Conflict prevention and decentralized governance: some remarks about the state of the art in theory and practice

Is there a link between decentralized governance and conflict prevention? This article tries to answer the question by presenting the state of the art of the intersection of both concepts. Provided that social conflict is inevitable and given the appearance of new threats and types of violence, as well as new demands for security based on people (human security), our societies should focus on promoting peaceful changes. Through an extensive analysis of the existing literature and the study of several cases, this paper suggests that decentralized governance can contribute to these efforts by transforming conflicts, bringing about power-sharing and inclusion incentives of minority groups. Albeit the complexity of assessing its impact on conflict prevention, it can be contended that decentralized governance might have very positive effects on the reduction of causes that bring about conflicts due to its ability to foster the creation of war/violence preventors. More specifically, this paper argues that decentralization can have a positive impact on the so-called triggers and accelerators (short- and medium-term causes).

Production of full-length cDNA sequences by sequencing and analysis of expressed sequence tags from Schistosoma mansoni

The number of sequences generated by genome projects has increased exponentially, but gene characterization has not followed at the same rate. Sequencing and analysis of full-length cDNAs is an important step in gene characterization that has been used nowadays by several research groups. In this work, we have selected Schistosoma mansoni clones for full-length sequencing, using an algorithm that investigates the presence of the initial methionine in the parasite sequence based on the positions of alignment start between two sequences. BLAST searches to produce such alignments have been performed using parasite expressed sequence tags produced by Minas Gerais Genome Network against sequences from the database Eukaryotic Cluster of Orthologous Groups (KOG). This procedure has allowed the selection of clones representing 398 proteins which have not been deposited as S. mansoni complete CDS in any public database. Dedicated sequencing of 96 of such clones with reads from both 5' and 3' ends has been performed. These reads have been assembled using PHRAP, resulting in the production of 33 full-length sequences that represent novel S. mansoni proteins. These results shall contribute to construct a more complete view of the biology of this important parasite.

A Method and Tool to Support the Analysis and Enhance the Understanding of Peer-to-Peer Learning Experiences

In this paper we look at how a web-based social software can be used to make qualitative data analysis of online peer-to-peer learning experiences. Specifically, we propose to use Cohere, a web-based social sense-making tool, to observe, track, annotate and visualize discussion group activities in online courses. We define a specific methodology for data observation and structuring, and present results of the analysis of peer interactions conducted in discussion forum in a real case study of a P2PU course. Finally we discuss how network visualization and analysis can be used to gather a better understanding of the peer-to-peer learning experience. To do so, we provide preliminary insights on the social, dialogical and conceptual connections that have been generated within one online discussion group.

Using problem-based learning for introducing producer theory and market structure in intermediate microeconomics

This paper shows how instructors can use the problem‐based learning method to introduce producer theory and market structure in intermediate microeconomics courses. The paper proposes a framework where different decision problems are presented to students, who are asked to imagine that they are the managers of a firm who need to solve a problem in a particular business setting. In this setting, the instructors’ role isto provide both guidance to facilitate student learning and content knowledge on a just‐in‐time basis

Conditional compositional biplots: theory and application

The biplot has proved to be a powerful descriptive and analytical tool in many areasof applications of statistics. For compositional data the necessary theoreticaladaptation has been provided, with illustrative applications, by Aitchison (1990) andAitchison and Greenacre (2002). These papers were restricted to the interpretation ofsimple compositional data sets. In many situations the problem has to be described insome form of conditional modelling. For example, in a clinical trial where interest isin how patients’ steroid metabolite compositions may change as a result of differenttreatment regimes, interest is in relating the compositions after treatment to thecompositions before treatment and the nature of the treatments applied. To study thisthrough a biplot technique requires the development of some form of conditionalcompositional biplot. This is the purpose of this paper. We choose as a motivatingapplication an analysis of the 1992 US President ial Election, where interest may be inhow the three-part composition, the percentage division among the three candidates -Bush, Clinton and Perot - of the presidential vote in each state, depends on the ethniccomposition and on the urban-rural composition of the state. The methodology ofconditional compositional biplots is first developed and a detailed interpretation of the1992 US Presidential Election provided. We use a second application involving theconditional variability of tektite mineral compositions with respect to major oxidecompositions to demonstrate some hazards of simplistic interpretation of biplots.Finally we conjecture on further possible applications of conditional compositionalbiplots

Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method.

