Reliability-based design optimization strategies based on FORM: a review

In deterministic optimization, the uncertainties of the structural system (i.e. dimension, model, material, loads, etc) are not explicitly taken into account. Hence, resulting optimal solutions may lead to reduced reliability levels. The objective of reliability based design optimization (RBDO) is to optimize structures guaranteeing that a minimum level of reliability, chosen a priori by the designer, is maintained. Since reliability analysis using the First Order Reliability Method (FORM) is an optimization procedure itself, RBDO (in its classical version) is a double-loop strategy: the reliability analysis (inner loop) and the structural optimization (outer loop). The coupling of these two loops leads to very high computational costs. To reduce the computational burden of RBDO based on FORM, several authors propose decoupling the structural optimization and the reliability analysis. These procedures may be divided in two groups: (i) serial single loop methods and (ii) unilevel methods. The basic idea of serial single loop methods is to decouple the two loops and solve them sequentially, until some convergence criterion is achieved. On the other hand, uni-level methods employ different strategies to obtain a single loop of optimization to solve the RBDO problem. This paper presents a review of such RBDO strategies. A comparison of the performance (computational cost) of the main strategies is presented for several variants of two benchmark problems from the literature and for a structure modeled using the finite element method.

Design and control techniques of optical networks

The world of communication has changed quickly in the last decade resulting in the the rapid increase in the pace of peoples’ lives. This is due to the explosion of mobile communication and the internet which has now reached all levels of society. With such pressure for access to communication there is increased demand for bandwidth. Photonic technology is the right solution for high speed networks that have to supply wide bandwidth to new communication service providers. In particular this Ph.D. dissertation deals with DWDM optical packet-switched networks. The issue introduces a huge quantity of problems from physical layer up to transport layer. Here this subject is tackled from the network level perspective. The long term solution represented by optical packet switching has been fully explored in this years together with the Network Research Group at the department of Electronics, Computer Science and System of the University of Bologna. Some national as well as international projects supported this research like the Network of Excellence (NoE) e-Photon/ONe, funded by the European Commission in the Sixth Framework Programme and INTREPIDO project (End-to-end Traffic Engineering and Protection for IP over DWDM Optical Networks) funded by the Italian Ministry of Education, University and Scientific Research. Optical packet switching for DWDM networks is studied at single node level as well as at network level. In particular the techniques discussed are thought to be implemented for a long-haul transport network that connects local and metropolitan networks around the world. The main issues faced are contention resolution in a asynchronous variable packet length environment, adaptive routing, wavelength conversion and node architecture. Characteristics that a network must assure as quality of service and resilience are also explored at both node and network level. Results are mainly evaluated via simulation and through analysis.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

Design of wireless sensor networks for fluid dynamic applications

In fluid dynamics research, pressure measurements are of great importance to define the flow field acting on aerodynamic surfaces. In fact the experimental approach is fundamental to avoid the complexity of the mathematical models for predicting the fluid phenomena. It’s important to note that, using in-situ sensor to monitor pressure on large domains with highly unsteady flows, several problems are encountered working with the classical techniques due to the transducer cost, the intrusiveness, the time response and the operating range. An interesting approach for satisfying the previously reported sensor requirements is to implement a sensor network capable of acquiring pressure data on aerodynamic surface using a wireless communication system able to collect the pressure data with the lowest environmental–invasion level possible. In this thesis a wireless sensor network for fluid fields pressure has been designed, built and tested. To develop the system, a capacitive pressure sensor, based on polymeric membrane, and read out circuitry, based on microcontroller, have been designed, built and tested. The wireless communication has been performed using the Zensys Z-WAVE platform, and network and data management have been implemented. Finally, the full embedded system with antenna has been created. As a proof of concept, the monitoring of pressure on the top of the mainsail in a sailboat has been chosen as working example.

Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments

This work presents exact, hybrid algorithms for mixed resource Allocation and Scheduling problems; in general terms, those consist into assigning over time finite capacity resources to a set of precedence connected activities. The proposed methods have broad applicability, but are mainly motivated by applications in the field of Embedded System Design. In particular, high-performance embedded computing recently witnessed the shift from single CPU platforms with application-specific accelerators to programmable Multi Processor Systems-on-Chip (MPSoCs). Those allow higher flexibility, real time performance and low energy consumption, but the programmer must be able to effectively exploit the platform parallelism. This raises interest in the development of algorithmic techniques to be embedded in CAD tools; in particular, given a specific application and platform, the objective if to perform optimal allocation of hardware resources and to compute an execution schedule. On this regard, since embedded systems tend to run the same set of applications for their entire lifetime, off-line, exact optimization approaches are particularly appealing. Quite surprisingly, the use of exact algorithms has not been well investigated so far; this is in part motivated by the complexity of integrated allocation and scheduling, setting tough challenges for ``pure'' combinatorial methods. The use of hybrid CP/OR approaches presents the opportunity to exploit mutual advantages of different methods, while compensating for their weaknesses. In this work, we consider in first instance an Allocation and Scheduling problem over the Cell BE processor by Sony, IBM and Toshiba; we propose three different solution methods, leveraging decomposition, cut generation and heuristic guided search. Next, we face Allocation and Scheduling of so-called Conditional Task Graphs, explicitly accounting for branches with outcome not known at design time; we extend the CP scheduling framework to effectively deal with the introduced stochastic elements. Finally, we address Allocation and Scheduling with uncertain, bounded execution times, via conflict based tree search; we introduce a simple and flexible time model to take into account duration variability and provide an efficient conflict detection method. The proposed approaches achieve good results on practical size problem, thus demonstrating the use of exact approaches for system design is feasible. Furthermore, the developed techniques bring significant contributions to combinatorial optimization methods.

Design, implementation and evaluation of a virtual laboratory for Computer Engineering Education

Broad consensus has been reached within the Education and Cognitive Psychology research communities on the need to center the learning process on experimentation and concrete application of knowledge, rather than on a bare transfer of notions. Several advantages arise from this educational approach, ranging from the reinforce of students learning, to the increased opportunity for a student to gain greater insight into the studied topics, up to the possibility for learners to acquire practical skills and long-lasting proficiency. This is especially true in Engineering education, where integrating conceptual knowledge and practical skills assumes a strategic importance. In this scenario, learners are called to play a primary role. They are actively involved in the construction of their own knowledge, instead of passively receiving it. As a result, traditional, teacher-centered learning environments should be replaced by novel learner-centered solutions. Information and Communication Technologies enable the development of innovative solutions that provide suitable answers to the need for the availability of experimentation supports in educational context. Virtual Laboratories, Adaptive Web-Based Educational Systems and Computer-Supported Collaborative Learning environments can significantly foster different learner-centered instructional strategies, offering the opportunity to enhance personalization, individualization and cooperation. More specifically, they allow students to explore different kinds of materials, to access and compare several information sources, to face real or realistic problems and to work on authentic and multi-facet case studies. In addition, they encourage cooperation among peers and provide support through coached and scaffolded activities aimed at fostering reflection and meta-cognitive reasoning. This dissertation will guide readers within this research field, presenting both the theoretical and applicative results of a research aimed at designing an open, flexible, learner-centered virtual lab for supporting students in learning Information Security.

An evolutionary approach to the design of experiments for combinatorial optimization with an application to enzyme engineering

In a large number of problems the high dimensionality of the search space, the vast number of variables and the economical constrains limit the ability of classical techniques to reach the optimum of a function, known or unknown. In this thesis we investigate the possibility to combine approaches from advanced statistics and optimization algorithms in such a way to better explore the combinatorial search space and to increase the performance of the approaches. To this purpose we propose two methods: (i) Model Based Ant Colony Design and (ii) Naïve Bayes Ant Colony Optimization. We test the performance of the two proposed solutions on a simulation study and we apply the novel techniques on an appplication in the field of Enzyme Engineering and Design.

Metaheuristics for Search Problems in Genomics - New Algorithms and Applications

In this thesis we made the first steps towards the systematic application of a methodology for automatically building formal models of complex biological systems. Such a methodology could be useful also to design artificial systems possessing desirable properties such as robustness and evolvability. The approach we follow in this thesis is to manipulate formal models by means of adaptive search methods called metaheuristics. In the first part of the thesis we develop state-of-the-art hybrid metaheuristic algorithms to tackle two important problems in genomics, namely, the Haplotype Inference by parsimony and the Founder Sequence Reconstruction Problem. We compare our algorithms with other effective techniques in the literature, we show strength and limitations of our approaches to various problem formulations and, finally, we propose further enhancements that could possibly improve the performance of our algorithms and widen their applicability. In the second part, we concentrate on Boolean network (BN) models of gene regulatory networks (GRNs). We detail our automatic design methodology and apply it to four use cases which correspond to different design criteria and address some limitations of GRN modeling by BNs. Finally, we tackle the Density Classification Problem with the aim of showing the learning capabilities of BNs. Experimental evaluation of this methodology shows its efficacy in producing network that meet our design criteria. Our results, coherently to what has been found in other works, also suggest that networks manipulated by a search process exhibit a mixture of characteristics typical of different dynamical regimes.

