(Table 1) Age markers and errors for the last 1215 ka in IODP Exp302

Despite its importance in the global climate system, age-calibrated marine geologic records reflecting the evolution of glacial cycles through the Pleistocene are largely absent from the central Arctic Ocean. This is especially true for sediments older than 200 ka. Three sites cored during the Integrated Ocean Drilling Program's Expedition 302, the Arctic Coring Expedition (ACEX), provide a 27 m continuous sedimentary section from the Lomonosov Ridge in the central Arctic Ocean. Two key biostratigraphic datums and constraints from the magnetic inclination data are used to anchor the chronology of these sediments back to the base of the Cobb Mountain subchron (1215 ka). Beyond 1215 ka, two best fitting geomagnetic models are used to investigate the nature of cyclostratigraphic change. Within this chronology we show that bulk and mineral magnetic properties of the sediments vary on predicted Milankovitch frequencies. These cyclic variations record ''glacial'' and ''interglacial'' modes of sediment deposition on the Lomonosov Ridge as evident in studies of ice-rafted debris and stable isotopic and faunal assemblages for the last two glacial cycles and were used to tune the age model. Potential errors, which largely arise from uncertainties in the nature of downhole paleomagnetic variability, and the choice of a tuning target are handled by defining an error envelope that is based on the best fitting cyclostratigraphic and geomagnetic solutions.

Investigating the Association Between Computer-Mediated Communication (CMC) and the Health of Canadian Young People: A Mixed Methods Study

Canadian young people are increasingly more connected through technological devices. This computer-mediated communication (CMC) can result in heightened connection and social support but can also lead to inadequate personal and physical connections. As technology evolves, its influence on health and well-being is important to investigate, especially among youth. This study aims to investigate the potential influences of computer-mediated communication (CMC) on the health of Canadian youth, using both quantitative and qualitative research approaches. This mixed-methods study utilized data from the 2013-2014 Health Behaviour in School-aged Children survey for Canada (n=30,117) and focus group data involving Ontario youth (7 groups involving 40 youth). In the quantitative component, a random-effects multilevel Poisson regression was employed to identify the effects of CMC on loneliness, stratified to explore interaction with family communication quality. A qualitative, inductive content analysis was applied to the focus group transcripts using a grounded theory inspired methodology. Through open line-by-line coding followed by axial coding, main categories and themes were identified. The quality of family communication modified the association between CMC use and loneliness. Among youth experiencing the highest quartile of family communication, daily use of verbal and social media CMC was significantly associated with reports of loneliness. The qualitative analysis revealed two overarching concepts that: (1) the health impacts of CMC are multidimensional and (2) there exists a duality of both positive and negative influences of CMC on health. Four themes were identified within this framework: (1) physical activity, (2) mental and emotional disturbance, (3) mindfulness, and (4) relationships. Overall, there is a high proportion of loneliness among Canadian youth, but this is not uniform for all. The associations between CMC and health are influenced by external and contextual factors, including family communication quality. Further, the technologically rich world in which young people live has a diverse impact on their health. For youth, their relationships with others and the context of CMC use shape overall influences on their health.

Strontium isotopes and sedimentology of a marine Triassic succession (upper Ladinian) of the westernmost Tethys, Spain

Chemical Stratigraphy, or the study of the variation of chemical elements within sedimentary sequences, has gradually become an experienced tool in the research and correlation of global geologic events. In this paper 87Sr/ 86Sr ratios of the Triassic marine carbonates (Muschelkalk facies) of southeast Iberian Ranges, Iberian Peninsula, are presented and the representative Sr-isotopic curve constructed for the upper Ladinian interval. The studied stratigraphic succession is 102 meters thick, continuous, and well preserved. Previous paleontological data from macro and micro, ammonites, bivalves, foraminifera, conodonts and palynological assemblages, suggest a Fassanian-Longobardian age (Late Ladinian). Although diagenetic minerals are present in small amounts, the elemental data content of bulk carbonate samples, especially Sr contents, show a major variation that probably reflects palaeoenvironmental changes. The 87Sr/86Sr ratios curve shows a rise from 0.707649 near the base of the section to 0.707741 and then declines rapidly to 0.707624, with a final values rise up to 0.70787 in the upper part. The data up to meter 80 in the studied succession is broadly concurrent with 87Sr/86Sr ratios of sequences of similar age and complements these data. Moreover, the sequence stratigraphic framework and its key surfaces, which are difficult to be recognised just based in the facies analysis, are characterised by combining variations of the Ca, Mg, Mn, Sr and CaCO3 contents

Benefits and resource implications of family meetings for hospitalized palliative care patients: research protocol.