In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.

Parental altruism under imperfect information: Theory and evidence

Can we reconcile the predictions of the altruism model of the family withthe evidence on parental monetary transfers in the US? This paper providesa new assessment of this question. I expand the altruism model by introducingeffort of the child and by relaxing the assumption of perfect informationof the parent about the labor market opportunities of the child. First,I solve and simulate a model of altruism and labor supply under imperfectinformation. Second, I use cross-sectional data to test the following prediction of the model: Are parental transfers especially responsive tothe income variations of children who are very attached to the labor market? The results of the analysis suggest that imperfect informationaccounts for many of the patterns of intergenerational transfers in theUS.

Endogeneous matching in university-industry collaboration: Theory and empirical evidence from the UK

We develop a two-sided matching model to analyze collaboration between heterogeneousacademics and firms. We predict a positive assortative matching in terms of both scientificability and affinity for type of research, but negative assortative in terms of ability on one sideand affinity in the other. In addition, the most able and most applied academics and the mostable and most basic firms shall collaborate rather than stay independent. Our predictionsreceive strong support from the analysis of the teams of academics and firms that proposeresearch projects to the UK's Engineering and Physical Sciences Research Council.

Network governance and the domestic adoption of soft rules

European regulatory networks (ERNs) are in charge of producing and disseminating non-bindings standards, guidelines and recommendations in a number of important domains, such as banking and finance, electricity and gas, telecommunications, and competition regulation. The goal of these soft rules is to promote 'best practices', achieve co-ordination among regulatory authorities and ensure the consistent application of harmonized pro-competition rules across Europe. This contribution examines the domestic adoption of the soft rules developed within the four main ERNs. Different factors are expected to influence the process of domestic adoption: the resources of regulators; the existence of a review panel; and the interdependence of the issues at stake. The empirical analysis supports hypotheses about the relevance of network-level factors: monitoring and public reporting procedures increase the final level of adoption, while soft rules concerning highly interdependent policy areas are adopted earlier.

Artificially Intelligent and Adaptive Methods for Prediction and Analysis of Superheater Fireside Corrosion in Fluidized Bed Boilers

Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.

Thermodynamic stability of nanosized multicomponent bubbles/droplets: The square gradient theory and the capillary approach

Formation of nanosized droplets/bubbles from a metastable bulk phase is connected to many unresolved scientific questions. We analyze the properties and stability of multicomponent droplets and bubbles in the canonical ensemble, and compare with single-component systems. The bubbles/droplets are described on the mesoscopic level by square gradient theory. Furthermore, we compare the results to a capillary model which gives a macroscopic description. Remarkably, the solutions of the square gradient model, representing bubbles and droplets, are accurately reproduced by the capillary model except in the vicinity of the spinodals. The solutions of the square gradient model form closed loops, which shows the inherent symmetry and connected nature of bubbles and droplets. A thermodynamic stability analysis is carried out, where the second variation of the square gradient description is compared to the eigenvalues of the Hessian matrix in the capillary description. The analysis shows that it is impossible to stabilize arbitrarily small bubbles or droplets in closed systems and gives insight into metastable regions close to the minimum bubble/droplet radii. Despite the large difference in complexity, the square gradient and the capillary model predict the same finite threshold sizes and very similar stability limits for bubbles and droplets, both for single-component and two-component systems.

GPRS/EDGE Session Tracing and Analysis in Abis and AGPRS Interfaces

Efficient problem solving in cellular networks is important when enhancing the network performance and liability. Analysis of calls and packet switched sessions in protocol level between the network elements is an important part of this process. They can provide very detailed information about error situations which otherwise would be difficult to recognise. In this thesis we seek solutions for monitoring GPRS/EDGE sessions in two specific interfaces simultaneously in such manner that all information important to the users will be provided in easily understandable form. This thesis focuses on Abis and AGPRS interfaces of GSM radio network and introduces a solution for managing the correlation between these interfaces by using signalling messages and common parameters as linking elements. ~: Finally this thesis presents an implementation of GPRS/EDGE session monitoring application for Abis and AGPRS interfaces and evaluates its benefits to the end users. Application is implemented as a part of Windows based 3G/GSM network analyser.