Multicelled Behaviour in E. coli: Design and experimental characterization of an engineered library of hybrid promoters.

Synthetic biology has recently had a great development, many papers have been published and many applications have been presented, spanning from the production of biopharmacheuticals to the synthesis of bioenergetic substrates or industrial catalysts. But, despite these advances, most of the applications are quite simple and don’t fully exploit the potential of this discipline. This limitation in complexity has many causes, like the incomplete characterization of some components, or the intrinsic variability of the biological systems, but one of the most important reasons is the incapability of the cell to sustain the additional metabolic burden introduced by a complex circuit. The objective of the project, of which this work is part, is trying to solve this problem through the engineering of a multicellular behaviour in prokaryotic cells. This system will introduce a cooperative behaviour that will allow to implement complex functionalities, that can’t be obtained with a single cell. In particular the goal is to implement the Leader Election, this procedure has been firstly devised in the field of distributed computing, to identify the process that allow to identify a single process as organizer and coordinator of a series of tasks assigned to the whole population. The election of the Leader greatly simplifies the computation providing a centralized control. Further- more this system may even be useful to evolutionary studies that aims to explain how complex organisms evolved from unicellular systems. The work presented here describes, in particular, the design and the experimental characterization of a component of the circuit that solves the Leader Election problem. This module, composed of an hybrid promoter and a gene, is activated in the non-leader cells after receiving the signal that a leader is present in the colony. The most important element, in this case, is the hybrid promoter, it has been realized in different versions, applying the heuristic rules stated in [22], and their activity has been experimentally tested. The objective of the experimental characterization was to test the response of the genetic circuit to the introduction, in the cellular environment, of particular molecules, inducers, that can be considered inputs of the system. The desired behaviour is similar to the one of a logic AND gate in which the exit, represented by the luminous signal produced by a fluorescent protein, is one only in presence of both inducers. The robustness and the stability of this behaviour have been tested by changing the concentration of the input signals and building dose response curves. From these data it is possible to conclude that the analysed constructs have an AND-like behaviour over a wide range of inducers’ concentrations, even if it is possible to identify many differences in the expression profiles of the different constructs. This variability accounts for the fact that the input and the output signals are continuous, and so their binary representation isn’t able to capture the complexity of the behaviour. The module of the circuit that has been considered in this analysis has a fundamental role in the realization of the intercellular communication system that is necessary for the cooperative behaviour to take place. For this reason, the second phase of the characterization has been focused on the analysis of the signal transmission. In particular, the interaction between this element and the one that is responsible for emitting the chemical signal has been tested. The desired behaviour is still similar to a logic AND, since, even in this case, the exit signal is determined by the hybrid promoter activity. The experimental results have demonstrated that the systems behave correctly, even if there is still a substantial variability between them. The dose response curves highlighted that stricter constrains on the inducers concentrations need to be imposed in order to obtain a clear separation between the two levels of expression. In the conclusive chapter the DNA sequences of the hybrid promoters are analysed, trying to identify the regulatory elements that are most important for the determination of the gene expression. Given the available data it wasn’t possible to draw definitive conclusions. In the end, few considerations on promoter engineering and complex circuits realization are presented. This section aims to briefly recall some of the problems outlined in the introduction and provide a few possible solutions.

