Currently society is facing a set of interconnected challenges, known collectively as the Sustainability Challenge, which are systematically increasing socio-ecological unsustainability on a scale never experienced before.  In order to address the Sustainability Challenge, Social Labs provide an approach that is systemic, participatory and emergent, enabling solutions that are responsive to the dynamic nature of those interconnected challenges. Our research explores how a specific lab - U.Lab - can be re-designed in order to move society strategically toward a sustainable future. We use the Framework for Strategic Sustainable Development, designed to help practitioners to facilitate society’s transition towards sustainable development, as well as concepts of strategic sustainable development, which support s shift from unsustainable systems, structures and practices towards sustainable ones in a strategic way. Our research follows Design Research Methodology (DRM). DRM aims for the formulation, validation and development of theories and models in the field of design. U.Lab’s experiential response to the Sustainability Challenge inspires participants to question paradigms of thought and societal norms. However, U.Lab is still an emerging social technology and lacks boundary conditions and a scientific basis for understanding our current reality and creating the solutions that will lead society systematically towards a sustainable future.

Current methods for reaching and defining success in society are not sustainable. A major shift in society’s definition of economic success is required, and organizations represent a key leverage point in the transition to a sustainable economy. This research looks to practices within organizations with a sustainability purpose in an attempt to understand how their organizational culture creates an environment for continual strategic decision making towards sustainability. A combination of literature review and structured interviews were used to elicit the cultural practices of 18 organizations with a clear social and ecological sustainability purpose. The research confirmed the importance of organizational culture for maintaining alignment with a sustainability purpose by fostering motivation and commitment towards sustainability at both a collective and individual level in the organization. Eight overarching areas of practice were identified as being present in the organizations included in the study. The practices identified help organizations to act strategically and in the right direction towards sustainability on a daily basis, standing as a complement to the strategic prioritization model of the FSSD. / <p>giancarlo@pucci.cr</p>

Esta pesquisa apresenta um sistema de suporte a decisão (SSD) para o planejamento e gerenciamento integrado de bacias hidrográficas, denominado Riverhelp!, e também sugere nova metodologia para o uso desse tipo de ferramenta de análise. O objetivo geral é desenvolver um SSD que possa auxiliar a gestão de recursos hídricos. Para isso o SSD utiliza e integra tecnologias avançadas em um só sistema computacional flexível e que pode ser utilizado e entendido por especialistas e outros participantes do processo decisório. O programa é composto por quatro módulos principais e tem código aberto baseado na tecnologia OpenMI o que permite aos usuários alterar e incluir funções. Outra propriedade que merece destaque é sua completa integração com um sistema de informações geográficas permitindo a análise temporal e espacial da bacia hidrográfica. Essa ferramenta pode, por exemplo, ser usada para análises de disponibilidade de água em quantidade e qualidade, para o estudo de ecossistemas, para a otimização e operação de reservatórios e para auxiliar no processo de outorga de direito de uso da água. Uma aplicação do Riverhelp! para as bacias hidrográficas dos rios Piracicaba, Capivari e Jundiaí ilustra as diversas possibilidades de uso do sistema. Os resultados dessa investigação reforçam a importância e a necessidade de uma nova geração de SSD que considerem e analisem de maneira integrada os complexos assuntos relacionados à gestão da bacia hidrográfica. O desenvolvimento do Riverhelp! contribui significativamente para o avanço das pesquisas relacionadas ao tema de planejamento e gerenciamento integrado de recursos hídricos fornecendo um SSD com características únicas, que associa ferramentas para avaliação ambiental, modelos de simulação e otimização de qualidade e quantidade de água superficial e subterrânea, sistema de informações geográficas, diferentes bancos de dados, funções para análises estatísticas e técnicas multiobjetivo para análise de cenários. / This research presents a decision support system (DSS) for integrated water resources planning and management (IWRM) named Riverhelp! and suggests new methodology for the use of this kind of analysis tool as well. The general goal is to develop an appropriate DSS that can help IWRM process. In order to do so, the DSS uses and combines advanced technologies and techniques currently available. It integrates different methodologies in just one computational system, which is flexible and can be used and understood not only by specialists but also by general users who are not familiar with modelling. The DSS Riverhelp! has four main building blocks and an open computational core based on the OpenMI technology which allows users to access it programmatically and to add new tools or to change computations in almost any way they want. Another important characteristic is that the DSS Riverhelp! is fully integrated with a geographic information system (GIS). Most of all, it puts time and spatial information together and is therefore a great package for data management of river basins. This system can be used for hydrological analyses, assessment of water availability, water resources planning, water quality and quantity studies, reservoir systems nonlinear optimization and so on. In this research a Riverhelp! application for the Piraciaba, Capivari and Jundiaí river basins shows several possibilities for its use. The results of this study emphasize the importance and necessity of a new generation of decision support systems that are able to analyze and take into account the complex issues associated to river basin management in an integrated approach. The Riverhelp! development makes significant contributions for research advance in the integrated water resources planning and management field providing a DDS with unique characteristics that combines environmental assessment tools, water quality and quantity simulation and optimization models for surface water and groundwater, geographic information system, sophisticated databases, statistical tools and multicriteria techniques for scenario analyses.

