Understanding the bioactivity of plant tannins: developments in analysis methods and structure-activity studies

Tannins, typically segregated into two major groups, the hydrolyzable tannins (HTs) and the proanthocyanidins (PAs), are plant polyphenolic secondary metabolites found throughout the plant kingdom. On one hand, tannins may cause harmful nutritional effects on herbivores, for example insects, and hence they work as plants’ defense against plant-eating animals. On the other hand, they may affect positively some herbivores, such as mammals, for example by their antioxidant, antimicrobial, anti-inflammatory or anticarcinogenic activities. This thesis focuses on understanding the bioactivity of plant tannins, their anthelmintic properties and the tools used for the qualitative and quantitative analysis of this endless source of structural diversity. The first part of the experimental work focused on the development of ultra-high performance liquid chromatography−tandem mass spectrometry (UHPLC-MS/MS) based methods for the rapid fingerprint analysis of bioactive polyphenols, especially tannins. In the second part of the experimental work the in vitro activity of isolated and purified HTs and their hydrolysis product, gallic acid, was tested against egg hatching and larval motility of two larval developmental stages, L1 and L2, of a common ruminant gastrointestinal parasite, Haemonchus contortus. The results indicated clear relationships between the HT structure and the anthelmintic activity. The activity of the studied compounds depended on many structural features, including size, functional groups present in the structure, and the structural rigidness. To further understand tannin bioactivity on a molecular level, the interaction between bovine serum albumin (BSA), and seven HTs and epigallocatechin gallate was examined. The objective was to define the effect of pH on the formation on tannin–protein complexes and to evaluate the stability of the formed complexes by gel electrophoresis and MALDI-TOF-MS. The results indicated that more basic pH values had a stabilizing effect on the tannin–protein complexes and that the tannin oxidative activity was directly linked with their tendency to form covalently stabilized complexes with BSA at increased pH.

Using Network Analysis to Understand and Advance Falls Prevention Services and Programs

The purpose of this study was to understand referral linkages that exist among falls prevention agencies in a southern Ontario region using network analysis theory. This was a single case study which included fifteen individual interviews. The data was analyzed through the constant comparative approach. Ten themes emerged and are classified into internal and external factors. Themes associated with internal factors are: 1) health professionals initiating services; 2) communication strategies; 3) formal partnerships; 4) trust; 5) program awareness; and 6) referral policies. Themes associated with external factors are: 1) client characteristics; 2) primary and community care collaboration; 3) networking; and 4) funding. Recommendations to improve the referral pathway are: 1) electronic database; 2) electronic referral forms; 3) educating office staff; and 4) education days. This study outlined the benefit of using network analysis to understand referral pathways and the importance of implementing strategies that will improve falls prevention referral pathways.

Semantic network analysis of ontologies

A key argument for modeling knowledge in ontologies is the easy re-use and re-engineering of the knowledge. However, beside consistency checking, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as (labeled, directed) graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA). While social network structures in general currently receive high attention in the Semantic Web community, there are only very few SNA applications up to now, and virtually none for analyzing the structure of ontologies. We illustrate in this paper the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality based on Hermitian matrices, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size.

Lethal Closeness: The Evolution of a Small-World Drug Trafficking Network

The evolution of the drug trafficking network –so-called– ‘Cartel del Norte del Valle’, is studied using network analysis methods. We found that the average length between any pair of its members was bounded by 4 –an attribute of smallworld networks. In this tightly connected network, informational shocks induce fear and the unleashing of searches of threatening nodes, using available paths. Lethal violence ensues in clusters of increasing sizes that fragment the network, without compromising, however, the survival of the largest component, which proved to be resilient to massive violence. In spite of a success from the point of view of head counting, the US’ socialization program for drug traffickers did not effectively change the cyclical dynamics of the drug dealing business: war survivors took over what was left from the old network initiating a new cycle of business and violence.

