Drug utilisation in a neonatal intensive care unit of a swiss university hospital

Introduction Medication errors in hospitalsmay occur at any step of the medication process including prescription, transcription, preparation and administration, and may originate with any of the actors involved. Neonatal intensive care units (NICU) take care of extremely frail patients in whom errors could have dramatic consequences. Our objective was to assess the frequency and nature of medication errors in the NICU of a university hospital in order to propose measures for improvement.Materials & Methods The design was that of an observational prospective study over 4 consecutivemonths. All patients receiving C 3drugs were included. For each patient, observations during the different stages were compiled in a computer formulary and compared with the litterature. Setting: The 11-bed NICU of our university hospital.Main outcome measures:(a) Frequency and nature of medication errors in prescription,transcription, preparation and administration.(b) Drugs affected by errors.Results 83 patients were included. 505 prescriptions and transcriptions, 447 preparations and 464 administrations were analyzed. 220 medications errors were observed: 102 (46.4%) at prescription, 25 (11.4%) at transcription, 19 (8.6%) at preparation and 73 (33.2%) at administration. Uncomplete/ambiguous orders (24; 23.5%) were the most common errors observed at prescription, followed by wrong name (21; 20.6%), wrong dose (17; 16.7%) and omission (15; 14.7%). Wrong time (33; 45.2%) and wrong administration technique (31; 42.5%) were the most important medication errors during administration. According to the ATC classification, systemic antibacterials (53; 24.1%) were the most implicated, followed by perfusion solutions (40; 18.2%), respiratory system products (30; 13.6%), and mineral supplements and antithrombotic agents (20; 9.1%).Discussions, Conclusion Proposed recommendations: ? Better teaching of neonatal prescription to medical interns;? Improved prescription form to avoid omissions and ambiguities;? Development of a neonatal drug formulary, including prescription,preparation and administration modalities to reduce errors at different stages;? Presence of a clinical pharmacist in the NICU.Disclosure of Interest None Declared

Bootstrapping a statistical speech translator from a rule-based one

We describe a series of experiments in which we start with English to French and English to Japanese versions of an Open Source rule-based speech translation system for a medical domain, and bootstrap correspondign statistical systems. Comparative evaluation reveals that the rule-based systems are still significantly better than the statistical ones, despite the fact that considerable effort has been invested in tuning both the recognition and translation components; also, a hybrid system only marginally improved recall at the cost of a los in precision. The result suggests that rule-based architectures may still be preferable to statistical ones for safety-critical speech translation tasks.

Hybridikäytön mitoitus liikkuvan työkoneen energian talteenottojärjestelmäksi

Työssä tarkastellaan sähköisiä energian talteenottomahdollisuuksia liikkuvissa työkoneissa. Työssä esitetään kolme erityyppistä liikkuvaan työkoneeseen soveltuvaa sähköisen energian talteenottojärjestelmää sekä mitoitetaan hybridikäyttö kahdelle erityyppiselle työkonesovellukselle kuormituskäyrien perusteella. Lisäksi työssä lasketaan hybridijärjestelmää käyttämällä saavutettava energiansäästö nykyiseen käyttöön verrattuna.

Time-series forecasting of pollutant concentration levels using particle swarm optimization and artificial neural networks

This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series, but also determines the best neural network architecture. An experimental analysis is performed using four real time series and the results are shown in terms of six performance measures. The experimental results demonstrate that the proposed methodology achieves a fair prediction of the presented pollutant time series by using compact networks.

Kaivoslastauskoneen hybridisointianalyysi virtuaali- ja in-loop -simuloinnin avulla