6 Abstract Due to its effect on fitness and many biological processes is body size one of the most important attribute of organisms. Body size is positively correlated with fecundity in insects and other ectotherms. Growth, which determine body size, is therefore crucial feature of animals. Study of growth can elucidate some aspects of body size evolution. Unfortunatelly, many insects life-history studies do not consider its complexity, especially the existence of distinct larval instars. Inaccurate record of growth trajectory may result also in biased differences in growth between sexually dimorphic sexes. Aim of this thesis is to record growth trajectories of two flower beetle species (Coleoptera: Scarabaeidae: Cetoniinae). These growth trajectories enable to define proximate mechanisms of growth with regard to individual instars. Determination of developmental mechanisms of sexual size dimorphism is another goal of this study. The growth is clearly divided in three distinct periods. In each individual period (i.e. instar) is described by asymptotic curve. The instars are not independent on each other - the growth in following instar is influenced by growth in previous. There are no differences in growth characteristics between sexes. Sexual size dimorphism is caused by differences in growth rate between...

Objective: The purpose of this study was to determine speech-language pathologists’ (SLPs’) perceptions regarding the concept of severity of speech sound disorder (SSD). Methods: An online survey of 40 questions was created using REDCap® and disseminated to currently practicing SLPs across the United States. A total of 296 responses were completed, and data were analyzed using descriptive statistics and coding according to grounded theory. Results: The top five factors SLPs consider when determining SSD severity are types of errors, intelligibility, perceptual judgment, normative data, and percentile rankings. Most SLPs were unfamiliar with the International Classification of Functioning, Disability and Health (WHO, 2001), which was reflected in how they prioritized the ICF component of body function over activity/participation and personal factors. Conclusion: SLPs need a standard, biopsychosocial model for rating SSD severity, clinical training and continuing education on the ICF, and exposure to holistic tools for assessing children with SSD.

À la base de l’évolution de la technologie microélectronique actuelle, la réduction des dimensions critiques des MOSFET standards pour améliorer leurs performances électriques a atteint depuis quelques années ses limites physiques. L’utilisation de nanocomposants innovateurs ayant une configuration planaire, comme solution de remplacement, semble être une voie prometteuse pour certaines applications. Les diodes autocommutantes, Self-Switching Diodes (SSD), en font partie. Les SSD sont des composants unipolaires à deux accès ayant une caractéristique I-V non-linéaire semblable à celle d’une diode bipolaire. Leur configuration planaire rend leur fabrication plus facile et réduit considérablement les capacités parasites intrinsèques. Cette thèse porte sur la fabrication, la simulation et la caractérisation électrique de SSD fabriquées sur des substrats en SOI (Silicon-On-Insulator). Les dispositifs SSD ont été réalisés au départ grâce à des gravures par FIB (Focussed Ion Beam). Cette technique polyvalente nous permet de contrôler en temps réel les conditions de gravure. Par la suite, nous avons procédé à une fabrication massive de SSD en utilisant la technique d’électrolithographie et de gravure sèche. Les simulations effectuées principalement avec TCAD-Medici nous ont permis d’optimiser et d’investiguer en détails l’effet critique des paramètres géométriques (longueur, largeur et épaisseur du canal conducteur ainsi que la largeur des tranchées isolantes) et des paramètres physiques (densité surfacique aux niveaux des interfaces isolant/semiconducteur, densité des dopants et type de diélectrique dans les tranchées isolantes) des SSD sur les caractéristiques électriques, les valeurs de la tension seuil et les phénomènes de transport non linéaire qui ont lieu dans le canal conducteur de ce type de composants. Les mesures expérimentales de caractéristiques I-V de SSD ayant des canaux conducteurs de largeurs et de longueurs variables confirment les prévisions de nos simulations. Bien que le comportement électrique des SSD ressemble à celui d’un MISFET, nous démontrons le fait que l’on ne peut modéliser leurs caractéristiques I-V avec les mêmes expressions en nous basant sur le principe de fonctionnement spécifique à chacun de ces deux dispositifs.

