Teoría del caos y la complejidad en la representación de la relación estratégica comunitaria y marketing en los estados financieros

El presente trabajo tiene como finalidad caracterizar conceptos y elementos clave del caos y de la complejidad existente en la relación entre las organizaciones y la comunidad. Esta relación parte de la base de satisfacer las necesidades de los actores involucrados y, así mismo, mejorar el desempeño de cada uno, y contribuir al bienestar de la sociedad y a la perdurabilidad de las empresas. Para alcanzar el objetivo planteado, inicialmente se hace necesario contextualizar conceptos que estarán presentes durante todo el escrito. Por esto se expondrán términos como teoría de la complejidad, teoría del caos, los aspectos más representativos de la relación comunitaria y el marketing y su impacto en las comunidades. La teoría de la complejidad permitirá entender los sistemas como un todo, en donde las relaciones e interacciones de cada una de sus diferentes partes nos conducen a innumerables escenarios posibles. También se buscará entender la importancia de la relación organización-comunidad, ya que la comunidad puede jugar un papel determinante cuando las organizaciones se adaptan a los cambios. Es de suma importancia establecer relaciones estratégicas con la comunidad, entendiendo a la comunidad como un sistema o grupo social con determinadas características, que permitan tanto a las organizaciones como a la misma comunidad entender, comprender y satisfacer eficazmente las necesidades subyacentes y, así, llegar a establecer un entorno de retroalimentación continua y sostenibilidad a lo largo del tiempo. Actualmente, el funcionamiento del mundo ha cambiado en cierta medida, ya que antes la base del conocimiento se centraba en función del orden y la regularidad. Ahora, en cambio, se destaca la creatividad y la dinámica que son causadas por el desorden y la irregularidad presentes en los sistemas. El mundo se plantea como un grupo de innumerables sistemas auto-organizados, donde su funcionamiento puede provocar resultados impredecibles o aleatorios. La materia de complejidad en los sistemas se ha desarrollado por diferentes autores según aproximaciones desde diferentes ramas de la ciencia, como la cibernética, basada en los mecanismos de retroalimentación y control; desde la teoría general de los sistemas, que da énfasis en el dinamismo presente en los sistemas y cómo la organización está presente en su estructura. En el presente proyecto se realizará un estudio de tipo teórico-conceptual: se seleccionarán las bases de datos, fuentes de información y los documentos más representativos o que proporcionen la mayor información posible que permita el completo entendimiento de la investigación y de sus alcances propuestos. Es así que esta investigación busca aportar más elementos dentro de los diferentes estudios que pretenden explicar y mejorar la perdurabilidad de las empresas bajo las diferentes líneas de investigación. A través del tiempo, el GIPE ha ido evolucionando de acuerdo con los resultados de las investigaciones y se ha centrado en cuatro líneas de investigación: Liderazgo, Realidad, Estrategia y Gerencia. El proyecto de investigación “Relación de las organizaciones con el medio y marketing” hace parte de la línea de gerencia y busca identificar oportunidades gerenciales para las organizaciones que las acerquen al conocimiento y manejo de las áreas funcionales (Facultad de Administración, 2013). Además, el proyecto se adentra en las organizaciones en entornos complejos y su relación con la comunidad, y se observa así la organización como un ser vivo que contribuye al bienestar de la sociedad que, finalmente, es lo que garantiza su perdurabilidad.

