Three essays on major trends in a slow clockspeed industry : the case of industrial automation

The motivation for this research initiated from the abrupt rise and fall of minicomputers which were initially used both for industrial automation and business applications due to their significantly lower cost than their predecessors, the mainframes. Later industrial automation developed its own vertically integrated hardware and software to address the application needs of uninterrupted operations, real-time control and resilience to harsh environmental conditions. This has led to the creation of an independent industry, namely industrial automation used in PLC, DCS, SCADA and robot control systems. This industry employs today over 200'000 people in a profitable slow clockspeed context in contrast to the two mainstream computing industries of information technology (IT) focused on business applications and telecommunications focused on communications networks and hand-held devices. Already in 1990s it was foreseen that IT and communication would merge into one Information and communication industry (ICT). The fundamental question of the thesis is: Could industrial automation leverage a common technology platform with the newly formed ICT industry? Computer systems dominated by complex instruction set computers (CISC) were challenged during 1990s with higher performance reduced instruction set computers (RISC). RISC started to evolve parallel to the constant advancement of Moore's law. These developments created the high performance and low energy consumption System-on-Chip architecture (SoC). Unlike to the CISC processors RISC processor architecture is a separate industry from the RISC chip manufacturing industry. It also has several hardware independent software platforms consisting of integrated operating system, development environment, user interface and application market which enables customers to have more choices due to hardware independent real time capable software applications. An architecture disruption merged and the smartphone and tablet market were formed with new rules and new key players in the ICT industry. Today there are more RISC computer systems running Linux (or other Unix variants) than any other computer system. The astonishing rise of SoC based technologies and related software platforms in smartphones created in unit terms the largest installed base ever seen in the history of computers and is now being further extended by tablets. An underlying additional element of this transition is the increasing role of open source technologies both in software and hardware. This has driven the microprocessor based personal computer industry with few dominating closed operating system platforms into a steep decline. A significant factor in this process has been the separation of processor architecture and processor chip production and operating systems and application development platforms merger into integrated software platforms with proprietary application markets. Furthermore the pay-by-click marketing has changed the way applications development is compensated: Three essays on major trends in a slow clockspeed industry: The case of industrial automation 2014 freeware, ad based or licensed - all at a lower price and used by a wider customer base than ever before. Moreover, the concept of software maintenance contract is very remote in the app world. However, as a slow clockspeed industry, industrial automation has remained intact during the disruptions based on SoC and related software platforms in the ICT industries. Industrial automation incumbents continue to supply systems based on vertically integrated systems consisting of proprietary software and proprietary mainly microprocessor based hardware. They enjoy admirable profitability levels on a very narrow customer base due to strong technology-enabled customer lock-in and customers' high risk leverage as their production is dependent on fault-free operation of the industrial automation systems. When will this balance of power be disrupted? The thesis suggests how industrial automation could join the mainstream ICT industry and create an information, communication and automation (ICAT) industry. Lately the Internet of Things (loT) and weightless networks, a new standard leveraging frequency channels earlier occupied by TV broadcasting, have gradually started to change the rigid world of Machine to Machine (M2M) interaction. It is foreseeable that enough momentum will be created that the industrial automation market will in due course face an architecture disruption empowered by these new trends. This thesis examines the current state of industrial automation subject to the competition between the incumbents firstly through a research on cost competitiveness efforts in captive outsourcing of engineering, research and development and secondly researching process re- engineering in the case of complex system global software support. Thirdly we investigate the industry actors', namely customers, incumbents and newcomers, views on the future direction of industrial automation and conclude with our assessments of the possible routes industrial automation could advance taking into account the looming rise of the Internet of Things (loT) and weightless networks. Industrial automation is an industry dominated by a handful of global players each of them focusing on maintaining their own proprietary solutions. The rise of de facto standards like IBM PC, Unix and Linux and SoC leveraged by IBM, Compaq, Dell, HP, ARM, Apple, Google, Samsung and others have created new markets of personal computers, smartphone and tablets and will eventually also impact industrial automation through game changing commoditization and related control point and business model changes. This trend will inevitably continue, but the transition to a commoditized industrial automation will not happen in the near future.