Planar electronic devices represent an attractive approach towards roll-to-roll printed electronics without the need for the sequential, precisely aligned, patterning steps inherent in the fabrication of conventional ‘3D’ electronic devices. Self-switching diodes (SSDs) and in-plane-gate field-effect transistors (IPG-FETs) can be patterned using a single process into a substrate precoated with semiconductor.These devices function in depletion mode, requiring the semiconductor to be doped in order for the devices to function. To achieve this, a reliable and controllable method was developed for doping organic semiconducting polymers by the immersion of optimally deposited films in a solution of dopant. The process was shown to apply both semicrystalline and air-stable, amorphous materials indicating that the approach is broadly applicable to a wide range of organic semiconductors.Simultaneously with the development of the doping protocol specialised hot-embossing equipment was designed and constructed and a high-yielding method of patterning the structures of IPG-FETs and SSDs was arrived at. This method allowed for consistent and reliable patterning of features with a minimum line-width of 200nm.Following the development of these doping and patterning processes these were combined to fabricate controllably doped, functioning planar devices. SSDs showed true zero-threshold rectification behaviour with no observed breakdown in the reverse direction up to 100 V. IPG-FETs showed switching behaviour in response to an applied gate potential and were largely free of detectable gate leakage current, verifying the quality of the patterning process.Furthermore, high-performance semiconducting polymer PAAD was synthesised and characterised in field-effect transistors as steps towards its use in planar electronic devices. It was also shown that this material could be doped using the developed immersion doping protocol and that this protocol was compatible with top-gated device architectures and the use of fluoropolymer CYTOP as a dielectric.