BACKGROUND:
Palliative care focuses on supporting patients diagnosed with advanced, incurable disease; it is 'family centered', with the patient and their family (the unit of care) being core to all its endeavours. However, approximately 30-50% of carers experience psychological distress which is typically under recognised and consequently not addressed. Family meetings (FM) are recommended as a means whereby health professionals, together with family carers and patients discuss psychosocial issues and plan care; however there is minimal empirical research to determine the net effect of these meetings and the resources required to implement them systematically. The aims of this study were to evaluate: (1) if family carers of hospitalised patients with advanced disease (referred to a specialist palliative care in-patient setting or palliative care consultancy service) who receive a FM report significantly lower psychological distress (primary outcome), fewer unmet needs, increased quality of life and feel more prepared for the caregiving role; (2) if patients who receive the FM experience appropriate quality of end-of-life care, as demonstrated by fewer hospital admissions, fewer emergency department presentations, fewer intensive care unit hours, less chemotherapy treatment (in last 30 days of life), and higher likelihood of death in the place of their choice and access to supportive care services; (3) the optimal time point to deliver FM and; (4) to determine the cost-benefit and resource implications of implementing FM meetings into routine practice.
METHODS:
Cluster type trial design with two way randomization for aims 1-3 and health economic modeling and qualitative interviews with health for professionals for aim 4.
DISCUSSION:
The research will determine whether FMs have positive practical and psychological impacts on the family, impacts on health service usage, and financial benefits to the health care sector. This study will also provide clear guidance on appropriate timing in the disease/care trajectory to provide a family meeting.

Inverse Association Between Gluteofemoral Obesity and Risk of Barrett's Esophagus in a Pooled Analysis

BACKGROUND & AIMS: Gluteofemoral obesity (determined by measurement of subcutaneous fat in hip and thigh regions) could reduce risks of cardiovascular and diabetic disorders associated with abdominal obesity. We evaluated whether gluteofemoral obesity also reduces risk of Barrett's esophagus (BE), a premalignant lesion associated with abdominal obesity.

METHODS: We collected data from non-Hispanic white participants in 8 studies in the Barrett's and Esophageal Adenocarcinoma Consortium. We compared measures of hip circumference (as a proxy for gluteofemoral obesity) from cases of BE (n=1559) separately with 2 control groups: 2557 population-based controls and 2064 individuals with gastroesophageal reflux disease (GERD controls). Study-specific odds ratios (OR) and 95% confidence intervals (95% CI) were estimated using individual participant data and multivariable logistic regression and combined using random effects meta-analysis.

RESULTS: We found an inverse relationship between hip circumference and BE (OR per 5 cm increase, 0.88; 95% CI, 0.81-0.96), compared with population-based controls in a multivariable model that included waist circumference. This association was not observed in models that did not include waist circumference. Similar results were observed in analyses stratified by frequency of GERD symptoms. The inverse association with hip circumference was only statistically significant among men (vs population-based controls: OR, 0.85; 95% CI, 0.76-0.96 for men; OR, 0.93; 95% CI, 0.74-1.16 for women). For men, within each category of waist circumference, a larger hip circumference was associated with decreased risk of BE. Increasing waist circumference was associated with increased risk of BE in the mutually adjusted population-based and GERD control models.

CONCLUSIONS: Although abdominal obesity is associated with increased risk of BE, there is an inverse association between gluteofemoral obesity and BE, particularly among men.