Modelling, control and supervision for a class of hybrid systems

The aim of this thesis is to narrow the gap between two different control techniques: the continuous control and the discrete event control techniques DES. This gap can be reduced by the study of Hybrid systems, and by interpreting as Hybrid systems the majority of large-scale systems. In particular, when looking deeply into a process, it is often possible to identify interaction between discrete and continuous signals. Hybrid systems are systems that have both continuous, and discrete signals. Continuous signals are generally supposed continuous and differentiable in time, since discrete signals are neither continuous nor differentiable in time due to their abrupt changes in time. Continuous signals often represent the measure of natural physical magnitudes such as temperature, pressure etc. The discrete signals are normally artificial signals, operated by human artefacts as current, voltage, light etc. Typical processes modelled as Hybrid systems are production systems, chemical process, or continuos production when time and continuous measures interacts with the transport, and stock inventory system. Complex systems as manufacturing lines are hybrid in a global sense. They can be decomposed into several subsystems, and their links. Another motivation for the study of Hybrid systems is the tools developed by other research domains. These tools benefit from the use of temporal logic for the analysis of several properties of Hybrid systems model, and use it to design systems and controllers, which satisfies physical or imposed restrictions. This thesis is focused in particular types of systems with discrete and continuous signals in interaction. That can be modelled hard non-linealities, such as hysteresis, jumps in the state, limit cycles, etc. and their possible non-deterministic future behaviour expressed by an interpretable model description. The Hybrid systems treated in this work are systems with several discrete states, always less than thirty states (it can arrive to NP hard problem), and continuous dynamics evolving with expression: with Ki ¡ Rn constant vectors or matrices for X components vector. In several states the continuous evolution can be several of them Ki = 0. In this formulation, the mathematics can express Time invariant linear system. By the use of this expression for a local part, the combination of several local linear models is possible to represent non-linear systems. And with the interaction with discrete events of the system the model can compose non-linear Hybrid systems. Especially multistage processes with high continuous dynamics are well represented by the proposed methodology. Sate vectors with more than two components, as third order models or higher is well approximated by the proposed approximation. Flexible belt transmission, chemical reactions with initial start-up and mobile robots with important friction are several physical systems, which profits from the benefits of proposed methodology (accuracy). The motivation of this thesis is to obtain a solution that can control and drive the Hybrid systems from the origin or starting point to the goal. How to obtain this solution, and which is the best solution in terms of one cost function subject to the physical restrictions and control actions is analysed. Hybrid systems that have several possible states, different ways to drive the system to the goal and different continuous control signals are problems that motivate this research. The requirements of the system on which we work is: a model that can represent the behaviour of the non-linear systems, and that possibilities the prediction of possible future behaviour for the model, in order to apply an supervisor which decides the optimal and secure action to drive the system toward the goal. Specific problems can be determined by the use of this kind of hybrid models are: - The unity of order. - Control the system along a reachable path. - Control the system in a safe path. - Optimise the cost function. - Modularity of control The proposed model solves the specified problems in the switching models problem, the initial condition calculus and the unity of the order models. Continuous and discrete phenomena are represented in Linear hybrid models, defined with defined eighth-tuple parameters to model different types of hybrid phenomena. Applying a transformation over the state vector : for LTI system we obtain from a two-dimensional SS a single parameter, alpha, which still maintains the dynamical information. Combining this parameter with the system output, a complete description of the system is obtained in a form of a graph in polar representation. Using Tagaki-Sugeno type III is a fuzzy model which include linear time invariant LTI models for each local model, the fuzzyfication of different LTI local model gives as a result a non-linear time invariant model. In our case the output and the alpha measure govern the membership function. Hybrid systems control is a huge task, the processes need to be guided from the Starting point to the desired End point, passing a through of different specific states and points in the trajectory. The system can be structured in different levels of abstraction and the control in three layers for the Hybrid systems from planning the process to produce the actions, these are the planning, the process and control layer. In this case the algorithms will be applied to robotics ¡V a domain where improvements are well accepted ¡V it is expected to find a simple repetitive processes for which the extra effort in complexity can be compensated by some cost reductions. It may be also interesting to implement some control optimisation to processes such as fuel injection, DC-DC converters etc. In order to apply the RW theory of discrete event systems on a Hybrid system, we must abstract the continuous signals and to project the events generated for these signals, to obtain new sets of observable and controllable events. Ramadge & Wonham¡¦s theory along with the TCT software give a Controllable Sublanguage of the legal language generated for a Discrete Event System (DES). Continuous abstraction transforms predicates over continuous variables into controllable or uncontrollable events, and modifies the set of uncontrollable, controllable observable and unobservable events. Continuous signals produce into the system virtual events, when this crosses the bound limits. If this event is deterministic, they can be projected. It is necessary to determine the controllability of this event, in order to assign this to the corresponding set, , controllable, uncontrollable, observable and unobservable set of events. Find optimal trajectories in order to minimise some cost function is the goal of the modelling procedure. Mathematical model for the system allows the user to apply mathematical techniques over this expression. These possibilities are, to minimise a specific cost function, to obtain optimal controllers and to approximate a specific trajectory. The combination of the Dynamic Programming with Bellman Principle of optimality, give us the procedure to solve the minimum time trajectory for Hybrid systems. The problem is greater when there exists interaction between adjacent states. In Hybrid systems the problem is to determine the partial set points to be applied at the local models. Optimal controller can be implemented in each local model in order to assure the minimisation of the local costs. The solution of this problem needs to give us the trajectory to follow the system. Trajectory marked by a set of set points to force the system to passing over them. Several ways are possible to drive the system from the Starting point Xi to the End point Xf. Different ways are interesting in: dynamic sense, minimum states, approximation at set points, etc. These ways need to be safe and viable and RchW. And only one of them must to be applied, normally the best, which minimises the proposed cost function. A Reachable Way, this means the controllable way and safe, will be evaluated in order to obtain which one minimises the cost function. Contribution of this work is a complete framework to work with the majority Hybrid systems, the procedures to model, control and supervise are defined and explained and its use is demonstrated. Also explained is the procedure to model the systems to be analysed for automatic verification. Great improvements were obtained by using this methodology in comparison to using other piecewise linear approximations. It is demonstrated in particular cases this methodology can provide best approximation. The most important contribution of this work, is the Alpha approximation for non-linear systems with high dynamics While this kind of process is not typical, but in this case the Alpha approximation is the best linear approximation to use, and give a compact representation.

