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Over the past few years, studying abroad and other educational international experiences have become increasingly highly regarded. Nevertheless, research shows that only a minority of students actually take part in
academic mobility programs. But what is it that distinguishes those students who take up these international opportunities from those who do not? In this
study we reviewed recent quantitative studies on why (primarily German) students choose to travel abroad or not. This revealed a pattern of predictive factors. These indicate the key role played by students’ personal and social background, as well as previous international travel and the course of studies they are enrolled in. The study then focuses on teaching students. Both facilitating and debilitating factors are discussed and included in a model illustrating the decision-making process these students use. Finally, we discuss the practical implications for ways in which international, studyrelated travel might be increased in the future. We suggest that higher education institutions analyze individual student characteristics, offering differentiated programs to better meet the needs of different groups, thus raising the likelihood of disadvantaged students participating in academic international travel.
The plant pathogen Pseudomonas syringae is a gram-negative bacterium which infects a wide range of plant species including important crops plants. To suppress plant immunity and cause disease P.syringae injects type-III effector proteins (T3Es) into the plant cell cytosol. In this study, we identified a novel target of the well characterized bacterial T3E HopZ1a. HopZ1a is an acetyltransferase that was shown to disrupt vesicle transport during innate immunity by acetylating tubulin. Using a yeast-two-hybrid screen approach, we identified a REMORIN (REM) protein from tobacco as a novel HopZ1a target. HopZ1a interacts with REM at the plasma membrane (PM) as shown by split-YFP experiments. Interestingly, we found that PBS1, a well-known kinase involved in plant immunity also interacts with REM in pull-down assays, and at the PM as shown by BiFC. Furthermore, we confirmed that REM is phosphorylated by PBS1 in vitro. Overexpression of REM provokes the upregulation of defense genes and leads to disease-like phenotypes pointing to a role of REM in plant immune signaling. Further protein-protein interaction studies reveal novel REM binding partners with a possible role in plant immune signaling. Thus, REM might act as an assembly hub for an immune signaling complex targeted by HopZ1a. Taken together, this is the first report describing that a REM protein is targeted by a bacterial effector. How HopZ1a might mechanistically manipulate the plant immune system through interfering with REM function will be discussed.
Declarative languages for knowledge representation and reasoning provide constructs to define preference relations over the set of possible interpretations, so that preferred models represent optimal solutions of the encoded problem. We introduce the notion of approximation for replacing preference relations with stronger preference relations, that is, relations comparing more pairs of interpretations. Our aim is to accelerate the computation of a non-empty subset of the optimal solutions by means of highly specialized algorithms. We implement our approach in Answer Set Programming (ASP), where problems involving quantitative and qualitative preference relations can be addressed by ASPRIN, implementing a generic optimization algorithm. Unlike this, chains of approximations allow us to reduce several preference relations to the preference relations associated with ASP’s native weak constraints and heuristic directives. In this way, ASPRIN can now take advantage of several highly optimized algorithms implemented by ASP solvers for computing optimal solutions
An energy consumption model for multiModal wireless sensor networks based on wake-up radio receivers
(2018)
Energy consumption is a major concern in Wireless Sensor Networks. A significant waste of energy occurs due to the idle listening and overhearing problems, which are typically avoided by turning off the radio, while no transmission is ongoing. The classical approach for allowing the reception of messages in such situations is to use a low-duty-cycle protocol, and to turn on the radio periodically, which reduces the idle listening problem, but requires timers and usually unnecessary wakeups. A better solution is to turn on the radio only on demand by using a Wake-up Radio Receiver (WuRx). In this paper, an energy model is presented to estimate the energy saving in various multi-hop network topologies under several use cases, when a WuRx is used instead of a classical low-duty-cycling protocol. The presented model also allows for estimating the benefit of various WuRx properties like using addressing or not.
The globally distributed sperm whale (Physeter macrocephalus) has a partly matrilineal social structure with predominant male dispersal. At the beginning of 2016, a total of 30 male sperm whales stranded in five different countries bordering the southern North Sea. It has been postulated that these individuals were on a migration route from the north to warmer temperate and tropical waters where females live in social groups. By including samples from four countries (n = 27), this event provided a unique chance to genetically investigate the maternal relatedness and the putative origin of these temporally and spatially co-occuring male sperm whales. To utilize existing genetic resources, we sequenced 422 bp of the mitochondrial control region, a molecular marker for which sperm whale data are readily available from the entire distribution range. Based on four single nucleotide polymorphisms (SNPs) within the mitochondrial control region, five matrilines could be distinguished within the stranded specimens, four of which matched published haplotypes previously described in the Atlantic. Among these male sperm whales, multiple matrilineal lineages co-occur. We analyzed the population differentiation and could show that the genetic diversity of these male sperm whales is comparable to the genetic diversity in sperm whales from the entire Atlantic Ocean. We confirm that within this stranding event, males do not comprise maternally related individuals and apparently include assemblages of individuals from different geographic regions. (c) 2017 Deutsche Gesellschaft fur Saugetierkunde. Published by Elsevier GmbH. All rights reserved.
The Aral Sea desiccation and related changes in hydroclimatic conditions on a regional level is a hot topic for past decades. The key problem of scientific research projects devoted to an investigation of modern Aral Sea basin hydrological regime is its discontinuous nature - the only limited amount of papers takes into account the complex runoff formation system entirely. Addressing this challenge we have developed a continuous prediction system for assessing freshwater inflow into the Small Aral Sea based on coupling stack of hydrological and data-driven models. Results show a good prediction skill and approve the possibility to develop a valuable water assessment tool which utilizes the power of classical physically based and modern machine learning models both for territories with complex water management system and strong water-related data scarcity. The source code and data of the proposed system is available on a Github page (https://github.com/SMASHIproject/IWRM2018).
A balance to death
(2018)
Leaf senescence plays a crucial role in nutrient recovery in late-stage plant development and requires vast transcriptional reprogramming by transcription factors such as ORESARA1 (ORE1). A proteolytic mechanism is now found to control ORE1 degradation, and thus senescence, during nitrogen starvation.
Detecting and recognizing text in natural scene images is a challenging, yet not completely solved task. In recent years several new systems that try to solve at least one of the two sub-tasks (text detection and text recognition) have been proposed. In this paper we present SEE, a step towards semi-supervised neural networks for scene text detection and recognition, that can be optimized end-to-end. Most existing works consist of multiple deep neural networks and several pre-processing steps. In contrast to this, we propose to use a single deep neural network, that learns to detect and recognize text from natural images, in a semi-supervised way. SEE is a network that integrates and jointly learns a spatial transformer network, which can learn to detect text regions in an image, and a text recognition network that takes the identified text regions and recognizes their textual content. We introduce the idea behind our novel approach and show its feasibility, by performing a range of experiments on standard benchmark datasets, where we achieve competitive results.
