An integrated multi-agent framework for optimizing time, cost and environmental impact of construction processes

Environmentally conscious construction has received a significant amount of research attention during the last decades. Even though construction literature is rich in studies that emphasize the importance of environmental impact during the construction phase, most of the previous studies failed to combine environmental analysis with other project performance criteria in construction. This is mainly because most of the studies have overlooked the multi-objective nature of construction projects. In order to achieve environmentally conscious construction, multi-objectives and their relationships need to be successfully analyzed in the complex construction environment. The complex construction system is composed of changing project conditions that have an impact on the relationship between time, cost and environmental impact (TCEI) of construction operations. Yet, this impact is still unknown by construction professionals. Studying this impact is vital to fulfill multiple project objectives and achieve environmentally conscious construction. This research proposes an analytical framework to analyze the impact of changing project conditions on the relationship of TCEI. This study includes green house gas (GHG) emissions as an environmental impact category. The methodology utilizes multi-agent systems, multi-objective optimization, analytical network process, and system dynamics tools to study the relationships of TCEI and support decision-making under the influence of project conditions. Life cycle assessment (LCA) is applied to the evaluation of environmental impact in terms of GHG. The mixed method approach allowed for the collection and analysis of qualitative and quantitative data. Structured interviews of professionals in the highway construction field were conducted to gain their perspectives in decision-making under the influence of certain project conditions, while the quantitative data were collected from the Florida Department of Transportation (FDOT) for highway resurfacing projects. The data collected were used to test the framework. The framework yielded statistically significant results in simulating project conditions and optimizing TCEI. The results showed that the change in project conditions had a significant impact on the TCEI optimal solutions. The correlation between TCEI suggested that they affected each other positively, but in different strengths. The findings of the study will assist contractors to visualize the impact of their decision on the relationship of TCEI.

Systems of exchange values as tools for multi-agent organizations

This paper introduces systems of exchange values as tools for the organization of multi-agent systems. Systems of exchange values are defined on the basis of the theory of social exchanges, developed by Piaget and Homans. A model of social organization is proposed, where social relations are construed as social exchanges and exchange values are put into use in the support of the continuity of the performance of social exchanges. The dynamics of social organizations is formulated in terms of the regulation of exchanges of values, so that social equilibrium is connected to the continuity of the interactions. The concept of supervisor of social equilibrium is introduced as a centralized mechanism for solving the problem of the equilibrium of the organization The equilibrium supervisor solves such problem making use of a qualitative Markov Decision Process that uses numerical intervals for the representation of exchange values.

Multi-Agent Simulation and Management Practices

Intelligent agents offer a new and exciting way of understanding the world of work. Agent-Based Simulation (ABS), one way of using intelligent agents, carries great potential for progressing our understanding of management practices and how they link to retail performance. We have developed simulation models based on research by a multi-disciplinary team of economists, work psychologists and computer scientists. We will discuss our experiences of implementing these concepts working with a well-known retail department store. There is no doubt that management practices are linked to the performance of an organisation (Reynolds et al., 2005; Wall & Wood, 2005). Best practices have been developed, but when it comes down to the actual application of these guidelines considerable ambiguity remains regarding their effectiveness within particular contexts (Siebers et al., forthcoming a). Most Operational Research (OR) methods can only be used as analysis tools once management practices have been implemented. Often they are not very useful for giving answers to speculative ‘what-if’ questions, particularly when one is interested in the development of the system over time rather than just the state of the system at a certain point in time. Simulation can be used to analyse the operation of dynamic and stochastic systems. ABS is particularly useful when complex interactions between system entities exist, such as autonomous decision making or negotiation. In an ABS model the researcher explicitly describes the decision process of simulated actors at the micro level. Structures emerge at the macro level as a result of the actions of the agents and their interactions with other agents and the environment. We will show how ABS experiments can deal with testing and optimising management practices such as training, empowerment or teamwork. Hence, questions such as “will staff setting their own break times improve performance?” can be investigated.

