Background: Laparoscopic surgery for colorectal cancer is a novel healthcare technology, for which much research evidence has been published. The objectives of this work were to compare the oncologic outcomes of this technology across different study types, and to define patterns of adoption on the basis of the literature. Methods: A comprehensive systematic review of the literature was conducted using 1) existing systematic reviews, 2) randomized controlled trials (RCTs), and 3) observational studies. Outcomes of interest were overall survival, and total lymph node harvest. Outcomes were compared for congruence. Adoption was evaluated by means of summary expert opinions in the literature. Results: 1) Existing systematic reviews were of low to moderate quality and displayed evidence of overlap and duplication. 2) Laparoscopy was not inferior to open surgery in terms of oncologic outcomes in any study type. 3) Oncologic outcomes from RCTs and observational studies were congruent. 4) Expert opinion in the literature has been supportive of this technology, paralleling the publication of large RCTs. Conclusions: The evaluation of laparoscopic surgery for colorectal cancer in RCTs and observational studies suggests that it is not inferior to open surgery. Adoption of this technology has paralleled RCT evidence.

Data centres are key to high availability and around the clock access to information. As the number of data centres increases to satisfy the demand for data, so does their energy consumption. This thesis is a case study of the data centres located in the Node Pole region in the North of Sweden. It aims to look at aspects of both the energy supply of Norrbotten and the actual technologies used by the data centres to utilise this energy supply. Using a literature review to gather primary data, the first research question analyses the energy supply of Norrbotten, investigating its specificities through energy security theories, particularly looking through the aspects of availability, accessibility and affordability. The second question examines the Node Pole’s implementation response to the specific energy supply of the North of Sweden, and whether this response is efficient and sustainable, using the four Rs theory and the Energy Efficiency Directive (EED). The results of the analysis show that the North of Sweden is currently in a privileged position: the energy produced in Norrbotten benefits from high availability criteria, is in oversupply, and thanks to the prevalence of hydropower and wind power in the energy mix, is very low in GHG emissions. The Swedish grid is reliable and robust, and Norbotten is no exception to that rule, providing the Node Pole with an accessible “plug and play” module to the electricity grid. In addition, the recent tax rebate aimed at the data centre industry means that the energy is affordable, more so in fact than in many other European countries. This assessment makes for a favourable breeding ground for data centres in the region from an energy security perspective. Meanwhile, the Node Pole data centres use ground-breaking cooling technologies consisting of airside cooling combined with adiabatic pads for humidity control (no separate humidification system), simple air filtration facilities (thanks to the outstanding air quality of the area),  and aerodynamic architectural premises layouts for better flow, reducing the cooling costs by increasing the efficiency of the overall air conditioning system. This technology is paired with innovative power distribution solutions (non-standard voltage and less UPS batteries), thereby considerably reducing the electricity consumption again and the waste of energy caused by voltage conversion. Combining the auspicious energy offerings of the Norrbotten region with the ingenious practical implementations of the data centres thus unleashes a new potential for more efficient and sustainable data centres.