In university teaching today, it is common practice to record regular lectures and special events such as conferences and speeches. With these recordings, a large fundus of video teaching material can be created quickly and easily. Typically, lectures have a length of about one and a half hours and usually take place once or twice a week based on the credit hours. Depending on the number of lectures and other events recorded, the number of recordings available is increasing rapidly, which means that an appropriate form of provisioning is essential for the students. This is usually done in the form of lecture video platforms. In this work, we have investigated how lecture video platforms and the contained knowledge can be improved and accessed more easily by an increasing number of students. We came up with a multistep process we have applied to our own lecture video web portal that can be applied to other solutions as well.
Operational decisions in business processes can be modeled by using the Decision Model and Notation (DMN). The complementary use of DMN for decision modeling and of the Business Process Model and Notation (BPMN) for process design realizes the separation of concerns principle. For supporting separation of concerns during the design phase, it is crucial to understand which aspects of decision-making enclosed in a process model should be captured by a dedicated decision model. Whereas existing work focuses on the extraction of decision models from process control flow, the connection of process-related data and decision models is still unexplored. In this paper, we investigate how process-related data used for making decisions can be represented in process models and we distinguish a set of BPMN patterns capturing such information. Then, we provide a formal mapping of the identified BPMN patterns to corresponding DMN models and apply our approach to a real-world healthcare process.
Riback et al. (Reports, 13 October 2017, p. 238) used small-angle x-ray scattering (SAXS) experiments to infer a degree of compaction for unfolded proteins in water versus chemical denaturant that is highly consistent with the results from Forster resonance energy transfer (FRET) experiments. There is thus no "contradiction" between the two methods, nor evidence to support their claim that commonly used FRET fluorophores cause protein compaction.
ASEDS
(2018)
The Massive adoption of social media has provided new ways for individuals to express their opinion and emotion online. In 2016, Facebook introduced a new reactions feature that allows users to express their psychological emotions regarding published contents using so-called Facebook reactions. In this paper, a framework for predicting the distribution of Facebook post reactions is presented. For this purpose, we collected an enormous amount of Facebook posts associated with their reactions labels using the proposed scalable Facebook crawler. The training process utilizes 3 million labeled posts for more than 64,000 unique Facebook pages from diverse categories. The evaluation on standard benchmarks using the proposed features shows promising results compared to previous research. The final model is able to predict the reaction distribution on Facebook posts with a recall score of 0.90 for "Joy" emotion.
Background:
The overall goal of the project ‘StiEL’ is to contribute to the professional development of teachers and other educational staff working at German secondary schools. The aim is to develop an evidence-based training concept for the inclusion of students with diverse abilities. The project is organized as a collaborative research effort of three partnering institutions and funded by the German Federal Ministry of Education and Research from 2018-2021.
Methods:
To support the on-going transition towards inclusive school practices, a multi-stage approach is envisaged. The first phase aims at a scoping review of existing literature and programmes on inclusion. The overview is supplemented by interviews with school staff members. Training modules are developed in the second project phase. The third phase of StiEL puts the newly developed training program into practice. The knowledge and skills acquired by the participants through the training as well as the teaching and management of inclusive classrooms after the training are evaluated through longitudinal and ethnographic approaches. The final project phase creates a best practice manual and makes the modules available via open access databases.
Results:
The presentation will focus on the first phase and try to explore the health-related consequences of the transition towards an inclusive school system in Germany for different participants. We will present preliminary results of expert interviews as well as some results from the literature screening. Due to our findings the current practice on German schools towards the road to inclusion is very stressful for all participants. We will explore recommendations for health promoting schools under conditions of inclusion.
Conclusions:
In terms of health-related consequences for all participants, the road to inclusion is very ambitious but also very stressful. Regarding the development of an inclusive school system, we need to focus much more on health and health promotion.
Editorial
(2018)
"Never doubt that a small group of thoughtful, committed citizens can change the world; indeed, it's the only thing that ever has. - Margaret Mead."
With the last issue of this year we want to point out directions towards what will come and what challenges and opportunities lie ahead of us. More needed than ever are joint creative efforts to find ways to collaborate and innovate in order to secure the wellbeing of our earth for the next generation to come. We have found ourselves puzzled that we could assemble a sustainability issue without having a call for papers or a special issue. In fact, many of the submissions we currently receive, deal with sustainable, ecological or novel approaches to management and organizations. As creativity and innovation are undisputable necessary ingredients for reaching the sustainable development goals, empirical proof and research in this area are still in their infancy. While the role of design and design thinking has been highlighted before for solving wicked societal problems, a lot more research is needed which creative and innovative ways organisations and societies can take to find solutions to climate change, poverty, hunger and education. We would therefore like to call to you, our readers and writers to tackle these problems with your research.
The first article in this issue addresses one of the above named challenges - the role of innovation for achieving the transition to a low-carbon energy world. In “Innovating for low-carbon energy through hydropower: Enabling a conservation charity's transition to a low-carbon community”, the authors John Gallagher, Paul Coughlan, A. Prysor Williams and Aonghus McNabola look at how an eco-design approach has supported a community transition to low-carbon. They highlight the importance of effective management as well as external collaboration and how the key for success lay in fostering an open environment for creativity and idea sharing. The second article addresses another of the grand challenges, the future of mobility and uses a design-driven approach to develop scenarios for mobility in cities. In “Designing radical innovations of meanings for society: envisioning new scenarios for smart mobility”, the authors Claudio Dell'Era, Naiara Altuna and Roberto Verganti investigate how new meanings can be designed and proposed to society rather than to individuals in the particular context of smart mobility. Through two case studies the authors argue for a multi-level perspective, taking the perspective of the society to solve societal challenges while considering the needs of the individual. The latter is needed because we will not change if our needs are not addressed. Furthermore, the authors find that both, meaning and technology need to be considered to create radical innovation for society. The role of meaning continues in the third article in this issue. The authors Marta Gasparin and William Green show in their article “Reconstructing meaning without redesigning products: The case of the Serie7 chair” how meaning changes over time even though the product remains the same. Through an in-depth retrospective study of the Serie 7 chair the authors investigate the relationship between meaning and the materiality of the object, and show the importance of materiality in constructing product meaning over long periods. Translating this meaning over the course of the innovation process is an important task of management in order to gain buy-in from all involved stakeholders. In the following article “A systematic approach for new technology development by using a biomimicry-based TRIZ contradiction matrix” the authors Byungun Yoon, Chaeguk Lim, Inchae Park and Dooseob Yoon develop a systematic process combining biomimicry and technology-based TRIZ in order to solve technological problems or develop new technologies based on completely new sources or combinations from technology and biology.
