957 resultados para cyber-physical systems


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The translational diffusion of water in compacted clays at a high hydration level has been investigated by quasielastic neutron scattering at a time-of-flight spectrometer FOCUS (SINQ). Four compacted clays with systematic structural differences have been studied: Na-montmorillonite, Na-illite, kaolinite and pyrophyllite. The QENS experiments were performed using two different incident wavelengths in order to access a larger Q range and verify the data analysis. The translational diffusion coefficient for water in Na-montmorillonite and Na-illite are lower than those for bulk water, whereas the preliminary results for kaolinite and pyrophyllite show larger diffusion coefficient.

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Complete NotI, SfiI, XbaI and BlnI cleavage maps of Escherichia coli K-12 strain MG1655 were constructed. Techniques used included: CHEF pulsed field gel electrophoresis; transposon mutagenesis; fragment hybridization to the ordered $\lambda$ library of Kohara et al.; fragment and cosmid hybridization to Southern blots; correlation of fragments and cleavage sites with EcoMap, a sequence-modified version of the genomic restriction map of Kohara et al.; and correlation of cleavage sites with DNA sequence databases. In all, 105 restriction sites were mapped and correlated with the EcoMap coordinate system.^ NotI, SfiI, XbaI and BlnI restriction patterns of five commonly used E. coli K-12 strains were compared to those of MG1655. The variability between strains, some of which are separated by numerous steps of mutagenic treatment, is readily detectable by pulsed-field gel electrophoresis. A model is presented to account for the difference between the strains on the basis of simple insertions, deletions, and in one case an inversion. Insertions and deletions ranged in size from 1 kb to 86 kb. Several of the larger features have previously been characterized and some of the smaller rearrangements can potentially account for previously reported genetic features of these strains.^ Some aspects of the frequency and distribution of NotI, SfiI, XbaI and BlnI cleavage sites were analyzed using a method based on Markov chain theory. Overlaps of Dam and Dcm methylase sites with XbaI and SfiI cleavage sites were examined. The one XbaI-Dam overlap in the database is in accord with the expected frequency of this overlap. The occurrence of certain types of SfiI-Dcm overlaps are overrepresented. Of the four subtypes of SfiI-Dcm overlap, only one has a partial inhibitory effect on the activity of SfiI. Recognition sites for all four enzymes are rarer than expected based on oligonucleotide frequency data, with this effect being much stronger for XbaI and BlnI than for NotI and SfiI. The latter two enzyme sites are rare mainly due to apparent negative selection against GGCC (both) and CGGCCG (NotI). The former two enzyme sites are rare mainly due to effects of the VSP repair system on certain di-tri- and tetranucleotides, most notably CTAG. Models are proposed to explain several of the anomalies of oligonucleotide distribution in E. coli, and the biological significance of the systems that produce these anomalies is discussed. ^

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Climate change is clearly discernible in observed climate records in Switzerland. It impacts on natural systems, ecosystems, and economic sectors such as agriculture, tourism, and energy, and it affects Swiss livelihood in various ways. The observed and projected changes call for a response from the political system, which in Switzerland is characterized by federalism and direct democratic instruments. Swiss climate science embraces natural and social sciences and builds on institutionalized links between researchers, public, and private stakeholders. In this article, we review the physical, institutional, and political aspects of climate change in Switzerland. We show how the current state of Swiss climate science and policy developed over the past 20 years in the context of international developments and national responses. Specific to Switzerland is its topographic setting with mountain regions and lowlands on both sides of the Alpine ridge, which makes climate change clearly apparent and for some aspects (tourist sector, hydropower, and extreme events) highly relevant and better perceivable (e.g., retreating glaciers). Not surprisingly the Alpine region is of central interest in Swiss climate change studies.

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We consider a large quantum system with spins 12 whose dynamics is driven entirely by measurements of the total spin of spin pairs. This gives rise to a dissipative coupling to the environment. When one averages over the measurement results, the corresponding real-time path integral does not suffer from a sign problem. Using an efficient cluster algorithm, we study the real-time evolution from an initial antiferromagnetic state of the two-dimensional Heisenberg model, which is driven to a disordered phase, not by a Hamiltonian, but by sporadic measurements or by continuous Lindblad evolution.

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The challenge for sustainable organic dairy farming is identification of cows that are well adapted to forage-based production systems. Therefore, the aim of this study was to compare the grazing behaviour, physical activity and metabolic profile of two different Holstein strains kept in an organic grazing system without concentrate supplementation. Twelve Swiss (HCH ; 566 kg body weight (BW) and 12 New Zealand Holstein-Friesian (HNZ ; 530 kg BW) cows in mid-lactation were kept in a rotational grazing system. After an adaptation period, the milk yield, nutrient intake, physical activity and grazing behaviour were recorded for each cow for 7 days. On three consecutive days, blood was sampled at 07:00, 12:00 and 17:00 h from each cow by jugular vein puncture. Data were analysed using linear mixed models. No differences were found in milk yield, but milk fat (3.69 vs. 4.05%, P = 0.05) and milk protein percentage (2.92 vs. 3.20%, P < 0.01) were lower in HCH than in HNZ cows. Herbage intake did not differ between strains, but organic matter digestibility was greater (P = 0.01) in HCH compared to HNZ cows. The HCH cows spent less (P = 0.04) time ruminating (439 vs. 469 min/day) and had a lower (P = 0.02) number of ruminating boli when compared to the HNZ cows. The time spent eating and physical activity did not differ between strains. Concentrations of IGF-1 and T3 were lower (P ≤ 0.05) in HCH than HNZ cows. In conclusion, HCH cows were not able to increase dry matter intake in order to express their full genetic potential for milk production when kept in an organic grazing system without concentrate supplementation. On the other hand, HNZ cows seem to compensate for the reduced nutrient availability better than HCH cows but could not use that advantage for increased production efficiency