Coupling short-term (B2G model) and long-term (g-function) models for ground source heat exchanger simulation in TRNSYS. Application in a real installation

Ground-source heat pump (GSHP) systems represent one of the most promising techniques for heating and cooling in buildings. These systems use the ground as a heat source/sink, allowing a better efficiency thanks to the low variations of the ground temperature along the seasons. The ground-source heat exchanger (GSHE) then becomes a key component for optimizing the overall performance of the system. Moreover, the short-term response related to the dynamic behaviour of the GSHE is a crucial aspect, especially from a regulation criteria perspective in on/off controlled GSHP systems. In this context, a novel numerical GSHE model has been developed at the Instituto de Ingeniería Energética, Universitat Politècnica de València. Based on the decoupling of the short-term and the long-term response of the GSHE, the novel model allows the use of faster and more precise models on both sides. In particular, the short-term model considered is the B2G model, developed and validated in previous research works conducted at the Instituto de Ingeniería Energética. For the long-term, the g-function model was selected, since it is a previously validated and widely used model, and presents some interesting features that are useful for its combination with the B2G model. The aim of the present paper is to describe the procedure of combining these two models in order to obtain a unique complete GSHE model for both short- and long-term simulation. The resulting model is then validated against experimental data from a real GSHP installation.

Digital collaborations and entrepreneurship – the role of shareconomy and crowdsourcing in the era of smart city

The thesis begins with the classical cooperation and transfers it to the digital world. This work gives a detailed overview of the young fields of research smart city, shareconomy and crowdsourcing and links these fields with entrepreneurship. The core research aim is the finding of connections between the research fields smart city, shareconomy and crowdsourcing and entrepreneurial activities and the specific fields of application, success factors and conditions for entrepreneurs. The thesis consists of seven peer-reviewed publications. Based on primary and secondary data, the existence of entrepreneurial opportunities in the fields of smart city, shareconomy and crowdsourcing could be confirmed. The first part (publications 1-3) of the thesis are literature reviews to secure the fundamental base for further research. This part consists of newly created definitions and an extreme sharpening of the research fields for the near future. In the second part of the thesis (publications 4-7), empirical field work (in-depth interviews with entrepreneurs) and quantitative analyses (fuzzy set/qualitative comparative analysis and binary logistic regression analysis) contribute to the field of research with additional new insights. Summarizing, the insights are multi-layered: theoretical (e.g. new definitions, sharpening of the research field), methodical (e.g. first time application of the fuzzy set/qualitative comparative analysis in the field of crowdfunding) and qualitative (first time application of in-depth interviews with entrepreneurs in the fields of smart city and shareconomy). The global research question could be answered: the link between entrepreneurship and smart city, shareconomy and crowdfunding could be confirmed, concrete fields of application could be identified and further developments could be touched upon. This work strongly contributes to the young fields of research through much-needed basic work, new qualitative approaches, innovative methods and new insights and offers opportunities for discussion, criticism and support for further research.

Socioeconomic Status and Health Behavior in Nepal

Thesis (Master's)--University of Washington, 2016-07

Exact Solution of Bayes and Minimax Change-Detection Problems

The challenge of detecting a change in the distribution of data is a sequential decision problem that is relevant to many engineering solutions, including quality control and machine and process monitoring. This dissertation develops techniques for exact solution of change-detection problems with discrete time and discrete observations. Change-detection problems are classified as Bayes or minimax based on the availability of information on the change-time distribution. A Bayes optimal solution uses prior information about the distribution of the change time to minimize the expected cost, whereas a minimax optimal solution minimizes the cost under the worst-case change-time distribution. Both types of problems are addressed. The most important result of the dissertation is the development of a polynomial-time algorithm for the solution of important classes of Markov Bayes change-detection problems. Existing techniques for epsilon-exact solution of partially observable Markov decision processes have complexity exponential in the number of observation symbols. A new algorithm, called constellation induction, exploits the concavity and Lipschitz continuity of the value function, and has complexity polynomial in the number of observation symbols. It is shown that change-detection problems with a geometric change-time distribution and identically- and independently-distributed observations before and after the change are solvable in polynomial time. Also, change-detection problems on hidden Markov models with a fixed number of recurrent states are solvable in polynomial time. A detailed implementation and analysis of the constellation-induction algorithm are provided. Exact solution methods are also established for several types of minimax change-detection problems. Finite-horizon problems with arbitrary observation distributions are modeled as extensive-form games and solved using linear programs. Infinite-horizon problems with linear penalty for detection delay and identically- and independently-distributed observations can be solved in polynomial time via epsilon-optimal parameterization of a cumulative-sum procedure. Finally, the properties of policies for change-detection problems are described and analyzed. Simple classes of formal languages are shown to be sufficient for epsilon-exact solution of change-detection problems, and methods for finding minimally sized policy representations are described.