Sensitivity of feature-based analysis methods of storm tracks to the form of background field removal

For the tracking of extrema associated with weather systems to be applied to a broad range of fields it is necessary to remove a background field that represents the slowly varying, large spatial scales. The sensitivity of the tracking analysis to the form of background field removed is explored for the Northern Hemisphere winter storm tracks for three contrasting fields from an integration of the U. K. Met Office's (UKMO) Hadley Centre Climate Model (HadAM3). Several methods are explored for the removal of a background field from the simple subtraction of the climatology, to the more sophisticated removal of the planetary scales. Two temporal filters are also considered in the form of a 2-6-day Lanczos filter and a 20-day high-pass Fourier filter. The analysis indicates that the simple subtraction of the climatology tends to change the nature of the systems to the extent that there is a redistribution of the systems relative to the climatological background resulting in very similar statistical distributions for both positive and negative anomalies. The optimal planetary wave filter removes total wavenumbers less than or equal to a number in the range 5-7, resulting in distributions more easily related to particular types of weather system. For the temporal filters the 2-6-day bandpass filter is found to have a detrimental impact on the individual weather systems, resulting in the storm tracks having a weak waveguide type of behavior. The 20-day high-pass temporal filter is less aggressive than the 2-6-day filter and produces results falling between those of the climatological and 2-6-day filters.

Automated organizational network analysis for enterprise 2.0

Social Networking Sites have recently become a mainstream communications technology for many people around the world. Major IT vendors are releasing social software designed for use in a business/commercial context. These Enterprise 2.0 technologies have impressive collaboration and information sharing functionality, but so far they do not have any organizational network analysis (ONA) features that reveal any patterns of connectivity within business units. This paper shows the impact of organizational network analysis techniques and social networks on organizational performance, we also give an overview on current enterprise social software, and most importantly, we highlight how Enterprise 2.0 can help automate an organizational network analysis.

Bridging the gap between research and practice in organizational network analysis: a conversation between Rob Cross and Martin Kilduff

The article features a conversation between Rob Cross and Martin Kilduff about organizational network analysis in research and practice. It demonstrates the value of using social network perspectives in HRM. Drawing on the discussion about managing personal networks; managing the networks of others; the impact of social networking sites on perceptions of relationships; and ethical issues in organizational network analysis, we propose specific suggestions to bring social network perspectives closer to HRM researchers and practitioners and rebalance our attention to people and to their relationships.

Use of social network analysis to indentify the coopetition in a commercial cluster plan

The cluster provides a greater commercial relationship between the companies that comprise it. This encourages companies to adopt competitive structures that allow solving problems that would hardly alone (Lubeck et. Al., 2011). With that this paper aims to describe the coopetition between companies operating on a commercial cluster planned, from the point of view of retailers, taking as a basis the theoretical models proposed by Bengtsson and Kock (1999) and Leon (2005) and operationalized by means of Social Network Analysis (SNA). Data collection consisted of two phases, the first exploratory aspect to identify the actors, and the second was characterized as descriptive as it aims to describe the coopetition among the enterprises. As a result we identified the companies that cooperate and compete simultaneously (coopetition), firms that only compete, companies just cooperate and businesses that do not compete and do not cooperate (coexistence)

Identification of steel bars immersed in reinforced concrete based on experimental results of eddy current testing and artificial neural network analysis

This paper presents an experimental research on the use of eddy current testing (ECT) and artificial neural networks (ANNs) in order to identify the gauge and position of steel bars immersed in concrete structures. The paper presents details of the ECT probe and concrete specimens constructed for the tests, and a study about the influence of the concrete on the values of measured voltages. After this, new measurements were done with a greater number of specimens, simulating a field condition and the results were used to generate training and validation vectors for multilayer perceptron ANNs. The results show a high percentage of correct identification with respect to both, the gauge of the bar and of the thickness of the concrete cover. © 2013 Copyright Taylor and Francis Group, LLC.

Use of Stress Analysis Methods to Evaluate the Biomechanics of Oral Rehabilitation With Implants

Because the biomechanical behavior of dental implants is different from that of natural tooth, clinical problems may occur. The mechanism of stress distribution and load transfer to the implant/bone interface is a critical issue affecting the success rate of implants. Therefore, the aim of this study was to conduct a brief literature review of the available stress analysis methods to study implant-supported prosthesis loading and to discuss their contributions in the biomechanical evaluation of oral rehabilitation with implants. Several studies have used experimental, analytical, and computational models by means of finite element models (FEM), photoelasticity, strain gauges and associations of these methods to evaluate the biomechanical behavior of dental implants. The FEM has been used to evaluate new components, configurations, materials, and shapes of implants. The greatest advantage of the photoelastic method is the ability to visualize the stresses in complex structures, such as oral structures, and to observe the stress patterns in the whole model, allowing the researcher to localize and quantify the stress magnitude. Strain gauges can be used to assess in vivo and in vitro stress in prostheses, implants, and teeth. Some authors use the strain gauge technique with photoelasticity or FEM techniques. These methodologies can be widely applied in dentistry, mainly in the research field. Therefore, they can guide further research and clinical studies by predicting some disadvantages and streamlining clinical time.