Implementação de um CRM analítico na Fundação INATEL

As soluções informáticas de Customer Relationship Management (CRM) e os sistemas de suporte à informação, designados por Business Intelligence (BI), permitem a recolha de dados e a sua transformação em informação e em conhecimento, vital para diferenciação das organizações num Mundo globalizado e em constante mudança. A construção de um Data Warehouse corporativo é fundamental para as organizações que utilizam vários sistemas operacionais de modo a ser possível a agregação da informação. A Fundação INATEL – uma fundação privada de interesse público, 100% estatal – é um exemplo deste tipo de organização. Com uma base de dados de clientes superior a 250.000, atuando em áreas tão diferentes como sejam o Turismo, a Cultura e o Desporto, sustentado em mais de 25 sistemas informáticos autónomos. A base de estudo deste trabalho é a procura de identificação dos benefícios da implementação de um CRM Analítico na Fundação INATEL. Apresentando-se assim uma metodologia para a respetiva implementação e sugestão de um modelo de dados para a obtenção de uma visão única do cliente, acessível a toda a organização, de modo a garantir a total satisfação e consequente fidelização à marca INATEL. A disponibilização desta informação irá proporcionar um posicionamento privilegiado da Fundação INATEL e terá um papel fundamental na sua sustentabilidade económica.

Chemical composition observed over the mid-Atlantic and the detection of pollution signatures far from source regions

The atmospheric composition of the central North Atlantic region has been sampled using the FAAM BAe146 instrumented aircraft during the Intercontinental Transport of Ozone and Precursors (ITOP) campaign, part of the wider International Consortium for Atmospheric Research on Transport and Transformation (ICARTT). This paper presents an overview of the ITOP campaign. Between late July and early August 2004, twelve flights comprising 72 hours of measurement were made in a region from approximately 20 to 40°W and 33 to 47°N centered on Faial Island, Azores, ranging in altitude from 50 to 9000 m. The vertical profiles of O3 and CO are consistent with previous observations made in this region during 1997 and our knowledge of the seasonal cycles within the region. A cluster analysis technique is used to partition the data set into air mass types with distinct chemical signatures. Six clusters provide a suitable balance between cluster generality and specificity. The clusters are labeled as biomass burning, low level outflow, upper level outflow, moist lower troposphere, marine and upper troposphere. During this summer, boreal forest fire emissions from Alaska and northern Canada were found to provide a major perturbation of tropospheric composition in CO, PAN, organic compounds and aerosol. Anthropogenic influenced air from the continental boundary layer of the USA was clearly observed running above the marine boundary layer right across the mid-Atlantic, retaining high pollution levels in VOCs and sulfate aerosol. Upper level outflow events were found to have far lower sulfate aerosol, resulting from washout on ascent, but much higher PAN associated with the colder temperatures. Lagrangian links with flights of other aircraft over the USA and Europe show that such signatures are maintained many days downwind of emission regions. Some other features of the data set are highlighted, including the strong perturbations to many VOCs and OVOCs in this remote region.