Systems biology in the development of HIV vaccines.

PURPOSE OF REVIEW: In the present review, we will provide the scientific rationale for applying systems biology to the development of vaccines and particularly HIV vaccines, the predictive power of systems biology on the vaccine immunological profile, the correlation between systems biology and the immunological functional profiles of different candidate vaccines, and the value of systems biology in the selection process of identifying the best-in-class candidate vaccines and in the decision process to move into in-vivo evaluation in clinical trials. RECENT FINDINGS: Systems biology has been recently applied to the characterization of the protective yellow fever vaccine YF17D and of seasonal flu vaccines. This has been instrumental in the identification of the components of the immune response that need to be stimulated by the vaccine in order to generate protective immunity. It is worth noting that a systems biology approach is currently being performed to identify correlates of immune protection of the RV144 Thai vaccine, the only known vaccine that showed modest protection against HIV reacquisition. SUMMARY: Systems biology represents a novel and powerful approach to predict the vaccine immunological profile, to identify the protective components of the immune response, and to help in the selection process of the best-in-class vaccines to move into clinical development.

Artificial muscle to wash blood out of fibrillating atrium: an alternative to lifelong anticoagulation.

The Atripump is a motorless, volume displacement pump based on artificial muscle technology that could reproduce the pump function of normal atrium. It could help prevent blood clots due to blood stagnation and eventually avoid anticoagulation therapy in atrial fibrillation (AF). An animal study has been designed to assess mechanical effects of this pump on fibrillating atrium. The Atripump is a dome shaped silicone coated nitinol actuator. A pacemaker like control unit drives the actuator. In five adult sheep, the right atrium (RA) was exposed and dome sutured onto the epicardium. Atrial fibrillation was induced using rapid epicardial pacing (600 beats/min). Ejection fraction of the RA was obtained with intracardiac ultrasound in baseline, AF and Atripump assisted AF conditions. The dome's contraction rate was 60/min with power supply of 12V, 400 mA for 200 ms and ran for 2 hours in total. Mean temperature on the RA was 39+/-1.5 degrees C. Right atrium ejection fraction was 31% in baseline conditions, 5% and 20% in AF and assisted AF, respectively. In two animals a thrombus appeared in the right appendix and washed out once the pump was turned on. The Atripump washes blood out the RA acting as an anticoagulant device. Possible clinical implications in patients with chronic AF are prevention of embolism of cardiac origin and avoidance of hemorrhagic complication due to chronic anticoagulation.

A novel pediatric biventricular assist device: in vitro test results.

Most ventricular assist devices (VADs) currently used in infants are extracorporeal. These VADs require long-term anticoagulation therapy and extensive surgery, and two devices are needed for biventricular support. We designed a biventricular assist device based on shape memory alloy that reproduces the hemodynamic effects of cardiomyoplasty, supporting the heart with a compressing movement, and evaluated its performance in a dedicated mockup system. Nitinol fibers are the device's key component. Ejection fraction (EF), cardiac output (CO), and generated systolic pressure were measured on a test bench. Our test bench settings were a preload range of 0-15 mm Hg, an afterload range of 0-160 mm Hg, and a heart rate (HR) of 20, 30, 40, and 60 beats/min. A power supply of 15 volts and 3.5 amperes was necessary. The EF range went from 34.4% to 1.2% as the afterload and HR increased, along with a CO from 180 to 6 ml/min. The device generated a maximal systolic pressure of 25 mm Hg. Cardiac compression for biventricular assistance in child-sized heart using shape memory alloy is technically feasible. Further testing remains necessary to assess this VAD's in vivo performance range and its reliability.

Artificial muscle for end-stage heart failure.

