Renaturing cities using a regionally-focused biodiversity-led multifunctional benefits approach to urban green infrastructure

If a ‘Renaturing of Cities’ strategy is to maximise the ecosystem service provision of urban green infrastructure (UGI), then detailed consideration of a habitat services, biodiversity-led approach and multifunctionality are necessary rather than relying on the assumed benefits of UGI per se. The paper presents preliminary data from three case studies, two in England and one in Germany, that explore how multifunctionality can be achieved, the stakeholders required, the usefulness of an experimental approach for demonstrating transformation, and how this can be fed back into policy. We argue that incorporating locally contextualised biodiversity-led UGI design into the planning and policy spheres contributes to the functioning and resilience of the city and provides the adaptability to respond to locally contextualised challenges, such as overheating, flooding, air pollution, health and wellbeing as well as biodiversity loss. Framing our research to encompass both the science of biodiversity-led UGI and co-developing methods for incorporating a strategic approach to implementation of biodiversity-led UGI by planners and developers addresses a gap in current knowledge and begins to address barriers to UGI implementation. By combining scientific with policy learning and defined urban environmental targets with community needs, our research to date has begun to demonstrate how nature-based solutions to building resilience and adaptive governance can be strategically incorporated within cities through UGI.

New methods for PID autotuning

In this paper a recent approach for PID autotuning, involving neural networks, is ferther developed. To make this approach adaptive, optimal PID values must be known on-line. In this paper neural network models of tuning criteria, together with the use of genetic algorithms, are proposed to solve this problem.

Impact of an evidence-based online module on best practice in physical therapy for children with developmental coordination disorder: a mixed methods study

Aims : This study evaluates the impact of a Developmental Coordination Disorder (DCD) evidence-based online module including synthesized resources, practical strategies, and interactive component on self-reported physical therapist (PT) knowledge, skills, and practice. Methods : PTs from across Canada completed questionnaires before, immediately after, and 2 months following completion of the module. Questionnaires used 7-point Likert scale items and short open-ended questions; analyzes used paired t-tests and a thematic approach. Results : Fifty PTs completed both pre- and post-questionnaires; 41 of these completed the follow-up questionnaire. Most items (79%) evaluating self-reported knowledge and skills increased significantly following module completion and this increase was maintained two months later. Most participants (92%) reported an increase in their confidence to provide DCD evidence-based services. Participants plan to modify their evaluative practices (e.g., involving children in goal setting) and their management of DCD (e.g., using best practice principles, providing resources to families and physicians). At the 2- month follow-up, 46% of participants had returned to the module to review information (e.g., video, resources) or to download handouts. Conclusion : An online module developed collaboratively with PTs has the potential not only to increase PTs’ knowledge, but also to support them in implementing evidence-based services for children with DCD.

Machine learning methods for quantitative structure-property relationship modeling

Tese de doutoramento, Informática (Bioinformática), Universidade de Lisboa, Faculdade de Ciências, 2014

Methods for the transfer function design of multiple narrow-band bandpass sigma-delta modulators

This paper presents the design analysis of novel tunable narrow-band bandpass sigma-delta modulators, which can achieve concurrent multiple noise-shaping for multi-tone input signals. Four different design methodologies based on the noise transfer functions of comb filters, slink filters, multi-notch filters and fractional delay comb filters are applied for the design of these multiple-band sigma-delta modulators. The latter approach utilises conventional comb filters in conjunction with FIR, or allpass IIR fractional delay filters, to deliver the desired nulls for the quantisation noise transfer function. Detailed simulation results show that FIR fractional delay comb filter-based sigma-delta modulators tune accurately to most centre frequencies, but suffer from degraded resolution at frequencies close to Nyquist. However, superior accuracies are obtained from their allpass IIR fractional delay counterpart at the expense of a slight shift in noise-shaping bands at very high frequencies. The merits and drawbacks of each technique for the various sigma-delta topologies are assessed in terms of in-band signal-to-noise ratios, accuracy of tunability and coefficient complexity for ease of implementation.

