Electron Transport through Disordered Domain Walls: Coherent and Incoherent Regimes

We study electron transport through a domain wall in a ferromagnetic nanowire subject to spin-dependent scattering. A scattering matrix formalism is developed to address both coherent and incoherent transport properties. The coherent case corresponds to elastic scattering by static defects, which is dominant at low temperatures, while the incoherent case provides a phenomenological description of the inelastic scattering present in real physical systems at room temperature. It is found that disorder scattering increases the amount of spin-mixing of transmitted electrons, reducing the adiabaticity. This leads, in the incoherent case, to a reduction of conductance through the domain wall as compared to a uniformly magnetized region which is similar to the giant magnetoresistance effect. In the coherent case, a reduction of weak localization, together with a suppression of spin-reversing scattering amplitudes, leads to an enhancement of conductance due to the domain wall in the regime of strong disorder. The total effect of a domain wall on the conductance of a nanowire is studied by incorporating the disordered regions on either side of the wall. It is found that spin-dependent scattering in these regions increases the domain wall magnetoconductance as compared to the effect found by considering only the scattering inside the wall. This increase is most dramatic in the narrow wall limit, but remains significant for wide walls.Comment: 23 pages, 12 figure

The pros and cons of getting engaged in an online social community embedded within digital cognitive behavioral therapy for insomnia: survey among users

Background: Sleepio is a proven digital sleep improvement programme based on cognitive behavioural therapy (CBT) techniques. Users have the option to join an online community that includes weekly expert discussions, peer-to-peer discussion forums and personal message walls. Objective: The aims of this study were to (1) explore the reasons for deciding to engage with the Sleepio online community, (2) explore the potential benefits arising from engagement with the online community, (3) identify and describe any problematic issues related to use of the online community. Methods: In total, 100 respondents (70% female; mean age 51, range 26-82 years) completed the online survey. Most respondents had started Sleepio with chronic sleep problems (59% to to 10 years, 35% >10years), and had actively engaged with the online community (85% had made a discussion or wall post). At the time of the survey, respondents had used Sleepio for a median of 12 weeks (range from 3 weeks to 2 years). Results: Responses to the open-ended questions were analysed using thematic analysis. This analysis revealed five initial drivers for engagement including: 1) the desire to connect with people facing similar issues; 2) seeking personalised advice; 3) curiosity; 4) being invited by other members; and 5) wanting to use all available sleep improvement tools. Advantages of engagement included: access to continuous support, reduced sense of isolation, being part of a non-judgmental community, personalised advice, positive comparisons with others, encouragement to keep going, and altruism. Five potential disadvantages were: design and navigation issues, uncertain quality of user-generated content, negative comparisons with others, excessive time commitments, and data privacy concerns. Participants related their community experiences to engagement with the Sleepio programme with the many stating it had supported their efforts to achieve sleep improvement, as well as helping with adherence and commitment to the programme. Conclusions: Despite some concerns, members regarded the Sleepio community as a valuable resource. Online communities may be a useful means through which to support long-term engagement with online therapy for insomnia

What have we learnt from EUPORIAS climate service prototypes?

The international effort toward climate services, epitomised by the development of the Global Framework for Climate Services and, more recently the launch of Copernicus Climate Change Service has renewed interest in the users and the role they can play in shaping the services they will eventually use. Here we critically analyse the results of the five climate service prototypes that were developed as part of the EU funded project EUPORIAS. Starting from the experience acquired in each of the projects we attempt to distil a few key lessons which, we believe, will be relevant to the wider community of climate service developers

Theory and Computation of the Spheroidal Wave Functions

In this paper we report on a package, written in the Mathematica computer algebra system, which has been developed to compute the spheroidal wave functions of Meixner [J. Meixner and R.W. Schaefke, Mathieusche Funktionen und Sphaeroidfunktionen, 1954] and is available online (www.physics.uwa.edu.au/~falloon/spheroidal/spheroidal.html). This package represents a substantial contribution to the existing software, since it computes the spheroidal wave functions to arbitrary precision for general complex parameters mu, nu, gamma and argument z; existing software can only handle integer mu, nu and does not give arbitrary precision. The package also incorporates various special cases and computes analytic power series and asymptotic expansions in the parameter gamma. The spheroidal wave functions of Flammer [C. Flammer, Spheroidal Wave Functions, 1957] are included as a special case of Meixner's more general functions. This paper presents a concise review of the general theory of spheroidal wave functions and a description of the formulas and algorithms used in their computation, and gives high-precision numerical examples.Comment: 26 pages, 4 Appendices, 5 Table

The Views of Mental Health Manager Towards the Use of a Family Work Model for Psychosis in Guangzhou, China

