Comparison of human and computer-based selective cleaning

Abstract

Cell-Cell interaction in erythropoiesis: role of human monocytes

Erythroid burst forming units (BFU-E) are proliferative cells present in peripheral blood and bone marrow which may be precursors of the erythroid colony forming cell found in the bone marrow. To examine the possible role of monocyte-macrophages in the modulation of erythropoiesis, the effect of monocytes on peripheral blood BFU-E proliferation in response to erythropoietin was investigated in the plasma clot culture system. Peripheral blood mononuclear cells from normal human donors were separated into four fractions. Fraction-I cells were obtained from the interface of Ficoll-Hypaque gradients (20-30% monocytes; 60-80% lymphocytes); fraction-II cells were fraction-I cells that were nonadherent to plastic (2-10% monocytes; 90-98% lymphocytes); fraction-III cells were obtained by incubation of fraction-II cells with carbonyl iron followed by Ficoll-Hypaque centrifugation (>99% lymphocytes); and fraction-IV cells represented the adherent population of fraction-II cells released from the plastic by lidocaine (>95% monocytes). When cells from these fractions were cultured in the presence of erythropoietin, the number of BFU-E-derived colonies was inversely proportional to the number of monocytes present (r = ¿0.96, P < 0.001). The suppressive effect of monocytes on BFU-E proliferation was confirmed by admixing autologous purified monocytes (fraction-IV cells) with fraction-III cells. Monocyte concentrations of ¿20% completely suppressed BFU-E activity. Reduction in the number of plated BFU-E by monocyte dilution could not account for these findings: a 15% reduction in the number of fraction-III cells plated resulted in only a 15% reduction in colony formation. These results indicate that monocyte-macrophages may play a significant role in the regulation of erythropoiesis and be involved in the pathogenesis of the hypoproliferative anemias associated with infection and certain neoplasia in which increased monocyte activity and monopoiesis also occur.

A study of the interaction between Helicobacter pylori and components of the human fibrinolytic system

The interaction of plasminogen, tissue plasminogen activator (t-PA) and urokinase with a clinical strain of Helicobacter pylori was studied. Plasminogen bound to the surface of H. pylori cells in a concentration-dependent manner and could be activated to the enzymatic form, plasmin, by t-PA. Affinity chromatography assays revealed a plasminogen-binding protein of 58.9 kDa in water extracts of surface proteins. Surface-associated plasmin activity, detected with the chromogenic substrate CBS 00.65, was observed only when plasminogen and an exogenous activator were added to the cell suspension. The two physiologic plasminogen activators, t-PA and urokinase, were also shown to bind to and remain active on the surface of bacterial cells. epsilon-Aminocaproic acid caused partial inhibition of t-PA binding, suggesting that the kringle 2 structure of this activator is involved in the interaction with surface receptors. The activation of plasminogen by t-PA, but not urokinase, strongly depended on the presence of cells and a 25-fold enhancer effect on the initial velocity of activation by t-PA compared to urokinase was established. Furthermore, a relationship between cell concentration and the initial velocity of activation was demonstrated. These findings support the concept that plasminogen activation by t-PA on the bacterial surface is a surface-dependent reaction which offers catalytic advantages.

Glycosaminoglycans affect the interaction of human plasma kallikrein with plasminogen, factor XII and inhibitors

Human plasma kallikrein, a serine proteinase, plays a key role in intrinsic blood clotting, in the kallikrein-kinin system, and in fibrinolysis. The proteolytic enzymes involved in these processes are usually controlled by specific inhibitors and may be influenced by several factors including glycosaminoglycans, as recently demonstrated by our group. The aim of the present study was to investigate the effect of glycosaminoglycans (30 to 250 µg/ml) on kallikrein activity on plasminogen and factor XII and on the inhibition of kallikrein by the plasma proteins C1-inhibitor and antithrombin. Almost all available glycosaminoglycans (heparin, heparan sulfate, bovine and tuna dermatan sulfate, chondroitin 4- and 6-sulfates) reduced (1.2 to 3.0 times) the catalytic efficiency of kallikrein (in a nanomolar range) on the hydrolysis of plasminogen (0.3 to 1.8 µM) and increased (1.9 to 7.7 times) the enzyme efficiency in factor XII (0.1 to 10 µM) activation. On the other hand, heparin, heparan sulfate, and bovine and tuna dermatan sulfate improved (1.2 to 3.4 times) kallikrein inhibition by antithrombin (1.4 µM), while chondroitin 4- and 6-sulfates reduced it (1.3 times). Heparin and heparan sulfate increased (1.4 times) the enzyme inhibition by the C1-inhibitor (150 nM).

