A new technique to automatically quantify microstructures of fine grained carbonate mylonites: two-step etching combined with SEM imaging and image analysis

A two-step etching technique for fine-grained calcite mylonites using 0.37% hydrochloric and 0.1% acetic acid produces a topographic relief which reflects the grain boundary geometry. With this technique, calcite grain boundaries become more intensely dissolved than their grain interiors but second phase minerals like dolomite, quartz, feldspars, apatite, hematite and pyrite are not affected by the acid and therefore form topographic peaks. Based on digital backscatter electron images and element distribution maps acquired on a scanning electron microscope, the geometry of calcite and the second phase minerals can be automatically quantified using image analysis software. For research on fine-grained carbonate rocks (e.g. dolomite calcite mixtures), this low-cost approach is an attractive alternative to the generation of manual grain boundary maps based on photographs from ultra-thin sections or orientation contrast images.

Stakeholder analysis combined with social network analysis provides fine-grained insights into water infrastructure planning processes

Environmental policy and decision-making are characterized by complex interactions between different actors and sectors. As a rule, a stakeholder analysis is performed to understand those involved, but it has been criticized for lacking quality and consistency. This lack is remedied here by a formal social network analysis that investigates collaborative and multi-level governance settings in a rigorous way. We examine the added value of combining both elements. Our case study examines infrastructure planning in the Swiss water sector. Water supply and wastewater infrastructures are planned far into the future, usually on the basis of projections of past boundary conditions. They affect many actors, including the population, and are expensive. In view of increasing future dynamics and climate change, a more participatory and long-term planning approach is required. Our specific aims are to investigate fragmentation in water infrastructure planning, to understand how actors from different decision levels and sectors are represented, and which interests they follow. We conducted 27 semi-structured interviews with local stakeholders, but also cantonal and national actors. The network analysis confirmed our hypothesis of strong fragmentation: we found little collaboration between the water supply and wastewater sector (confirming horizontal fragmentation), and few ties between local, cantonal, and national actors (confirming vertical fragmentation). Infrastructure planning is clearly dominated by engineers and local authorities. Little importance is placed on longer-term strategic objectives and integrated catchment planning, but this was perceived as more important in a second analysis going beyond typical questions of stakeholder analysis. We conclude that linking a stakeholder analysis, comprising rarely asked questions, with a rigorous social network analysis is very fruitful and generates complementary results. This combination gave us deeper insight into the socio-political-engineering world of water infrastructure planning that is of vital importance to our well-being.

A Passive WiFi Source Localization System based on Fine-grained Power-based Trilateration

Indoor localization systems become more interesting for researchers because of the attractiveness of business cases in various application fields. A WiFi-based passive localization system can provide user location information to third-party providers of positioning services. However, indoor localization techniques are prone to multipath and Non-Line Of Sight (NLOS) propagation, which lead to significant performance degradation. To overcome these problems, we provide a passive localization system for WiFi targets with several improved algorithms for localization. Through Software Defined Radio (SDR) techniques, we extract Channel Impulse Response (CIR) information at the physical layer. CIR is later adopted to mitigate the multipath fading problem. We propose to use a Nonlinear Regression (NLR) method to relate the filtered power information to propagation distances, which significantly improves the ranging accuracy compared to the commonly used log-distance path loss model. To mitigate the influence of ranging errors, a new trilateration algorithm is designed as well by combining Weighted Centroid and Constrained Weighted Least Square (WC-CWLS) algorithms. Experiment results show that our algorithm is robust against ranging errors and outperforms the linear least square algorithm and weighted centroid algorithm.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

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.

Fine-grained indoor positioning and tracking systems

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.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

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.

The influence of nano-scale second-phase particles on deformation of fine grained calcite mylonites

Grey and white carbonate mylonites were collected along thrust planes of the Helvetic Alps. They are characterised by very small grain sizes and non-random grain shape (SPO) and crystallographic preferred orientation (CPO). Presumably they deformed in the field of grain size sensitive flow by recrystallisation accommodated intracrystalline deformation in combination with granular flow. Both mylonites show a similar mean grain size, but in the grey mylonites the grain size range is larger, the grain shapes are more elongate and the dynamically recrystallised calcite grains are more often twinned. Grey mylonites have an oblique CPO, while the CPO in white mylonites is symmetric with respect to the shear plane. Combustion analysis and TEM investigations revealed that grey mylonites contain a higher amount of highly structured kerogens with particle sizes of a few tens of nanometers, which are finely dispersed at the grain boundaries. During deformation of the rock, nano-scale particles reduced the migration velocity of grain boundaries by Zener drag resulting in slower recrystallisation rates of the calcite aggregate. In the grey mylonites, more strain increments were accommodated by individual grains before they became refreshed by dynamic recrystallisation than in white mylonites, where grain boundary migration was less hindered and recrystallisation cycles were faster. Consequently, grey mylonites represent ‘deformation’ microfabrics while white mylonites are characterised by ‘recrystallisation’ microfabrics. Field geologists must utilise this different deformation behavior when applying the obliquity in CPO and SPO of the respective mylonites as reliable shear sense indicators.