A rewarding experience? Exploring how crowdfunding is affecting music industry business models.

This paper provides an exploratory study of how rewards-based crowdfunding affects business model development for music industry artists, labels and live sector companies. The empirical methodology incorporated a qualitative, semi-structured, three-stage interview design with fifty seven senior executives from industry crowdfunding platforms and three stakeholder groups. The results and analysis cover new research ground and provide conceptual models to develop theoretical foundations for further research in this field. The findings indicate that the financial model benefits of crowdfunding for independent artists are dependent on fan base demographic variables relating to age group and genre due to sustained apprehension from younger audiences. Furthermore, major labels are now considering a more user-centric financial model as an innovation strategy, and the impact of crowdfunding on their marketing model may already be initiating its development in terms of creativity, strength and artist relations.

Spectral Frame Analysis and Learning through Graph Structure

This dissertation investigates the connection between spectral analysis and frame theory. When considering the spectral properties of a frame, we present a few novel results relating to the spectral decomposition. We first show that scalable frames have the property that the inner product of the scaling coefficients and the eigenvectors must equal the inverse eigenvalues. From this, we prove a similar result when an approximate scaling is obtained. We then focus on the optimization problems inherent to the scalable frames by first showing that there is an equivalence between scaling a frame and optimization problems with a non-restrictive objective function. Various objective functions are considered, and an analysis of the solution type is presented. For linear objectives, we can encourage sparse scalings, and with barrier objective functions, we force dense solutions. We further consider frames in high dimensions, and derive various solution techniques. From here, we restrict ourselves to various frame classes, to add more specificity to the results. Using frames generated from distributions allows for the placement of probabilistic bounds on scalability. For discrete distributions (Bernoulli and Rademacher), we bound the probability of encountering an ONB, and for continuous symmetric distributions (Uniform and Gaussian), we show that symmetry is retained in the transformed domain. We also prove several hyperplane-separation results. With the theory developed, we discuss graph applications of the scalability framework. We make a connection with graph conditioning, and show the in-feasibility of the problem in the general case. After a modification, we show that any complete graph can be conditioned. We then present a modification of standard PCA (robust PCA) developed by Cand\`es, and give some background into Electron Energy-Loss Spectroscopy (EELS). We design a novel scheme for the processing of EELS through robust PCA and least-squares regression, and test this scheme on biological samples. Finally, we take the idea of robust PCA and apply the technique of kernel PCA to perform robust manifold learning. We derive the problem and present an algorithm for its solution. There is also discussion of the differences with RPCA that make theoretical guarantees difficult.

Análisis de la percepción de seguridad en puentes peatonales: una aproximación mediante modelación híbrida

Este artículo de investigación científica y tecnológica estudia la percepción de seguridad en el uso de puentes peatonales, empleando un enfoque sustentado en dos campos principales: el microeconómico y el psicológico. El trabajo hace la estimación simultánea de un modelo híbrido de elección y variables latentes con datos de una encuesta de preferencias declaradas, encontrando mejor ajuste que un modelo mixto de referencia, lo que indica que la percepción de seguridad determina el comportamiento de los peatones cuando se enfrentan a la decisión de usar o no un puente peatonal. Se encontró que el sexo, la edad y el nivel de estudios son atributos que inciden en la percepción de seguridad. El modelo calibrado sugiere varias estrategias para aumentar el uso de puentes peatonales que son discutidas, encontrando que el uso de barreras ocasiona una pérdida de utilidad, en los peatones, que debería ser estudiada como extensión del presente trabajo.