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.

Control of Robot by Means of Human Thought

Brain computer interface (BCI) is a kind of human machine interface, which provides a new interaction method between human and computer or other equipment. The most significant characteristic of BCI system is that its control input is brain electrical activities acquired from the brain instead of traditional input such as hands or eyes. BCI technique has rapidly developed during last two decades and it has mainly worked as an auxiliary technique to help the disable people improve their life qualities. With the appearance of low cost novel electrical devices such as EMOTIV, BCI technique has been applied to the general public through many useful applications including video gaming, virtual reality and virtual keyboard. The purpose of this research is to be familiar with EMOTIV EPOC system and make use of it to build an EEG based BCI system for controlling an industrial manipulator by means of human thought. To build a BCI system, an acquisition program based on EMOTIV EPOC system is designed and a MFC based dialog that works as an operation panel is presented. Furthermore, the inverse kinematics of RV-3SB industrial robot was solved. In the last part of this research, the designed BCI system with human thought input is examined and the results indicate that the system is running smoothly and displays clearly the motion type and the incremental displacement of the motion.

Interaction between human cytomegalovirus UL136 protein and ATP1B1 protein

Interplay between the host and human cytomegalovirus (HCMV) has a pivotal role in the outcome of infection. A region (referred to as UL/b’) present in the Toledo strain of HCMV and low passage clinical isolates contains 19 additional genes, which are absent in the highly passaged laboratory strain AD169. Products of the UL/b’ genes may determine the manifestations of HCMV infection in vivo. However, little is known about the host factors, which interact with UL/b’ proteins. This study was conducted to investigate the function of the HCMV UL136 protein. By yeast two-hybrid screening, the β1 subunit of the host Na+/K+-ATPase (ATP1B1) was identified to be a candidate protein, which interacts with the HCMV UL136 protein. The interaction was further evaluated both in vitro by pull-down assay and in vivo by immunofluorescent co-localization. The results showed that the UL136 protein can interact with ATP1B1 in vitro. Co-localization of UL136-EGFP and ATP1B1-DsRed in cell membranes suggests that ATP1B1 was a partner of the UL136 protein. It can be proposed that the HCMV UL136 protein may have important roles in processes such as cell-to-cell spread, and in maintaining cell osmotic pressure and intracellular ion homeostasis during HCMV infection.

Novel Interaction Techniques for Mobile Augmented Reality applications. A Systematic Literature Review

This study reviews the research on interaction techniques and methods that could be applied in mobile augmented reality scenarios. The review is focused on themost recent advances and considers especially the use of head-mounted displays. Inthe review process, we have followed a systematic approach, which makes the reviewtransparent, repeatable, and less prone to human errors than if it was conducted in amore traditional manner. The main research subjects covered in the review are headorientation and gaze-tracking, gestures and body part-tracking, and multimodality– as far as the subjects are related to human-computer interaction. Besides these,also a number of other areas of interest will be discussed.

