A complexity-based diagnostic on the democratic unity roundtable mud: problems and alternatives (2008-2016)

Este trabajo exploratorio estudia al movimiento pol��tico Mesa de la Unidad Democr��tica (MUD), creada con el fin de oponerse la Gobierno socialista existente en venezuela. La cr��tica que este documento realiza, parte desde el punto de vista de la Ciencia de la Complejidad. Algunos conceptos clave de sistemas complejos han sido utilizados para explicar el funcionamiento y organizaci��n de la MUD, esto con el objetivo de generar un diagn��stico integral de los problemas que enfrenta, y evidenciar las nuevas percepciones sobre comportamientos perjudiciales que el partido tiene actualmente. Con el enfoque de la complejidad se pretende ayudar a comprender mejor el contexto que enmarca al partido y, para, finalmente aportar una serie de soluciones a los problemas de cohesi��n que presen

La construcci��n de sentido (���sensemaking���) de un entorno estrat��gico turbulento por parte de los altos directivos: un estudio en una multinacional automotriz

Este art��culo presenta los resultados de una investigaci��n realizada al interior de dos contextos. Por un lado, el te��rico, en el marco de uno de los discursos m��s relevantes en los campos de la estrategia organizacional, de la managerial and organizational cognition (MOC) y, en general, de los estudios organizacionales (organization studies): la construcci��n de sentido (sensemaking). Por el otro, el emp��rico, en una de las grandes compa����as multinacionales del sector automotriz con presencia global. Esta corporaci��n enfrenta una permanente tensi��n entre lo que dicta la casa matriz, en relaci��n con el cumplimiento de metas y est��ndares espec��ficos, considerando el mundo entero, y los retos que, teniendo en cuenta lo regional y lo local, experimentan los altos directivos encargados de hacer prosperar la empresa en estos lugares. La aproximaci��n implementada fue cualitativa. Esto en atenci��n a la naturaleza de la problem��tica abordada y la tradici��n del campo. Los resultados permiten ampliar el actual nivel de comprensi��n acerca de los procesos de sensemaking de los altos directivos al enfrentar un entorno estrat��gico turbulento.

The Rational for Auto Vaccines in Poultry Colibacillosis

Colibacillosis is a rather important economic problem for poultry production, associated to Avian Pathogenic Escherichia coli (APEC) strains, which may cause several extraintestinal pathologies, such as airsacculitis and cellulitis in broiler chickens, and salpingitis and peritonitis in broiler breeders, leading to septicemic mortality. Control of morbidity and mortality in the outbrakes of colibacillosis may be performed with antibiotics and/or by vaccination. The use antibiotics is frequently inef - fective as Escherichia coli ( E. coli ) is considered the largest reservoir of antimicrobial resistance, characteristic that may even transmit to other bacteria, turning the situation into a serious problem of public health. Vaccination may be the alternative solution but as many different strains arise, flock-specific autovaccines seem to be needed under several possible protocols, with live attenuated and/or inactivated vaccines from different strains that should be identified and characterized according to their virulence factors, within different flocks.

Are Decision Makers Rational in Ambiguous Situations?

This research work analyzes human behavior in complex situations and explains how decisions makers act in ambiguous situations. The objective of this research work is to study the sunk cost effect and the completion percentage effect of an investment project in a decision-making process. This research work uses a ���retrospective rationality��� approach to justify irrational behaviors such as the sunk cost effect, the completion percentage effect of an investment project and the irrational escalation since decision-makers are repeatedly affected by the decisions on past irreversible investments. This research work evaluates three sunk cost levels, and three completion percentage levels of an investment project, besides three neutral situations in a business environment and a personal decision situation. Graduate students in three Portuguese Management Schools responded to the questionnaires. Model results show that the value of resources invested is crucial for understanding the students��� rational behavior, who participated in this research work. These results disclose statistical evidence that the information on sunk costs and completion percentage of an investment project determines human behavior under irrational escalation in ambiguous situations. As a consequence, decision makers have the opportunity to interpret their decisions, since the scenarios do not allow a unique definition of rational choice, it is not correct to judge the irrational decision makers that decide to continue to invest in ambiguous situations. Keywords: Human Behavior, Sunk costs Effect, Completion Percentage Effect of an Investment Project, Irrational Escalation, Ambiguous Situations.