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We study the real-time evolution of large open quantum spin systems in two spatial dimensions, whose dynamics is entirely driven by a dissipative coupling to the environment. We consider different dissipative processes and investigate the real-time evolution from an ordered phase of the Heisenberg or XY model towards a disordered phase at late times, disregarding unitary Hamiltonian dynamics. The corresponding Kossakowski-Lindblad equation is solved via an efficient cluster algorithm. We find that the symmetry of the dissipative process determines the time scales, which govern the approach towards a new equilibrium phase at late times. Most notably, we find a slow equilibration if the dissipative process conserves any of the magnetization Fourier modes. In these cases, the dynamics can be interpreted as a diffusion process of the conserved quantity.

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Using quantum Monte Carlo, we study the nonequilibrium transport of magnetization in large open strongly correlated quantum spin-12 systems driven by purely dissipative processes that conserve the uniform or staggered magnetization, disregarding unitary Hamiltonian dynamics. We prepare both a low-temperature Heisenberg ferromagnet and an antiferromagnet in two parts of the system that are initially isolated from each other. We then bring the two subsystems in contact and study their real-time dissipative dynamics for different geometries. The flow of the uniform or staggered magnetization from one part of the system to the other is described by a diffusion equation that can be derived analytically.

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Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as a fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range-based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranges and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1:3m for mean accuracy and 2:2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

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The ability to determine what activity of daily living a person performs is of interest in many application domains. It is possible to determine the physical and cognitive capabilities of the elderly by inferring what activities they perform in their houses. Our primary aim was to establish a proof of concept that a wireless sensor system can monitor and record physical activity and these data can be modeled to predict activities of daily living. The secondary aim was to determine the optimal placement of the sensor boxes for detecting activities in a room. A wireless sensor system was set up in a laboratory kitchen. The ten healthy participants were requested to make tea following a defined sequence of tasks. Data were collected from the eight wireless sensor boxes placed in specific places in the test kitchen and analyzed to detect the sequences of tasks performed by the participants. These sequence of tasks were trained and tested using the Markov Model. Data analysis focused on the reliability of the system and the integrity of the collected data. The sequence of tasks were successfully recognized for all subjects and the averaged data pattern of tasks sequences between the subjects had a high correlation. Analysis of the data collected indicates that sensors placed in different locations are capable of recognizing activities, with the movement detection sensor contributing the most to detection of tasks. The central top of the room with no obstruction of view was considered to be the best location to record data for activity detection. Wireless sensor systems show much promise as easily deployable to monitor and recognize activities of daily living.

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Indoor positioning has attracted considerable attention for decades due to the increasing demands for location based services. In the past years, although numerous methods have been proposed for indoor positioning, it is still challenging to find a convincing solution that combines high positioning accuracy and ease of deployment. Radio-based indoor positioning has emerged as a dominant method due to its ubiquitousness, especially for WiFi. RSSI (Received Signal Strength Indicator) has been investigated in the area of indoor positioning for decades. However, it is prone to multipath propagation and hence fingerprinting has become the most commonly used method for indoor positioning using RSSI. The drawback of fingerprinting is that it requires intensive labour efforts to calibrate the radio map prior to experiments, which makes the deployment of the positioning system very time consuming. Using time information as another way for radio-based indoor positioning is challenged by time synchronization among anchor nodes and timestamp accuracy. Besides radio-based positioning methods, intensive research has been conducted to make use of inertial sensors for indoor tracking due to the fast developments of smartphones. However, these methods are normally prone to accumulative errors and might not be available for some applications, such as passive positioning. This thesis focuses on network-based indoor positioning and tracking systems, mainly for passive positioning, which does not require the participation of targets in the positioning process. To achieve high positioning accuracy, we work on some information of radio signals from physical-layer processing, such as timestamps and channel information. The contributions in this thesis can be divided into two parts: time-based positioning and channel information based positioning. First, for time-based indoor positioning (especially for narrow-band signals), we address challenges for compensating synchronization offsets among anchor nodes, designing timestamps with high resolution, and developing accurate positioning methods. Second, we work on range-based positioning methods with channel information to passively locate and track WiFi targets. Targeting less efforts for deployment, we work on range-based methods, which require much less calibration efforts than fingerprinting. By designing some novel enhanced methods for both ranging and positioning (including trilateration for stationary targets and particle filter for mobile targets), we are able to locate WiFi targets with high accuracy solely relying on radio signals and our proposed enhanced particle filter significantly outperforms the other commonly used range-based positioning algorithms, e.g., a traditional particle filter, extended Kalman filter and trilateration algorithms. In addition to using radio signals for passive positioning, we propose a second enhanced particle filter for active positioning to fuse inertial sensor and channel information to track indoor targets, which achieves higher tracking accuracy than tracking methods solely relying on either radio signals or inertial sensors.

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Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranging and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1.3m for mean accuracy and 2.2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

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One component systems are treated from the point of view of the Gibbs' phase rule.