Valle d’Aosta section of the Sesia Zone: multi-stage HP metamorphism and assembly of a rifted continental margin

The spectrum characteristic of the EMC ranges from eclogites (containing omphacite and/or jadeite, garnet, phengite, glaucophane, zoisite, chloritoid, rutile) to phengite schists, calcschists, and marbles, as well as a variety of orthogneisses. Despite the intense polyphase deformation and HP-metamorphic recrystallization, it is possible in some locations to recognize pre-Alpine characteristics in some of the protoliths. For instance, two types of felsic orthogneiss can be distinguished in the Aosta Valley, one derived from Permian granitoids (with local preservation of intrusive contacts, magmatic inclusions, leucocratic veins and other magmatic structures; Stop 3), the other derived from pre-Variscan leuco-monzogranite, such as the building stone mined at the “Argentera” quarry near Settimo Vittone / Montestrutto (Stop 2; so-called “Verde Argento” contains jadeite, phengite, K-feldspar, quartz). Polycyclic and more rarely monocyclic metasediments contain evidence of a complex Alpine PTDt-evolution, locally including relics of their prograde history from blueschist, one or more stages at eclogite facies. Recent petrochronological studies have dated this HP-evolution of the Sesia Zone in some detail. In the area visited, clear evidence of HP-cycling has been identified in one km-size tectonic slice (Stop 1), but not in adjacent parts of the EMC, indicating “yo-yo tectonics”. Partial retrogression and attendant ductile to brittle deformation of the HP-rocks is evident in one of the outcrops (Stop 4). Apart from the four localities in the Sesia Zone, a final outcrop introduces HP-rocks of the adjacent Piemonte oceanic unit, specifically calc-schists and ophiolite members of the “Zermatt-Saas” zone. The hilltop outcrop (Stop 5) displays foliated antigorite schist with peridotite relics (clinopyroxene, spinel) containing lenses derived from doleritic dykes. These fine-grained metarodingites and the folded veins containing Mg-chlorite and titanoclinohumite within serpentinite once again indicate equilibration under low-temperature eclogite facies conditions. However, these units reached that HP stage more than 20 Ma after the youngest eclogite facies imprint recognized in the Sesia Zone. Despite nearly half a century of intense study in the Sesia Zone, the complex assembly of its HP-terranes and their relation to more external parts of the Western Alps remains incompletely understood. This field guide merely introduces a few of the classic outcrops and discusses some of the critical evidence they contain, but it could not incorporate details on each stage of the evolution recognized so far.

The SCITEAS experiment: Optical characterizations of sublimating icy planetary analogues

We have designed and built a laboratory facility to investigate the spectro-photometric and morphologic properties of different types of ice-bearing planetary surface analogs and follow their evolution upon exposure to a low pressure and low temperature environment. The results obtained with this experiment are used to verify and improve our interpretations of current optical remote-sensing datasets. They also provide valuable information for the development and operation of future optical instruments. The Simulation Chamber for Imaging the Temporal Evolution of Analogue Samples (SCITEAS) is a small thermal vacuum chamber equipped with a variety of ports and feedthroughs that permit both in-situ and remote characterizations as well as interacting with the sample. A large quartz window located directly above the sample is used to observe its surface from outside with a set of visible and near-infrared cameras. The sample holder can be easily and quickly inserted and removed from the chamber and is compatible with the other measurement facilities of the Laboratory for Outflow Studies of Sublimating Materials (LOSSy) at the University of Bern. We report here on the results of two of the first experiments performed in the SCITEAS chamber. In the first experiment, fine-grained water ice mixed with dark organic and mineral matter was left to sublime in vacuum and at low temperature, simulating the evolution of the surface of a comet nucleus approaching the Sun. We observed and characterized the formation and evolution of a crust of refractory organic and mineral matter at the surface of the sample and linked the evolution of its structure and texture to its spectro-photometric properties. In the second experiment, a frozen soil was prepared by freezing a mixture of smectite mineral and water. The sample was then left to sublime for 6 h to simulate the loss of volatiles from icy soil at high latitudes on Mars. Colour images were produced using the definitions of the filters foreseen for the CaSSIS imager of the Exomars/TGO mission in order to prepare future science operations.

Replaying past changes in multi-developer projects

What was I working on before the weekend? and What were the members of my team working on during the last week? are common questions that are frequently asked by a developer. They can be answered if one keeps track of who changes what in the source code. In this work, we present Replay, a tool that allows one to replay past changes as they happened at a fine-grained level, where a developer can watch what she has done or understand what her colleagues have done in past development sessions. With this tool, developers are able to not only understand what sequence of changes brought the system to a certain state (e.g., the introduction of a defect), but also deduce reasons for why her colleagues performed those changes. One of the applications of such a tool is also discovering the changes that broke the code of a developer.

Flattening Traits

Traits are fine-grained components that can be used to compose classes, while avoiding many of the problems of multiple inheritance and mixin-based approaches. Since most implementations of traits have focused on dynamically-typed languages, the question naturally arises, how can one best introduce traits to statically-typed languages, like Java and C#?

Model-Centric, Context-Aware Software Adaptation

Software must be constantly adapted to changing requirements. The time scale, abstraction level and granularity of adaptations may vary from short-term, fine-grained adaptation to long-term, coarse-grained evolution. Fine-grained, dynamic and context-dependent adaptations can be particularly difficult to realize in long-lived, large-scale software systems. We argue that, in order to effectively and efficiently deploy such changes, adaptive applications must be built on an infrastructure that is not just model-driven, but is both model-centric and context-aware. Specifically, this means that high-level, causally-connected models of the application and the software infrastructure itself should be available at run-time, and that changes may need to be scoped to the run-time execution context. We first review the dimensions of software adaptation and evolution, and then we show how model-centric design can address the adaptation needs of a variety of applications that span these dimensions. We demonstrate through concrete examples how model-centric and context-aware designs work at the level of application interface, programming language and runtime. We then propose a research agenda for a model-centric development environment that supports dynamic software adaptation and evolution.