influenzae and Haemophilus haemolyticus in Australian indigenous children with bronchiectasis

A PCR for protein D (hpd#3) was used to differentiate nontypeable Haemophilus influenzae (NTHI) from Haemophilus haemolyticus. While 90% of nasopharyngeal specimens and 100% of lower-airway specimens from 84 Indigenous Australian children with bronchiectasis had phenotypic NTHI isolates confirmed as H. influenzae, only 39% of oropharyngeal specimens with phenotypic NTHI had H. influenzae. The nasopharynx is therefore the preferred site for NTHI colonization studies, and NTHI is confirmed as an important lower-airway pathogen