Työssä tutkitaan raskaiden työkoneiden hybridisointimitoitusta simuloimalla. Työssä esitetään simulation-in-the-loop-simulointiin perustuva järjestelmä, jolla esimerkkitapauksena oleva kaivoslastauskone työympäristöineen voidaan mallintaa mekaaniselta osaltaan monikappaledynamiikkaan perustuvalla ohjelmistolla ja hybridijärjestelmän osalta Simulinkissa. Yhdistetty simulointi mahdollistaa hybridityökoneen virtuaalimallin ohjaamisen käyttäjän toimesta reaaliajassa. Simuloinnista saadaan tuloksena mm. työsykli, jota voidaan käyttää hybridisointimitoitukseen. Hybridisointi toteutetaan kahdella erilaisella kokoonpanolla, joista analysoidaan suorituskykyä sekä polttoaineen kulutusta. Tuloksia verrataan pelkästään dieselmoottoria voimanlähteenä käyttävään lastauskoneeseen. Työssä tehty tutkimus osoittaa, että (sarja-) hybridisoinnilla voidaan saavuttaa merkittäviä etuja raskaiden työkoneiden polttoainetehokkuudessa. Dieselmoottoria voidaan ajaa sellaisessa staattisessa toimintapisteessä, jonka hyötysuhde on korkea riippumatta työkoneen kuormituksesta. Saavutettu hyöty on toteutetussa tutkimuksessa parhaimmillaan jopa 56 % vähennys polttoaineenkulutuksessa. Lisäksi tarvittava dieselin nimellisteho pienenee huomattavasti. Tutkimuksen osana esitellään myös Hardware-in-the-Loop -laitteisto, jonka avulla voidaan liittää oikea sähkömoottori ja taajuudenmuuttaja osaksi virtuaalisesti simuloitua työkonetta.

Energy Efficiency of a Diesel-Electric MobileWorking Machine

The power demand of many mobile working machines such as mine loaders, straddle carriers and harvesters varies significantly during operation, and typically, the average power demand of a working machine is considerably lower than the demand for maximum power. Consequently, for most of the time, the diesel engine of a working machine operates at a poor efficiency far from its optimum efficiency range. However, the energy efficiency of dieseldriven working machines can be improved by electric hybridization. This way, the diesel engine can be dimensioned to operate within its optimum efficiency range, and the electric drive with its energy storages responds to changes in machine loading. A hybrid working machine can be implemented in many ways either as a parallel hybrid, a series hybrid or a combination of these two. The energy efficiency of hybrid working machines can be further enhanced by energy recovery and reuse. This doctoral thesis introduces the component models required in the simulation model of a working machine. Component efficiency maps are applied to the modelling; the efficiency maps for electrical machines are determined analytically in the whole torque–rotational speed plane based on the electricalmachine parameters. Furthermore, the thesis provides simulation models for parallel, series and parallel-series hybrid working machines. With these simulation models, the energy consumption of the working machine can be analysed. In addition, the hybridization process is introduced and described. The thesis provides a case example of the hybridization and dimensioning process of a working machine, starting from the work cycle of the machine. The selection and dimensioning of the hybrid system have a significant impact on the energy consumption of a hybrid working machine. The thesis compares the energy consumption of a working machine implemented by three different hybrid systems (parallel, series and parallel-series) and with different component dimensions. The payback time of a hybrid working machine and the energy storage lifetime are also estimated in the study.

Identification of flexural stiffness parameters of beams

A three degree of freedom model of the dynamic mass at the middle of a test sample, resembling a Stockbridge neutraliser, is introduced. This model is used to identify the hereby called equivalent complex cross section flexural stiffness (ECFS) of the beam element which is part of the whole test sample. This ECFS, once identified, gives the effective cross section flexural stiffness of the beam as well as its effective damping, measured as the loss factor of an equivalent viscoelastic beam. The beam element of the test sample may be of any complexity, such as a segment of stranded cable of the ACSR type. These data are important parameters for the design of overhead power transmission lines and other cable structures. A cost function is defined and used in the identification of the ECFS. An experiment, designed to measure the dynamic masses of two test samples, is described. Experimental and identified results are presented and discussed.