Quality and analysis of administration processes in server operations

IT outsourcing refers to the way companies focus on their core competencies and buy the supporting functions from other companies specialized in that area. Service is the total outcome of numerous of activities by employees and other resources to provide solutions to customers' problems. Outsourcing and service business have their unique characteristics. Service Level Agreements quantify the minimum acceptable service to the user. The service quality has to be objectively quantified so that its achievement or non-achievement of it can be monitored. Usually offshoring refers to the transferring of tasks to low-cost nations. Offshoring presents a lot of challenges that require special attention and they need to be assessed thoroughly. IT Infrastructure management refers to installation and basic usability assistance of operating systems, network and server tools and utilities. ITIL defines the industry best practices for organizing IT processes. This thesis did an analysis of server operations service and the customers’ perception of the quality of daily operations. The agreed workflows and processes should be followed better. Service providers’ processes are thoroughly defined but both the customer and the service provider might disobey them. Service provider should review the workflows regarding customer functions. Customer facing functions require persistent skill development, as they communicate the quality to the customer. Service provider needs to provide better organized communication and knowledge exchange methods between the specialists in different geographical locations.

Network Structures and Modularity among Biofuel Heating System Manufacturers

The aim of this thesis was to study network structures and modularity among biofuel heating system manufacturers in the Finnish bioenergy sector by utilizing the perspectives of numerous Finnish bioenergy specialists. The study is qualitative due to the fact that the research material was gathered with semi-structured theme interviews during May and June 2010. The research methodology used in the thesis combines conceptual and action-oriented approach. Networks, value nets, and modularity were studied from different perspectives. Three network and platform strategies were discovered and a general network structure was formed. Moreover, benefits and disadvantages of networks and modularity among biofuel heating system manufacturers were illustrated. The analysis provides a comprehensive perception of the industry. The results of the research were constructed by implementing existing theories into practice. Also future recommendations for the biofuel heating system manufacturers were given. The results can be considered to be beneficial because the number of previous studies about the subject is relatively small. The reliability of the study is eminent because the number of the interviews was inclusive.

Design and Analysis of Forward Error Control Coding and Signaling for Guaranteeing QoS in Wireless Broadcast Systems

Broadcasting systems are networks where the transmission is received by several terminals. Generally broadcast receivers are passive devices in the network, meaning that they do not interact with the transmitter. Providing a certain Quality of Service (QoS) for the receivers in heterogeneous reception environment with no feedback is not an easy task. Forward error control coding can be used for protection against transmission errors to enhance the QoS for broadcast services. For good performance in terrestrial wireless networks, diversity should be utilized. The diversity is utilized by application of interleaving together with the forward error correction codes. In this dissertation the design and analysis of forward error control and control signalling for providing QoS in wireless broadcasting systems are studied. Control signaling is used in broadcasting networks to give the receiver necessary information on how to connect to the network itself and how to receive the services that are being transmitted. Usually control signalling is considered to be transmitted through a dedicated path in the systems. Therefore, the relationship of the signaling and service data paths should be considered early in the design phase. Modeling and simulations are used in the case studies of this dissertation to study this relationship. This dissertation begins with a survey on the broadcasting environment and mechanisms for providing QoS therein. Then case studies present analysis and design of such mechanisms in real systems. The mechanisms for providing QoS considering signaling and service data paths and their relationship at the DVB-H link layer are analyzed as the first case study. In particular the performance of different service data decoding mechanisms and optimal signaling transmission parameter selection are presented. The second case study investigates the design of signaling and service data paths for the more modern DVB-T2 physical layer. Furthermore, by comparing the performances of the signaling and service data paths by simulations, configuration guidelines for the DVB-T2 physical layer signaling are given. The presented guidelines can prove useful when configuring DVB-T2 transmission networks. Finally, recommendations for the design of data and signalling paths are given based on findings from the case studies. The requirements for the signaling design should be derived from the requirements for the main services. Generally, these requirements for signaling should be more demanding as the signaling is the enabler for service reception.