Fractal descriptors for quantifying brain complexity in MRI

Magnetic Resonance Imaging (MRI) is the in vivo technique most commonly employed to characterize changes in brain structures. The conventional MRI-derived morphological indices are able to capture only partial aspects of brain structural complexity. Fractal geometry and its most popular index, the fractal dimension (FD), can characterize self-similar structures including grey matter (GM) and white matter (WM). Previous literature shows the need for a definition of the so-called fractal scaling window, within which each structure manifests self-similarity. This justifies the existence of fractal properties and confirms Mandelbrot���s assertion that "fractals are not a panacea; they are not everywhere". In this work, we propose a new approach to automatically determine the fractal scaling window, computing two new fractal descriptors, i.e., the minimal and maximal fractal scales (mfs and Mfs). Our method was implemented in a software package, validated on phantoms and applied on large datasets of structural MR images. We demonstrated that the FD is a useful marker of morphological complexity changes that occurred during brain development and aging and, using ultra-high magnetic field (7T) examinations, we showed that the cerebral GM has fractal properties also below the spatial scale of 1 mm. We applied our methodology in two neurological diseases. We observed the reduction of the brain structural complexity in SCA2 patients and, using a machine learning approach, proved that the cerebral WM FD is a consistent feature in predicting cognitive decline in patients with small vessel disease and mild cognitive impairment. Finally, we showed that the FD of the WM skeletons derived from diffusion MRI provides complementary information to those obtained from the FD of the WM general structure in T1-weighted images. In conclusion, the fractal descriptors of structural brain complexity are candidate biomarkers to detect subtle morphological changes during development, aging and in neurological diseases.

Peptidomimetic ligands for tuning integrin-mediated signalling: rational design, synthesis and theranostic applications

Integrins are ��/��-heterodimeric transmembrane adhesion receptors that mediate cell-cell and cell-ECM interactions. Integrins are bidirectional signalling receptors that respond to external signals (���outside-in��� signalling) and in parallel, transduce internal signals to the matrix (���inside-out��� signalling), to regulate vital cellular functions including migration, survival, growth and differentiation. Therefore, dysregulation of these tightly regulated processes often results in uncontrolled integrin activation and abnormal tissue expression that is responsible for many diseases. Because of their important roles in physiological and pathological events, they represent a validated target for therapeutic and diagnostic purposes. The aim of the present Thesis was focused on the development of peptidic ligands for ��4��1 and ��v��3 integrin subtypes, involved in inflammatory responses (leukocytes recruitment and extravasation) and cancer progression (angiogenesis, tumor growth, metastasis), respectively. Following the peptidomimetic strategy, we designed and synthesized a small library of linear and cyclic hybrid ��/��-peptidomimetics based on the phenylureido-LDV scaffolds for the treatment of chronic inflammatory autoimmune diseases. In order to implement a fast and non-invasive diagnostic method for monitoring the course of the inflammatory processes, a flat glass-surface of dye-loaded Zeolite L-crystal nanoparticles was coated with bioactive ��4��1-peptidomimetics to detect specific integrin-expressing cells as biomarkers of inflammatory diseases. Targeted drug delivery has been considered a promising alternative to overcome the pharmacokinetic limitations of conventional anticancer drugs. Thus, a novel Small-Molecule Drug Conjugate was synthesized by connecting the highly cytotoxic Cryptophycin to the tumor-targeting RGDfK-peptide through a protease-cleavable linker. Finally, in view to making the peptide synthesis more sustainable and greener, we developed an alternative method for peptide bonds formation employing solvent-free mechanochemistry and ultra-mild minimal solvent-grinding conditions in common, inexpensive laboratory equipment. To this purpose, standard amino acids, coupling agents and organic-green solvents were used in the presence of nanocrystalline hydroxyapatite as a reusable, bio-compatible inorganic basic catalyst.