Lämmöntuotanto älykkäässä energiaverkossa

Energiaverkon edistäminen tulee olemaan tulevaisuudessa suuressa roolissa niin Suomessa kuin maailmalla. Tällöin yhtenä vaihtoehtona on älykkyyden tuominen koko energiajärjestelmään niin sähkön kuin lämmönkin osalta. Tällöin voidaan vähentää kulutushuippujen aikaista energian käyttöä ja saada koko verkoston energiankulutus profiili tasaiseksi. Tässä työssä tarkastellaan spot-sähkön hyödyntämismahdollisuuksia lämmöntuotannossa. Työssä kehitetyn mallinnustyökalun avulla tutkittiin erilaisia ajotapoja ja erilaisten järjestelmien kokonaiskustannuksia. Työssä esitellään esimerkkilaskennan avulla spot-sähkön käytöstä syntyviä kustannuksia ja keinoja vaikuttaa niihin eri järjestelmä muutoksin. Malli mahdollistaa erilaisten järjestelmien ja niiden ajotapojen tutkimista. Mallilla voidaan myös tutkia erilaisten alueiden kulutuskäyttäytymistä ja hyödyntää sitä kustannuslaskelmiin. Voidaan todeta, että työssä muodostunut malli on toimiva ja sitä voidaan hyödyntää alueellisten lämmöntuotantojärjestelmien ajotapojen optimointiin.

Sähköverkosta irti olevan pienhybridijärjestelmän toteutus

Lappeen siniset –partiolippukunnalla on käytössään leiripaikka Humaljärvellä, Lappeenrannassa. Leiripaikalla ei ole liityntää sähköverkkoon, joten leiripaikalle on asennettu kaksi erillistä aurinkovoimalla toimivaa sähköjärjestelmää. Leiripaikan sähköistetyt rakennukset ovat pääkämppä ja saunan sekä vanhan kämpän muodostama kokonaisuus. Aurinkopaneeleilla tuotettu sähköenergia varastoidaan akustoihin. Lippukunta on havainnot käytössä, ettei talvella tuotettu aurinkoenergia riitä kattamaan pääkämpän sähkönkulutusta, joten leiripaikalle on päätetty hankkia tuulivoimala lisäämään tuotantoa. Tässä kandidaatin työssä esitellään hybridijärjestelmään kuuluvien aurinko- ja tuulivoiman toimintaperiaatteita sekä näiden komponentteja. Aurinko- ja tuulivoimalla tuotetulle sähköenergialle lasketaan arviot, joita verrataan leiripaikan sähköjärjestelmän arvioituun kulutukseen. Leiripaikalle tulevaa tuuliturbiinia ja sen lataussäädintä testataan laboratoriossa, jotta varmistutaan niiden soveltuvuudesta sekä toimivuudesta kohteeseen. Testausten ja laitteiden datalehtien avulla suunnitellaan leiripaikalle toimiva hybridijärjestelmä, joka kattaa leiripaikan ympärivuotisen sähkönkulutuksen.

Sähkö- ja hybridibussien tilanneselvitys

Työn tavoitteena on selvittää, minkälaisia sähkö- ja hybridibusseja maailmalla on käytössä. Työssä tutustutaan sähkö- ja hybridibussien tekniikkaan yleisellä tasolla. Tarkastellaan eri valmistajien bussien tekniikoita myös yksityiskohtaisemmin. Vertaillaan hieman bussien suorituskykyjä. Tuloksena tarkasteltavien bussien tärkeimmät ominaisuudet kerättiin taulukoihin ja vertailtiin niitä. Saatiin selville, että sähkö- ja hybridibussivalikoima on hyvin laaja. Yhtä optimaalista sähkö- tai hybridijärjestelmää ei ole vielä kehitetty vaan busseissa käytetään erilaisia sovelluksia esimerkiksi moottorin, voimansiirron ja energiavaraston osalta.

The 42-kDa coat protein of Andean potato mottle virus acts as a transcriptional activator in yeast

Interactions of viral proteins play an important role in the virus life cycle, especially in capsid assembly. Andean potato mottle comovirus (APMoV) is a plant RNA virus with a virion formed by two coat proteins (CP42 and CP22). Both APMoV coat protein open reading frames were cloned into pGBT9 and pGAD10, two-hybrid system vectors. HF7c yeast cells transformed with the p9CP42 construct grew on yeast dropout selection media lacking tryptophan and histidine. Clones also exhibited ß-galactosidase activity in both qualitative and quantitative assays. These results suggest that CP42 protein contains an amino acid motif able to activate transcription of His3 and lacZ reporter genes in Saccharomyces cerevisiae. Several deletions of the CP42 gene were cloned into the pGBT9 vector to locate the region involved in this activation. CP42 constructions lacking 12 residues from the C-terminal region and another one with 267 residues deleted from the N-terminus are still able to activate transcription of reporter genes. However, transcription activation was not observed with construction p9CP42deltaC57, which does not contain the last 57 amino acid residues. These results demonstrate that a transcription activation domain is present at the C-terminus of CP42 between residues 267 and 374.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