In the fifth article in this issue “Innovating via Building Absorptive Capacity: Interactive Effects of Top Management Support of Learning, Employee Learning Orientation, and Decentralization Structure” the authors Li-Yun Sun, Chenwei Li and Yuntao Dong examine the effect of learning-related personal and contextual factors on organizational absorptive capability and subsequent innovative performance. The authors find positive effects as well as a moderation influence of decentralized organizational decision-making structures. In the sixth article “Creativity within boundaries: social identity and the development of new ideas in franchise systems” the authors Fanny Simon, Catherine Allix-Desfautaux, Nabil Khelil and Anne-Laure Le Nadant address the paradox of balancing novelty and conformity for creativity in a franchise system. This research is one of the first we know to explicitly address creativity and innovation in such a rigid and pre-determined system. Using a social identity perspective, they can show that social control, which may be exerted by manipulating group identity, is an efficient lever to increase both the creation and the diffusion of the idea. Furthermore, they show that franchisees who do not conform to the norm of the group are stigmatized and must face pressure from the group to adapt their behaviors. This has important implications for future research. In the following article “Exploring employee interactions and quality of contributions in intra-organisational innovation platforms” the authors Dimitra Chasanidou, Njål Sivertstol and Jarle Hildrum examine the user interactions in an intra-organisational innovation platform, and also address the influence of user interactions for idea development. The authors find that employees communicate through the innovation platform with different interaction, contribution and collaboration types and propose three types of contribution qualities—passive, efficient and balanced contribution. In the eighth article “Ready for Take-off”: How Open Innovation influences startup success” Cristina Marullo, Elena Casprini, Alberto di Minin and Andrea Piccaluga seek to predict new venture success based on factors that can be observed in the pre-startup phase. The authors introduce different variables of founding teams and how these relate to startup success. Building on large-scale dataset of submitted business plans at UC Berkeley, they can show that teams with high skills diversity and past joint experience are a lot better able to prevent the risk of business failure at entry and to adapt the internal resources to market conditions. Furthermore, it is crucial for the team to integrate many external knowledge sources into their process (openness) in order to be successful. The crucial role of knowledge and how it is communicated and shared is the focal point of Natalya Sergeeva's and Anna Trifilova's article on “The role of storytelling in the innovation process”. They authors can show how storytelling has an important role to play when it comes to motivating employees to innovate and promoting innovation success stories inside and outside the organization. The deep human desire to hear and experience stories is also addressed in the last article in this issue “Gamification Approaches to the Early Stage of Innovation” by Rui Patricio, Antonio Moreira and Francesco Zurlo. Using gamification approaches at the early stage of innovation promises to create better team coherence, let employees experience fun and engagement, improve communication and foster knowledge exchange. Using an analytical framework, the authors analyze 15 articles that have looked at gamification in the context of innovation management before. They find that gamification indeed supports firms in becoming better at performing complex innovation tasks and managing innovation challenges. Furthermore, gamification in innovation creates a space for inspiration, improves creativity and the generation of high potential ideas.
Modern routing algorithms reduce query time by depending heavily on preprocessed data. The recently developed Navigation Data Standard (NDS) enforces a separation between algorithms and map data, rendering preprocessing inapplicable. Furthermore, map data is partitioned into tiles with respect to their geographic coordinates. With the limited memory found in portable devices, the number of tiles loaded becomes the major factor for run time. We study routing under these restrictions and present new algorithms as well as empirical evaluations. Our results show that, on average, the most efficient algorithm presented uses more than 20 times fewer tile loads than a normal A*.
Modern server systems with large NUMA architectures necessitate (i) data being distributed over the available computing nodes and (ii) NUMA-aware query processing to enable effective parallel processing in database systems. As these architectures incur significant latency and throughout penalties for accessing non-local data, queries should be executed as close as possible to the data. To further increase both performance and efficiency, data that is not relevant for the query result should be skipped as early as possible. One way to achieve this goal is horizontal partitioning to improve static partition pruning. As part of our ongoing work on workload-driven partitioning, we have implemented a recent approach called aggressive data skipping and extended it to handle both analytical as well as transactional access patterns. In this paper, we evaluate this approach with the workload and data of a production enterprise system of a Global 2000 company. The results show that over 80% of all tuples can be skipped in average while the resulting partitioning schemata are surprisingly stable over time.
We investigated online electrophysiological components of distributional learning, specifically of tones by listeners of a non tonal language. German listeners were presented with a bimodal distribution of syllables with lexical tones from a synthesized continuum based on Cantonese level tones. Tones were presented in sets of four standards (within-category tokens) followed by a deviant (across-category token). Mismatch negativity (MMN) was measured. Earlier behavioral data showed that exposure to this bimodal distribution improved both categorical perception and perceptual acuity for level tones [I]. In the present study we present analyses of the electrophysiological response recorded during this exposure, i.e., the development of the MMN response during distributional learning. This development over time is analyzed using Generalized Additive Mixed Models and results showed that the MMN amplitude increased for both within and across-category tokens, reflecting higher perceptual acuity accompanying category formation. This is evidence that learners zooming in on phonological categories undergo neural changes associated with more accurate phonetic perception.
We consider chimera states in a one-dimensional medium of nonlinear nonlocally coupled phase oscillators. Stationary inhomogeneous solutions of the Ott-Antonsen equation for a complex order parameter that correspond to fundamental chimeras have been constructed. Stability calculations reveal that only some of these states are stable. The direct numerical simulation has shown that these structures under certain conditions are transformed to breathing chimera regimes because of the development of instability. Further development of instability leads to turbulent chimeras.
We propose a new temporal extension of the logic of Here-and-There (HT) and its equilibria obtained by combining it with dynamic logic over (linear) traces. Unlike previous temporal extensions of HT based on linear temporal logic, the dynamic logic features allow us to reason about the composition of actions. For instance, this can be used to exercise fine grained control when planning in robotics, as exemplified by GOLOG. In this paper, we lay the foundations of our approach, and refer to it as Linear Dynamic Equilibrium Logic, or simply DEL. We start by developing the formal framework of DEL and provide relevant characteristic results. Among them, we elaborate upon the relationships to traditional linear dynamic logic and previous temporal extensions of HT.
Foreword
(2018)
Imaginar la nación
(2018)
I can see it in your face
(2018)
We present a project combining lidar, photometer and particle counter data with a regularization software tool for a closure study of aerosol microphysical property retrieval. In a first step only lidar data are used to retrieve the particle size distribution (PSD). Secondly, photometer data are added, which results in a good consistency of the retrieved PSDs. Finally, those retrieved PSDs may be compared with the measured PSD from a particle counter. The data here were taken in Ny Alesund, Svalbard, as an example.
Learning how to prove
(2018)
We have developed an alternative approach to teaching computer science students how to prove. First, students are taught how to prove theorems with the Coq proof assistant. In a second, more difficult, step students will transfer their acquired skills to the area of textbook proofs. In this article we present a realisation of the second step. Proofs in Coq have a high degree of formality while textbook proofs have only a medium one. Therefore our key idea is to reduce the degree of formality from the level of Coq to textbook proofs in several small steps. For that purpose we introduce three proof styles between Coq and textbook proofs, called line by line comments, weakened line by line comments, and structure faithful proofs. While this article is mostly conceptional we also report on experiences with putting our approach into practise.
