Brief interventions to reduce ecstasy use : a multi-site randomized controlled trial

Studies examining the ability of motivational enhancement therapy (MET) to augment education provision among ecstasy users have produced mixed results and none have examined whether treatment fidelity was related to ecstasy use outcomes. The primary objectives of this multi-site, parallel, two-group randomized controlled trial were to determine if a single-session of MET could instill greater commitment to change and reduce ecstasy use and related problems more so than an education-only intervention and whether MET sessions delivered with higher treatment fidelity are associated with better outcomes. The secondary objective was to assess participants’ satisfaction with their assigned interventions. Participants (N = 174; Mage = 23.62) at two Australian universities were allocated randomly to receive a 15-minute educational session on ecstasy use (n = 85) or a 50-minute session of MET that included an educational component (n = 89). Primary outcomes were assessed at baseline, and then at 4-, 16-, and 24-weeks post-baseline, while the secondary outcome measure was assessed 4-weeks post-baseline by researchers blind to treatment allocation. Overall, the treatment fidelity was acceptable to good in the MET condition. There were no statistical differences at follow-up between the groups on the primary outcomes of ecstasy use, ecstasy-related problems, and commitment to change. Both interventions groups reported a 50% reduction in their ecstasy use and a 20% reduction in the severity of their ecstasy-related problems at the 24-week follow up. Commitment to change slightly improved for both groups (9% - 17%). Despite the lack of between-group statistical differences on primary outcomes, participants who received a single session of MET were slightly more satisfied with their intervention than those who received education only. MI fidelity was not associated with ecstasy use outcomes. Given these findings, future research should focus on examining mechanisms of change. Such work may suggest new methods for enhancing outcomes.

The effect of the addition of hip strengthening exercises to a lumbopelvic exercise programme for the treatment of non-specific low back pain : a randomized controlled trial

Objectives To compare the efficacy of two exercise programs in reducing pain and disability for individuals with non-specific low back pain and to examine the underlying mechanical factors related to pain and disability for individuals with NSLBP. Design A single-blind, randomized controlled trial. Methods: Eighty participants were recruited from eleven community-based general medical practices and randomized into two groups completing either a lumbopelvic motor control or a combined lumbopelvic motor control and progressive hip strengthening exercise therapy program. All participants received an education session, 6 rehabilitation sessions including real time ultrasound training, and a home based exercise program manual and log book. The primary outcomes were pain (0-100mm visual analogue scale), and disability (Oswestry Disability Index V2). The secondary outcomes were hip strength (N/kg) and two-dimensional frontal plane biomechanics (°) measure during the static Trendelenburg test and while walking. All outcomes were measured at baseline and at 6-week follow up. Results There was no statistical difference in the change in pain (xˉ = -4.0mm, t= -1.07, p =0.29, 95%CI -11.5, 3.5) or disability (xˉ = -0.3%, t= -0.19, p =0.85, 95%CI -3.5, 2.8) between groups. Within group comparisons revealed clinically meaningful reductions in pain for both Group One (xˉ =-20.9mm, 95%CI -25.7, -16.1) and Group Two (xˉ =-24.9, 95%CI -30.8, -19.0). Conclusion Both exercise programs had similar efficacy in reducing pain. The addition of hip strengthening exercises to a motor control exercise program does not appear to result in improved clinical outcome for pain for individuals with non-specific low back pain.

The OnTrack Diabetes web-based program for type 2 diabetes and dysphoria self-management: A randomized controlled trial protocol