A take on complexity: bio-molecules and human metabolism interaction modelling for health and nutrition with machine learning

The advent of omic data production has opened many new perspectives in the quest for modelling complexity in biophysical systems. With the capability of characterizing a complex organism through the patterns of its molecular states, observed at different levels through various omics, a new paradigm of investigation is arising. In this thesis, we investigate the links between perturbations of the human organism, described as the ensemble of crosstalk of its molecular states, and health. Machine learning plays a key role within this picture, both in omic data analysis and model building. We propose and discuss different frameworks developed by the author using machine learning for data reduction, integration, projection on latent features, pattern analysis, classification and clustering of omic data, with a focus on 1H NMR metabolomic spectral data. The aim is to link different levels of omic observations of molecular states, from nanoscale to macroscale, to study perturbations such as diseases and diet interpreted as changes in molecular patterns. The first part of this work focuses on the fingerprinting of diseases, linking cellular and systemic metabolomics with genomic to asses and predict the downstream of perturbations all the way down to the enzymatic network. The second part is a set of frameworks and models, developed with 1H NMR metabolomic at its core, to study the exposure of the human organism to diet and food intake in its full complexity, from epidemiological data analysis to molecular characterization of food structure.

Harnessing the cellular and molecular complexity of high-risk neuroblastoma to investigate novel potential treatment approaches

Neuroblastoma (NB) is the most common type of tumor in infants and the third most common cancer in children. Current clinical practices employ a variety of strategies for NB treatment, ranging from standard chemotherapy to immunotherapy. Due to a lack of knowledge about the molecular mechanisms underlying the disease's onset, aggressive phenotype, and therapeutic resistance, these approaches are ineffective in the majority of instances. MYCN amplification is one of the most well-known genetic alterations associated with high risk in NB. The following work is divided into three sections and aims to provide new insights into the biology of NB and hypothetical new treatment strategies. First, we identified RUNX1T1 as a key gene involved in MYCN-driven NB onset in a transgenic mouse model. Our results suggested that that RUNX1T1 may recruit the Co-REST complex on target genes that regulate the differentiation of NB cells and that the interaction with RCOR3 is essential. Second, we provided insights into the role of MYCN in dysregulating the CDK/RB/E2F pathway controlling the G1/S transition of the cell cycle. We found that RB is dispensable in regulating MYCN amplified NB's cell cycle, providing the rationale for using cyclin/CDK complexes inhibitors in NBs carrying MYCN amplification and relatively high levels of RB1 expression. Third, we generated an M13 bacteriophage platform to target GD2-expressing cells in NB. Here, we generated a recombinant M13 phage capable of binding GD2-expressing cells selectively (M13GD2). Our results showed that M13GD2 chemically conjugated with the photosensitizer ECB04 preserves the retargeting capability, inducing cell death even at picomolar concentrations upon light irradiation. These results provided proof of concept for M13 phage employment in targeted photodynamic therapy for NB, an exciting strategy to overcome resistance to classical immunotherapy.

Low-molecular-weight gels: from the rational design to the application of versatile soft materials

Low-molecular-weight (LMW) gels are a versatile class of soft materials that gained increasing interest over the last few decades. They are made of a small percentage, often lower than 1.0 %, of organic molecules called gelators, dispersed in a liquid medium. Such molecules have a molecular weight usually lower than 1 kDa. The gelator molecules start to interact after the addition of a trigger, and form fibres, whose entanglement traps the solvent through capillary forces. A plethora of LMW gelators have been designed, including short peptides. Such gelators present several advantages: the synthesis is easy and can be easily scaled up; they are usually biocompatible and biodegradable; the gelation phenomenon can be rationalised by making small variation on the peptide scaffold; they find application in several fields. In this thesis, an overview of several peptide based LMW gels is presented. In each study, the gelation conditions were carefully studied, and the final materials were thoroughly investigated. First, the gelation ability of a fluorinated phenylalanine was assessed, to understand how the presence of a rigid moiety and the presence of fluorine may influence the gelation. In this context, a method for the dissolution of sensitive gelators was studied. Then, the control over the gel formation was studied both over time and space, taking advantage of either the pH-annealing of the gel or the reaction-diffusion of a hydrolysing reagent. Some gels were probed for various applications. Due to their ability of trapping water and organic solvents, we used gels for trapping pollutants dissolved in water, as well as a medium for the controlled release of either fragrances or bioactive compounds. Finally, the interaction of the gel matrix with a light-responsive molecule was assessed to understand wether the gel properties or the interaction of the additive with light were affected.