Kim et al. recently measured the structure factor of deeply supercooled water droplets (Reports, 22 December 2017, p. 1589). We raise several concerns about their data analysis and interpretation. In our opinion, the reported data do not lead to clear conclusions about the origins of water’s anomalies.
The present work is part of a collaborative H2020 European funded research project called SENSKIN, that aims to improve Structural Health Monitoring (SHM) for transport infrastructure through the development of an innovative monitoring and management system for bridges based on a novel, inexpensive, skin-like sensor. The integrated SENSKIN technology will be implemented in the case of steel and concrete bridges, and tested, field-evaluated and benchmarked on actual bridge environment against a conventional health monitoring solution developed by Mistras Group Hellas. The main objective of the present work is to implement the autonomous, fully functional strain monitoring system based on commercially available off-the-shelf components, that will be used to accomplish direct comparison between the performance of the innovative SENSKIN sensors and the conventional strain sensors commonly used for structural monitoring of bridges. For this purpose, the mini Structural Monitoring System (mini SMS) of Physical Acoustics Corporation, a comprehensive data acquisition unit designed specifically for long-term unattended operation in outdoor environments, was selected. For the completion of the conventional system, appropriate foil-type strain sensors were selected, driven by special conditioners manufactured by Mistras Group. A comprehensive description of the strain monitoring system and its peripheral components is provided in this paper. For the evaluation of the integrated system’s performance and the effect of various parameters on the long-term behavior of sensors, several test steel pieces instrumented with different strain sensors configurations were prepared and tested in both laboratory and field ambient conditions. Furthermore, loading tests were performed aiming to validate the response of the system in monitoring the strains developed in steel beam elements subject to bending regimes. Representative results obtained from the above experimental tests have been included in this paper as well.
Business processes constantly generate, manipulate, and consume data that are managed by organizational databases. Despite being central to process modeling and execution, the link between processes and data is often handled by developers when the process is implemented, thus leaving the connection unexplored during the conceptual design. In this paper, we introduce, formalize, and evaluate a novel conceptual view that bridges the gap between process and data models, and show some kinds of interesting insights that can be derived from this novel proposal.
Pace-of-life syndromes
(2018)
This introduction to the topical collection on Pace-of-life syndromes: a framework for the adaptive integration of behaviour, physiology, and life history provides an overview of conceptual, theoretical, methodological, and empirical progress in research on pace-of-life syndromes (POLSs) over the last decade. The topical collection has two main goals. First, we briefly describe the history of POLS research and provide a refined definition of POLS that is applicable to various key levels of variation (genetic, individual, population, species). Second, we summarise the main lessons learned from current POLS research included in this topical collection. Based on an assessment of the current state of the theoretical foundations and the empirical support of the POLS hypothesis, we propose (i) conceptual refinements of theory, particularly with respect to the role of ecology in the evolution of (sexual dimorphism in) POLS, and (ii) methodological and statistical approaches to the study of POLS at all major levels of variation. This topical collection further holds (iii) key empirical examples demonstrating how POLS structures may be studied in wild populations of (non) human animals, and (iv) a modelling paper predicting POLS under various ecological conditions. Future POLS research will profit from the development of more explicit theoretical models and stringent empirical tests of model assumptions and predictions, increased focus on how ecology shapes (sex-specific) POLS structures at multiple hierarchical levels, and the usage of appropriate statistical tests and study designs. Significance statement As an introduction to the topical collection, we summarise current conceptual, theoretical, methodological and empirical progress in research on pace-of-life syndromes (POLSs), a framework for the adaptive integration of behaviour, physiology and life history at multiple hierarchical levels of variation (genetic, individual, population, species). Mixed empirical support of POLSs, particularly at the within-species level, calls for an evaluation and refinement of the hypothesis. We provide a refined definition of POLSs facilitating testable predictions. Future research on POLSs will profit from the development of more explicit theoretical models and stringent empirical tests of model assumptions and predictions, increased focus on how ecology shapes (sex-specific) POLSs structures at multiple hierarchical levels and the usage of appropriate statistical tests and study designs.
Stable covalently photo-cross-linked porous poly(ionic liquid) membrane with gradient pore size
(2018)
Porous polyelectrolyte membranes stable in a highly ionic environment are obtained by covalent crosslinking of an imidazolium-based poly(ionic liquid). The crosslinking reaction involves the UV light-induced thiol-ene (click) chemistry, and the phase separation, occurring during the crosslinking step, generates a fully interconnected porous structure in the membrane. The porosity is on the order of the micrometer scale and the membrane shows a gradient of pore size across the membrane cross-section. The membrane can separate polystyrene latex particles of different size and undergoes actuation in contact with acetone due to the asymmetric porous structure.
The problem of constructing and maintaining a tree topology in a distributed manner is a challenging task in WSNs. This is because the nodes have limited computational and memory resources and the network changes over time. We propose the Dynamic Gallager-Humblet-Spira (D-GHS) algorithm that builds and maintains a minimum spanning tree. To do so, we divide D-GHS into four phases, namely neighbor discovery, tree construction, data collection, and tree maintenance. In the neighbor discovery phase, the nodes collect information about their neighbors and the link quality. In the tree construction, D-GHS finds the minimum spanning tree by executing the Gallager-Humblet-Spira algorithm. In the data collection phase, the sink roots the minimum spanning tree at itself, and each node sends data packets. In the tree maintenance phase, the nodes repair the tree when communication failures occur. The emulation results show that D-GHS reduces the number of control messages and the energy consumption, at the cost of a slight increase in memory size and convergence time.
3D point cloud technology facilitates the automated and highly detailed digital acquisition of real-world environments such as assets, sites, cities, and countries; the acquired 3D point clouds represent an essential category of geodata used in a variety of geoinformation applications and systems. In this paper, we present a web-based system for the interactive and collaborative exploration and inspection of arbitrary large 3D point clouds. Our approach is based on standard WebGL on the client side and is able to render 3D point clouds with billions of points. It uses spatial data structures and level-of-detail representations to manage the 3D point cloud data and to deploy out-of-core and web-based rendering concepts. By providing functionality for both, thin-client and thick-client applications, the system scales for client devices that are vastly different in computing capabilities. Different 3D point-based rendering techniques and post-processing effects are provided to enable task-specific and data-specific filtering and highlighting, e.g., based on per-point surface categories or temporal information. A set of interaction techniques allows users to collaboratively work with the data, e.g., by measuring distances and areas, by annotating, or by selecting and extracting data subsets. Additional value is provided by the system's ability to display additional, context-providing geodata alongside 3D point clouds and to integrate task-specific processing and analysis operations. We have evaluated the presented techniques and the prototype system with different data sets from aerial, mobile, and terrestrial acquisition campaigns with up to 120 billion points to show their practicality and feasibility.