Introdução: o carcinoma de endométrio é uma das neoplasias ginecológicas mais comuns nos países industrializados. O tratamento desta doença é primariamente cirúrgico. Segundo a normatização da Federação Internacional de Ginecologia e Obstetrícia (FIGO), a cirurgia ideal consiste na realização de histerectomia total, anexectomia bilateral, linfadenectomia retroperitonial e coleta de citologia peritoneal. No entanto, a realização sistemática da linfadenectomia tem sido contestada. Alguns centros de referência acreditam que deva ser realizada apenas em um grupo de pacientes com alto risco para disseminação linfática da doença. O desafio é encontrar marcadores pré-operatórios que possam ser preditivos da presença de doença linfonodal e, assim , virem a ser utilizados para a definição da necessidade da linfadenectomia. Objetivos: verificar se a expressão imuno-histoquímica (IMH) positiva da p53 na amostra endometrial diagnóstica e, se o valor sérico do CA 125 obtido no tempo pré-operatório, podem ser efetivos para prever a presença de doença linfonodal. Métodos: um estudo transversal restrospectivo foi realizado. Foram incluídas 111 pacientes com carcinoma de endométrio submetidas a histerectomia com anexectomia bilateral e linfadenectomia com ou sem citologia peritoneal. Noventa pacientes apresentavam CA 125 pré-operatório e 73, a avaliação da p53. Cinquenta e quatro pacientes apresentavam as duas variáveis em combinação. Foram estabelecidas as associações entre o valor de CA 125 e da expressão IMH da p53 com o envolvimento linfonodal. Uma curva ROC foi construída para identificar o valor de CA 125 com melhor Sensibilidade (S) e Especificidade (E) para doença linfonodal. / Introduction: endometrial carcinoma is one of the most common gynecological malignancies in industrialized countries. The treatment of this disease is primarily surgical. According to the International Federation of Gynecology and Obstetrics surgery ideal consists in performing total hysterectomy, bilateral adnexectomy, retroperitoneal lymphadenectomy and peritoneal cytology. However, the systematic lymphadenectomy has been disputed, and should only be performed in a group of patients at high risk of lymphatic spread of the disease. The challenge is to find preoperative markers that may be predictive of the presence of lymph node disease and thus come to be used to determine the necessity of lymphadenectomy. Objectives: to determine whether the positive immunohistochemical expression (IMH) of p53 in diagnostic endometrial sample and, if the value of serum CA 125, obtained during pre-operative, can be effective to predict the presence of lymph node disease. Methods: a cross-sectional study was conducted. The final sample consisted of 111 patients with endometrial carcinoma undergoing hysterectomy with bilateral adnexectomy and lymphadenectomy with or without peritoneal cytology. Ninety two patients had preoperative CA 125 and 73, evaluation of p53. Fifty four patients had both variables in combination. Associations have been established between the value of CA 125 and IMH expression of p53 with lymph node involvement. A ROC curve was constructed to identify the value of CA 125 with better sensitivity (S) and specificity (E) for lymph node disease.

Afin d'accélérer et automatiser l'analyse par ultrasons quantitatifs de ganglions lymphatiques de patients atteints d'un cancer, plusieurs segmentations automatiques des trois milieux rencontrés (le parenchyme du ganglion, la graisse périnodale et le sérum physiologique) sont étudiées. Une analyse statistique du signal d'enveloppe a permis d'identifier la distribution gamma comme le meilleur compromis en termes de qualité de la modélisation, simplicité du modèle et rapidité de l'estimation des paramètres. Deux nouvelles méthodes de segmentation basées sur l'approche par ensemble de niveaux et la distribution gamma sont décrites. Des statistiques locales du signal d'enveloppe permettent de tenir compte des inhomogénéités du signal dues à l'atténuation et la focalisation des ultrasons. La méthode appelée LRGDF modélise les statistiques du speckle dans des régions dont la taille est contrôlable par une fonction lisse à support compact. La seconde, appelée STS-LS, considère des coupes transverses, perpendiculaires au faisceau, pour gagner en efficacité. Une troisième méthode basée sur la classification par forêt aléatoire a été conçue pour initialiser et accélérer les deux précédentes. Ces méthodes automatiques sont comparées à une segmentation manuelle effectuée par un expert. Elles fournissent des résultats satisfaisants aussi bien sur des données simulées que sur des données acquises sur des ganglions lymphatiques de patients atteints d'un cancer colorectal ou du sein. Les paramètres ultrasonores quantitatifs estimés après segmentation automatique ou après segmentation manuelle par un expert sont comparables. / This work investigates approaches to obtain automatic segmentation of three media (i.e., lymph node parenchyma, perinodal fat and normal saline) in lymph node (LN) envelope data to expedite quantitative ultrasound (QUS) in dissected LNs from cancer patients. A statistical modeling study identified a two-parameter gamma distribution as the best model for data from the three media based on its high fitting accuracy, its analytically less-complex probability density function (PDF), and closed-form expressions for its parameter estimation. Two novel level-set segmentation methods that made use of localized statistics of envelope data to handle data inhomogeneities caused by attenuation and focusing effects were developed. The first, local region-based gamma distribution fitting (LRGDF), employed the gamma PDFs to model speckle statistics of envelope data in local regions at a controllable scale using a smooth function with a compact support. The second, statistical transverse-slice-based level-set (STS-LS), used gamma PDFs to locally model speckle statistics in consecutive transverse slices. A novel method was then designed and evaluated to automatically initialize the LRGDF and STS-LS methods using random forest classification with new proposed features. Methods developed in this research provided accurate, automatic and efficient segmentation results on simulated envelope data and data acquired for LNs from colorectal- and breast-cancer patients as compared with manual expert segmentation. Results also demonstrated that accurate QUS estimates are maintained when automatic segmentation is applied to evaluate excised LN data.