Introduction to Multi-Agent Simulation

When designing systems that are complex, dynamic and stochastic in nature, simulation is generally recognised as one of the best design support technologies, and a valuable aid in the strategic and tactical decision making process. A simulation model consists of a set of rules that define how a system changes over time, given its current state. Unlike analytical models, a simulation model is not solved but is run and the changes of system states can be observed at any point in time. This provides an insight into system dynamics rather than just predicting the output of a system based on specific inputs. Simulation is not a decision making tool but a decision support tool, allowing better informed decisions to be made. Due to the complexity of the real world, a simulation model can only be an approximation of the target system. The essence of the art of simulation modelling is abstraction and simplification. Only those characteristics that are important for the study and analysis of the target system should be included in the simulation model. The purpose of simulation is either to better understand the operation of a target system, or to make predictions about a target system’s performance. It can be viewed as an artificial white-room which allows one to gain insight but also to test new theories and practices without disrupting the daily routine of the focal organisation. What you can expect to gain from a simulation study is very well summarised by FIRMA (2000). His idea is that if the theory that has been framed about the target system holds, and if this theory has been adequately translated into a computer model this would allow you to answer some of the following questions: · Which kind of behaviour can be expected under arbitrarily given parameter combinations and initial conditions? · Which kind of behaviour will a given target system display in the future? · Which state will the target system reach in the future? The required accuracy of the simulation model very much depends on the type of question one is trying to answer. In order to be able to respond to the first question the simulation model needs to be an explanatory model. This requires less data accuracy. In comparison, the simulation model required to answer the latter two questions has to be predictive in nature and therefore needs highly accurate input data to achieve credible outputs. These predictions involve showing trends, rather than giving precise and absolute predictions of the target system performance. The numerical results of a simulation experiment on their own are most often not very useful and need to be rigorously analysed with statistical methods. These results then need to be considered in the context of the real system and interpreted in a qualitative way to make meaningful recommendations or compile best practice guidelines. One needs a good working knowledge about the behaviour of the real system to be able to fully exploit the understanding gained from simulation experiments. The goal of this chapter is to brace the newcomer to the topic of what we think is a valuable asset to the toolset of analysts and decision makers. We will give you a summary of information we have gathered from the literature and of the experiences that we have made first hand during the last five years, whilst obtaining a better understanding of this exciting technology. We hope that this will help you to avoid some pitfalls that we have unwittingly encountered. Section 2 is an introduction to the different types of simulation used in Operational Research and Management Science with a clear focus on agent-based simulation. In Section 3 we outline the theoretical background of multi-agent systems and their elements to prepare you for Section 4 where we discuss how to develop a multi-agent simulation model. Section 5 outlines a simple example of a multi-agent system. Section 6 provides a collection of resources for further studies and finally in Section 7 we will conclude the chapter with a short summary.

Robust Adaptive Control with Applications to Multi-Agent Systems and Mobile Robotics

This thesis deals with robust adaptive control and its applications, and it is divided into three main parts. The first part is about the design of robust estimation algorithms based on recursive least squares. First, we present an estimator for the frequencies of biased multi-harmonic signals, and then an algorithm for distributed estimation of an unknown parameter over a network of adaptive agents. In the second part of this thesis, we consider a cooperative control problem over uncertain networks of linear systems and Kuramoto systems, in which the agents have to track the reference generated by a leader exosystem. Since the reference signal is not available to each network node, novel distributed observers are designed so as to reconstruct the reference signal locally for each agent, and therefore decentralizing the problem. In the third and final part of this thesis, we consider robust estimation tasks for mobile robotics applications. In particular, we first consider the problem of slip estimation for agricultural tracked vehicles. Then, we consider a search and rescue application in which we need to drive an unmanned aerial vehicle as close as possible to the unknown (and to be estimated) position of a victim, who is buried under the snow after an avalanche event. In this thesis, robustness is intended as an input-to-state stability property of the proposed identifiers (sometimes referred to as adaptive laws), with respect to additive disturbances, and relative to a steady-state trajectory that is associated with a correct estimation of the unknown parameter to be found.