The Amyloid-precursor-like protein 1 (APLP1) is a neuronal type I transmembrane protein which plays a role in synaptic adhesion and synaptogenesis. Past investigations indicated that APLP1 is involved in the formation of protein-protein complexes that bridge the junctions between neighboring cells. Nevertheless, APLP1-APLP1 trans interactions have never been directly observed in higher eukaryotic cells. Here, we investigate APLP1 interactions and dynamics directly in living human embryonic kidney (HEK) cells, using fluorescence fluctuation spectroscopy techniques, namely cross-correlation scanning fluorescence correlation spectroscopy (sFCS) and Number&Brightness (N&B). Our results show that APLP1 forms homotypic trans complexes at cell-cell contacts. In the presence of zinc ions, the protein forms macroscopic clusters, exhibiting an even higher degree of trans binding and strongly reduced dynamics. Further evidence from Giant Plasma Membrane Vesicles and live cell actin staining suggests that the presence of an intact cortical cytoskeleton is required for zinc-induced cis multimerization. Subsequently, large adhesion platforms bridging interacting cells are formed through APLP1-APLP1 direct trans interactions. Taken together, our results provide direct evidence that APLP1 functions as a neuronal zinc-dependent adhesion protein and provide a more detailed understanding of the molecular mechanisms driving the formation of APLP1 adhesion platforms. Further, they show that fluorescence fluctuation spectroscopy techniques are useful tools for the investigation of protein-protein interactions at cell-cell adhesion sites.
Development of a tool to identify intensive care patients at risk of meropenem therapy failure
(2018)
The problem of atmospheric emission from OH molecules is a long standing problem for near-infrared astronomy. PRAXIS is a unique spectrograph which is fed by fibres that remove the OH background and is optimised specifically to benefit from OH-Suppression. The OH suppression is achieved with fibre Bragg gratings, which were tested successfully on the GNOSIS instrument. PRAXIS uses the same fibre Bragg gratings as GNOSIS in its first implementation, and will exploit new, cheaper and more efficient, multicore fibre Bragg gratings in the second implementation. The OH lines are suppressed by a factor of similar to 1000, and the expected increase in the signal-to-noise in the interline regions compared to GNOSIS is a factor of similar to 9 with the GNOSIS gratings and a factor of similar to 17 with the new gratings. PRAXIS will enable the full exploitation of OH suppression for the first time, which was not achieved by GNOSIS (a retrofit to an existing instrument that was not OH-Suppression optimised) due to high thermal emission, low spectrograph transmission and detector noise. PRAXIS has extremely low thermal emission, through the cooling of all significantly emitting parts, including the fore-optics, the fibre Bragg gratings, a long length of fibre, and the fibre slit, and an optical design that minimises leaks of thermal emission from outside the spectrograph. PRAXIS has low detector noise through the use of a Hawaii-2RG detector, and a high throughput through a efficient VPH based spectrograph. PRAXIS will determine the absolute level of the interline continuum and enable observations of individual objects via an IFU. In this paper we give a status update and report on acceptance tests.
Live migration is an important feature in modern software-defined datacenters and cloud computing environments. Dynamic resource management, load balance, power saving and fault tolerance are all dependent on the live migration feature. Despite the importance of live migration, the cost of live migration cannot be ignored and may result in service availability degradation. Live migration cost includes the migration time, downtime, CPU overhead, network and power consumption. There are many research articles that discuss the problem of live migration cost with different scopes like analyzing the cost and relate it to the parameters that control it, proposing new migration algorithms that minimize the cost and also predicting the migration cost. For the best of our knowledge, most of the papers that discuss the migration cost problem focus on open source hypervisors. For the research articles focus on VMware environments, none of the published articles proposed migration time, network overhead and power consumption modeling for single and multiple VMs live migration. In this paper, we propose empirical models for the live migration time, network overhead and power consumption for single and multiple VMs migration. The proposed models are obtained using a VMware based testbed.
No other means of communication determines through its seemingly unrestricted possibilities our everyday life more than the internet. From the mid-90s onwards, more and more technical advancements in the field of communication appear on the market, which in turn call for new terminology. In the first place, it is the internet (essentially based on the interaction between users and experts), which requires effective nomenclature in order to mediate between lay users and their restricted knowledge on the one, and experts and their sophisticated terminology on the other hand. At the interface between the new and complex realities and the need for simple linguistic access, a huge quantity of metaphoric denominations is used, making abstract innovations more comprehensible. Metaphor in the internet discourse serves to "reduce verticality" (Stenschke 2006) between specialized terminology and common language. The paper deals with metaphors based on spatial concepts. Space and spatiality play a key role in cognitive theories of metaphor as these theories themselves (according to Lakoff/Johnson 1980) are often based on the application of spatial concepts to non-spatial relations. After describing spatial concepts in general (referring to the internet), the paper explores which kind of metaphor takes advantage of the complexity present in the internet and how the medial space is linguistically recaptured in terms of spatial perception.
Skeletal muscle alterations during aging lead to dysfunctional metabolism, correlating with frailty and early mortality. The loss of proteostasis is a hallmark of aging. Whether proteostasis loss plays a role in muscle aging remains elusive. To address this question we collected muscles, Soleus (SOL, type I) and Extensor digitorum longus (EDL, type II), from young (4 months) and old (25 months) C57BL/6 mice and evaluated the proteasomal system. Initial work showed decreased 26 S activity in old SOL. EDL displayed lower proteasomal activity in both ages compared to any of the SOL ages. Moreover, in order to understand if during aging there is the so-called “fiber switch from fast-to-slow”, we performed western blots against sMHC and fMHC (slow and fast myosin heavy chain, respectively). Preliminary results suggest that young SOL is composed by slow twitch fibers but also contains fast twitch fibers, while young EDL seems to be mostly composed by fast twitch fibers that level down during aging, suggesting the switch. As a conclusion, EDL seems to have less proteasomal activity, however, if this is a contributor or a consequence to the muscle fiber switch during aging still needs further investigation.
We present a prototype of an integrated reasoning environment for educational purposes. The presented tool is a fragment of a proof assistant and automated theorem prover. We describe the existing and planned functionality of the theorem prover and especially the functionality of the educational fragment. This currently supports working with terms of the untyped lambda calculus and addresses both undergraduate students and researchers. We show how the tool can be used to support the students' understanding of functional programming and discuss general problems related to the process of building theorem proving software that aims at supporting both research and education.
Currently we are witnessing profound changes in the geospatial domain. Driven by recent ICT developments, such as web services, serviceoriented computing or open-source software, an explosion of geodata and geospatial applications or rapidly growing communities of non-specialist users, the crucial issue is the provision and integration of geospatial intelligence in these rapidly changing, heterogeneous developments. This paper introduces the concept of Servicification into geospatial data processing. Its core idea is the provision of expertise through a flexible number of web-based software service modules. Selection and linkage of these services to user profiles, application tasks, data resources, or additional software allow for the compilation of flexible, time-sensitive geospatial data handling processes. Encapsulated in a string of discrete services, the approach presented here aims to provide non-specialist users with geospatial expertise required for the effective, professional solution of a defined application problem. Providing users with geospatial intelligence in the form of web-based, modular services, is a completely different approach to geospatial data processing. This novel concept puts geospatial intelligence, made available through services encapsulating rule bases and algorithms, in the centre and at the disposal of the users, regardless of their expertise.