Replicating the Networking, Mentoring and Venture Creation Benefits of Entrepreneurship Centres on a Shoestring: A Student-centred Approach to Entrepreneurship Education and Venture Creation

As support for both university-level entrepreneurial education and the use of experiential learning methods to foster student entrepreneurs increases, so too have the number of university-established or affiliated entrepreneurship centers. The activity at the center of this study aimed to combine experiential learning methods with assets associated with entrepreneurship centers, including venture creation, networking, and mentoring. Students were invited to participate in a competition wherein they were guided through the business creation process and pitched their ideas to investor judges who chose the winner and provided capital start-up funding and consulting. This research puts forth that university faculty at institutions without entrepreneurship centers can organize experiences to provide the benefits of entrepreneurship centers. The study used interviews to find that many of the benefits of entrepreneurship centers were able to be replicated using this method. The project is outlined, outcomes are analyzed, and the results and lessons learned are discussed.

A Community Hub Approach to Older People’s Housing

Purpose. This paper explores the potential of housing with care schemes to act as community hubs. The analysis highlights a range of benefits, barriers and facilitators. Design/methodology/approach. Data is presented from the ASSET project (Adult Social Services Environments and Settings) which used a mixed methods approach including a review of the literature, surveys and in-depth case study interviews. Findings. Most housing with care schemes have a restaurant or café, communal lounge, garden, hairdresser, activity room and laundrette, while many also have a library, gym, computer access and a shop. Many of these facilities are open not just to residents but also to the wider community, reflecting a more integrated approach to community health and adult social care, by sharing access to primary health care and social services between people living in the scheme and those living nearby. Potential benefits of this approach include the integration of older people’s housing, reduced isolation and increased cost effectiveness of local services through economies of scale and by maximising preventative approaches to health and wellbeing. Successful implementation of the model depends on a range of criteria including being located within or close to a residential area and having on-site facilities that are accessible to the public. Originality and Value. This paper is part of a very new literature on community hub models of housing with care in the UK. In the light of new requirements under the Care Act to better coordinate community services, it provides insights into how this approach can work and offers an analysis of the benefits and challenges that will be of interest to commissioners and providers as well as planners. This was a small scale research project based on four case studies. Caution should be taken when considering the findings in different settings.

New methods for meta-analysis under a fixed effects framework, with frequentist and Bayesian estimation.

Thesis (Ph.D.)--University of Washington, 2015

Bevacizumab in NF2-related vestibular schwannomas: a nationally coordinated approach to delivery and prospective evaluation

Background: NF2 patients develop multiple nervous system tumors including bilateral vestibular schwannomas (VS). The tumors and their surgical treatment are associated with deafness, neurological disability, and mortality. Medical treatment with bevacizumab has been reported to reduce VS growth and to improve hearing. In addition to evaluating these effects, this study also aimed to determine other important consequences of treatment including patient-reported quality of life and the impact of treatment on surgical VS rates. Methods: Patients treated with bevacizumab underwent serial prospective MRI, audiology, clinical, CTCAE-4.0 adverse events, and NFTI-QOL quality-of-life assessments. Tumor volumetrics were classified according to the REiNs criteria and annual VS surgical rates reviewed. Results: Sixty-one patients (59% male), median age 25 years (range, 10–57), were reviewed. Median follow-up was 23 months (range, 3–53). Partial volumetric tumor response (all tumors) was seen in 39% and 51% had stabilization of previously growing tumors. Age and pretreatment growth rate were predictors of response. Hearing was maintained or improved in 86% of assessable patients. Mean NFTI-QOL scores improved from 12.0 to 10.7 (P < .05). Hypertension was observed in 30% and proteinuria in 16%. Twelve treatment breaks occurred due to adverse events. The rates of VS surgery decreased after the introduction of bevacizumab. Conclusion: Treatment with bevacizumab in this large, UK-wide cohort decreased VS growth rates and improved hearing and quality of life. The potential risk of surgical iatrogenic damage was also reduced due to an associated reduction in VS surgical rates. Ongoing follow-up of this cohort will determine the long-term benefits and risks of bevacizumab treatment.