Protocols for obtainment and isolation of two mesenchymal stem cell sources in sheep

PURPOSE: To evaluate different protocols to isolate stem cells from ovine umbilical cord blood and adipose tissue. METHODS: There were used 5 samples of umbilical blood and 5 samples of perirenal adipose tissue from 10 female sheep. All the samples were obtained through surgery, to harvest aseptic samples. There were used 3 protocols for obtainment and culture of umbilical cord blood stem cells and 4 protocols for ovine adipose tissue stem cells. RESULTS: It was possible to observe only one successful protocol for the obtainment of umbilical cord blood stem cells. When analyzing the techniques used to obtain adipose tissue stem cells, only one of the methods was effective as well. Through colony forming unit assay, there were obtained 58 colonies of cells after seven days in culture. Flow citometry tests revealed the cells were positive to CD44 and exhibited negative reaction to CD38, CD45, CD41/61. These cells showed a growth curve with very well defined phases LOG, LAG and PLATEAU. This phases are typically seem in mesenchymal stem cells growth curves. CONCLUSIONS: The isolation and culture of mesenchymal stem cells from ovine umbilical cord blood are complex and request more detailed assays. Stem cells from fat tissue sheep showed mesenchymal characteristics, according to their cell growth curve, ability to origin colonies of fibroblastoid cells and positive reactivity with the antibody CD44 by flow citometry.

Activation of Neural and Pluripotent Stem Cell Signatures Correlates with Increased Malignancy in Human Glioma

The presence of stem cell characteristics in glioma cells raises the possibility that mechanisms promoting the maintenance and self-renewal of tissue specific stem cells have a similar function in tumor cells. Here we characterized human gliomas of various malignancy grades for the expression of stem cell regulatory proteins. We show that cells in high grade glioma co-express an array of markers defining neural stem cells (NSCs) and that these proteins can fulfill similar functions in tumor cells as in NSCs. However, in contrast to NSCs glioma cells co-express neural proteins together with pluripotent stem cell markers, including the transcription factors Oct4, Sox2, Nanog and Klf4. In line with this finding, in high grade gliomas mesodermal-and endodermal-specific transcription factors were detected together with neural proteins, a combination of lineage markers not normally present in the central nervous system. Persistent presence of pluripotent stem cell traits could only be detected in solid tumors, and observations based on in vitro studies and xenograft transplantations in mice imply that this presence is dependent on the combined activity of intrinsic and extrinsic regulatory cues. Together these results demonstrate a general deregulated expression of neural and pluripotent stem cell traits in malignant human gliomas, and indicate that stem cell regulatory factors may provide significant targets for therapeutic strategies.

Integration and visualization of systems biology data in context of the genome

Background: High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results: The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions: Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment.

Molecular Characterization of Strains of Respiratory Syncytial Virus Identified in a Hematopoietic Stem Cell Transplant Outpatient Unit Over 2 Years: Community or Nosocomial Infection?

Respiratory syncytial virus (RSV) is recognized as the leading cause of nosocomial respiratory infection among hematopoietic stem cell transplant (HSCT) recipients, causing considerable morbidity and mortality. RSV is easily transmitted by contact with contaminated surfaces, and in HSCT units, more than 50% of RSV infections have been characterized as of nosocomial origin. From April 2001 to October 2002, RSV was identified by direct immunofluorescent assay in 42 symptomatic HSCT recipients. Seven RSV strains from 2001 and 12 RSV strains from 2002 were sequenced. RNA extraction, cDNA synthesis, and seminested polymerase chain reaction (PCR) with primers complementary to RSV genes G and F were pet-formed. PCR products were analyzed by nucleotide sequencing of the C-terminal region of gene G for typing (in group A or B). Of the 7 strains analyzed in 2001, only 2 belonged to group B; the other 5 belonged to group A. Of these 7 strains, 3 were identical and were from recipients receiving outpatient care. In 2002, of the 12 strains analyzed, 3 belonged to group A and the other 9 belonged to group B. Of these 9 strains, 7 were genetically identical and were also from recipients receiving outpatient care. Therefore, multiple strains of RSV cocirculated in the hematopoietic stem cell transplant units (ward and outpatient units) between 2001 and 2002. Nosocomial transmission was more likely to occur at the HSCT outpatient unit than in the HSCT ward. Infection control practices should also be implemented in the outpatient setting.