Examining the growth and evolution of magnetic fields in clusters of galaxies: a numerical perspective

Magnetic fields are ubiquitous in galaxy cluster atmospheres and have a variety of astrophysical and cosmological consequences. Magnetic fields can contribute to the pressure support of clusters, affect thermal conduction, and modify the evolution of bubbles driven by active galactic nuclei. However, we currently do not fully understand the origin and evolution of these fields throughout cosmic time. Furthermore, we do not have a general understanding of the relationship between magnetic field strength and topology and other cluster properties, such as mass and X-ray luminosity. We can now begin to answer some of these questions using large-scale cosmological magnetohydrodynamic (MHD) simulations of the formation of galaxy clusters including the seeding and growth of magnetic fields. Using large-scale cosmological simulations with the FLASH code combined with a simplified model of the acceleration of cosmic rays responsible for the generation of radio halos, we find that the galaxy cluster frequency distribution and expected number counts of radio halos from upcoming low-frequency sur- veys are strongly dependent on the strength of magnetic fields. Thus, a more complete understanding of the origin and evolution of magnetic fields is necessary to understand and constrain models of diffuse synchrotron emission from clusters. One favored model for generating magnetic fields is through the amplification of weak seed fields in active galactic nuclei (AGN) accretion disks and their subsequent injection into cluster atmospheres via AGN-driven jets and bubbles. However, current large-scale cosmological simulations cannot directly include the physical processes associated with the accretion and feedback processes of AGN or the seeding and merging of the associated SMBHs. Thus, we must include these effects as subgrid models. In order to carefully study the growth of magnetic fields in clusters via AGN-driven outflows, we present a systematic study of SMBH and AGN subgrid models. Using dark-matter only cosmological simulations, we find that many important quantities, such as the relationship between SMBH mass and galactic bulge velocity dispersion and the merger rate of black holes, are highly sensitive to the subgrid model assumptions of SMBHs. In addition, using MHD calculations of an isolated cluster, we find that magnetic field strengths, extent, topology, and relationship to other gas quantities such as temperature and density are also highly dependent on the chosen model of accretion and feedback. We use these systematic studies of SMBHs and AGN inform and constrain our choice of subgrid models, and we use those results to outline a fully cosmological MHD simulation to study the injection and growth of magnetic fields in clusters of galaxies. This simulation will be the first to study the birth and evolution of magnetic fields using a fully closed accretion-feedback cycle, with as few assumptions as possible and a clearer understanding of the effects of the various parameter choices.

Explaining dinophysis cf. acuminata abundance in Antifer (Normandy, France) using dynamic linear regression

Classical regression analysis can be used to model time series. However, the assumption that model parameters are constant over time is not necessarily adapted to the data. In phytoplankton ecology, the relevance of time-varying parameter values has been shown using a dynamic linear regression model (DLRM). DLRMs, belonging to the class of Bayesian dynamic models, assume the existence of a non-observable time series of model parameters, which are estimated on-line, i.e. after each observation. The aim of this paper was to show how DLRM results could be used to explain variation of a time series of phytoplankton abundance. We applied DLRM to daily concentrations of Dinophysis cf. acuminata, determined in Antifer harbour (French coast of the English Channel), along with physical and chemical covariates (e.g. wind velocity, nutrient concentrations). A single model was built using 1989 and 1990 data, and then applied separately to each year. Equivalent static regression models were investigated for the purpose of comparison. Results showed that most of the Dinophysis cf. acuminata concentration variability was explained by the configuration of the sampling site, the wind regime and tide residual flow. Moreover, the relationships of these factors with the concentration of the microalga varied with time, a fact that could not be detected with static regression. Application of dynamic models to phytoplankton time series, especially in a monitoring context, is discussed.

Porosity imaged by a vector projection algorithm correlates with fractal dimension measured on 3D models obtained by microCT

International audience