We analyze the problem of response suggestion in a closed domain along a real-world scenario of a digital library. We present a text-processing pipeline to generate question-answer pairs from chat transcripts. On this limited amount of training data, we compare retrieval-based, conditioned-generation, and dedicated representation learning approaches for response suggestion. Our results show that retrieval-based methods that strive to find similar, known contexts are preferable over parametric approaches from the conditioned-generation family, when the training data is limited. We, however, identify a specific representation learning approach that is competitive to the retrieval-based approaches despite the training data limitation.
Background: Pavlovian processes are thought to play an important role in the development, maintenance and relapse of alcohol dependence, possibly by influencing and usurping on- going thought and behavior. The influence of Pavlovian stimuli on on-going behavior is paradigmatically measured by Pavlovian-to-instrumental-transfer (PIT) tasks. These involve multiple stages and are complex. Whether increased PIT is involved in human alcohol
dependence is uncertain. We therefore aimed to establish and validate a modified PIT paradigm that would be robust, consistent, and tolerated by healthy controls as well as by patients suffering from alcohol dependence, and to explore whether alcohol dependence is associated with enhanced Pavlovian-Instrumental transfer.
Methods: 32 recently detoxified alcohol-dependent patients and 32 age and gender matched healthy controls performed a PIT task with instrumental go/no-go approach behaviours. The task involved both Pavlovian stimuli associated with monetary rewards and losses, and images of drinks.
Results: Both patients and healthy controls showed a robust and temporally stable PIT effect. Strengths of PIT effects to drug-related and monetary conditioned stimuli were highly correlated. Patients more frequently showed a PIT effect and the effect was stronger in response to aversively conditioned CSs (conditioned suppression), but there was no group difference in response to appetitive CSs.
Conclusion: The implementation of PIT has favorably robust properties in chronic alcohol- dependent patients and in healthy controls. It shows internal consistency between monetary and drug-related cues. The findings support an association of alcohol dependence with an increased propensity towards PIT.
The classification of vulnerabilities is a fundamental step to derive formal attributes that allow a deeper analysis. Therefore, it is required that this classification has to be performed timely and accurate. Since the current situation demands a manual interaction in the classification process, the timely processing becomes a serious issue. Thus, we propose an automated alternative to the manual classification, because the amount of identified vulnerabilities per day cannot be processed manually anymore. We implemented two different approaches that are able to automatically classify vulnerabilities based on the vulnerability description. We evaluated our approaches, which use Neural Networks and the Naive Bayes methods respectively, on the base of publicly known vulnerabilities.
We compare the robustness of humans and current convolutional deep neural networks (DNNs) on object recognition under twelve different types of image degradations. First, using three well known DNNs (ResNet-152, VGG-19, GoogLeNet) we find the human visual system to be more robust to nearly all of the tested image manipulations, and we observe progressively diverging classification error-patterns between humans and DNNs when the signal gets weaker. Secondly, we show that DNNs trained directly on distorted images consistently surpass human performance on the exact distortion types they were trained on, yet they display extremely poor generalisation abilities when tested on other distortion types. For example, training on salt-and-pepper noise does not imply robustness on uniform white noise and vice versa. Thus, changes in the noise distribution between training and testing constitutes a crucial challenge to deep learning vision systems that can be systematically addressed in a lifelong machine learning approach. Our new dataset consisting of 83K carefully measured human psychophysical trials provide a useful reference for lifelong robustness against image degradations set by the human visual system.
An essential, respected, and critical aspect of the modern practice of science and scientific publishing is peer review. The process of peer review facilitates best practices in scientific conduct and communication, ensuring that manuscripts published as accurate, valuable, and clearly communicated. The over 152 papers published in Tectonics in 2017 benefit from the time, effort, and expertise of our reviewers who have provided thoughtfully considered advice on each manuscript. This role is critical to advancing our understanding of the evolution of the continents and their margins, as these reviews lead to even clearer and higher-quality papers. In 2017, the over 423 papers submitted to Tectonics were the beneficiaries of more than 786 reviews provided by 562 members of the tectonics community and related disciplines. To everyone who has volunteered their time and intellect to peer reviewing, thank you for helping Tectonics and all other AGU Publications provide the best science possible.
Editorial: Reaching to Grasp Cognition: Analyzing Motor Behavior to Investigate Social Interactions
(2018)
Why choice matters
(2018)
Measures of democracy are in high demand. Scientific and public audiences use them to describe political realities and to substantiate causal claims about those realities. This introduction to the thematic issue reviews the history of democracy measurement since the 1950s. It identifies four development phases of the field, which are characterized by three recurrent topics of debate: (1) what is democracy, (2) what is a good measure of democracy, and (3) do our measurements of democracy register real-world developments? As the answers to those questions have been changing over time, the field of democracy measurement has adapted and reached higher levels of theoretical and methodological sophistication. In effect, the challenges facing contemporary social scientists are not only limited to the challenge of constructing a sound index of democracy. Today, they also need a profound understanding of the differences between various measures of democracy and their implications for empirical applications. The introduction outlines how the contributions to this thematic issue help scholars cope with the recurrent issues of conceptualization, measurement, and application, and concludes by identifying avenues for future research.
PlAnalyzer
(2018)
In this work we propose PIAnalyzer, a novel approach to analyze PendingIntent related vulnerabilities. We empirically evaluate PIAnalyzer on a set of 1000 randomly selected applications from the Google Play Store and find 1358 insecure usages of Pendinglntents, including 70 severe vulnerabilities. We manually inspected ten reported vulnerabilities out of which nine correctly reported vulnerabilities, indicating a high precision. The evaluation shows that PIAnalyzer is efficient with an average execution time of 13 seconds per application.
The collaboration during the modeling process is uncomfortable and characterized by various limitations. Faced with the successful transfer of first process modeling languages to the augmented world, non-transparent processes can be visualized in a more comprehensive way. With the aim to rise comfortability, speed, accuracy and manifoldness of real world process augmentations, a framework for the bidirectional interplay of the common process modeling world and the augmented world has been designed as morphologic box. Its demonstration proves the working of drawn AR integrations. Identified dimensions were derived from (1) a designed knowledge construction axiom, (2) a designed meta-model, (3) designed use cases and (4) designed directional interplay modes. Through a workshop-based survey, the so far best AR modeling configuration is identified, which can serve for benchmarks and implementations.