A calcineurin inhibitory protein overexpressed in Down's syndrome interacts with the product of a ubiquitously expressed transcript

The Down's syndrome candidate region 1 (DSCR1) protein, encoded by a gene located in the human chromosome 21, interacts with calcineurin and is overexpressed in Down's syndrome patients. As an approach to clarifying a putative function for this protein, in the present study we used the yeast two-hybrid system to identify DSCR1 partners. The two-hybrid system is a method that allows the identification of protein-protein interactions through reconstitution of the activity of the yeast GAL 4 transcriptional activator. The gene DSCR1 fused to the GAL 4 binding domain (BD) was used to screen a human fetal brain cDNA library cloned in fusion with the GAL 4 activation domain (AD). Three positive clones were found and sequence analysis revealed that all the plasmids coded for the ubiquitously expressed transcript (UXT). UXT, which is encoded in human Xp11, is a 157-amino acid protein present in both cytosol and nucleus of the cells. This positive interaction of DSCR1 and UXT was confirmed in vivo by mating the yeast strain AH109 (MATa)expressing AD-UXT with the strain Y187 (MATalpha) expressing BD-DSCR1, and in vitro by co-immunoprecipitation experiments. These results may help elucidate a new function for DSCR1 and its participation in Down's syndrome pathogenesis.

Proteomic inventory of myocardial proteins from patients with chronic Chagas' cardiomyopathy

Chronic Chagas' disease cardiomyopathy (CCC) is an often fatal outcome of Trypanosoma cruzi infection, with a poorer prognosis than other cardiomyopathies. CCC is refractory to heart failure treatments, and is the major indication of heart transplantation in Latin America. A diffuse myocarditis, plus intense myocardial hypertrophy, damage and fibrosis, in the presence of very few T. cruzi forms, are the histopathological hallmarks of CCC. To gain a better understanding of the pathophysiology of CCC, we analyzed the protein profile in the affected CCC myocardium. Homogenates from left ventricular myocardial samples of end-stage CCC hearts explanted during heart transplantation were subjected to two-dimensional electrophoresis with Coomassie blue staining; protein identification was performed by MALDI-ToF mass spectrometry and peptide mass fingerprinting. The identification of selected proteins was confirmed by immunoblotting. We demonstrated that 246 proteins matched in gels from two CCC patients. They corresponded to 112 distinct proteins. Along with structural/contractile and metabolism proteins, we also identified proteins involved in apoptosis (caspase 8, caspase 2), immune system (T cell receptor ß chain, granzyme A, HLA class I) and stress processes (heat shock proteins, superoxide dismutases, and other oxidative stress proteins). Proteins involved in cell signaling and transcriptional factors were also identified. The identification of caspases and oxidative stress proteins suggests the occurrence of active apoptosis and significant oxidative stress in CCC myocardium. These results generated an inventory of myocardial proteins in CCC that should contribute to the generation of hypothesis-driven experiments designed on the basis of the classes of proteins identified here.

A software engineering approach to distributed systems for composite modeling

The goal of this thesis is to define and validate a software engineering approach for the development of a distributed system for the modeling of composite materials, based on the analysis of various existing software development methods. We reviewed the main features of: (1) software engineering methodologies; (2) distributed system characteristics and their effect on software development; (3) composite materials modeling activities and the requirements for the software development. Using the design science as a research methodology, the distributed system for creating models of composite materials is created and evaluated. Empirical experiments which we conducted showed good convergence of modeled and real processes. During the study, we paid attention to the matter of complexity and importance of distributed system and a deep understanding of modern software engineering methods and tools.