Volcanic gases and the reaction of sulfur dioxide with aluminosilicate glasses

Volcanic gases are an important part of the volatile cycle in active planetary systems and contribute significantly to the mobilization and transport of metals to planetary surfaces. On Earth, Venus, Mars and Io, SO2 is the most abundant corrosive species in volcanic gases, and basalts are ubiquitous on these planetary bodies. The reaction between SO2 and silicate rocks forms oxidized sulfate and reduced sulfide. This reaction is a key process in the formation of porphyry deposits. In volcanic eruption plumes SO2 reacts with volcanic ash and is scavenged onto the surface of the ash particles. Knowledge of the reaction mechanisms between volcanic gas and rocks, minerals and glasses, and processes controlling the metal mobilization and transport in volcanic gas can constrain models of volatile and metal budgets of planetary crusts and surfaces. Using thermochemical modelling, I present a new model for the composition of volcanic gas on the Moon and compare it to a terrestrial volcanic gas from Erta Ale volcano (Ethiopia). The main species in lunar volcanic gas are H2, S2 and CO. This finding is in contrast to previous studies which suggested that CO was the sole driver of explosive volcanic eruptions on the Moon. This lunar volcanic gas has a lower capacity for metal transport compared to the Cl- and H2O-rich volcanic gas from Erta Ale volcano. To identify how SO2-glass reactions occur at high temperature and to investigate what might promote and limit these reactions, I present results from an experimental study. Pure SO2 was reacted with silicate glasses in the system anorthite-diopside-albite and with Fe-bearing natural basaltic glasses. The sulfate reaction products are relatively enriched in Ca compared to the silicate glass composition, in particular in experiments with Fe-free anorthite-diopside glasses. On these Fe-free glasses CaSO4 is the sole observed phase in the coatings at 800 °C, whereas at 600 °C minor amounts of MgSO4 were detected. At 800 °C, the flux of Ca from the silicate glass to the surface exceeds that of Mg by a factor of up to 330, whereas at 600 °C this factor is only 3. The rate of reaction is not constant, decreasing by an order of magnitude from 1 h to 24 h at 800 °C. The reaction of SO2 with tholeiitic basalt glasses produces coatings of CaSO4, MgSO4, Na2SO4 and oxides including Fe2O3 and TiO2. In addition, the reaction modifies the basalt glass because Ca, Mg and Na are lost to the coating. This results in the nucleation of crystalline spherulites and needles including SiO2, Al2O3, as well as Fe-Na-rich and Mg-rich pyroxenes. VIII The results suggest that the structural properties of the silicate glass substrate control the diffusive transport of Ca, Na, Mg, Fe and Ti to the surface which in turn controls the overall reaction rate and the formation of sulfates, oxides and silicates. These findings can be applied to predicting reactions on planetary surfaces and at shallow levels within their crusts

Einsatz von Robotern und virtuellen Realitätssystemen nach einem Schlaganfall - ein Ersatz für die Ergotherapie? : Können diese technologischen Geräte zu verbesserten motorischen Funktionen der oberen Extremitäten bei Erwachsenen beitragen?

Darstellung des Themas: Menschen nach einem Schlaganfall sind häufig eingeschränkt in den motorischen Fertigkeiten. Diese Einschränkungen haben einen negativen Einfluss auf die Handlungsfähigkeit der Betroffenen. In den letzten Jahrzehnten hat der Einsatz von Robotern und virtuellen Realitätssystemen in der Schlaganfalltherapie für die Verbesserung motorischer Funktionen massiv zugenommen. Ziel: Die Arbeit hat zum Ziel, die Wirksamkeit von Robotern und virtuellen Realitätssystemen im Training von motorischen Funktionen der oberen Extremitäten aufzuzeigen. Daraus wird abgeleitet, inwiefern diese neuen Technologien die Ergotherapie ergänzen oder ersetzen können. Abschliessend werden Empfehlungen für den Einsatz in der ergotherapeutischen Praxis generiert. Methode: Eine systematische Literaturrecherche wurde durchgeführt. Für die Beantwortung der Fragestellung wurden Studien, Reviews und Artikel von Expertinnen und Experten eingeschlossen. Ergebnisse: Die Ergebnisse zeigen grösstenteils signifikante motorische Verbesserungen beim Einsatz von roboterbasierten und virtuellen Realitätstherapien in Kombination mit konventionellen Therapien gegenüber alleinigen konventionellen Therapien auf. Schlussfolgerungen: Der Einsatz von Robotik und virtuellen Realitätssystemen ist in der ergotherapeutischen Behandlung als Ergänzung sinnvoll. Jedoch haben diese modernen Technologien nach heutigem Forschungsstand nicht das Potenzial, die Ergotherapie zu ersetzen

