Sediment concentration prediction and statistical evaluation for annual load estimation

We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.

Statistical power calculation and sample size determination for environmental studies with data below detection limits

Power calculation and sample size determination are critical in designing environmental monitoring programs. The traditional approach based on comparing the mean values may become statistically inappropriate and even invalid when substantial proportions of the response values are below the detection limits or censored because strong distributional assumptions have to be made on the censored observations when implementing the traditional procedures. In this paper, we propose a quantile methodology that is robust to outliers and can also handle data with a substantial proportion of below-detection-limit observations without the need of imputing the censored values. As a demonstration, we applied the methods to a nutrient monitoring project, which is a part of the Perth Long-Term Ocean Outlet Monitoring Program. In this example, the sample size required by our quantile methodology is, in fact, smaller than that by the traditional t-test, illustrating the merit of our method.

Medicines information sources and services for consumers : A special focus on the Internet and people with depression

The range of consumer health and medicines information sources has diversified along with the increased use of the Internet. This has led to a drive to develop medicines information services and to better incorporate the Internet and e-mail into routine practice in health care and in community pharmacies. To support the development of such services more information is needed about the use of online information by consumers, particularly of those who may be the most likely to use and to benefit from the new sources and modes of medicines communication. This study explored the role and utilization of the Internet-based medicines information and information services in the context of a wider network of information sources accessible to the public in Finland. The overall aim was to gather information to develop better and more accessible sources of information for consumers and services to better meet the needs of consumers. Special focus was on the needs and information behavior among people with depression and using antidepressant medicines. This study applied both qualitative and quantitative methods. Consumer medicines information needs and sources were identified by analyzing the utilization of the University Pharmacy operated national drug information call center (Study I) and surveying Finnish adults (n=2348) use of the different medicines information sources (Study II). The utilization of the Internet as a source of antidepressant information among people with depression was explored by focus group discussions among people with depression and with current or past use of the antidepressant(s) (n=29, Studies III & IV). Pharmacy response to the needs of consumers in term of providing e-mail counseling was assessed by conducting a virtual pseudo customer study among the Finnish community pharmacies (n=161, Study V). Physicians and pharmacists were the primary sources of medicines information. People with mental disorders were more frequent users of telephone- and Internet-based medicines information sources and patient information leaflets than people without mental disorders. These sources were used to complement rather than replace information provided face-to-face by health professionals. People with depression used the Internet to seek facts about antidepressants, to share experiences with peers, and for the curiosity. They described that the access to online drug information was empowering. Some people reported lacking the skills necessary to assess the quality of online information. E-mail medication counseling services provided by community pharmacies were rare and varied in quality. Study results suggest that rather than discouraging the use of the Internet, health professionals should direct patients to use accurate and reliable sources of online medicines information. Health care providers, including community pharmacies should also seek to develop new ways of communicating information about medicines with consumers. This study determined that people with depression and using antidepressants need services enabling interactive communication not only with health care professionals, but also with peers. Further research should be focused on developing medicines information service facilitating communication among different patient and consumer groups.

Understanding consumers' decisions to adopt technology-enabled transformative services

This study extends understanding of consumers' decisions to adopt transformative services delivered via technology. It incorporates competitive effects into the model of goal-directed behavior which, in keeping with the majority of consumer decision making models, neglects to explicitly account for competition. A goal-level operationalization of competition, incorporating both direct and indirect competition, is proposed. A national web-based survey collected data from 431 respondents about their decisions to adopt mental health services delivered via mobile phone. The findings show that the extent to which consumers perceived using these transformative services to be more instrumental to achieving their goals than competition had the greatest impact on their adoption decisions. This finding builds on the limited empirical evidence for the inclusion of competitive effects to more fully explain consumers' decisions to adopt technology-based and other services. It also provides support for a broader operationalization of competition with respect to consumers' personal goals.