Alkyl nitrates in outflow from North America over the North Atlantic during Intercontinental Transport of Ozone and Precursors 2004

This paper is based on alkyl nitrate measurements made over the North Atlantic as part of the International Consortium for Research on Atmospheric Transport and Transformation (ICARTT). The focus is on the analysis of air samples collected on the UK BAe-146 aircraft during the Intercontinental Transport of Ozone and Precursors (ITOP) project, but air samples collected on board the NASA DC-8 and NOAA WP-3D aircraft as part of a Lagrangian experiment are also used. The ratios between the alkyl nitrates and their parent hydrocarbons are compared with those expected from chemical theory. Further, a box model is run to investigate the temporal evolution of the alkyl nitrates in three Lagrangian case studies and compared to observations. The air samples collected during ITOP do not appear to be strongly influenced by oceanic sources, but rather are influenced by emissions from the N.E. United States and from Alaskan fires. There also appears to be a widespread common source of ethyl nitrate and 1-propyl nitrate other than from their parent hydrocarbons. The general agreement between the alkyl nitrate data and photochemical theory suggests that during the first few days of transport from the source region, photochemical production of alkyl nitrates, and thus ozone, had taken place. The observations in the more photochemically processed air masses are consistent with the alkyl nitrate production reactions no longer dominating the peroxy radical self/cross reactions. Further, the results also suggest that the rates of photochemical processing in the Alaskan smoke plumes were small.

Forest fire plumes over the North Atlantic: p-TOMCAT model simulations with aircraft and satellite measurements from the ITOP/ICARTT campaign

Intercontinental Transport of Ozone and Precursors (ITOP) (part of International Consortium for Atmospheric Research on Transport and Transformation (ICARTT)) was an intense research effort to measure long-range transport of pollution across the North Atlantic and its impact on O3 production. During the aircraft campaign plumes were encountered containing large concentrations of CO plus other tracers and aerosols from forest fires in Alaska and Canada. A chemical transport model, p-TOMCAT, and new biomass burning emissions inventories are used to study the emissions long-range transport and their impact on the troposphere O3 budget. The fire plume structure is modeled well over long distances until it encounters convection over Europe. The CO values within the simulated plumes closely match aircraft measurements near North America and over the Atlantic and have good agreement with MOPITT CO data. O3 and NOx values were initially too great in the model plumes. However, by including additional vertical mixing of O3 above the fires, and using a lower NO2/CO emission ratio (0.008) for boreal fires, O3 concentrations are reduced closer to aircraft measurements, with NO2 closer to SCIAMACHY data. Too little PAN is produced within the simulated plumes, and our VOC scheme's simplicity may be another reason for O3 and NOx model-data discrepancies. In the p-TOMCAT simulations the fire emissions lead to increased tropospheric O3 over North America, the north Atlantic and western Europe from photochemical production and transport. The increased O3 over the Northern Hemisphere in the simulations reaches a peak in July 2004 in the range 2.0 to 6.2 Tg over a baseline of about 150 Tg.

Stages of organizational transformation in transition economies: A dynamic capabilities approach

How do organizations previously dominated by the state develop dynamic capabilities that would support their growth in a competitive market economy? We develop a theoretical framework of organizational transformation that explains the processes by which organizations learn and develop dynamic capabilities in transition economies. Specifically, the framework theorizes about the importance of, and inter-relationships between, leadership, organizational learning, dynamic capabilities, and performance over three stages of transformation. Propositions derived from this framework explain the pre-conditions enabling organizational learning, the linkages between types of learning and functions of dynamic capabilities, and the feedback from dynamic capabilities to organizational learning that allows firms in transition economies to regain their footing and build long-term competitive advantage. We focus on transition contexts, where these processes have been magnified and thus offer new insights into strategizing in radically altered environments.

