1,864 research outputs found

    Cavity Enhanced Optical Vernier Spectroscopy, Broad Band, High Resolution, High Sensitivity

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    A femtosecond frequency comb provides a vast number of equidistantly spaced narrow band laser modes that can be simultaneously tuned and frequency calibrated with 15 digits accuracy. Our Vernier spectrometer utilizes all of theses modes in a massively parallel manner to rapidly record both absorption and dispersion spectra with a sensitivity that is provided by a high finesse broad band optical resonator and a resolution that is only limited by the frequency comb line width while keeping the required setup simple.Comment: 11 pages, 3 figures, submitted to PR

    From RTK to PPP‑RTK: towards real‑time kinematic precise point positioning to support autonomous driving of inland waterway vessels

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    PPP-RTK is Precise Point Positioning (PPP) using corrections from a ground reference network, which enables single receiver users with integer ambiguity resolution thereby improving its performance. However, most of the PPP-RTK studies are investigated and evaluated in a static situation or a post-processing mode because of the complexity of implementation in real-time practical applications. Moreover, although PPP-RTK achieves a faster convergence than PPP, it typically needs 30 s or even longer to derive high-accuracy results. We have implemented a real-time PPP-RTK approach based on undifferenced observations and State-Space Representation corrections with a fast convergence of less than 30 s to support autonomous driving of inland waterway vessels. The PPP-RTK performances and their feasibility to support autonomous driving have been evaluated and validated in a real-time inland waterway navigation. It proves the PPP-RTK approach can realize a precise positioning of less than 10 cm in horizontal with a rapid convergence. The convergence time is within 10 s after a normal bridge passing and less than 30 s after a complicated bridge passing. Moreover, the PPP-RTK approach can be extended to outside of the GNSS station network. Even if the location is 100 km away from the border of the GNSS station network, the PPP-RTK convergence time after a bridge passing is also normally less than 30 s. We have realized the first automated entry into a waterway lock for a vessel supported by PPP-RTK and taken the first step toward autonomous driving of inland vessels based on PPP-RTK

    Precise Point Positioning to support an automatic entering of a waterway lock

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    Inland waterway transport is the transport mode with the lowest CO2 emission per tonne kilometre. However, there is a substantial potential for modal shift from road and rail to inland vessel transport. The increase of the grade of automation or even autonomous inland vessels could be a key enabler for this modal shift. By far the most challenging phase of inland navigation is the passing of waterway locks. Here, typically a ship with the dimension of 11.4 x 100 m has to enter a 12 m wide lock chamber, leaving just a few dm space on each side of the vessel. In order to support the automation of this manoeuvre, very accurate position, heading, turn rate and velocity information is required. Within the project SCIPPPER (2018-2022) such a driver assistant function has been developed. The idea was using the absolute Precise Point Positioning (PPP) instead of Real Time Kinematic (RTK) to achieve the required 10 cm horizontal accuracy. The reason was an expected reduction in the amount of PPP correction data and a significantly enlarged service area. Both facts would enable the correction data transmission over the VHF Data Exchange System (VDES) - the next generation of the Automatic Identification System (AIS). While a stable mobile internet connection is unfortunately not available at all inland waterways, currently AIS Base stations are being operated on all main inland waterways in Germany. By upgrading the AIS base stations to VDES stations, in the future all inland vessels on the main waterways could potentially benefit from the highly accurate positioning service. Besides the high accuracy, the reduction of the convergence time is one of the key challenges for the application of PPP for inland vessels. In order to shorten the PPP convergence time, we were using an SSR (state space representation) correction service from a regional network including not only global corrections like satellite clock, orbit, code and phase biases but also regional ionospheric and tropospheric corrections. These corrections were provided by using the GNSS station network of SAPOS (Satelliten Positionierungsdienst der deutschen Landesvermessung). In cooperation with the Working Committee of the Surveying and Mapping Agencies of the States of the Federal Republic of Germany (AdV) and Geo++, an SSR correction data stream has been prepared and optimised for the inland vessel application. By separating the corrections into high (5s update) and low rate (30s update) corrections, an average data rate of about 0.3 kbits/s was achieved, which is a significant reduction compared to RTK correction (4-5 kbit/s). In the paper the details of our real time PPP positioning solver with ambiguity resolution based on GPS and GALILEO observations will be given. Furthermore, the results of static as well as dynamic measurement campaigns in challenging inland waterway scenarios will be presented. In the final demonstration of the SCIPPPER project an 82 m long vessel automatically entered a waterway lock by using PPP as the main source for global positioning of the vessel. While the paper focuses on the positioning part, also a main overview of the complete driver assistant function will be presented