Adsorption isitherms for neutral organic compounds-A hierarchy in modelling: Part IV. Charge of maximum adsorption-Statistical mechanical basis

The charge at which adsorption of orgamc compounds attains a maximum ( \sigma MAX M) at an electrochenucal interface is analysed using several multi-state models in a hierarchical manner The analysis is based on statistical mechamcal results for the following models (A) two-state site parity, (B) two-state muhl-slte, and (C) three-state site parity The coulombic interactions due to permanent and reduced dipole effects (using mean field approximation), electrostatic field effects and specific substrate interactions have been taken into account. The simplest model in the hierarchy (two-state site parity) yields the exphcit dependence of ( \sigma MAX M) on the permanent dipole moment, polarizability of the solvent and the adsorbate, lattice spacing, effective coordination number, etc Other models in the baerarchy bring to hght the influence of the solvent structure and the role of substrate interactions, etc As a result of this approach, the "composition" of oM.x m terms of the fundamental molecular constants becomes clear. With a view to use these molecular results to maxamum advantage, the derived results for ( \sigma MAX M) have been converted into those involving experimentally observable parameters lake Co, C 1, E N, etc Wherever possible, some of the earlier phenomenologlcal relations reported for ( \sigma MAX M), notably by Parsons, Damaskm and Frumkln, and Trasattl, are shown to have a certain molecular basis, vlz a simple two-state sate panty model.As a corollary to the hxerarcbacal modelling, \sigma MAX M and the potential corresponding to at (Emax) are shown to be constants independent of 0max or Corg for all models The lmphcatlon of our analysis f o r OmMa x with respect to that predicted by the generalized surface layer equation (which postulates Om~ and Ema x varlaUon with 0) is discussed in detail Finally we discuss an passing o M. and the electrosorptlon valency an this context.

Predicting health programme participation: A gravity‐based, hierarchical modelling approach

Statistical analyses of health program participation seek to address a number of objectives compatible with the evaluation of demand for current resources. In this spirit, a spatial hierarchical model is developed for disentangling patterns in participation at the small area level, as a function of population-based demand and additional variation. For the former, a constrained gravity model is proposed to quantify factors associated with spatial choice and account for competition effects, for programs delivered by multiple clinics. The implications of gravity model misspecification within a mixed effects framework are also explored. The proposed model is applied to participation data from a no-fee mammography program in Brisbane, Australia. Attention is paid to the interpretation of various model outputs and their relevance for public health policy.

Statistical Optimization of Iron Electrodes for Alkaline Storage Batteries

A pressed-plate Fe electrode for alkalines storage batteries, designed using a statistical method (fractional factorial technique), is described. Parameters such as the configuration of the base grid, electrode compaction temperature and pressure, binder composition, mixing time, etc. have been optimised using this method. The optimised electrodes have a capacity of 300 plus /minus 5 mA h/g of active material (mixture of Fe and magnetite) at 7 h rate to a cut-off voltage of 8.86V vs. Hg/HgO, OH exp 17 ref.

Domain Adaptation on the Statistical Manifold

In this paper, we tackle the problem of unsupervised domain adaptation for classification. In the unsupervised scenario where no labeled samples from the target domain are provided, a popular approach consists in transforming the data such that the source and target distributions be- come similar. To compare the two distributions, existing approaches make use of the Maximum Mean Discrepancy (MMD). However, this does not exploit the fact that prob- ability distributions lie on a Riemannian manifold. Here, we propose to make better use of the structure of this man- ifold and rely on the distance on the manifold to compare the source and target distributions. In this framework, we introduce a sample selection method and a subspace-based method for unsupervised domain adaptation, and show that both these manifold-based techniques outperform the cor- responding approaches based on the MMD. Furthermore, we show that our subspace-based approach yields state-of- the-art results on a standard object recognition benchmark.