Background: The prevalence of type 2 diabetes is rising with the majority of patients practicing inadequate disease self-management. Depression, anxiety, and diabetes-specific distress present motivational challenges to adequate self-care. Health systems globally struggle to deliver routine services that are accessible to the entire population, in particular in rural areas. Web-based diabetes self-management interventions can provide frequent, accessible support regardless of time and location Objective: This paper describes the protocol of an Australian national randomized controlled trial (RCT) of the OnTrack Diabetes program, an automated, interactive, self-guided Web program aimed to improve glycemic control, diabetes self-care, and dysphoria symptoms in type 2 diabetes patients. Methods: A small pilot trial is conducted that primarily tests program functionality, efficacy, and user acceptability and satisfaction. This is followed by the main RCT, which compares 3 treatments: (1) delayed program access: usual diabetes care for 3 months postbaseline followed by access to the full OnTrack Diabetes program; (2) immediate program: full access to the self-guided program from baseline onward; and (3) immediate program plus therapist support via Functional Imagery Training (FIT). Measures are administered at baseline and at 3, 6, and 12 months postbaseline. Primary outcomes are diabetes self-care behaviors (physical activity participation, diet, medication adherence, and blood glucose monitoring), glycated hemoglobin A1c (HbA1c) level, and diabetes-specific distress. Secondary outcomes are depression, anxiety, self-efficacy and adherence, and quality of life. Exposure data in terms of program uptake, use, time on each page, and program completion, as well as implementation feasibility will be conducted. Results: This trial is currently underway with funding support from the Wesley Research Institute in Brisbane, Australia. Conclusions: This is the first known trial of an automated, self-guided, Web-based support program that uses a holistic approach in targeting both type 2 diabetes self-management and dysphoria. Findings will inform the feasibility of implementing such a program on an ongoing basis, including in rural and regional locations.

A model predictive approach for community battery energy storage system optimization

This paper presents an efficient algorithm for optimizing the operation of battery storage in a low voltage distribution network with a high penetration of PV generation. A predictive control solution is presented that uses wavelet neural networks to predict the load and PV generation at hourly intervals for twelve hours into the future. The load and generation forecast, and the previous twelve hours of load and generation history, is used to assemble load profile. A diurnal charging profile can be compactly represented by a vector of Fourier coefficients allowing a direct search optimization algorithm to be applied. The optimal profile is updated hourly allowing the state of charge profile to respond to changing forecasts in load.

Lifecycle optimization and tradeoff analysis among competing objectives for a road corridor

While the philosophical motivation behind Civil Infrastructure Management Systems is to achieve optimal level of service at a minimum cost, the allocation of scarce resources among competing alternatives is still a matter of debate. It appears to be widely accepted that results from tradeoff analysis can be measured by the degree of accomplishment of the objectives. Road management systems not only deal with different asset types but also with conflicting objectives. This paper presents a case study of lifecycle optimization with tradeoff analysis for a road corridor in New Brunswick. Objectives of the study included condition of bridge and roads and road safety. A road safety index was created based on potential for improvement. Road condition was based on roughness, rutting and cracking. Initial results show lack of sustainability in bridge performance. Therefore, bridges where broken by components: deck, superstructure and substructure. Visual inspections, in addition to construction age of each bridge, were combined to generate a surrogate apparent age. Two life cycle analysis were conducted; one aimed to minimize overall cost while achieving sustainable results and another one purely for optimization. -used to identify required levels of budget. Such analyses were used to identify the minimum required budget and to demonstrate that with the same amount of money it was possible to achieve better levels of performance. Dominance and performance driven criteria were combined to identify and select an optimal result. It was found that achievement of optimally sustained results is conditioned by the availability of treatments for all asset classes at across their life spans. For the case study a disaggregated bridge condition index was introduced to the original algorithm to attempt to achieve sustainability in all bridges components, however lack of early stage treatments for substructures produce declining trends for such a component.

An efficiency optimization scheme for bidirectional inductive power transfer systems

Unidirectional inductive power transfer (UIPT) systems allow loads to consume power while bidirectional IPT (BIPT) systems are more suitable for loads requiring two way power flow such as vehicle to grid (V2G) applications with electric vehicles (EVs). Many attempts have been made to improve the performance of BIPT systems. In a typical BIPT system, the output power is control using the pickup converter phase shift angle (PSA) while the primary converter regulates the input current. This paper proposes an optimized phase shift modulation strategy to minimize the coil losses of a series – series (SS) compensated BIPT system. In addition, a comprehensive study on the impact of power converters on the overall efficiency of the system is also presented. A closed loop controller is proposed to optimize the overall efficiency of the BIPT system. Theoretical results are presented in comparison to both simulations and measurements of a 0.5 kW prototype to show the benefits of the proposed concept. Results convincingly demonstrate the applicability of the proposed system offering high efficiency over a wide range of output power.