    Quantum to Classical Transition in a Single-Ion Laser

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    Stimulated emission of photons from a large number of atoms into the mode of a strong light field is the principle mechanism for lasing in "classical" lasers. The onset of lasing is marked by a threshold which can be characterised by a sharp increase in photon flux as a function of external pumping strength. The same is not necessarily true for the fundamental building block of a laser: a single trapped atom interacting with a single optical radiation mode. It has been shown that such a "quantum" laser can exhibit thresholdless lasing in the regime of strong coupling between atom and radiation field. However, although theoretically predicted, a threshold at the single-atom level could not be experimentally observed so far. Here, we demonstrate and characterise a single-atom laser with and without threshold behaviour by changing the strength of atom-light field coupling. We observe the establishment of a laser threshold through the accumulation of photons in the optical mode even for a mean photon number substantially lower than for the classical case. Furthermore, self-quenching occurs for very strong external pumping and constitutes an intrinsic limitation of single-atom lasers. Moreover, we find that the statistical properties of the emitted light can be adjusted for weak external pumping, from the quantum to the classical domain. Our observations mark an important step towards fundamental understanding of laser operation in the few-atom limit including systems based on semiconductor quantum dots or molecules.Comment: 19 pages, 4 figures, 10 pages supplement, accepted by Nature Physic

    Temporary exclusion of ill children from childcare centres in Switzerland: practice, problems and potential solutions.

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    BACKGROUND: In childcare centres, temporary exclusion of ill children, if their illness poses a risk of spread of harmful diseases to others, is a central approach to fight disease transmission. However, not all ill children need to be excluded. Previous studies suggested that childcare centre staff have difficulties in deciding whether or not to exclude an ill child, even when official ill-child guidelines are used. We aimed to describe, quantify and analyse these ambiguities and discuss potential solutions. METHODS: For this cross-sectional study, we sent postal surveys to 488 childcare centre directors in the Swiss Canton of Zurich, where no official ill-child guideline is in place. We asked for exclusion criteria for ill children and ambiguities faced when dealing with ill children. We checked whether existing guidelines provided solutions to the ambiguities identified. RESULTS: 249/488 (51%) directors responded to the survey. The most common exclusion criteria were fever (87.4%) and contagiousness (52.2%). Ambiguities were mostly caused by conjunctivitis (23.7%) and use of antipyretic drugs (22.9%). Roughly one third of the ambiguities identified could have been resolved with existing guidelines, another third if existing guidelines contained additional information. For the last third, clear written directives are difficult to formulate. CONCLUSIONS: Written recommendations may help to clarify when an ill child should temporarily be excluded. However, such a guideline should cover the topics antipyretic drugs and teething and have room for modification to local circumstances. Collaboration with a paediatrician may be of additional benefit

    Evaluation of a Bayesian inference network for ligand-based virtual screening

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    Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query. Here, we modify the approach to enable a Bayesian inference network to be used for chemical similarity searching, where a database is ranked in order of decreasing probability of bioactivity. Results Bayesian inference networks were implemented using two different types of network and four different types of belief function. Experiments with the MDDR and WOMBAT databases show that a Bayesian inference network can be used to provide effective ligand-based screening, especially when the active molecules being sought have a high degree of structural homogeneity; in such cases, the network substantially out-performs a conventional, Tanimoto-based similarity searching system. However, the effectiveness of the network is much less when structurally heterogeneous sets of actives are being sought. Conclusion A Bayesian inference network provides an interesting alternative to existing tools for ligand-based virtual screening

    Refining the treatment of pancreatic cancer from big data to improved individual survival

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    Pancreatic cancer is one of the most lethal cancers worldwide, most notably in Europe and North America. Great strides have been made in combining the most effective conventional therapies to improve survival at least in the short and medium term. The start of treatment can only be made once a diagnosis is made, which at this point, the tumor volume is already very high in the primary cancer and systemically. If caught at the earliest opportunity (in circa 20% patients) surgical resection of the primary followed by combination chemotherapy can achieve 5-year overall survival rates of 30%–50%. A delay in detection of even a few months after symptom onset will result in the tumor having only borderline resectabilty (in 20%–30% of patients), in which case the best survival is achieved by using short-course chemotherapy before tumor resection as well as adjuvant chemotherapy. Once metastases become visible (in 40%–60% of patients), cure is not possible, palliative cytotoxics only being able to prolong life by few months. Even in apparently successful therapy in resected and borderline resectable patients, the recurrence rate is very high. Considerable efforts to understand the nature of pancreatic cancer through large-scale genomics, transcriptomics, and digital profiling, combined with functional preclinical models, using genetically engineered mouse models and patient derived organoids, have identified the critical role of the tumor microenvironment in determining the nature of chemo- and immuno-resistance. This functional understanding has powered fresh and exciting approaches for the treatment of this cancer
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