Fra openness ed embeddedness: network analysis di un distretto industriale glocale.

Il distretto è un luogo relazionale dinamico dove le imprese danno luogo a differenti comportamenti economici di vario genere e natura, cooperando in un certo senso per lo sviluppo e la crescita del distretto stesso. In un primo momento di formazione del distretto si sono delineati comportamenti di tipo path dependent per vantaggi economici dovuti alla distribuzione delle imprese nel territorio, ma con il tempo si sono cominciati ad avere comportamenti espansionistici differenti sia dall'interno che dall'esterno del distretto influendo direttamente sulla struttura del stesso. É ragionevole dunque pensare che gli attori guardino al rapporto “locale/globale” con una sorta di "strabismo", da un lato leggendo il distretto (dall’interno come dall’esterno) come un luogo privilegiato per la formazione di economie di prossimità, dall’altro puntando a disporre le catene produttive nello spazio globale, alla ricerca dei vantaggi derivanti da un minor costo del lavoro o dalla immediata prossimità dei mercati di sbocco. il distretto viene dunque attraversato da dinamiche che lo globalizzano ma, al contempo, ne preservano (almeno per ora) la specificità. Non è più possibile leggere la sua forma economica solo nella logica della embeddedness, e non sarebbe certo corretto farlo solo in chiave di openness. Si tratta dunque di interrogarsi sul rapporto più di integrazione/complementarità che di contrapposizione fra openness ed embeddedness. In questa tesi verrà descritto un metodo d'approccio per dare un valore al fenomeno di Openness e Embeddedness presente nel distretto partendo da un dataset di dati relazionali ricavati da due database economici Amadeus e Aida. Non essendo possibile trovare pubblicamente dati sulle reti di fornitura delle singole aziende, siamo partiti dai dati relazionali di cinque aziende “seme”, ed attraverso una ricerca ricorsiva nelle relazioni di azionariato/partecipazione, siamo riusciti ad ottenere un campione di analisi che ci permette di mettere in luce tramite la custer analysis le principali tipologie di reti di imprese presenti nel distretto ed estese nello spazio globale.

Large-scale Network Analysis on Distributed Architectures

Questa dissertazione esamina le sfide e i limiti che gli algoritmi di analisi di grafi incontrano in architetture distribuite costituite da personal computer. In particolare, analizza il comportamento dell'algoritmo del PageRank così come implementato in una popolare libreria C++ di analisi di grafi distribuiti, la Parallel Boost Graph Library (Parallel BGL). I risultati qui presentati mostrano che il modello di programmazione parallela Bulk Synchronous Parallel è inadatto all'implementazione efficiente del PageRank su cluster costituiti da personal computer. L'implementazione analizzata ha infatti evidenziato una scalabilità negativa, il tempo di esecuzione dell'algoritmo aumenta linearmente in funzione del numero di processori. Questi risultati sono stati ottenuti lanciando l'algoritmo del PageRank della Parallel BGL su un cluster di 43 PC dual-core con 2GB di RAM l'uno, usando diversi grafi scelti in modo da facilitare l'identificazione delle variabili che influenzano la scalabilità. Grafi rappresentanti modelli diversi hanno dato risultati differenti, mostrando che c'è una relazione tra il coefficiente di clustering e l'inclinazione della retta che rappresenta il tempo in funzione del numero di processori. Ad esempio, i grafi Erdős–Rényi, aventi un basso coefficiente di clustering, hanno rappresentato il caso peggiore nei test del PageRank, mentre i grafi Small-World, aventi un alto coefficiente di clustering, hanno rappresentato il caso migliore. Anche le dimensioni del grafo hanno mostrato un'influenza sul tempo di esecuzione particolarmente interessante. Infatti, si è mostrato che la relazione tra il numero di nodi e il numero di archi determina il tempo totale.