Mesenchymal Stem Cell Properties of Periodontal Ligament Cells From Deciduous and Permanent Teeth

Background: Human postnatal stem cells have been identified in periodontal ligaments (PDLs). In this study, the in vitro biologic properties of CD105(+) enriched cell subsets from PDLs harvested from deciduous (DePDL) and permanent (PePDL) teeth are comparatively assessed. Methods: PDL tissue was obtained from 12 teeth (six primary and six permanent) from which CD105(+) CD34(-) CD45(-) cells were isolated by magnetic cell sorting. To identify and quantitatively compare the stem cell markers, DePDL and PePDL cells were assessed for CD166 surface antigen expression by flow cytometry, real-time polymerase chain reaction, and immunostaining for Stro-1 and Oct-4, osteogenic and adipogenic differentiation, and proliferation rate by trypan blue method. Results: Magnetic cell sorting isolated cell populations containing 23.87% (+/- 11.98%) and 11.68% (+/- 6.27%) of CD105(+) expressing cells from PePDL and DePDL, respectively. Flow cytometric analysis demonstrated a higher proportion of CD105(+) cells coexpressing CD166 surface antigen in PePDL, whereas immunostaining and real-time polymerase chain reaction analysis demonstrated that both cell subsets expressed Stro-1 and Oct-4. DePDL-CD105(+) subsets were more proliferative compared to PePDL subsets, and both cell populations showed multipotential capabilities to differentiate in vitro to osteoblast/cementoblast- and adipocyte-like cells. However, a higher expression of adipogenic-related genes was observed in DePDL cells, whereas PePDL-CD105(+) cell subset presented a more homogeneous osteoblast/cementoblast response. Conclusion: These findings demonstrate that highly purified mesenchymal progenitor cell subsets can be obtained from the PDLs of both deciduous and permanent teeth, and further indicate phenotype dissimilarities that may have an impact on their clinical applications. J Periodontol 2010;81:1207-1215.

In vivo DNA electrotransfer

The use of electrotransfer for DNA delivery to prokaryotic cells, and eukaryotic cells in vitro, has been well known and widely used for many years. However, it is only recently that electric fields have been used to enhance DNA transfer to animal cells in vivo, and this is known as DNA electrotransfer or in vivo DNA electroporation. Some of the advantages of this method of somatic cell gene transfer are that it is a simple method that can be used to transfer almost any DNA construct to animal cells and tissues in vivo; multiple constructs can be co-transfected; it is equally applicable to dividing and nondividing cells; the DNA of interest does not need to be subeloned into a specific viral transfer vector and there is no need for the production of high titre viral stocks; and, as no viral genes are expressed there is less chance of an adverse immunologic reaction to vector sequences. The ease with which efficient in vivo gene transfer can be achieved with in vivo DNA electrotransfer is now allowing genetic analysis to be applied to a number of classic animal model systems where transgenic and embryonic stem cell techniques are not well developed, but for which a wealth of detailed descriptive embryological information is available, or surgical manipulation is much more feasible. As well as exciting applications in developmental biology, in vivo DNA electrotransfer is also being used to transfer genes to skeletal muscle and drive expression of therapeutically active proteins, and to examine exogenous gene and protein function in normal adult cells situated within the complex environment of a tissue and organ system in vivo. Thus, in effect providing the in vivo equivalent of the in vitro transient transfection assay. As the widespread use of in vivo electroporation has really only just begun, it is likely that the future will hold many more applications for this technology in basic research, biotechnology and clinical research areas.