A study of tectonic activity in the Basin-Range Province and on the San Andreas Fault. No. 1: Kinematics of Basin-Range intraplate extension

Strain rates assessed from brittle fracture and total brittle-ductile deformation measured from geodetic data were compared to estimates of paleo-strain from Quaternary geology for the intraplate Great Basin part of the Basin-Range, western United States. These data provide an assessment of the kinematics and mode of lithospheric extension that the western U.S. Cordillera has experienced from the past few million years to the present. Strain and deformation rates were determined by the seismic moment tensor method using historic seismicity and fault plane solutions for sub-regions of homogeneous strain. Contemporary deformation in the Great Basin occurs principally along the active seismic zones. The integrated opening rate across the entire Great Basin is accommodated by E-E extension at 8 to 10 mm/a in the north that diminishes to NW-SE extension of 3.5 mm/a in the south. Zones of maximum lithospheric extension correspond to belts of thin crust, high heat flow, and Quaternary basaltic volcanism, suggesting that these parameters are related through mechanism of extension such as a stress relaxation, allowing bouyant uplift and ascension of magmas

From Hospital-Level to Patient-Level Antibiotic Consumption Data: How Can We Improve Surveillance of Antibiotic Use in the Frame of Antibiotic Stewardship Programmes?

Infections with antimicrobial-resistant bacteria caused approximately 4.95 million deaths worldwide in 2019 and are, thus, one of the major threats to public health [1, 2]. Antimicrobial resistance is the ability of a microorganism to withstand antimicrobial treatment and occurs naturally [3]. However, its spread has been driven by the extensive use of antibiotics in agriculture, and human and veterinary medicine during recent decades [4]. Improving the adequate use of antibiotics in order to slow antimicrobial resistance, treat patients effectively and enhance patient safety is referred to as antibiotic stewardship [5]. Surveillance of antibiotic consumption is a crucial element in antibiotic stewardship programmes in defining interventions to optimise antibiotic use [6, 7]. The quantity of antibiotic consumption is analysed routinely in Switzerland. The Swiss Centre for Antibiotic Resistance (ANRESIS) has collected and analysed antimicrobial resistance data and antibiotic consumption data from an increasing number of microbiology laboratories and hospital pharmacies throughout Switzerland since 2006 [8]. Antimicrobial resistance data are provided at the patient-level while antibiotic consumption data are aggregated at the department or hospital-level per year or month. The results of the analyses are sent back to individual hospitals in the form of feedback and benchmark reports. The purpose of these reports is to support local antibiotic stewardship teams when defining interventions. The quality of antibiotic use has been analysed only sporadically in Switzerland [9, 10]. Recently, a consensus on quality indicators for antibiotic use was published [11]. This consensus includes antibiotic stewardship indicators that assess antibiotic treatment decisions. In recent years, most of the larger Swiss hospitals have implemented electronic medical record systems. Hence, patient-level antibiotic prescription data are increasingly available that could improve the monitoring of antibiotic use and provide better support for antibiotic stewardship programmes. Aims: The overall aims of this PhD thesis were, first, to evaluate the benefits of extracting patient-level antibiotic prescription data compared to hospital-level data and, second, to propose a method for incorporating these data into future surveillance of antibiotic use. The purpose of the first part was to assess whether associations between AMR and antibiotic consumption can be investigated using hospital-level data generated for routine surveillance. Three epidemiological projects aimed to investigate the temporal trends including explanatory variables of 1) consumption of antibiotics active against methicillin-resistant Staphylococcus aureus (MRSA), 2) the incidence of Staphylococcus aureus bloodstream infections and 3) extended-spectrum cephalosporin-resistant Klebsiella pneumoniae (ESCR-KP). The objective of the fourth project was to develop an interactive dashboard to improve data visualisation for routine surveillance. In the second part, we aimed to assess 5) the feasibility of converting patient-level antibiotic prescription data of the electronic medical record into antibiotic stewardship indicators. The last project (6) aimed to identify risk factors for the occurrence of extended-spectrum cephalosporin resistance in Escherichia coli and Klebsiella pneumoniae. Methods: Data from the ANRESIS database were used to analyse trends and risk factors for 1) consumption of anti-MRSA antibiotics (glycopeptides, daptomycin, linezolid) and 2) incidence of ESCR-KP in 21 hospitals between 2009 and 2019. The same data source was used for analysing 3) the incidence of Staphylococcus aureus bloodstream infections in 70 hospitals over time (2008-2021). Trends and risk factors were analysed by applying multiple linear regression models. 