Flash memories are solid-state non-volatile memories. They play a vital role especially in information storage in a wide range of consumer electronic devices and applications including smart phones, digital cameras, laptop computers, and satellite navigators. The demand for high density flash has surged as a result of the proliferation of these consumer electronic portable gadgets and the more features they offer – wireless internet, touch screen, video capabilities. The increase in the density of flash memory devices over the years has come as a result of continuous memory cell-size reduction. This size scaling is however approaching a dead end and it is widely agreed that further reduction beyond the 20 nm technological node is going to be very difficult, as it would result to challenges such as cross-talk or cell-to-cell interference, a high statistical variation in the number of stored electrons in the floating gate and high leakage currents due to thinner tunnel oxides. Because of these challenges a wide range of solutions in form of materials and device architectures are being investigated. Among them is three-dimensional (3-D) flash, which is widely acclaimed as the ideal solution, as they promise the integration of long-time retention and ultra-high density cells without compromising device reliability. However, current high temperature (>600 °C) growth techniques of the Polycrystalline silicon floating gate material are incompatible with 3-D flash memory; with vertically stacked memory layers, which require process temperatures to be ≤ 400 °C. There already exist some low temperature techniques for producing polycrystalline silicon such as laser annealing, solid-phase crystallization of amorphous silicon and metal-induced crystallization. However, these have some short-comings which make them not suitable for use in 3-D flash memory, e.g. the high furnace annealing temperatures (700 °C) in solid-phase crystallization of amorphous silicon which could potentially damage underlying memory layers in 3-D flash, and the metal contaminants in metal-induced crystallization which is a potential source of high leakage currents. There is therefore a need for alternative low temperature techniques that would be most suitable for flash memory purposes. With reference to the above, the main objective of this research was to develop a novel low temperature method for growing silicon structures at ≤ 400 °C. This thesis thus describes the development of a low-temperature method for polycrystalline silicon growth and the application of the technique in a capacitor-like flash memory device. It has been demonstrated that silicon structures with polycrystalline silicon-like properties can be grown at ≤ 400 °C in a 13.56 MHz radio frequency (RF) plasma-enhanced chemical vapour deposition (PECVD) reactor with the aid of Nickel Formate Dihydrate (NFD). It is also shown that the NFD coated on the substrates, thermally decomposes in-situ during the deposition process forming Ni particles that act as nucleation and growth sites of polycrystalline silicon. Silicon films grown by this technique and without annealing, have exhibited optical band gaps of ~ 1.2 eV compared to 1.78 eV for films grown under identical conditions but without the substrate being coated. These values were determined from UV-Vis spectroscopy and Tauc plots. These optical band gaps correspond to polycrystalline silicon and amorphous silicon respectively, meaning that the films grown on NFD-coated substrates are polycrystalline silicon while those grown on uncoated substrates remain amorphous. Moreover, this novel technique has been used to fabricate a capacitor-like flash memory that has exhibited hysteresis width corresponding to charge storage density in the order of 1012 cm-2 with a retention time well above 20 days for a device with silicon films grown at 300 °C. Films grown on uncoated films have not exhibit any significant hysteresis, and thus no flash memory-like behaviour. Given that all process temperatures throughout the fabrication of the devices are less than 400 °C and that no annealing of any sort was done on the material and devices, this growth method is thermal budget efficient and meets the crucial process temperature requirements of 3-D flash memory. Furthermore, the technique is glass compatible, which could prove a major step towards the acquisition of flash memory-integrated systems on glass, as well as other applications requiring low temperature polycrystalline silicon.

This paper concerns itself with object detection as a possible solution to Valmet’s quest for a visual-feedback system that can help operators and other personnel to more easily interact with their machines and equipment. New advancements in deep learning, specifically CNN models, have been exploring neural networks with detection-capabilities. Object detection has historically been mostly inaccessible to the industry due the complex solutions involving various tricky image processing algorithms. In that regard, deep learning offers a more easily accessible way to create scalable object detection solutions. This study has therefore chosen to review recent literature detailing detection models with a selective focus on factors making them realizable on ARM hardware and in turn mobile devices like phones. An attempt was made to single out the most lightweight and hardware efficient model and implement it as a prototype in order to help Valmet in their decision process around future object detection products. The survey led to the choice of a SSD-MobileNetsV2 detection architecture due to promising characteristics making it suitable for performance-constrained smartphones. This CNN model was implemented on Valmet’s phone of choice, Samsung Galaxy S8, and it successfully achieved object detection functionality. Evaluation shows a mean average precision of 60 % in detecting objects and a 4.7 FPS performance on the chosen phone model. TensorFlow was used for developing, training and evaluating the model. The report concludes with recommending Valmet to pursue solutions built on-top of these kinds of models and further wishes to express an optimistic outlook on this type of technology for the future. Realizing performance of this magnitude on a mid-tier phone using deep learning (which historically is very computationally intensive) sets us up for great strides with this type of technology in the future; and along with better smartphones, great benefits are expected to both industry and consumers. / Den här rapporten behandlar objekt detektering som en möjlig lösning på Valmets efterfrågan av ett visuellt återkopplingssystem som kan hjälpa operatörer och annan personal att lättare interagera med maskiner och utrustning. Nya framsteg inom djupinlärning har dem senaste åren möjliggjort framtagande av neurala nätverksarkitekturer med detekteringsförmågor. Då industrisektorn svårare tar till sig högst specialiserade algoritmer och komplexa bildbehandlingsmetoder (som tidigare varit fallet med objekt detektering) så ger djupinlärningsmetoder istället upphov till att skapa självlärande system som är återanpassningsbara och närmast intuitiva i dem fall där sådan teknologi åberopas. Den här studien har därför valt att studera ett par sådana teknologier för att hitta möjliga implementeringar som kan realiseras på något så enkelt som en mobiltelefon. Urvalet har därför bestått i att hitta detekteringsmodeller som är hårdvarumässigt resurssnåla och implementera ett sådant system för att agera prototyp och underlag till Valmets vidare diskussioner kring objekt-detekteringsslösningar. Studien valde att implementera en SSD-MobileNetsV2 modellarkitektur då den uppvisade lovande egenskaper kring hårdvarukraven. Modellen implementerades och utvärderades på Valmets mest förekommande telefon Samsung Galaxy S8 och resultatet visade på en god förmåga för modellen att detektera objekt. Den valda modellen gav 60 % precision på utvärderingsbilderna och lyckades nå 4.7 FPS på den implementerade telefonen. TensorFlow användes för programmering och som stödjande mjukvaruverktyg för träning, utvärdering samt vidare implementering. Studien påpekar optimistiska förväntningar av denna typ av teknologi; kombinerat med bättre smarttelefoner i framtiden kan det leda till revolutionerande lösningar för både industri och konsumenter.