Bacterial evolution by genomic island transfer occurs via DNA transformation in planta

Our understanding of the evolution of microbial pathogens has been advanced by the discovery of "islands" of DNA that differ from core genomes and contain determinants of virulence [1, 2]. The acquisition of genomic islands (GIs) by horizontal gene transfer (HGT) is thought to have played a major role in microbial evolution. There are, however, few practical demonstrations of the acquisition of genes that control virulence, and, significantly, all have been achieved outside the animal or plant host. Loss of a GI from the bean pathogen Pseudomonas syringae pv. phaseolicola (Pph) is driven by exposure to the stress imposed by the plant's resistance response [3]. Here, we show that the complete episomal island, which carries pathogenicity genes including the effector avrPphB, transfers between strains of Pph by transformation in planta and inserts at a specific att site in the genome of the recipient. Our results show that the evolution of bacterial pathogens by HGT may be achieved via transformation, the simplest mechanism of DNA exchange. This process is activated by exposure to plant defenses, when the pathogen is in greatest need of acquiring new genetic traits to alleviate the antimicrobial stress imposed by plant innate immunity [4].

Review: intellectual property aspects of plant transformation

One of the recurring themes of the debates concerning the application of genetic transformation technology has been the role of Intellectual Property Rights (IPR). This term covers both the content of patents and the confidential expertise usually related to methodology and referred to as 'Trade Secrets'. This review explains the concepts behind patent protection, and discusses the wide-ranging scope of existing patents that cover all aspects of transgenic technology, from selectable markers and novel promoters to methods of gene introduction. Although few of the patents in this area have any real commercial value, there are a small number of key patents that restrict the 'freedom to operate' of new companies seeking to exploit the methods. Over the last 20 years, these restrictions have forced extensive cross-licensing between ag-biotech companies and have been one of the driving forces behind the consolidation of these companies. Although such issues are often considered of little interest to the academic scientist working in the public sector, they are of great importance in any discussion of the role of 'public-good breeding' and of the relationship between the public and private sectors.

Bayesian retrieval of complete posterior PDFs of oceanic rain rate from microwave observations

A new Bayesian algorithm for retrieving surface rain rate from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) over the ocean is presented, along with validations against estimates from the TRMM Precipitation Radar (PR). The Bayesian approach offers a rigorous basis for optimally combining multichannel observations with prior knowledge. While other rain-rate algorithms have been published that are based at least partly on Bayesian reasoning, this is believed to be the first self-contained algorithm that fully exploits Bayes’s theorem to yield not just a single rain rate, but rather a continuous posterior probability distribution of rain rate. To advance the understanding of theoretical benefits of the Bayesian approach, sensitivity analyses have been conducted based on two synthetic datasets for which the “true” conditional and prior distribution are known. Results demonstrate that even when the prior and conditional likelihoods are specified perfectly, biased retrievals may occur at high rain rates. This bias is not the result of a defect of the Bayesian formalism, but rather represents the expected outcome when the physical constraint imposed by the radiometric observations is weak owing to saturation effects. It is also suggested that both the choice of the estimators and the prior information are crucial to the retrieval. In addition, the performance of the Bayesian algorithm herein is found to be comparable to that of other benchmark algorithms in real-world applications, while having the additional advantage of providing a complete continuous posterior probability distribution of surface rain rate.

Complete robot-eye calibration without special calibration objects

A robot mounted camera is useful in many machine vision tasks as it allows control over view direction and position. In this paper we report a technique for calibrating both the robot and the camera using only a single corresponding point. All existing head-eye calibration systems we have encountered rely on using pre-calibrated robots, pre- calibrated cameras, special calibration objects or combinations of these. Our method avoids using large scale non-linear optimizations by recovering the parameters in small dependent groups. This is done by performing a series of planned, but initially uncalibrated robot movements. Many of the kinematic parameters are obtained using only camera views in which the calibration feature is at, or near the image center, thus avoiding errors which could be introduced by lens distortion. The calibration is shown to be both stable and accurate. The robotic system we use consists of camera with pan-tilt capability mounted on a Cartesian robot, providing a total of 5 degrees of freedom.