Bien que les multithérapies aient révolutionné le traitement de l'infection VIH, ces traitements échouent aujourd'hui encore à éradiquer le virus de l'organisme. En cause, la faible accessibilité des antirétroviraux à certains tissus, notamment lymphoïdes, empêche l'élimination du virus dans ces réservoirs de l'infection. C’est actuellement un des principaux freins aux interruptions thérapeutiques, avec pour conséquence des traitements à vie pour les patients. Or les traitements actuels sont particulièrement contraignants pour le patient avec des prises multiples et quotidiennes d’antirétroviraux, ce qui limite leurs observances et leur qualité de vie.Au cours de cette thèse, des nanogels à base de chitosane ont été conçus et évalués au niveau cellulaire pour l’administration de l'enfuvirtide, un inhibiteur de fusion. La délivrance cellulaire de l'enfuvirtide a été modulée par les propriétés physico-chimiques des nanogels. Les nanogels ont également permis de maintenir l'activité antivirale de l'enfuvirtide sur les cellules infectées par le VIH. Quant aux études in vivo, elles ont montré le potentiel des nanogels pour cibler les ganglions lymphatiques, par voie sous-cutanée. De plus, les nanogels ont été incorporés dans un implant biodégradable à formation in situ. Après injection sous-cutanée, ces implants ont montré une libération prolongée sur plusieurs jours des nanogels. / Although highly active antiretroviral therapies (HAART) have significantly improved the HIV infection treatment, important hurdles remain towards an HIV cure. Due to their low bioavailability, penetration and/or residence time, antiretrovirals have restricted access to tissue compartments such as lymphoid tissue and latent HIV reservoirs. Reservoirs prevent the eradication of the virus and result in a lifelong treatment for HIV infected patients. Currently, compliance and the patient quality of life are limited by dose frequency.During this thesis, chitosan-based nanogels are developed and evaluated for the enfuvirtide delivery, an HIV-1 fusion inhibitor peptide. The cellular distribution of enfuvirtide delivered as nanogels show the combined effect of physicochemical properties in terms of particle size and surface charge. Nanogels also maintain the antiviral activity of enfuvirtide on HIV-infected cells. In vivo studies, after subcutaneous administration in mice, demonstrate the ability of nanogels to target lymph nodes. Furthermore, nanogels were incorporated in an in situ forming implant. After subcutaneous injection, the implant allows gradual release of nanogels over several days.

<div>Many real-world domains are relational, consisting of objects (e.g., users and pa- pers) linked to each other in various ways. Because class labels in graphs are often only available for a subset of the nodes, semi-supervised learning for graphs has been studied extensively to predict the unobserved class labels. For example, we can pre- dict political views in a partially labeled social graph dataset and get expected gross incomes of movies in an actor/movie graph with a few labels. Recently, advances in representation learning for graph data have made great strides for the semi-supervised node classification. However, most of the methods have mainly focused on learning node representations by considering simple relational properties (e.g., random walk) or aggregating nearby attributes, and it is still challenging to learn complex inter- action patterns in partially labeled graphs and provide explanations on the learned representations. </div><div><br></div><div>In this dissertation, multiple methods are proposed to alleviate both challenges for semi-supervised node classification. First, we propose a graph neural network architecture, REGNN, that leverages local inferences for unlabeled nodes. REGNN performs graph convolution to enable label propagation via high-order paths and predicts class labels for unlabeled nodes. In particular, our proposed attention layer of REGNN measures the role equivalence among nodes and effectively reduces the noise, which is generated during the aggregation of observed labels from distant neighbors at various distances. Second, we also propose a neural network archi- tecture that jointly captures both temporal and static interaction patterns, which we call Temporal-Static-Graph-Net (TSGNet). The architecture learns a latent rep- resentation of each node in order to encode complex interaction patterns. Our key insight is that leveraging both a static neighbor encoder, that learns aggregate neigh- bor patterns, and a graph neural network-based recurrent unit, that captures complex interaction patterns, improves the performance of node classification. Lastly, in spite of better performance of representation learning on node classification tasks, neural network-based representation learning models are still less interpretable than the pre- vious relational learning models due to the lack of explanation methods. To address the problem, we show that nodes with high bridgeness scores have larger impacts on node embeddings such as DeepWalk, LINE, Struc2Vec, and PTE under perturbation. However, it is computationally heavy to get bridgeness scores, and we propose a novel gradient-based explanation method, GRAPH-wGD, to find nodes with high bridgeness efficiently. In our evaluations, our proposed architectures (REGNN and TSGNet) for semi-supervised node classification consistently improve predictive performance on real-world datasets. Our GRAPH-wGD also identifies important nodes as global explanations, which significantly change both predicted probabilities on node classification tasks and k-nearest neighbors in the embedding space after perturbing the highly ranked nodes and re-learning low-dimensional node representations for DeepWalk and LINE embedding methods.</div>