Characterization of ENSO changes under idealised radiative forcing in an intermediate complexity general circulation model

Intermediate-complexity general circulation models are a fundamental tool to investigate the role of internal and external variability within the general circulation of the atmosphere and ocean. The model used in this thesis is an intermediate complexity atmospheric general circulation model (SPEEDY) coupled to a state-of-the-art modelling framework for the ocean (NEMO). We assess to which extent the model allows a realistic simulation of the most prominent natural mode of variability at interannual time scales: El-Ni��o Southern Oscillation (ENSO). To a good approximation, the model represents the ENSO-induced Sea Surface Temperature (SST) pattern in the equatorial Pacific, despite a cold tongue-like bias. The model underestimates (overestimates) the typical ENSO spatial variability during the winter (summer) seasons. The mid-latitude response to ENSO reveals that the typical poleward stationary Rossby wave train is reasonably well represented. The spectral decomposition of ENSO features a spectrum that lacks periodicity at high frequencies and is overly periodic at interannual timescales. We then implemented an idealised transient mean state change in the SPEEDY model. A warmer climate is simulated by an alteration of the parametrized radiative fluxes that corresponds to doubled carbon dioxide absorptivity. Results indicate that the globally averaged surface air temperature increases of 0.76 K. Regionally, the induced signal on the SST field features a significant warming over the central-western Pacific and an El-Ni��o-like warming in the subtropics. In general, the model features a weakening of the tropical Walker circulation and a poleward expansion of the local Hadley cell. This response is also detected in a poleward rearrangement of the tropical convective rainfall pattern. The model setting that has been here implemented provides a valid theoretical support for future studies on climate sensitivity and forced modes of variability under mean state changes.

Rational algorithms for the decomposition of Feynman integrals via intersection theory

The decomposition of Feynman integrals into a basis of independent master integrals is an essential ingredient of high-precision theoretical predictions, that often represents a major bottleneck when processes with a high number of loops and legs are involved. In this thesis we present a new algorithm for the decomposition of Feynman integrals into master integrals with the formalism of intersection theory. Intersection theory is a novel approach that allows to decompose Feynman integrals into master integrals via projections, based on a scalar product between Feynman integrals called intersection number. We propose a new purely rational algorithm for the calculation of intersection numbers of differential $n-$forms that avoids the presence of algebraic extensions. We show how expansions around non-rational poles, which are a bottleneck of existing algorithms for intersection numbers, can be avoided by performing an expansion in series around a rational polynomial irreducible over $\mathbb{Q}$, that we refer to as $p(z)-$adic expansion. The algorithm we developed has been implemented and tested on several diagrams, both at one and two loops.

Validation of an intermediate-complexity flood risk model for climate change adaptation

In questo lavoro di tesi viene presentato e validato un modello di rischio di alluvione a complessit�� intermedia per scenari climatici futuri. Questo modello appartiene a quella categoria di strumenti che mirano a soddisfare le esigenze identificate dal World Climate Research Program (WRCP) per affrontare gli effetti del cambiamento climatico. L'obiettivo perseguito �� quello di sviluppare, seguendo un approccio ``bottom-up" al rischio climatico regionale, strumenti che possano aiutare i decisori a realizzare l'adattamento ai cambiamenti climatici. Il modello qui presentato �� interamente basato su dati open-source forniti dai servizi Copernicus. Il contributo di questo lavoro di tesi riguarda lo sviluppo di un modello, formulato da (Ruggieri et al.), per stimare i danni di eventi alluvionali fluviali per specifici i livelli di riscaldamento globale (GWL). Il modello �� stato testato su tre bacini idrografici di medie dimensioni in Emilia-Romagna, Panaro, Reno e Secchia. In questo lavoro, il modello viene sottoposto a test di sensibilit�� rispetto a un'ipotesi enunciata nella formulazione del modello, poi vengono effettuate analisi relative all'ensemble multi-modello utilizzato per le proiezioni. Il modello viene quindi validato, confrontando i danni stimati nel clima attuale per i tre fiumi con i danni osservati e confrontando le portate simulate con quelle osservate. Infine, vengono stimati i danni associati agli eventi alluvionali in tre scenari climatici futuri caratterizzati da GWL di 1.5�� C, 2.0�� C e 3.0��C.