Examining human-centered design practice in the mobile apps era

Human-Centered Design (HCD) is a well-recognized approach to the design of interactive computing systems that supports everyday and professional lives of people. To that end, the HCD approach put central emphasis on the explicit understanding of users and context of use by involving users throughout the entire design and development process. With mobile computing, the diversity of users as well as the variety in the spatial, temporal, and social settings of the context of use has notably expanded, which affect the effort of interaction designers to understand users and context of use. The emergence of the mobile apps era in 2008 as a result of structural changes in the mobile industry and the profound enhanced capabilities of mobile devices, further intensify the embeddedness of technology in the daily life of people and the challenges that interaction designers face to cost-efficiently understand users and context of use. Supporting interaction designers in this challenge requires understanding of their existing practice, rationality, and work environment. The main objective of this dissertation is to contribute to interaction design theories by generating understanding on the HCD practice of mobile systems in the mobile apps era, as well as to explain the rationality of interaction designers in attending to users and context of use. To achieve that, a literature study is carried out, followed by a mixed-methods research that combines multiple qualitative interview studies and a quantitative questionnaire study. The dissertation contributes new insights regarding the evolving HCD practice at an important time of transition from stationary computing to mobile computing. Firstly, a gap is identified between interaction design as practiced in research and in the industry regarding the involvement of users in context; whereas the utilization of field evaluations, i.e. in real-life environments, has become more common in academic projects, interaction designers in the industry still rely, by large, on lab evaluations. Secondly, the findings indicate on new aspects that can explain this gap and the rationality of interaction designers in the industry in attending to users and context; essentially, the professional-client relationship was found to inhibit the involvement of users, while the mental distance between practitioners and users as well as the perceived innovativeness of the designed system are suggested in explaining the inclination to study users in situ. Thirdly, the research contributes the first explanatory model on the relation between the organizational context and HCD; essentially, innovation-focused organizational strategies greatly affect the cost-effective usage of data on users and context of use. Last, the findings suggest a change in the nature of HCD in the mobile apps era, at least with universal consumer systems; evidently, the central attention on the explicit understanding of users and context of use shifts from an early requirements phase and continual activities during design and development to follow-up activities. That is, the main effort to understand users is by collecting data on their actual usage of the system, either before or after the system is deployed. The findings inform both researchers and practitioners in interaction design. In particular, the dissertation suggest on action research as a useful approach to support interaction designers and further inform theories on interaction design. With regard to the interaction design practice, the dissertation highlights strategies that encourage a more cost-effective user- and context-informed interaction design process. With the continual embeddedness of computing into people’s life, e.g. with wearable devices and connected car systems, the dissertation provides a timely and valuable view on the evolving humancentered design.

Optimization-Based Robotic Manipulation for Safe Interaction with Human Operators

This thesis investigates a method for human-robot interaction (HRI) in order to uphold productivity of industrial robots like minimization of the shortest operation time, while ensuring human safety like collision avoidance. For solving such problems an online motion planning approach for robotic manipulators with HRI has been proposed. The approach is based on model predictive control (MPC) with embedded mixed integer programming. The planning strategies of the robotic manipulators mainly considered in the thesis are directly performed in the workspace for easy obstacle representation. The non-convex optimization problem is approximated by a mixed-integer program (MIP). It is further effectively reformulated such that the number of binary variables and the number of feasible integer solutions are drastically decreased. Safety-relevant regions, which are potentially occupied by the human operators, can be generated online by a proposed method based on hidden Markov models. In contrast to previous approaches, which derive predictions based on probability density functions in the form of single points, such as most likely or expected human positions, the proposed method computes safety-relevant subsets of the workspace as a region which is possibly occupied by the human at future instances of time. The method is further enhanced by combining reachability analysis to increase the prediction accuracy. These safety-relevant regions can subsequently serve as safety constraints when the motion is planned by optimization. This way one arrives at motion plans that are safe, i.e. plans that avoid collision with a probability not less than a predefined threshold. The developed methods have been successfully applied to a developed demonstrator, where an industrial robot works in the same space as a human operator. The task of the industrial robot is to drive its end-effector according to a nominal sequence of grippingmotion-releasing operations while no collision with a human arm occurs.