Family Interventions in Psychosis (FIP) have been promoted internationally but have been criticised for being based on western cultural models. This paper reports on a focus group study with 10 Integrated Mental Health Service Managers in Guangzhou, China using thematic analysis. Managers believed FIP might benefit families but identified potential difficulties due to (a) families avoiding services due to the ‘shame’ of mental illness (b) unrealistic expectations of services amongst families (c) deferral to ‘key decision-makers’ within families when discussing family issues with workers. The findings indicate that FIP work should focus on interaction between carers in the first instance with service users being introduced into sessions at a later date and that more attention needs to be given by the research community to how FIP may be adapted to cultural norms within China

A framework for the cross-sectoral integration of multi-model impact projections: land use decisions under climate impacts uncertainties

Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impactmodel setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making

Subjective response to antipsychotic treatment and compliance in schizophrenia. A naturalistic study comparing olanzapine, risperidone and haloperidol (EFESO Study)

BACKGROUND: In order to compare the effectiveness of different antipsychotic drugs in the treatment of schizophrenia it is very important to evaluate subjective response and compliance in patient cohorts treated according to routine clinical practice. METHOD: Outpatients with schizophrenia entered this prospective, naturalistic study when they received a new prescription for an antipsychotic drug. Treatment assignment was based on purely clinical criteria, as the study did not include any experimental intervention. Patients treated with olanzapine, risperidone or haloperidol were included in the analysis. Subjective response was measured using the 10-item version of the Drug Attitude Inventory (DAI-10), and treatment compliance was measured using a physician-rated 4 point categorical scale. RESULTS: A total of 2128 patients initiated treatment (as monotherapy) with olanzapine, 417 with risperidone, and 112 with haloperidol. Olanzapine-treated patients had significantly higher DAI-10 scores and significantly better treatment compliance compared to both risperidone- and haloperidol-treated patients. Risperidone-treated patients had a significantly higher DAI-10 score compared to haloperidol-treated patients. CONCLUSION: Subjective response and compliance were superior in olanzapine-treated patients, compared to patients treated with risperidone and haloperidol, in routine clinical practice. Differences in subjective response were explained largely, but not completely, by differences in incidence of EPS

Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios

Concerns over climate change are motivated in large part because of their impact on human society. Assessing the effect of that uncertainty on specific potential impacts is demanding, since it requires a systematic survey over both climate and impacts models. We provide a comprehensive evaluation of uncertainty in projected crop yields for maize, spring and winter wheat, rice, and soybean, using a suite of nine crop models and up to 45 CMIP5 and 34 CMIP6 climate projections for three different forcing scenarios. To make this task computationally tractable, we use a new set of statistical crop model emulators. We find that climate and crop models contribute about equally to overall uncertainty. While the ranges of yield uncertainties under CMIP5 and CMIP6 projections are similar, median impact in aggregate total caloric production is typically more negative for the CMIP6 projections (+1% to −19%) than for CMIP5 (+5% to −13%). In the first half of the 21st century and for individual crops is the spread across crop models typically wider than that across climate models, but we find distinct differences between crops: globally, wheat and maize uncertainties are dominated by the crop models, but soybean and rice are more sensitive to the climate projections. Climate models with very similar global mean warming can lead to very different aggregate impacts so that climate model uncertainties remain a significant contributor to agricultural impacts uncertainty. These results show the utility of large-ensemble methods that allow comprehensively evaluating factors affecting crop yields or other impacts under climate change. The crop model ensemble used here is unbalanced and pulls the assumption that all projections are equally plausible into question. Better methods for consistent model testing, also at the level of individual processes, will have to be developed and applied by the crop modeling community

Multi-objective calibration of RothC using measured carbon stocks and auxiliary data of a long-term experiment in Switzerland

Interactions between model parameters and low spatiotemporal resolution of available data mean that conventional soil organic carbon (SOC) models are often affected by equifinality, with consequent uncertainty in SOC forecasts. Estimation of belowground C inputs is another major source of uncertainty in SOC modelling. Models are usually calibrated on SOC stocks and fluxes from long‐term experiments (LTEs), whereas other point data are not used for constraining the model parameters. We used data from an agricultural long‐term (> 65 years) fertilization experiment to test a multi‐objective parameter estimation approach on the RothC model, combining SOC data from different fertilization treatments with microbial biomass, basal respiration and Zimmermann’s fractions data. We also compared two methods to estimate the belowground C inputs: a conventional scaling of belowground biomass from crop harvest yield and an alternative approach based on constant belowground C for cereals measured experimentally in the field. The resulting posterior parameter distributions still suffered from some equifinality; the most stable C pool kinetic constants and composition of exogenous organic matter were the most sensitive parameters. The use of fixed belowground C inputs for cereals improved the model performance, reducing the importance of treatment‐specific parameters and processes. The introduction of microbial biomass and basal respiration data was effective for increasing determination of the calibration, but also suggested a change in the model structure: the microbial biomass pool, which is proportional to the C inputs in the traditional models, could be represented by different microbial physiology functions