Plastic films for polytunnels can prolong the effective residual life of cypermethrin to over 6 months

Synthetic pyrethroid insecticides are degraded almost entirely by ultraviolet (UV)-catalysed oxidation. A bioassay using the beetle Tribolium confusum duVal caged on bandages soaked in 0.04% a.i. cypermethrin showed large differences in residual insecticide-life under three plastic films available for cladding polytunnels. Cypermethrin exposed to a UV film that transmitted 70% of UVB and 80% of UVA killed all beetles for 8 weeks, compared to only 3 weeks for cypermethrin exposed in a clear plastic envelope. Cypermethrin under a UV-absorbing film that reduced the transmission of UVB and UVA to 14% and 50%, respectively, gave a complete kill for 17 weeks. Reducing the transmission of UVB to virtually zero, and that of UVA to only 3%, using a UV-opaque film prolonged the effective life of the cypermethrin residue to 26 weeks, and some beetles were still killed for a further 11 weeks. Even after this time, beetles exposed to cypermethrin from the UV-opaque treatment were still affected by the insecticide, and only showed near-normal mobility after 24 months of pesticide exposure to the UV-opaque film. These results have implications for the recommended intervals between cypermethrin treatment and crop harvest, and on the time of introduction of insect-based biological control agents, when UV-opaque films are used in commercial horticulture.

Chemical ageing and transformation of diffusivity in semi-solid multi-component organic aerosol particles

Recent experimental evidence underlines the importance of reduced diffusivity in amorphous semi-solid or glassy atmospheric aerosols. This paper investigates the impact of diffusivity on the ageing of multi-component reactive organic particles representative of atmospheric cooking aerosols. We apply and extend the recently developed KM-SUB model in a study of a 12-component mixture containing oleic and palmitoleic acids. We demonstrate that changes in the diffusivity may explain the evolution of chemical loss rates in ageing semi-solid particles, and we resolve surface and bulk processes under transient reaction conditions considering diffusivities altered by oligomerisation. This new model treatment allows prediction of the ageing of mixed organic multi-component aerosols over atmospherically relevant time scales and conditions. We illustrate the impact of changing diffusivity on the chemical half-life of reactive components in semisolid particles, and we demonstrate how solidification and crust formation at the particle surface can affect the chemical transformation of organic aerosols.

Chemical ageing and transformation of diffusivity in semi-solid multi-component organic aerosol particles

Recent experimental evidence underlines the importance of reduced diffusivity in amorphous semi-solid or glassy atmospheric aerosols. This paper investigates the impact of diffusivity on the ageing of multi-component reactive organic particles approximating atmospheric cooking aerosols. We apply and extend the recently developed KMSUB model in a study of a 12-component mixture containing oleic and palmitoleic acids. We demonstrate that changes in the diffusivity may explain the evolution of chemical loss rates in ageing semi-solid particles, and we resolve surface and bulk processes under transient reaction conditions considering diffusivities altered by oligomerisation. This new model treatment allows prediction of the ageing of mixed organic multi-component aerosols over atmospherically relevant timescales and conditions. We illustrate the impact of changing diffusivity on the chemical half-life of reactive components in semi-solid particles, and we demonstrate how solidification and crust formation at the particle surface can affect the chemical transformation of organic aerosols.

Three dimensional picture of the local structure of 1,4-Polybutadiene from a complete atomistic model and neutron scattering data

An efficient method of combining neutron diffraction data over an extended Q range with detailed atomistic models is presented. A quantitative and qualitative mapping of the organization of the chain conformation in both glass and liquid phase has been performed. The proposed structural refinement method is based on the exploitation of the intrachain features of the diffraction pattern by the use of internal coordinates for bond lengths, valence angles and torsion rotations. Models are built stochastically by assignment of these internal coordinates from probability distributions with limited variable parameters. Variation of these parameters is used in the construction of models that minimize the differences between the observed and calculated structure factors. A series of neutron scattering data of 1,4-polybutadiene at the region 20320 K is presented. Analysis of the experimental data yield bond lengths for C-C and C=C of 1.54 and 1.35 Å respectively. Valence angles of the backbone were found to be at 112 and 122.8 for the CCC and CC=C respectively. Three torsion angles corresponding to the double bond and the adjacent R and β bonds were found to occupy cis and trans, s(, trans and g( and trans states, respectively. We compare our results with theoretical predictions, computer simulations, RIS models, and previously reported experimental results.