We describe a device made of artificial muscle for the treatment of end-stage heart failure as an alternative to current heart assist devices. The key component is a matrix of nitinol wires and aramidic fibers called Biometal muscle (BM). When heated electrically, it produces a motorless, smooth, and lifelike motion. The BM is connected to a carbon fiber scaffold, tightening the heart and providing simultaneous assistance to the left and right ventricles. A pacemaker-like microprocessor drives the contraction of the BM. We tested the device in a dedicated bench model of diseased heart. It generated a systolic pressure of 75 mm Hg and ejected a maximum of 330 ml/min, with an ejection fraction of 12%. The device required a power supply of 6 V, 250 mA. This could be the beginning of an era in which BMs integrate or replace the mechanical function of natural muscles.

Totally implantable robot to treat chronic atrial fibrillation

Chronic atrial fibrillation affects millions of people worldwide. Its surgical treatment often fails to restore the transport function of the atrium. This study first introduces the concept of an atrial assist device (AAD) to restore the pump function of the atrium. The AAD is developed to be totally implantable in the human body with a transcutaneous energy transfer system to recharge the implanted battery. The ADD consists of a motorless pump based on artificial muscle technology, positioned on the external surface of the atrium to compress it and restore its muscular activity. A bench model reproduces the function of a fibrillating atrium to assess the circulatory support that this pump can provide. Atripump (Nanopowers SA, Switzerland) is a dome-shaped silicone-coated nitinol actuator 5 mm high, sutured on the external surface of the atrium. A pacemaker-like control unit drives the actuator that compresses the atrium, providing the mechanical support to the blood circulation. Electrical characteristics: the system is composed of one actuator that needs a minimal tension of 15 V and has a maximum current of 1.5 A with a 50% duty cycle. The implantable rechargeable battery is made of a cell having the following specifications: nominal tension of a cell: 4.1 V, tension after 90% of discharge: 3.5 V, nominal capacity of a cell: 163 mA h. The bench model consists of an open circuit made of latex bladder 60 mm in diameter filled with water. The bladder is connected to a vertically positioned tube that is filled to different levels, reproducing changes in cardiac preload. The Atripump is placed on the outer surface of the bladder. Pressure, volume and temperature changes were recorded. The contraction rate was 1 Hz with a power supply of 12 V, 400 mA for 200 ms. Preload ranged from 15 to 21 cm H(2)O. Maximal silicone membrane temperature was 55 degrees C and maximal temperature of the liquid environment was 35 degrees C. The pump produced a maximal work of 16 x 10(-3) J. Maximal volume pumped was 492 ml min(-1). This artificial muscle pump is compact, follows the Starling law and reproduces the hemodynamic performances of a normal atrium. It could represent a new tool to restore the atrial kick in persistent atrial fibrillation.

Comparison of the polynomial model against explicit measurements of noise components for different mammography systems.

Given the adverse impact of image noise on the perception of important clinical details in digital mammography, routine quality control measurements should include an evaluation of noise. The European Guidelines, for example, employ a second-order polynomial fit of pixel variance as a function of detector air kerma (DAK) to decompose noise into quantum, electronic and fixed pattern (FP) components and assess the DAK range where quantum noise dominates. This work examines the robustness of the polynomial method against an explicit noise decomposition method. The two methods were applied to variance and noise power spectrum (NPS) data from six digital mammography units. Twenty homogeneously exposed images were acquired with PMMA blocks for target DAKs ranging from 6.25 to 1600 µGy. Both methods were explored for the effects of data weighting and squared fit coefficients during the curve fitting, the influence of the additional filter material (2 mm Al versus 40 mm PMMA) and noise de-trending. Finally, spatial stationarity of noise was assessed.Data weighting improved noise model fitting over large DAK ranges, especially at low detector exposures. The polynomial and explicit decompositions generally agreed for quantum and electronic noise but FP noise fraction was consistently underestimated by the polynomial method. Noise decomposition as a function of position in the image showed limited noise stationarity, especially for FP noise; thus the position of the region of interest (ROI) used for noise decomposition may influence fractional noise composition. The ROI area and position used in the Guidelines offer an acceptable estimation of noise components. While there are limitations to the polynomial model, when used with care and with appropriate data weighting, the method offers a simple and robust means of examining the detector noise components as a function of detector exposure.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.