Matrilines in Neolithic cattle from Orkney, Scotland reveals complex husbandry patterns of ancestry

mtDNA, isotopic and archaeozoological analyses of cattle teeth and bones from the Late Neolithic site of Links of Noltland, Orkney, Scotland revealed these animals followed similar grazing regimes but displayed diverse genetic origins and included one cattle skull that carried an aurochs (wild cattle) genetic haplotype. Morphometric analyses indicate the presence of some cattle larger than published dimensions of Neolithic domestic cattle. Several explanations for these finding are possible but may be the evidence of a complex pattern of domestic cattle introductions into Neolithic Orkney and interbreeding between domestic and wild cattle

Community experiences of organised crime in Scotland

The research explored community experiences of serious organised crime in Scotland (SOC). The report provides information on the nature and extent of the impact of SOC on everyday life in the community, as well as offering suggestions for policy development. The study sought to answer the following questions: 1)What are the relationships that exist between SOC and communities in Scotland? 2)What are the experiences and perceptions of residents, stakeholders and organisations of the scope and nature of SOC within their local area? and 3)How does SOC impact on community wellbeing, and to what extent can the harms associated with SOC be mitigated

Nonlinear Harmonic Distortion of Complementary Golay Codes

Recent advances in electronics miniaturization have led to the development of low-power, low-cost, point-of-care ultrasound scanners. Low-cost systems employing simple bi-level pulse generation devices need only utilize binary phase modulated coded excitations to significantly improve sensitivity; however the performance of complementary codes in the presence of nonlinear harmonic distortion has not been thoroughly investigated. Through simulation, it was found that nonlinear propagation media with little attenuative properties can significantly deteriorate the Peak Sidelobe Level (PSL) performance of complementary Golay coded pulse compression, resulting in PSL levels of -62 dB using nonlinear acoustics theory contrasted with -198 dB in the linear case. Simulations of 96 complementary pairs revealed that some pairs are more robust to sidelobe degradation from nonlinear harmonic distortion than others, up to a maximum PSL difference of 17 dB between the best and worst performing codes. It is recommended that users consider the effects of nonlinear harmonic distortion when implementing binary phase modulated complementary Golay coded excitations.</p

Representing temporal dependencies in human activity recognition.

Smart Homes offer the opportunity to perform continuous, long-term behavioural and vitals monitoring of residents, which may be employed to aid diagnosis and management of chronic conditions without placing additional strain on health services. A profile of the resident’s behaviour can be produced from sensor data, and then compared over time. Activity Recognition is a primary challenge for profile generation, however many of the approaches adopted fail to take full advantage of the inherent temporal dependencies that exist in the activities taking place. Long Short Term Memory (LSTM) is a form of recurrent neural network that uses previously learned examples to inform classification decisions. In this paper we present a variety of approaches to human activity recognition using LSTMs and consider the temporal dependencies that exist in binary ambient sensor data in order to produce case-based representations. These LSTM approaches are compared to the performance of a selection of baseline classification algorithms on several real world datasets. In general, it was found that accuracy in LSTMs improved as additional temporal information was presented to the classifier

Representing temporal dependencies in smart home activity recognition for health monitoring.

Long term health conditions, such as fall risk, are traditionally diagnosed through testing performed in hospital environments. Smart Homes offer the opportunity to perform continuous, long-term behavioural and vitals monitoring of residents, which may be employed to aid diagnosis and management of chronic conditions without placing additional strain on health services. A profile of the resident’s behaviour can be produced from sensor data, and then compared overtime. Activity Recognition is a primary challenge for profile generation, however many of the approaches adopted fail to take full advantage of the inherent temporal dependencies that exist in the activities taking place. Long Short Term Memory (LSTM) is a form of recurrent neural network that uses previously learned examples to inform classification decisions. In this paper we present a variety of approaches to human activity recognition using LSTMs which consider the temporal dependencies present in the sensor data in order to produce richer representations and improved classification accuracy. The LSTM approaches are compared to the performance of a selection of base line classification algorithms on several real world datasets. In general, it was found that accuracy in LSTMs improved as additional temporal information was presented to the classifier

Monitoring health in smart homes using simple sensors.