As organizações públicas e privadas são constantemente expostas a fatores internos e externos, que podem comprometer sua estabilidade diante das oscilações da economia e dos concorrentes. Nestas empresas, os tomadores de decisão são essenciais para analisar e avaliar todas as variáveis que envolvem estes fatores, com o objetivo de identificar o melhor caminho para os negócios. Entretanto, conseguir gerenciar os dados internos e externos à organização não é uma atividade simples. Neste contexto, os Sistemas de Suporte à Decisão (SSD) tornaram-se fundamentais para auxiliar os tomadores de decisão na solução de problemas mal estruturados ou sem nenhuma estruturação. Porém, a complexidade que envolve os projetos de implantação ou desenvolvimento de um SSD, geralmente compromete a efetividade dos testes que garantem a conformidade do sistema em relação às especificações previamente definidas. Uma solução para esse problema é considerar os atributos ou fatores de testabilidade nestes projetos, pois podem elevar o grau de eficácia e eficiência da atividade de teste e consequentemente contribuírem para redução do tempo e custos do projeto. Portanto, conseguir identificar esses atributos ou fatores que tenham influência na testabilidade dos SSD e algum método que permita analisar e avaliar o quanto estão presentes neste sistema, é essencial para aumentar a qualidade do sistema. Diante desta necessidade, este trabalho investigou e selecionou os principais fatores que podem influenciar no grau de testabilidade de um software e propôs um método para analisar e avaliar o quanto o SSD está considerando esses fatores em sua arquitetura. Com o objetivo de avaliar e validar o método de análise e avaliação, foram realizados testes de aplicabilidade em empresas de pequeno, médio e grande porte, bem como no meio acadêmico. Com os resultados obtidos nos testes, foi possível concluir que o método é específico para SSD, que pode ser usado como um guia durante o processo de desenvolvimento e auxiliar na classificação de SSD quanto a sua testabilidade. / Public and private organizations are constantly exposed to internal and external factors which could compromise their stability in the face of fluctuations in the economy and competitors. In these companies, decision makers are essential to analyze and evaluate all the variables regarding these factors, in order to identify the best way for business. However, managing internal and external data of the organization is not a simple activity. In this context, Decision Support Systems (DSS) have become essential to assist decision makers in solving unstructured problems or lock of structure. However, the complexity involved in the implementation of projects or development of a DSS usually compromises the effectiveness of tests that ensure compliance of the system in relation to previously defined specifications. One solution to this problem is to consider the attributes or testability factors in these projects, since they can raise the level of effectiveness and efficiency of testing activity and thus contribute to reducing the time and project costs. Therefore, the ability to identify these attributes or factors that influence testability of DSS and a process for analyzing and evaluating how much the present in this system, is essential to increase system quality. Given this need, this work investigated and selected the main factors that can influence the degree of testability of software and proposed a way to analyze and assess how the DSS is considering these factors in its architecture. In order to evaluate and validate the analysis and evaluation method, applicability tests were performed in small, medium and large companies, as well as in academy. As results obtained in the tests, it was concluded that the method is specific for DSS, which can be used as a guide during the development process and assist in the DSS classification regarding its testability.