Study of Candidate Genes for production and carcass traits in Italian Heavy Pigs: identification of a new DNA Markers, Expression Studies and Association Analysis using Different Experimental Design

Heavy pig breeding in Italy is mainly oriented for the production of high quality processed products. Of particular importance is the dry cured ham production, which is strictly regulated and requires specific carcass characteristics correlated with green leg characteristics. Furthermore, as pigs are slaughtered at about 160 kg live weight, the Italian pig breeding sector faces severe problems of production efficiency that are related to all biological aspects linked to growth, feed conversion, fat deposition and so on. It is well known that production and carcass traits are in part genetically determined. Therefore, as a first step to understand genetic basis of traits that could have a direct or indirect impact on dry cured ham production, a candidate gene approach can be used to identify DNA markers associated with parameters of economic importance. In this thesis, we investigated three candidate genes for carcass and production traits (TRIB3, PCSK1, MUC4) in pig breeds used for dry cured ham production, using different experimental approaches in order to find molecular markers associated with these parameters.

Einflüsse von Folienqualität und Blister-Design auf die Funktionalität von Blisterverpackungen

Ziel dieser Arbeit ist die Untersuchung der Einflüsse von Blister-Design und Folienqualität auf die Funktionalität von Blisterverpackungen. Hierzu werden analytische Methoden mittels Interferometrie, IR-Spektroskopie, Betarückstreuverfahren, Wirbelstromverfahren und Impedanzspektroskopie entwickelt, die zur quantitativen Bestimmung von Heißsiegellacken und Laminatbeschichtungen von Aluminium-Blisterfolien geeignet sind. Ein Vergleich der Methoden zeigt, dass sich das Betarückstreuverfahren, die Interferometrie und IR-Messungen für die Heißsiegellackbestimmung, die Interferometrie und das Wirbelstromverfahren für die Bestimmung von Kunststofflaminaten eignen.rnIm zweiten Abschnitt der Arbeit werden Einflüsse des Heißsiegellack-Flächengewichtes von Deckfolien auf die Qualität von Blisterverpackungen untersucht. Mit Zunahme des Flächengewichtes zeigt sich eine Erhöhung der Siegelnahtfestigkeit aber auch der Wasserdampfdurchlässigkeit von Blistern. Die untersuchten Heißsiegellacke zeigen Permeationskoeffizienten vergleichbar mit Polyvinylchlorid. In Untersuchungen zur Siegelprozessvalidität zeigt das Heißsiegellack-Flächengewicht nur geringfügige Auswirkungen auf diese. rnIm dritten Abschnitt der Arbeit werden Einflüsse des Blister-Designs auf die Benutzerfreundlichkeit von Blisterverpackungen durch eine Handlingstudie untersucht. Variationen der Öffnungskräfte von Durchdrück-Blistern wirken sich deutlich auf die Bewertungen der Blister durch die Probanden aus. Während die meisten Probanden alle getesteten Durchdrück-Blister innerhalb der Testdauer von 4 Minuten öffnen können (>84%), treten beim Peel-Blister und Peel-off-push-through-Blister deutlich mehr Handlingprobleme auf. Die Handlingprobleme korrelieren mit dem Alter, der Lebenssituation, der gesundheitlichen Verfassung und der Sehfähigkeit der Probanden. rn

Efficient parallel proximity queries and an application to highly complex motion planning problems with many narrow passages