We consider use of an ambient sensor network, installed in Smart Homes, to identify low level events taking place which can then be analysed to generate a resident's profile of activities of daily living (ADLs). These ADL profiles are compared to both the resident's typical profile and to known 'risky' profiles to support evidence-based interventions. Human activity recognition to identify ADLs from sensor data is a key challenge, a windowbased representation is compared on four existing datasets. We find that windowing works well, giving consistent performance. We also introduce FITsense, which is building a Smart Home environment to specifically identify increased risk of falls to allow interventions before falls occurs

“How people read and write and they don't even notice”: everyday lives and literacies on a Midlands council estate

This article presents data from a British Academy-funded study of the everyday literacy practices of three families living on a predominantly white working-class council housing estate on the edge of a Midlands city. The study explored, as one participant succinctly put it, “how people read and write and they don't even notice”. This alludes to the ways in which everyday practices may not be recognised as part of a dominant model of literacy. The study considered too the ways in which these literacy practices are part of a wider policy context that also fails to notice the impact of austerity politics on everyday lives. An emphasis on quantitative measures of disadvantage and public discourse which vilifies those facing economic challenge can overshadow the resilience and resourcefulness of individuals and families in making meaning from their experiences. Drawing together consideration of everyday lives and the everyday literacies which are part of them, this article explores the impact of the current policy context on access to both economic and cultural resources, showing how literacy, as part of this context, should be recognised as a powerful means not only of constricting lives but also of constructing them

Networked territorialism: the routes and roots of organised crime

In the digital age, space has become increasingly structured by the circuitry of global capital, communications and commodities. This ‘network society’ splinters and fragments territorial space according to the hidden logic of networked global capital; with successful criminal entrepreneurs connecting bases in low-risk, controllable territories with high-profit markets. Drawing on a recent, large-scale study of organised crime in Scotland, in this paper we elaborate the relationship between place, territory and criminal markets in two contrasting communities. The first is an urban neighbourhood with a longstanding organised crime footprint, where recognised local criminal groups have established deep roots. The second is a rural community with a negligible organised crime footprint, where the drug economy is serviced by a mobile criminal network based in England. Through comparison of the historical roots and contemporary routes of these criminal markets, we note both similarity and difference. While both communities demonstrated evidence of ‘networked territorialism’, key differences related to historical and social antecedents, in particular the impact of deindustrialisation

Applying the integrated trans-contextual model to mathematics activities in the classroom and homework behavior and attainment

The aim of the present study was to test hypotheses of the trans-contextual model. We predicted relations between perceived autonomy support, autonomous motivation toward mathematics learning activities in an educational context, autonomous motivation toward mathematics homework in an out-of-school context, social-cognitive variables and intentions for future engagement in mathematics homework, and mathematics homework outcomes. Secondary school students completed measures of perceived autonomy support from teachers and autonomous motivation for in-class mathematics activities; measures of autonomous motivation, social-cognitive variables, and intentions for out-of-school mathematics homework; and follow-up measures of students' mathematics homework outcomes: self-reported homework engagement and actual homework grades. Perceived autonomy support was related to autonomous motivation toward in-class mathematics activities. There were trans-contextual effects of autonomous motivation across educational and out-of-school contexts, and relations between out-of-school autonomous motivation, intentions, and mathematics homework outcomes. Findings support trans-contextual effects of autonomous motivation toward mathematics activities across educational and out-of-school contexts and homework outcomes

Attributable costs of surgical site infection and endometritis after low transverse cesarean delivery

BACKGROUND: Accurate data on costs attributable to hospital-acquired infections are needed in order to determine their economic impact and the cost-benefit of potential preventive strategies. OBJECTIVE: Determine the attributable costs of surgical site infection (SSI) and endometritis (EMM) after cesarean section using two different methods. DESIGN: Retrospective cohort. SETTING: Barnes-Jewish Hospital, a 1250-bed academic tertiary care hospital. PATIENTS: 1,605 women who underwent low transverse cesarean section from 7/1999 – 6/2001. METHODS: Attributable costs of SSI and EMM were determined by generalized least squares (GLS) and propensity score matched-pairs using administrative claims data to define underlying comorbidities and procedures. For the matched-pairs analyses, uninfected control patients were matched to patients with SSI or with EMM based on their propensity to develop infection, and the median difference in costs calculated. RESULTS: The attributable total hospital cost of SSI calculated by GLS was $3,529 and by propensity score matched-pairs was$2,852. The attributable total hospital cost of EMM calculated by GLS was $3,956 and by propensity score matched-pairs was$3,842. The majority of excess costs were associated with room and board and pharmacy costs. CONCLUSIONS: The costs of SSI and EMM were lower than SSI costs reported after more extensive operations. The attributable costs of EMM calculated using the two methods were very similar, while the costs of SSI calculated using propensity score matched-pairs were lower than the costs calculated by GLS. The difference in costs determined by the two methods needs to be considered by investigators performing cost analyses of hospital-acquired infections