The centrosome is not only the largest and most sophisticated protein complex within a eukaryotic cell, in the light of evolution, it is also one of its most ancient organelles. This special issue of "Cells" features representatives of three main, structurally divergent centrosome types, i.e., centriole-containing centrosomes, yeast spindle pole bodies (SPBs), and amoebozoan nucleus-associated bodies (NABs). Here, I discuss their evolution and their key-functions in microtubule organization, mitosis, and cytokinesis. Furthermore, I provide a brief history of centrosome research and highlight recently emerged topics, such as the role of centrioles in ciliogenesis, the relationship of centrosomes and centriolar satellites, the integration of centrosomal structures into the nuclear envelope and the involvement of centrosomal components in non-centrosomal microtubule organization.
One paragraph of the manuscript of the paper has been inadvertently omitted in the very final stage of its compilation due to a technical mistake. Since this paragraph discusses the declustering of the used earthquake catalogue and is therefore necessary for the understanding of the seismicity data preprocessing, the authors decided to provide this paragraph in form of a correction. The respective paragraph belongs to chapter 2 of the paper, where it was placed originally, and should be inserted into the published paper before the second to the last paragraph. The omitted text reads as follows:
Recently blockchain technology has been introduced to execute interacting business processes in a secure and transparent way. While the foundations for process enactment on blockchain have been researched, the execution of decisions on blockchain has not been addressed yet. In this paper we argue that decisions are an essential aspect of interacting business processes, and, therefore, also need to be executed on blockchain. The immutable representation of decision logic can be used by the interacting processes, so that decision taking will be more secure, more transparent, and better auditable. The approach is based on a mapping of the DMN language S-FEEL to Solidity code to be run on the Ethereum blockchain. The work is evaluated by a proof-of-concept prototype and an empirical cost evaluation.
Screeninginstrumente
(2018)
Oxidative posttranslationale Modifikationen endogener Proteine werden v. a. durch reaktive Sauerstoff- und Stickstoffspezies (engl:. Reactive Oxygen Species, ROS, reactive nitrogen species, RNS) hervorgerufen und können sowohl reversibel (z. B. Disulfidbindungen) als auch irreversibel (z. B. Proteincarbonyle) erfolgen [1–3]. Lange wurde angenommen, dass oxidative posttranslationale Proteinmodifikationen (oxPTPM) nur von untergeordneter Bedeutung für den Metabolismus sind. Tatsächlich handelt es sich jedoch um einen physiologischen Prozess, der über die Modulation der Proteinstruktur auch die Proteinfunktion (z. B. Enzymaktivität, Stabilität) und somit zahlreiche Stoffwechselwege wie den Energiestoffwechsel, die Immunfunktion, die vaskuläre Funktion sowie Apoptose und Genexpression beeinflussen kann. Die Bildung von oxPTPM ist dabei hochreguliert und hängt u. a. von der Proteinstruktur, der Verfügbarkeit von ROS und RNS sowie dem lokalen Mikromilieu der Zelle ab [2, 4].
In Europe, different countries developed a rich variety of sub-municipal institutions. Out of the plethora of intra- and sub-municipal decentralization forms (reaching from local outposts of city administration to “quasi-federal” structures), this book focuses on territorial sub-municipal units (SMUs) which combine multipurpose territorial responsibility with democratic legitimacy and can be seen as institutions promoting the articulation and realization of collective choices at a sub-municipal level.
Country chapters follow a common pattern that is facilitating systematic comparisons, while at the same time leaving enough space for national peculiarities and priorities chosen and highlighted by the authors, who also take advantage of the eventually existing empirical surveys and case studies.
Voice onset time (VOT), a primary cue for voicing in many languages including English and German, is known to vary greatly between speakers, but also displays robust within-speaker consistencies, at least in English. The current analysis extends these findings to German. VOT measures were investigated from voiceless alveolar and velar stops in CV syllables cued by a visual prompt in a cue-distractor task. Comparably to English, a considerable portion of German VOT variability can be attributed to the syllable’s vowel length and the stop’s place of articulation. Individual differences in VOT still remain irrespective of speech rate. However, significant correlations across places of articulation and between speaker-specific mean VOTs and standard deviations indicate that talkers employ a relatively unified VOT profile across places of articulation. This could allow listeners to more efficiently adapt to speaker-specific realisations.
Metamaterial Devices
(2018)
In our hands-on demonstration, we show several objects, the functionality of which is defined by the objects' internal micro-structure. Such metamaterial machines can (1) be mechanisms based on their microstructures, (2) employ simple mechanical computation, or (3) change their outside to interact with their environment. They are 3D printed from one piece and we support their creating by providing interactive software tools.
Introduction
(2018)
The present thematic set of studies comprises five concise review articles on the use of priming paradigms in different areas of bilingualism research. Their aim is to provide readers with a quick overview of how priming paradigms can be employed in particular subfields of bilingualism research and to make readers aware of the methodological issues that need to be considered when using priming techniques.
Preface
(2018)
One-tube osmotic fragility (OF) test is a rapid test used widely for screening thalassemia in countries with limited resources. The test has important limitation in that its accuracy relies on observers’ experience.
The iCheck Turbidity is a prototype of portable nephelometer developed by BioAnalyt (Bioanalyt GmbH, Germany). In this study, we assessed the applicability of the iCheck Turbidity, for checking turbidity of the OF-test
We study the rupture processes of Iquique earthquake 8.1 (2014/04/01) and its largest aftershock 7.7 (2014/04/03) that ruptured the North Chile subduction zone. High-rate Global Positioning System (GPS) recordings and strong motion data are used to reconstruct the evolution of the slip amplitude, rise time and rupture time of both earthquakes. A two-step inversion scheme is assumed, by first building prior models for both earthquakes from the inversion of the estimated static displacements and then, kinematic inversions in the frequency domain are carried out taken into account this prior information. The preferred model for the mainshock exhibits a seismic moment of 1.73 × 1021 Nm ( 8.1) and maximum slip of ∼9 m, while the aftershock model has a seismic moment of 3.88 × 1020 ( 7.7) and a maximum slip of ∼3 m. For both earthquakes, the final slip distributions show two asperities (a shallow one and a deep one) separated by an area with significant slip deficit. This suggests a segmentation along-dip which might be related to a change of the dipping angle of the subducting slab inferred from gravimetric data. Along-strike, the areas where the seismic ruptures stopped seem to be well correlated with geological features observed from geophysical information (high-resolution bathymetry, gravimetry and coupling maps) that are representative of the long-term segmentation of the subduction margin. Considering the spatially limited portions that were broken by these two earthquakes, our results support the idea that the seismic gap is not filled yet.
Konrad Repgen (1923-2017)
(2018)
Studies indicate that reliable access to power is an important enabler for economic growth. To this end, modern energy management systems have seen a shift from reliance on time-consuming manual procedures , to highly automated management , with current energy provisioning systems being run as cyber-physical systems . Operating energy grids as a cyber-physical system offers the advantage of increased reliability and dependability , but also raises issues of security and privacy. In this chapter, we provide an overview of the contents of this book showing the interrelation between the topics of the chapters in terms of smart energy provisioning. We begin by discussing the concept of smart-grids in general, proceeding to narrow our focus to smart micro-grids in particular. Lossy networks also provide an interesting framework for enabling the implementation of smart micro-grids in remote/rural areas, where deploying standard smart grids is economically and structurally infeasible. To this end, we consider an architectural design for a smart micro-grid suited to low-processing capable devices. We model malicious behaviour, and propose mitigation measures based properties to distinguish normal from malicious behaviour .