In vielen Bereichen der industriellen Fertigung, wie zum Beispiel in der Automobilindustrie, wer- den digitale Versuchsmodelle (sog. digital mock-ups) eingesetzt, um die Entwicklung komplexer Maschinen m ̈oglichst gut durch Computersysteme unterstu ̈tzen zu k ̈onnen. Hierbei spielen Be- wegungsplanungsalgorithmen eine wichtige Rolle, um zu gew ̈ahrleisten, dass diese digitalen Pro- totypen auch kollisionsfrei zusammengesetzt werden k ̈onnen. In den letzten Jahrzehnten haben sich hier sampling-basierte Verfahren besonders bew ̈ahrt. Diese erzeugen eine große Anzahl von zuf ̈alligen Lagen fu ̈r das ein-/auszubauende Objekt und verwenden einen Kollisionserken- nungsmechanismus, um die einzelnen Lagen auf Gu ̈ltigkeit zu u ̈berpru ̈fen. Daher spielt die Kollisionserkennung eine wesentliche Rolle beim Design effizienter Bewegungsplanungsalgorith- men. Eine Schwierigkeit fu ̈r diese Klasse von Planern stellen sogenannte “narrow passages” dar, schmale Passagen also, die immer dort auftreten, wo die Bewegungsfreiheit der zu planenden Objekte stark eingeschr ̈ankt ist. An solchen Stellen kann es schwierig sein, eine ausreichende Anzahl von kollisionsfreien Samples zu finden. Es ist dann m ̈oglicherweise n ̈otig, ausgeklu ̈geltere Techniken einzusetzen, um eine gute Performance der Algorithmen zu erreichen.rnDie vorliegende Arbeit gliedert sich in zwei Teile: Im ersten Teil untersuchen wir parallele Kollisionserkennungsalgorithmen. Da wir auf eine Anwendung bei sampling-basierten Bewe- gungsplanern abzielen, w ̈ahlen wir hier eine Problemstellung, bei der wir stets die selben zwei Objekte, aber in einer großen Anzahl von unterschiedlichen Lagen auf Kollision testen. Wir im- plementieren und vergleichen verschiedene Verfahren, die auf Hu ̈llk ̈operhierarchien (BVHs) und hierarchische Grids als Beschleunigungsstrukturen zuru ̈ckgreifen. Alle beschriebenen Verfahren wurden auf mehreren CPU-Kernen parallelisiert. Daru ̈ber hinaus vergleichen wir verschiedene CUDA Kernels zur Durchfu ̈hrung BVH-basierter Kollisionstests auf der GPU. Neben einer un- terschiedlichen Verteilung der Arbeit auf die parallelen GPU Threads untersuchen wir hier die Auswirkung verschiedener Speicherzugriffsmuster auf die Performance der resultierenden Algo- rithmen. Weiter stellen wir eine Reihe von approximativen Kollisionstests vor, die auf den beschriebenen Verfahren basieren. Wenn eine geringere Genauigkeit der Tests tolerierbar ist, kann so eine weitere Verbesserung der Performance erzielt werden.rnIm zweiten Teil der Arbeit beschreiben wir einen von uns entworfenen parallelen, sampling- basierten Bewegungsplaner zur Behandlung hochkomplexer Probleme mit mehreren “narrow passages”. Das Verfahren arbeitet in zwei Phasen. Die grundlegende Idee ist hierbei, in der er- sten Planungsphase konzeptionell kleinere Fehler zuzulassen, um die Planungseffizienz zu erh ̈ohen und den resultierenden Pfad dann in einer zweiten Phase zu reparieren. Der hierzu in Phase I eingesetzte Planer basiert auf sogenannten Expansive Space Trees. Zus ̈atzlich haben wir den Planer mit einer Freidru ̈ckoperation ausgestattet, die es erlaubt, kleinere Kollisionen aufzul ̈osen und so die Effizienz in Bereichen mit eingeschr ̈ankter Bewegungsfreiheit zu erh ̈ohen. Optional erlaubt unsere Implementierung den Einsatz von approximativen Kollisionstests. Dies setzt die Genauigkeit der ersten Planungsphase weiter herab, fu ̈hrt aber auch zu einer weiteren Perfor- mancesteigerung. Die aus Phase I resultierenden Bewegungspfade sind dann unter Umst ̈anden nicht komplett kollisionsfrei. Um diese Pfade zu reparieren, haben wir einen neuartigen Pla- nungsalgorithmus entworfen, der lokal beschr ̈ankt auf eine kleine Umgebung um den bestehenden Pfad einen neuen, kollisionsfreien Bewegungspfad plant.rnWir haben den beschriebenen Algorithmus mit einer Klasse von neuen, schwierigen Metall- Puzzlen getestet, die zum Teil mehrere “narrow passages” aufweisen. Unseres Wissens nach ist eine Sammlung vergleichbar komplexer Benchmarks nicht ̈offentlich zug ̈anglich und wir fan- den auch keine Beschreibung von vergleichbar komplexen Benchmarks in der Motion-Planning Literatur.

Reduction of inappropriate medications among older nursing-home residents: a nurse-led, pre/post-design, intervention study