4) A dashboard visualising antibiotic consumption of hospitals participating in the ANRESIS surveillance system was developed using the R software environment and packages such as Shiny and Plotly. For projects 5 and 6, patients hospitalised between 1 October 2019 and 30 September 2021 at Lucerne cantonal hospital and who received at least one dose of a systemic antibiotic were included. Antibiotic prescription data were obtained from the electronic medical record Epic software® and linked with microbiological data from the ANRESIS database. Antibiotic stewardship indicators proposed by the literature were collected and, if needed, rephrased or specified to be calculable (project 5). Algorithms were programmed in R to convert electronic medical record data into antibiotic stewardship indicators. These were calculated, and the validity of each output value was assessed and categorised as either good quality data, missing data due to incomplete documentation or data processing issues or not computable. For the resistance models with patient-level data, the dataset was restricted to patients with possibly nosocomial Escherichia coli and Klebsiella pneumoniae (project 6). A multiple logistic regression model was applied to investigate risk factors for the occurrence of extend-spectrum cephalosporin resistance in Escherichia coli and Klebsiella pneumoniae. Results: Analysis of hospital-level antibiotic consumption data revealed an increase in the consumption of anti-MRSA antibiotics in Switzerland between 2009 and 2019 (project 1). Hospitals with lower levels of consumption of anti-MRSA antibiotics were associated with having an antibiotic stewardship group and restrictions for prescriptions of anti-MRSA antibiotics. The MRSA incidence decreased significantly in the French-speaking region while increasing significantly in the German-speaking region, although at a low incidence level (project 2). The incidence of Staphylococcus aureus bloodstream infections increased in Switzerland between 2008 and 2021, mainly due to the increasing incidence of methicillin-susceptible Staphylococcus aureus bloodstream infections in elderly males. The increase was more pronounced in the German-speaking than in the French-speaking region. Project 3 described a significant increase in the incidence of invasive ESCR-KP infections in Switzerland between 2009 and 2019. The incidence was higher in university than in non-university hospitals and in the French-speaking compared to the German-speaking region. However, the incidence was not associated with antibiotic consumption. Analysing the overall ESCR-KP incidence (all sample sites) revealed high variability between university hospitals, mainly due to a high proportion of patients with screening isolates at Geneva University Hospital (50% of patients with ESCR-KP). A dashboard was developed that visualised antibiotic consumption of the user's hospital (project 4). The hospital-specific login provides free access to interactive graphics and interactive tables for the 71 hospitals that are part of the ANRESIS surveillance system. Antibiotic consumption is depicted graphically over ten years and the graphics can be adjusted according to selection criteria. A benchmark boxplot enables users to compare antibiotic consumption of their hospital with other hospitals of comparable size or in the same linguistic region. Project 5 demonstrated the feasibility of converting electronic medical records data into antibiotic stewardship indicators. In total, data from 25,338 hospitalisations from 20,723 individual patients were analysed and visualised in an interactive dashboard. Data extraction allowed us to program algorithms for 89% (25/28) of the indicators assessing treatment decisions, and data quality was classified as good in 46% (13/28). According to the data quality observed, the most important issues were A) missing (58% of hospitalisations) or meaningless (37% of hospitalisations) information on indication (e.g. general indication, infection) and B) data processing issues such as insufficiently categorised metadata. The result of the resistance model with patient-level data was not meaningful since the number of patients with ESCR isolates was too low (project 6). Conclusion: Our studies revealed that several national trends in antibiotic consumption and resistance were mainly caused by subpopulations. This demonstrates the need for stratifying surveillance analyses to formulate appropriate target measures at the right intervention level. Higher resolution data on antibiotic use are essential to provide better decision support to policy makers in hospitals and on regional and national committees. To improve surveillance analysis for hospitals, we developed a procedure that converts electronic medical record data into antibiotic stewardship indicators. The routine monitoring of these indicators would be very useful for local antibiotic stewardship teams when defining and measuring the effectiveness of interventions. This PhD project has demonstrated the benefit of patient-level antibiotic data and is therefore the first step towards integrating patient-level antibiotic prescription data into routine surveillance