The Human in the Loop: User Participation in Self-Adaptive Software

Self-adaptive software provides a profound solution for adapting applications to changing contexts in dynamic and heterogeneous environments. Having emerged from Autonomic Computing, it incorporates fully autonomous decision making based on predefined structural and behavioural models. The most common approach for architectural runtime adaptation is the MAPE-K adaptation loop implementing an external adaptation manager without manual user control. However, it has turned out that adaptation behaviour lacks acceptance if it does not correspond to a user’s expectations – particularly for Ubiquitous Computing scenarios with user interaction. Adaptations can be irritating and distracting if they are not appropriate for a certain situation. In general, uncertainty during development and at run-time causes problems with users being outside the adaptation loop. In a literature study, we analyse publications about self-adaptive software research. The results show a discrepancy between the motivated application domains, the maturity of examples, and the quality of evaluations on the one hand and the provided solutions on the other hand. Only few publications analysed the impact of their work on the user, but many employ user-oriented examples for motivation and demonstration. To incorporate the user within the adaptation loop and to deal with uncertainty, our proposed solutions enable user participation for interactive selfadaptive software while at the same time maintaining the benefits of intelligent autonomous behaviour. We define three dimensions of user participation, namely temporal, behavioural, and structural user participation. This dissertation contributes solutions for user participation in the temporal and behavioural dimension. The temporal dimension addresses the moment of adaptation which is classically determined by the self-adaptive system. We provide mechanisms allowing users to influence or to define the moment of adaptation. With our solution, users can have full control over the moment of adaptation or the self-adaptive software considers the user’s situation more appropriately. The behavioural dimension addresses the actual adaptation logic and the resulting run-time behaviour. Application behaviour is established during development and does not necessarily match the run-time expectations. Our contributions are three distinct solutions which allow users to make changes to the application’s runtime behaviour: dynamic utility functions, fuzzy-based reasoning, and learning-based reasoning. The foundation of our work is a notification and feedback solution that improves intelligibility and controllability of self-adaptive applications by implementing a bi-directional communication between self-adaptive software and the user. The different mechanisms from the temporal and behavioural participation dimension require the notification and feedback solution to inform users on adaptation actions and to provide a mechanism to influence adaptations. Case studies show the feasibility of the developed solutions. Moreover, an extensive user study with 62 participants was conducted to evaluate the impact of notifications before and after adaptations. Although the study revealed that there is no preference for a particular notification design, participants clearly appreciated intelligibility and controllability over autonomous adaptations.

Low cost eye tracking for human-machine interfacing

One of the main challenges for developers of new human-computer interfaces is to provide a more natural way of interacting with computer systems, avoiding excessive use of hand and finger movements. In this way, also a valuable alternative communication pathway is provided to people suffering from motor disabilities. This paper describes the construction of a low cost eye tracker using a fixed head setup. Therefore a webcam, laptop and an infrared lighting source were used together with a simple frame to fix the head of the user. Furthermore, detailed information on the various image processing techniques used for filtering the centre of the pupil and different methods to calculate the point of gaze are discussed. An overall accuracy of 1.5 degrees was obtained while keeping the hardware cost of the device below 100 euros.

Improving computer interaction for older people - studying mouse clicks

Interactions using a standard computer mouse can be particularly difficult for novice and older adult users. Tasks that involve positioning the mouse over a target and double-clicking to initiate some action can be a real challenge for many users. Hence, this paper describes a study that investigates the double-click interactions of older and younger adults and presents data that can help inform the development of methods of assistance. Twelve older adults (mean age = 63.9 years) and 12 younger adults (mean age = 20.8 years) performed click and double-click target selections with a computer mouse. Initial results show that older users make approximately twice as many errors as younger users when attempting double-clicks. For both age groups, the largest proportion of errors was due to difficulties with keeping the cursor steady between button presses. Compared with younger adults, older adults experienced more difficulties with performing two button presses within a required time interval. Understanding these interactions better is a step towards improving accessibility, and may provide some suggestions for future directions of research in this area.

From activity to active learning: drawing and dialogue interaction in virtual learning environments for computer-supported collaborative work in design.

Virtual learning environments (VLEs) would appear to be particular effective in computer-supported collaborative work (CSCW) for active learning. Most research studies looking at computer-supported collaborative design have focused on either synchronous or asynchronous modes of communication, but near-synchronous working has received relatively little attention. Yet it could be argued that near-synchronous communication encourages creative, rhetorical and critical exchanges of ideas, building on each other’s contributions. Furthermore, although many researchers have carried out studies on collaborative design protocol, argumentation and constructive interaction, little is known about the interaction between drawing and dialogue in near-synchronous collaborative design. The paper reports the first stage of an investigation into the requirements for the design and development of interactive systems to support the learning of collaborative design activities. The aim of the study is to understand the collaborative design processes while sketching in a shared white board and audio conferencing media. Empirical data on design processes have been obtained from observation of seven sessions with groups of design students solving an interior space-planning problem of a lounge-diner in a virtual learning environment, Lyceum, an in-house software developed by the Open University to support its students in collaborative learning.