Background: Medication-related problems are common in the growing population of older adults and inappropriate prescribing is a preventable risk factor. Explicit criteria such as the Beers criteria provide a valid instrument for describing the rate of inappropriate medication (IM) prescriptions among older adults. Objective: To reduce IM prescriptions based on explicit Beers criteria using a nurse-led intervention in a nursing-home (NH) setting. Study Design: The pre/post-design included IM assessment at study start (pre-intervention), a 4-month intervention period, IM assessment after the intervention period (post-intervention) and a further IM assessment at 1-year follow-up. Setting: 204-bed inpatient NH in Bern, Switzerland. Participants: NH residents aged ≥60 years. Intervention: The intervention included four key intervention elements: (i) adaptation of Beers criteria to the Swiss setting; (ii) IM identification; (iii) IM discontinuation; and (iv) staff training. Main Outcome Measure: IM prescription at study start, after the 4-month intervention period and at 1-year follow-up. Results: The mean±SD resident age was 80.3±8.8 years. Residents were prescribed a mean±SD 7.8±4.0 medications. The prescription rate of IMs decreased from 14.5% pre-intervention to 2.8% post-intervention (relative risk [RR] = 0.2; 95% CI 0.06, 0.5). The risk of IM prescription increased nonstatistically significantly in the 1-year follow-up period compared with post-intervention (RR = 1.6; 95% CI 0.5, 6.1). Conclusions: This intervention to reduce IM prescriptions based on explicit Beers criteria was feasible, easy to implement in an NH setting, and resulted in a substantial decrease in IMs. These results underscore the importance of involving nursing staff in the medication prescription process in a long-term care setting.

Problems in functioning from the patient perspective using the International Classification of Functioning, Disability and Health (ICF) as a reference

We conducted a qualitative, multicenter study using a focus group design to explore the lived experiences of persons with any kind of primary sleep disorder with regard to functioning and contextual factors using six open-ended questions related to the International Classification of Functioning, Disability and Health (ICF) components. We classified the results using the ICF as a frame of reference. We identified the meaningful concepts within the transcribed data and then linked them to ICF categories according to established linking rules. The six focus groups with 27 participants yielded a total of 6986 relevant concepts, which were linked to a total of 168 different second-level ICF categories. From the patient perspective, the ICF components: (1) Body Functions; (2) Activities & Participation; and (3) Environmental Factors were equally represented; while (4) Body Structures appeared poignantly less frequently. Out of the total number of concepts, 1843 concepts (26%) were assigned to the ICF component Personal Factors, which is not yet classified but could indicate important aspects of resource management and strategy development of those who have a sleep disorder. Therefore, treatment of patients with sleep disorders must not be limited to anatomical and (patho-)physiological changes, but should also consider a more comprehensive view that includes patient's demands, strategies and resources in daily life and the contextual circumstances surrounding the individual.

A navigation system for percutaneous needle interventions based on PET/CT images: design, workflow and error analysis of soft tissue and bone punctures

Percutaneous needle intervention based on PET/CT images is effective, but exposes the patient to unnecessary radiation due to the increased number of CT scans required. Computer assisted intervention can reduce the number of scans, but requires handling, matching and visualization of two different datasets. While one dataset is used for target definition according to metabolism, the other is used for instrument guidance according to anatomical structures. No navigation systems capable of handling such data and performing PET/CT image-based procedures while following clinically approved protocols for oncologic percutaneous interventions are available. The need for such systems is emphasized in scenarios where the target can be located in different types of tissue such as bone and soft tissue. These two tissues require different clinical protocols for puncturing and may therefore give rise to different problems during the navigated intervention. Studies comparing the performance of navigated needle interventions targeting lesions located in these two types of tissue are not often found in the literature. Hence, this paper presents an optical navigation system for percutaneous needle interventions based on PET/CT images. The system provides viewers for guiding the physician to the target with real-time visualization of PET/CT datasets, and is able to handle targets located in both bone and soft tissue. The navigation system and the required clinical workflow were designed taking into consideration clinical protocols and requirements, and the system is thus operable by a single person, even during transition to the sterile phase. Both the system and the workflow were evaluated in an initial set of experiments simulating 41 lesions (23 located in bone tissue and 18 in soft tissue) in swine cadavers. We also measured and decomposed the overall system error into distinct error sources, which allowed for the identification of particularities involved in the process as well as highlighting the differences between bone and soft tissue punctures. An overall average error of 4.23 mm and 3.07 mm for bone and soft tissue punctures, respectively, demonstrated the feasibility of using this system for such interventions. The proposed system workflow was shown to be effective in separating the preparation from the sterile phase, as well as in keeping the system manageable by a single operator. Among the distinct sources of error, the user error based on the system accuracy (defined as the distance from the planned target to the actual needle tip) appeared to be the most significant. Bone punctures showed higher user error, whereas soft tissue punctures showed higher tissue deformation error.