An evaluation of the solutions provided by the Rotterdam Rules to identifying the carrier

While the identification of the carrier under a contract for the carriage of goods by sea, whether as unimodal transport or as a leg of a multimodal transport, for the purposes of determining the person liable for the loss or the damage to goods carried, does not generally present a cargo interest with difficulties, there are instances in which it may do so. This minor dissertation evaluates the solutions provided by the Rotterdam Rules to certain 'identity of the carrier problems'

Fabrication of mirror templates in silica with micron-sized radii of curvature

We present the fabrication of exceptionally small-radius concave microoptics on fused silica substrates using CO2 laser ablation and subsequent reactive ion etching. The protocol yields on-axis near-Gaussian depressions with radius of curvature $\lesssim5$ microns at shallow depth and low surface roughness of 2 angstroms. This geometry is appealing for cavity quantum electrodynamics where small mode volumes and low scattering losses are desired. We study the optical performance of the structure within a tunable Fabry-Perot type microcavity, demonstrate near-coating-limited loss rates (F = 25,000) and small focal lengths consistent with their geometrical dimensions.Comment: 5 pages, 4 figure

The Convergence of Sparsified Gradient Methods

Distributed training of massive machine learning models, in particular deep neural networks, via Stochastic Gradient Descent (SGD) is becoming commonplace. Several families of communication-reduction methods, such as quantization, large-batch methods, and gradient sparsification, have been proposed. To date, gradient sparsification methods - where each node sorts gradients by magnitude, and only communicates a subset of the components, accumulating the rest locally - are known to yield some of the largest practical gains. Such methods can reduce the amount of communication per step by up to three orders of magnitude, while preserving model accuracy. Yet, this family of methods currently has no theoretical justification. This is the question we address in this paper. We prove that, under analytic assumptions, sparsifying gradients by magnitude with local error correction provides convergence guarantees, for both convex and non-convex smooth objectives, for data-parallel SGD. The main insight is that sparsification methods implicitly maintain bounds on the maximum impact of stale updates, thanks to selection by magnitude. Our analysis and empirical validation also reveal that these methods do require analytical conditions to converge well, justifying existing heuristics.Comment: NIPS 2018 - Advances in Neural Information Processing Systems; Authors in alphabetic orde

Towards Sustainable Sanitation in an Urbanising World

Urban sanitation in low‐ and middle‐income countries is at an inflection point. It is increasingly acknowledged that conventional sewer‐based sanitation cannot be the only solution for expanding urban areas. There are other objective reasons apart from the lack of capital. The lack of stable energy supplies, of spare parts and of human resources for reliable operation, and the increasing water scarcity are factors that seriously limit the expansion of centralised systems. This chapter argues that a new paradigm for urban sanitation is possible, if the heterogeneity within developing cities is reflected in the implementation of different sanitation systems, adapted to each urban context and integrated under one institutional roof. This new paradigm entails: (1) innovative management arrangements; (2) increased participation and the integration of individual, community and private sector initiatives; (3) thinking at scale to open new opportunities; (4) improved analysis of the situation and awareness raising. Moving beyond conventional approaches towards sustainable urbanisation needs to follow both a top‐down and a bottom‐up approach, with proper incentives and a variety of sanitation systems which, in a future perspective, will become part of the ‘urban ecosystem’

Distributed Learning over Unreliable Networks

Most of today's distributed machine learning systems assume {\em reliable networks}: whenever two machines exchange information (e.g., gradients or models), the network should guarantee the delivery of the message. At the same time, recent work exhibits the impressive tolerance of machine learning algorithms to errors or noise arising from relaxed communication or synchronization. In this paper, we connect these two trends, and consider the following question: {\em Can we design machine learning systems that are tolerant to network unreliability during training?} With this motivation, we focus on a theoretical problem of independent interest---given a standard distributed parameter server architecture, if every communication between the worker and the server has a non-zero probability $p$ of being dropped, does there exist an algorithm that still converges, and at what speed? The technical contribution of this paper is a novel theoretical analysis proving that distributed learning over unreliable network can achieve comparable convergence rate to centralized or distributed learning over reliable networks. Further, we prove that the influence of the packet drop rate diminishes with the growth of the number of \textcolor{black}{parameter servers}. We map this theoretical result onto a real-world scenario, training deep neural networks over an unreliable network layer, and conduct network simulation to validate the system improvement by allowing the networks to be unreliable