Model-based analysis and optimization of bioreactor for hematopoietic stem cell cultivation

One of the problems to be solved in attaining the full potentials of hematopoietic stem cell (HSC) applications is the limited availability of the cells. Growing HSCs in a bioreactor offers an alternative solution to this problem. Besides, it also offers the advantages of eliminating labour intensive process as well as the possible contamination involved in the periodic nutrient replenishments in the traditional T-flask stem cell cultivation. In spite of this, the optimization of HSC cultivation in a bioreactor has been barely explored. This manuscript discusses the development of a mathematical model to describe the dynamics in nutrient distribution and cell concentration of an ex vivo HSC cultivation in a microchannel perfusion bioreactor. The model was further used to optimize the cultivation by proposing three alternative feeding strategies in order to prevent the occurrence of nutrient limitation in the bioreactor. The evaluation of these strategies, the periodic step change increase in the inlet oxygen concentration, the periodic step change increase in the media inflow, and the feedback control of media inflow, shows that these strategies can successfully improve the cell yield of the bioreactor. In general, the developed model is useful for the design and optimization of bioreactor operation.

Facilitating lifestyle changes to manage menopausal symptoms in women with breast cancer: A randomized controlled pilot trial of The Pink Women’s Wellness Program

OBJECTIVE Women diagnosed as having breast cancer may experience difficulties with posttreatment effects such as menopausal symptoms. The aims of this pilot study were to (1) evaluate the impact of a multimodal lifestyle program on reducing menopausal symptoms in women with breast cancer and (2) examine the impact of the program on health-related quality of life (HRQoL) and adherence to lifestyle recommendations. METHODS Overall, 55 women aged 45 to 60 years with one moderate to severe menopausal symptom and a history of breast cancer were randomized into an intervention group (n = 26) or a control group (n = 29). Women in the intervention group received a lifestyle intervention (The Pink Women’s Wellness Program) that included clinical consultations and a tailored health education program. Measurements of menopausal symptoms (Greene Climacteric Scale), HRQoL (SF-12 and Functional Assessment of Cancer Therapy—Breast), and modifiable lifestyle factors (food intake, physical activity, smoking and alcohol use, and sleep disturbance) were taken at baseline and 12 weeks. RESULTS Women in the intervention group reported clinically significant reductions in many menopausal symptoms, specifically somatic symptoms (d = 0.52), vasomotor symptoms (d = 0.55), sexual dysfunction (d = .65), and overall menopausal symptoms (d = 0.54), at 12 weeks compared with the control group (d = 0.03, d = 0.24, d = 0.18, and d = 0.05, respectively). Women in the intervention group reported improvements in Functional Assessment of Cancer Therapy—Breast subscale scores, physical well-being and functional well-being, and Functional Assessment of Cancer Therapy—General total scores (intervention group: d = 0.54, d = 0.50, and d = 0.48, respectively; control group: d = 0.22, d = 0.11, and d = 0.05, respectively). CONCLUSIONS The Pink Women’s Wellness Program is effective in decreasing menopausal symptoms, thus improving HRQoL. This being a pilot study, further research is recommended to investigate the benefits of combining nonpharmacological interventions for women with breast cancer to reduce their treatment-related menopausal symptoms.

Managing and learning with multiple models: Objectives and optimization algorithms

The quality of environmental decisions should be gauged according to managers' objectives. Management objectives generally seek to maximize quantifiable measures of system benefit, for instance population growth rate. Reaching these goals often requires a certain degree of learning about the system. Learning can occur by using management action in combination with a monitoring system. Furthermore, actions can be chosen strategically to obtain specific kinds of information. Formal decision making tools can choose actions to favor such learning in two ways: implicitly via the optimization algorithm that is used when there is a management objective (for instance, when using adaptive management), or explicitly by quantifying knowledge and using it as the fundamental project objective, an approach new to conservation.This paper outlines three conservation project objectives - a pure management objective, a pure learning objective, and an objective that is a weighted mixture of these two. We use eight optimization algorithms to choose actions that meet project objectives and illustrate them in a simulated conservation project. The algorithms provide a taxonomy of decision making tools in conservation management when there is uncertainty surrounding competing models of system function. The algorithms build upon each other such that their differences are highlighted and practitioners may see where their decision making tools can be improved. © 2010 Elsevier Ltd.