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

Technical and economic resources management in smart grids using heuristic optimization methods

Intensive use of Distributed Generation (DG) represents a change in the paradigm of power systems operation making small-scale energy generation and storage decision making relevant for the whole system. This paradigm led to the concept of smart grid for which an efficient management, both in technical and economic terms, should be assured. This paper presents a new approach to solve the economic dispatch in smart grids. The proposed methodology for resource management involves two stages. The first one considers fuzzy set theory to define the natural resources range forecast as well as the load forecast. The second stage uses heuristic optimization to determine the economic dispatch considering the generation forecast, storage management and demand response

A hybrid recommendation approach for a tourism system

Many current e-commerce systems provide personalization when their content is shown to users. In this sense, recommender systems make personalized suggestions and provide information of items available in the system. Nowadays, there is a vast amount of methods, including data mining techniques that can be employed for personalization in recommender systems. However, these methods are still quite vulnerable to some limitations and shortcomings related to recommender environment. In order to deal with some of them, in this work we implement a recommendation methodology in a recommender system for tourism, where classification based on association is applied. Classification based on association methods, also named associative classification methods, consist of an alternative data mining technique, which combines concepts from classification and association in order to allow association rules to be employed in a prediction context. The proposed methodology was evaluated in some case studies, where we could verify that it is able to shorten limitations presented in recommender systems and to enhance recommendation quality.

A New Approach in the Design of Air Stripping Columns for the Treatment of Groundwater Contaminated With Volatile Organic Compounds

Volatile organic compounds are a common source of groundwater contamination that can be easily removed by air stripping in columns with random packing and using a counter-current flow between the phases. This work proposes a new methodology for column design for any type of packing and contaminant which avoids the necessity of an arbitrary chosen diameter. It also avoids the employment of the usual graphical Eckert correlations for pressure drop. The hydraulic features are previously chosen as a project criterion. The design procedure was translated into a convenient algorithm in C++ language. A column was built in order to test the design, the theoretical steady-state and dynamic behaviour. The experiments were conducted using a solution of chloroform in distilled water. The results allowed for a correction in the theoretical global mass transfer coefficient previously estimated by the Onda correlations, which depend on several parameters that are not easy to control in experiments. For best describe the column behaviour in stationary and dynamic conditions, an original mathematical model was developed. It consists in a system of two partial non linear differential equations (distributed parameters). Nevertheless, when flows are steady, the system became linear, although there is not an evident solution in analytical terms. In steady state the resulting ODE can be solved by analytical methods, and in dynamic state the discretization of the PDE by finite differences allows for the overcoming of this difficulty. To estimate the contaminant concentrations in both phases in the column, a numerical algorithm was used. The high number of resulting algebraic equations and the impossibility of generating a recursive procedure did not allow the construction of a generalized programme. But an iterative procedure developed in an electronic worksheet allowed for the simulation. The solution is stable only for similar discretizations values. If different values for time/space discretization parameters are used, the solution easily becomes unstable. The system dynamic behaviour was simulated for the common liquid phase perturbations: step, impulse, rectangular pulse and sinusoidal. The final results do not configure strange or non-predictable behaviours.

Analysis of Forest Fires by means of Pseudo Phase Plane and Multidimensional Scaling Methods

Forest fires dynamics is often characterized by the absence of a characteristic length-scale, long range correlations in space and time, and long memory, which are features also associated with fractional order systems. In this paper a public domain forest fires catalogue, containing information of events for Portugal, covering the period from 1980 up to 2012, is tackled. The events are modelled as time series of Dirac impulses with amplitude proportional to the burnt area. The time series are viewed as the system output and are interpreted as a manifestation of the system dynamics. In the first phase we use the pseudo phase plane (PPP) technique to describe forest fires dynamics. In the second phase we use multidimensional scaling (MDS) visualization tools. The PPP allows the representation of forest fires dynamics in two-dimensional space, by taking time series representative of the phenomena. The MDS approach generates maps where objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to better understand forest fires behaviour.

Dispatch of distributed Energy Resources to Provide Energy and Reserve in Smart Grids using a Particle Swarm Optimization Approach

The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.