Several areas in Southeast Asia are very vulnerable to climate change and unable to take immediate/effective actions on countermeasures due to insufficient capabilities. Malaysia, in particular the east coast of peninsular Malaysia and Sarawak, is known as one of the vulnerable regions to flood disaster. Prolonged and intense rainfall, natural activities and increase in runoff are the main reasons to cause flooding in this area. In addition, topographic conditions also contribute to the occurrence of flood disaster. Kuching city is located in the northwest of Borneo Island and part of Sarawak river catchment. This area is a developing state in Malaysia experiencing rapid urbanization since 2000s, which has caused the insufficient data availability in topography and hydrology. To deal with these challenging issues, this study presents a flood modelling framework using the remote sensing technologies and machine learning techniques to acquire the digital elevation model (DEM) with improved accuracy for the non-surveyed areas. Intensity–duration–frequency (IDF) curves were derived from climate model for various scenario simulations. The developed flood framework will be beneficial for the planners, policymakers, stakeholders as well as researchers in the field of water resource management in the aspect of providing better ideas/tools in dealing with the flooding issues in the region.
Beware of SMOMBIES
(2018)
Several research evaluated the user's style of walking for the verification of a claimed identity and showed high authentication accuracies in many settings. In this paper we present a system that successfully verifies a user's identity based on many real world smartphone placements and yet not regarded interactions while walking. Our contribution is the distinction of all considered activities into three distinct subsets and a specific one-class Support Vector Machine per subset. Using sensor data of 30 participants collected in a semi-supervised study approach, we prove that unsupervised verification is possible with very low false-acceptance and false-rejection rates. We furthermore show that these subsets can be distinguished with a high accuracy and demonstrate that this system can be deployed on off-the-shelf smartphones.
TrussFormer
(2018)
We present TrussFormer, an integrated end-to-end system that allows users to 3D print large-scale kinetic structures, i.e., structures that involve motion and deal with dynamic forces. TrussFormer builds on TrussFab, from which it inherits the ability to create static large-scale truss structures from 3D printed connectors and PET bottles. TrussFormer adds movement to these structures by placing linear actuators into them: either manually, wrapped in reusable components called assets, or by demonstrating the intended movement. TrussFormer verifies that the resulting structure is mechanically sound and will withstand the dynamic forces resulting from the motion. To fabricate the design, TrussFormer generates the underlying hinge system that can be printed on standard desktop 3D printers. We demonstrate TrussFormer with several example objects, including a 6-legged walking robot and a 4m-tall animatronics dinosaur with 5 degrees of freedom.
802.15.4 security protects against the replay, injection, and eavesdropping of 802.15.4 frames. A core concept of 802.15.4 security is the use of frame counters for both nonce generation and anti-replay protection. While being functional, frame counters (i) cause an increased energy consumption as they incur a per-frame overhead of 4 bytes and (ii) only provide sequential freshness. The Last Bits (LB) optimization does reduce the per-frame overhead of frame counters, yet at the cost of an increased RAM consumption and occasional energy-and time-consuming resynchronization actions. Alternatively, the timeslotted channel hopping (TSCH) media access control (MAC) protocol of 802.15.4 avoids the drawbacks of frame counters by replacing them with timeslot indices, but findings of Yang et al. question the security of TSCH in general. In this paper, we assume the use of ContikiMAC, which is a popular asynchronous MAC protocol for 802.15.4 networks. Under this assumption, we propose an Intra-Layer Optimization for 802.15.4 Security (ILOS), which intertwines 802.15.4 security and ContikiMAC. In effect, ILOS reduces the security-related per-frame overhead even more than the LB optimization, as well as achieves strong freshness. Furthermore, unlike the LB optimization, ILOS neither incurs an increased RAM consumption nor requires resynchronization actions. Beyond that, ILOS integrates with and advances other security supplements to ContikiMAC. We implemented ILOS using OpenMotes and the Contiki operating system.
This paper proposes an education approach for master and bachelor students to enhance their skills in the area of reliability, safety and security of the electronic components in automated driving. The approach is based on the active synergetic work of research institutes, academia and industry in the frame of joint lab. As an example, the jointly organized summer school with the respective focus is organized and elaborated.
For the last ten years, almost every theoretical result concerning the expected run time of a randomized search heuristic used drift theory, making it the arguably most important tool in this domain. Its success is due to its ease of use and its powerful result: drift theory allows the user to derive bounds on the expected first-hitting time of a random process by bounding expected local changes of the process - the drift. This is usually far easier than bounding the expected first-hitting time directly. Due to the widespread use of drift theory, it is of utmost importance to have the best drift theorems possible. We improve the fundamental additive, multiplicative, and variable drift theorems by stating them in a form as general as possible and providing examples of why the restrictions we keep are still necessary. Our additive drift theorem for upper bounds only requires the process to be nonnegative, that is, we remove unnecessary restrictions like a finite, discrete, or bounded search space. As corollaries, the same is true for our upper bounds in the case of variable and multiplicative drift.
One of the most important aspects of a randomized algorithm is bounding its expected run time on various problems. Formally speaking, this means bounding the expected first-hitting time of a random process. The two arguably most popular tools to do so are the fitness level method and drift theory. The fitness level method considers arbitrary transition probabilities but only allows the process to move toward the goal. On the other hand, drift theory allows the process to move into any direction as long as it move closer to the goal in expectation; however, this tendency has to be monotone and, thus, the transition probabilities cannot be arbitrary. We provide a result that combines the benefit of these two approaches: our result gives a lower and an upper bound for the expected first-hitting time of a random process over {0,..., n} that is allowed to move forward and backward by 1 and can use arbitrary transition probabilities. In case that the transition probabilities are known, our bounds coincide and yield the exact value of the expected first-hitting time. Further, we also state the stationary distribution as well as the mixing time of a special case of our scenario.
For theoretical analyses there are two specifics distinguishing GP from many other areas of evolutionary computation. First, the variable size representations, in particular yielding a possible bloat (i.e. the growth of individuals with redundant parts). Second, the role and realization of crossover, which is particularly central in GP due to the tree-based representation. Whereas some theoretical work on GP has studied the effects of bloat, crossover had a surprisingly little share in this work. We analyze a simple crossover operator in combination with local search, where a preference for small solutions minimizes bloat (lexicographic parsimony pressure); the resulting algorithm is denoted Concatenation Crossover GP. For this purpose three variants of the wellstudied Majority test function with large plateaus are considered. We show that the Concatenation Crossover GP can efficiently optimize these test functions, while local search cannot be efficient for all three variants independent of employing bloat control.