Structural Connectivity Of The Default Mode Network And Cognition In Alzheimer��s Disease.

Disconnectivity between the Default Mode Network (DMN) nodes can cause clinical symptoms and cognitive deficits in Alzheimer��s disease (AD). We aimed to examine the structural connectivity between DMN nodes, to verify the extent in which white matter disconnection affects cognitive performance. MRI data of 76 subjects (25 mild AD, 21 amnestic Mild Cognitive Impairment subjects and 30 controls) were acquired on a 3.0T scanner. ExploreDTI software (fractional Anisotropy threshold=0.25 and the angular threshold=60��) calculated axial, radial, and mean diffusivities, fractional anisotropy and streamline count. AD patients showed lower fractional anisotropy (P=0.01) and streamline count (P=0.029), and higher radial diffusivity (P=0.014) than controls in the cingulum. After correction for white matter atrophy, only fractional anisotropy and radial diffusivity remained significantly lower in AD compared to controls (P=0.003 and P=0.05). In the parahippocampal bundle, AD patients had lower mean and radial diffusivities (P=0.048 and P=0.013) compared to controls, from which only radial diffusivity survived for white matter adjustment (P=0.05). Regression models revealed that cognitive performance is also accounted for by white matter microstructural values. Structural connectivity within the DMN is important to the execution of high-complexity tasks, probably due to its relevant role in the integration of the network.

The Crystal-t Algorithm: A New Approach To Calculate The Sle Of Lipidic Mixtures Presenting Solid Solutions.

Lipidic mixtures present a particular phase change profile highly affected by their unique crystalline structure. However, classical solid-liquid equilibrium (SLE) thermodynamic modeling approaches, which assume the solid phase to be a pure component, sometimes fail in the correct description of the phase behavior. In addition, their inability increases with the complexity of the system. To overcome some of these problems, this study describes a new procedure to depict the SLE of fatty binary mixtures presenting solid solutions, namely the Crystal-T algorithm. Considering the non-ideality of both liquid and solid phases, this algorithm is aimed at the determination of the temperature in which the first and last crystal of the mixture melts. The evaluation is focused on experimental data measured and reported in this work for systems composed of triacylglycerols and fatty alcohols. The liquidus and solidus lines of the SLE phase diagrams were described by using excess Gibbs energy based equations, and the group contribution UNIFAC model for the calculation of the activity coefficients of both liquid and solid phases. Very low deviations of theoretical and experimental data evidenced the strength of the algorithm, contributing to the enlargement of the scope of the SLE modeling.

[principles Of Universality, Comprehensiveness And Equity In A Hearing Health Care Service].

This article analyzed whether the practices of hearing health care were consistent with the principles of universality, comprehensiveness and equity from the standpoint of professionals. It involved qualitative research conducted at a Medium Complexity Hearing Health Care Center. A social worker, three speech therapists, a physician and a psychologist constituted the study subjects. Interviews were conducted as well as observation registered in a field diary. The thematic analysis technique was used in the analysis of the material. The analysis of interviews resulted in the construction of the following themes: Universality and access to hearing health, Comprehensive Hearing Health Care and Hearing Health and Equity. The study identified issues that interfere with the quality of service and run counter to the principles of Brazilian Unified Health System. The conclusion reached was that a relatively simple investment in training and professional qualification can bring about significant changes in order to promote a more universal, comprehensive and equitable health service.