Motivation or demotivation of health workers providing maternal health services in rural areas in Vietnam: findings from a mixed-methods study

Background Motivation is an important driver for health professionals to maintain professional competencies, continue in a workforce and contribute to work tasks. While there is some research about motivation in health workers in low to middle income countries, maternal morbidity and mortality remains high in many low and middle income countries and this can be improved by improving the quality of maternal services and the training and skills maintenance of maternal health workers. This study examines the impact of motivation on maintenance of professional competence among maternal health workers in Vietnam using mixed methods. Methods The study consisted of a survey using a self-administered questionnaire of 240 health workers in 5 districts across two Vietnamese provinces and in-depth interviews with 43 health workers and health managers at the commune, district and provincial level to explore external factors that influenced motivation. The questionnaire includes a 23 item motivation instrument based on Kenyan health context, modified for Vietnamese language and culture. Results The 240 responses represented an estimated 95% of the target sample. Multivariate analysis showed that three factors contributed to the motivation of health workers: access to training (β = -0.14, p=0.03), ability to perform key tasks (β = 0.22, p=0.001), and shift schedule (β = -0.13, p=0.05). Motivation was higher in health workers self-identifying as competent or enabled to provide more care activities. Motivation was lower in those who worked more frequent night shifts and those who had received training in the last 12 months. The interviews identified that the latter was because they felt the training was irrelevant to them, and in some cases, they do not have opportunity to practice their learnt skills. The qualitative data also showed other factors relating to service context and organisational management practices contributed to motivation. Conclusions The study demonstrates the importance of understanding the motivations of health workers and the factors that contribute to this and may contribute to more effective management of the health workforce in low and middle income countries.

How Jung's concept of the wounded healer can guide learning and teaching in social work and human services

The concept of the “wounded healer” has been used to explain why those with adverse childhood histories often enter helping professions such as social work and human services (SWHS). Psychotherapist Carl Jung (1875–1961) believed wounded healers developed insight and resilience from their own experiences, enabling transformative interventions to occur with clients. Concerns exist that students with adverse childhood histories in SWHS may display unresolved emotional issues. This journal article explores how Jung’s interpretation of the wounded healer can be critically applied to understanding the learning needs of SWHS students with histories of abuse, neglect or other childhood adversity. The relevance of the wounded healer to SWHS education is explored in three key areas: - 1) the increased possibility of the occurrence of countertransference; - 2) the potential for vicarious traumatisation and burnout, and; - 3) personal and professional resilience displayed by SWHS students with a history of childhood adversity. The wounded healer metaphor allows for a more nuanced understanding of SWHS students with these histories. It also provides insight into the pedagogical considerations associated with teaching this student cohort.

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

Primary brain tumor patients’ supportive care needs and multidisciplinary rehabilitation, community and psychosocial support services: Awareness, referral and utilization

Primary brain tumors are associated with significant physical, cognitive and psychosocial changes. Although treatment guidelines recommend offering multidisciplinary rehabilitation and support services to address patients’ residual deficits, the extent to which patients access such services is unclear. This study aimed to assess patients’ supportive care needs early after diagnosis, and quantify service awareness, referral and utilization. A population-based sample of 40 adults recently diagnosed with primary brain tumors was recruited through the Queensland Cancer Registry, representing 18.9% of the eligible population of 203 patients. Patients or carer proxies completed surveys of supportive care needs at baseline (approximately three months after diagnosis) and three months later. Descriptive statistics summarized needs and service utilization, and linear regression identified predictors of service use. Unmet supportive care needs were highest at baseline for all domains, and highest for the physical and psychological needs domains at each time point. At follow-up, participants reported awareness of, referral to, and use of 32 informational, support, health professional or practical services. All or almost all participants were aware of at least one informational (100%), health professional (100%), support (97%) or practical service (94%). Participants were most commonly aware of speech therapists (97%), physiotherapists (94%) and diagnostic information from the internet (88%). Clinician referrals were most commonly made to physiotherapists (53%), speech therapists (50%) and diagnostic information booklets (44%), and accordingly, participants most commonly used physiotherapists (56%), diagnostic information booklets (47%), diagnostic information from the internet (47%), and speech therapists (43%). Comparatively low referral to and use of psychosocial services may limit patients’ abilities to cope with their condition and the changes they experience.