The diploma thesis deals with the implementation of own design of an electronic security system with the possibility of extension with the elements of home automation. The control panel is built using the Raspberry Pi3 B+ with a touch screen that communicates with the sensors using Bluetooth Low Energy technology.

This thesis describes creation of dynamically evolvable node, which will cooperate with other nodes. Group of these nodes will then create a distributed control system. The MQTT protocol is used for communications purposes between individual nodes. As hardware platform is used ESP32 and ESP8266. Whole operating system is written in MicroPython and supports a live uploading of user applications written in the same language. Later in thesis is decribed creation of monitoring node on Raspberry Pi, which control network. Complete system can be then used to control a intelligent house.

Internet Protocol Television (IPTV) transmits the television signal over the TCP/IP family of protocols. Its advantages are for example that the transmitting is not only one-way as in the “classical” TV broadcasting, but it can provide feedback such as interactivity. There are also some problems which avoids development, for example low channel capacity of access networks. That is why new methods , for example how to get more efficiency in IPTV transmission, are proposed. The main task of this diploma thesis is to visualize tree structure of relations between nodes in the network, based on understanding of principles of the hierarchical summarization and IPTV transmitting. The nodes in the tree structure provide computing and summarizing of the data in back-way channel. There is the data from the end users in this channel. In the first part of this diploma thesis there is explained the principle of IPTV and its differences as compared with classical TV broadcasting. The part is also aimed for the supported services, advantages and disadvantages. There is explained the compressing data with the MPEG-2 and MPEG-4 standards and problems with transport networks called “last mile problem.” To transmitting data IPTV uses Source Specific Multicast – every user connects to the multicast session with requested TV program. Feedback is provided by unicast. Feedback network uses the hierarchical summarization principle to reduce the data. This problem, connected with RTP, RTCP and TTP protocols, is in the work described as well. There is an international experimental network called PlanetLab mentioned in theoretical part of this work. Proposed structure of new protocol and applications including the visualization for IPTV broadcast, is tested in that network. In the practical part of this work there are discussed possibilities and methods for the visualization and data storage. Because of high availability and flexibility, there were chosen web technologies, such as MySQL for data storage. The tree model is executed by Java. The visualization is solved by web technologies, source code for visualization is dynamically generated by scripts in JSP (Java Server Pages). Graphical output is provided by the vector format SVG (Scalable Vector Graphics) which is created for graphical expression on the internet and in the mobile phones. There were created interactive web application thanks its ability to cooperation with Javascript technology. This application visualizes relation-tree structure of nodes. In this work there are explained basics of all used technologies, there are also given reasons for chosen methods and formats. Examples and interesting parts of solution are mentioned as well.

This masters thesis deals with technics of localization for wireless senzor networks with a focus on anchor free location algorithm by authors G. Jianquan and Z. Wei. It also describes the available simulations frameworks based on OMNeT++ platform and implementation of the anchor free algorithm in the simulation program Castalia. Furthermore, it deals with the energy demands of this algorithm based on results of simulations that were done for the communication unit IRIS.