A randomized controlled trial of a program to reduce adolescent road-related medically-treated injuries

Background Injury is the leading cause of adolescent death and injury around the road is a common source of adolescent injuries. Skills for Preventing Injury in Youth (SPIY) is a comprehensive program developed in Australia for early adolescents (term-long curriculum, including looking out for friends, first-aid training coupled with teacher school-connectedness professional development). Jessors’ Protection-Risk Framework guided the program approach focusing on building protective relationships. Method A randomized controlled trial with 35 schools was undertaken. Students completed surveys at baseline, six-months post-intervention and twelve-months post intervention. There were 1686 students (56% female) who completed the twelve-month survey, including the Extended-Adolescent Injury Checklist whereby students self-report on medically-treated injuries over the previous three-months (only road-related items are reported in this study; cycling, motorcycle riding, pedestrian, and riding as a passenger). Randomly selected SPIY classes also participated in focus groups and reported on perceptions of SPIY and injury risk behavior. Results As a check of randomization baseline differences of the variables were examined, with no significant differences between intervention and control groups. At the 12-month follow-up, there were fewer medically-treated injuries among the intervention students compared with the control group, particularly associated with being a passenger. The process evaluation revealed students perceived change in injury risk and risk behaviors. Conclusions While data analyses are continuing, the results indicate that the program seeking to encourage adolescents to look out for their friends, build connections to school and provide first aid skills training goes some way to reducing self-reported medically-treated injuries around the road.

Do-Rank: DCG optimization for learning-to-rank in tag-based item recommendation systems

Discounted Cumulative Gain (DCG) is a well-known ranking evaluation measure for models built with multiple relevance graded data. By handling tagging data used in recommendation systems as an ordinal relevance set of {negative,null,positive}, we propose to build a DCG based recommendation model. We present an efficient and novel learning-to-rank method by optimizing DCG for a recommendation model using the tagging data interpretation scheme. Evaluating the proposed method on real-world datasets, we demonstrate that the method is scalable and outperforms the benchmarking methods by generating a quality top-N item recommendation list.

Randomized controlled trial of an improved version of MobileMums, an intervention for increasing physical activity in women with young children

Background Women with young children (<5 years) are an important group for physical activity intervention. Purpose To evaluate the feasibility, acceptability and efficacy of MobileMums- a physical activity intervention for women with young children. Methods Women were randomized to MobileMums (n=133) or a control group (n=130). MobileMums was delivered primarily via individually-tailored text messages. Moderate to vigorous physical activity (MVPA) was measured by self-report and accelerometer at baseline, end of the intervention (13-weeks) and 6-months later (9-months). Changes were analyzed using repeated measures models. Results MobileMums was feasible to deliver and acceptable to women. Self-reported MVPA duration (minutes/week) and frequency (days/week) increased significantly post intervention (13-week intervention effect 48.5 min/week, 95%CI [13.4, 82.9] and 1.6 days/week, 95%CI [0.6, 2.6]). Intervention effects were not maintained 6-months later. No effects observed in accelerometer-derived MVPA. Conclusions MobileMums increased women’s self-reported MVPA immediately post intervention. Future investigations need to target sustained physical activity improvements.

Evolutionary optimization and game strategies for advanced multi-disciplinary design : applications to aeronautics and UAV design

Many complex aeronautical design problems can be formulated with efficient multi-objective evolutionary optimization methods and game strategies. This book describes the role of advanced innovative evolution tools in the solution, or the set of solutions of single or multi disciplinary optimization. These tools use the concept of multi-population, asynchronous parallelization and hierarchical topology which allows different models including precise, intermediate and approximate models with each node belonging to the different hierarchical layer handled by a different Evolutionary Algorithm. The efficiency of evolutionary algorithms for both single and multi-objective optimization problems are significantly improved by the coupling of EAs with games and in particular by a new dynamic methodology named “Hybridized Nash-Pareto games”. Multi objective Optimization techniques and robust design problems taking into account uncertainties are introduced and explained in detail. Several applications dealing with civil aircraft and UAV, UCAV systems are implemented numerically and discussed. Applications of increasing optimization complexity are presented as well as two hands-on test cases problems. These examples focus on aeronautical applications and will be useful to the practitioner in the laboratory or in industrial design environments. The evolutionary methods coupled with games presented in this volume can be applied to other areas including surface and marine transport, structures, biomedical engineering, renewable energy and environmental problems.