A Pilot Randomized Trial Comparing CD-34Selected Versus Unmanipulated Hemopoietic Stem Cell Transplantation for Severe, Refractory Rheumatoid Arthritis

Objective. Evidence from animal studies, case reports, and phase I studies suggests that hemopoietic stem cell transplantation (HSCT) can be effective in the treatment of rheumatoid arthritis (RA). It is unclear, however, if depletion of T cells in the stem cell product infused after high-dose chemotherapy is beneficial in prolonging responses by reducing the number of infused autoreactive T cells. This pilot multicenter, randomized trial was undertaken to obtain feasibility data on whether CD34 selection (as a form of T cell depletion) of an autologous stem cell graft is of benefit in the HSCT procedure in patients with severe, refractory RA. Methods. Thirty-three patients with severe RA who had been treated unsuccessfully with methotrexate and at least 1 other disease-modifying agent were enrolled in the trial. The patients received high-dose immunosuppressive treatment with 200 mg/kg cyclophosphamide followed by an infusion of autologous stem cells that were CD34 selected or unmanipulated. Safety, efficacy (based on American College of Rheumatology [ACR] response criteria), and time to recurrence of disease were assessed on a monthly basis for up to 12 months. Results. All patients were living at the end of the study, with no major unexpected toxicities. Overall, on an intent-to-treat basis, ACR 20% response (ACR20) was achieved in 70% of the patients. An ACR70 response was attained in 27.7% of the 18 patients who had received CD34-selected cells and 53.3% of the 15 who had received unmanipulated cells (P = 0.20). The median time to disease recurrence was 147 days in the CD34-selected cell group and 201 days in the unmanipulated cell group (P = 0.28). There was no relationship between CD4 lymphopenia and response, but 72% of rheumatoid factor (RF)-positive patients had an increase in RF titer prior to recurrence of disease. Conclusion. HSCT can be performed safely in patients with RA, and initial results indicate significant responses in patients with severe, treatment-resistant disease. Similar outcomes were observed in patients undergoing HSCT with unmanipulated cells and those receiving CD34-selected cells. Larger studies are needed to confirm these findings.

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.

Multi-agent simulation of continental, regional, and micro electricity markets

Renewable based power generation has significantly increased over the last years. However, this process has evolved separately from electricity markets, leading to an inadequacy of the present market models to cope with huge quantities of renewable energy resources, and to take full advantage of the presently existing and the increasing envisaged renewable based and distributed energy resources. This paper proposes the modelling of electricity markets at several levels (continental, regional and micro), taking into account the specific characteristics of the players and resources involved in each level and ensuring that the proposed models accommodate adequate business models able to support the contribution of all the resources in the system, from the largest to the smaller ones. The proposed market models are integrated in MASCEM (Multi- Agent Simulator of Competitive Electricity Markets), using the multi agent approach advantages for overcoming the current inadequacy and significant limitations of the presently existing electricity market simulators to deal with the complex electricity market models that must be adopted.

A new approach for multi-agent coalition formation and management in the scope of electricity markets

This paper presents a new methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using the multi-agent market simulator MASCEM, taking advantage of its ability to provide the means to model and simulate VPP (Virtual Power Producers). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. The new features include the development of particular individual facilitators to manage the communications amongst the members of each coalition independently from the rest of the simulation, and also the mechanisms for the classification of the agents that are candidates to join the coalition. In addition, a global study on the results of the Iberian Electricity Market is performed, to compare and analyze different approaches for defining consistent and adequate strategies to integrate into the agents of MASCEM. This, combined with the application of learning and prediction techniques provide the agents with the ability to learn and adapt themselves, by adjusting their actions to the continued evolving states of the world they are playing in.