Search

The improvement of search engines for geospatial data on the World Wide Web has been a subject of research, particularly concerning the challenges in discovering and utilizing geospatial web services. Despite the establishment of standards by the Open Geospatial Consortium (OGC), the implementation of these services varies significantly among providers, leading to issues in dataset discoverability and usability. This paper presents a proof of concept for a search engine tailored to geospatial services in Switzerland. It addresses challenges such as scraping data from various OGC web service providers, enhancing metadata quality through Natural Language Processing, and optimizing search functionality and ranking methods. Semantic augmentation techniques are applied to enhance metadata completeness and quality, which are stored in a high-performance NoSQL database for efficient data retrieval. The results show improvements in dataset discoverability and search relevance, with NLP-extracted information contributing significantly to ranking accuracy. Overall, the GeoHarvester proof of concept demonstrates the feasibility of improving the discoverability and usability of geospatial web services through advanced search engine techniques. [ABSTRACT FROM AUTHOR]

Homosexuality is a sensitive issue in Africa that inspires a great deal of public contention and controversy and attracts much social science research interest. Due to the sensitivity of the issue, conducting empirical research on homosexuality in Africa or within African population groups could be subject to several challenges. This article presents an autoethnographic account of my experiences conducting empirical research on attitudes towards homosexuality among Cameroonians based at home and those living in Switzerland. The paper highlights the key challenges, surprises, and lessons learned experienced in the different stages of the research process, from design to data collection, analysis, and publication of findings. Drawing on these experiences, the article calls attention to some aspects that young researchers embarking on research in sensitive topics should be aware of and should plan for upfront. It proposes practical coping approaches that can support young researchers to navigate the difficult waters of researching homosexuality in challenging settings so they can achieve their research goals within the timeframe and resources available to them. [ABSTRACT FROM AUTHOR]

The estimation of Chlorophyll-a concentration is crucial for monitoring freshwater ecosystem health, particularly in lakes, as it is closely linked to eutrophication processes. Satellite imagery enables synoptic and frequent evaluations of Chlorophyll-a in water bodies, providing essential insights into spatiotemporal eutrophication dynamics. Frontier applications in water remote sensing support the utilization of machine and deep learning models applied to hyperspectral satellite imagery. This paper presents a comparative analysis of conventional machine and deep learning models—namely, Random Forest Regressor, Support Vector Regressor, Long Short-Term Memory, and Gated Recurrent Unit networks—for estimating Chlorophyll-a concentrations. The analysis is based on data from the PRecursore IperSpettrale della Missione Applicativa (PRISMA) hyperspectral mission, complemented by low-resolution Chlorophyll-a concentration maps. The analysis focuses on three sub-alpine lakes, spanning Northern Italy and Switzerland as testing areas. Through a series of modelling experiments, best-performing model configurations are pinpointed for both Chlorophyll-a concentration estimations and the improvement of spatial resolution in predictions. Support Vector Regressor demonstrated a superior performance in Chlorophyll-a concentration estimations, while Random Forest Regressor emerged as the most effective solution for refining the spatial resolution of predictions. [ABSTRACT FROM AUTHOR]

This paper aims to describe the outcomes of the Main10ance project, which focused on developing an integrated HBIM-GIS platform to support the maintenance and conservation plans for the historic built heritage. The pilot case is the UNESCO complex of the Sacri Monti, located in northern Italy and Switzerland, which consists of groups of chapels and architectural artifacts holding significant historical and cultural value. Given their importance, specific maintenance plans involving multiple stakeholders and specialists are required. This study focuses on creating a unified system that semantically and spatially describes the architectural elements of the case study and the surrounding context and indoor assets. After a 3D integrated metric survey and the related data processing, parametric 3D models were created in a BIM environment, and a spatial database was developed to incorporate both geometric and alphanumeric entities. The database enables interoperability among different actors and domains, gathering heritage-related information crucial for restoration and conservation purposes. Additionally, the custom 4MAIN10ANCE web platform was developed with different levels of details (LODs), enabling the retrieval of both 2D and 3D data and establishing connections between the BIM models of the chapels and associated information. [ABSTRACT FROM AUTHOR]

From December 2021 to May 2022, MeteoSwiss and Meteomatics conducted a proof of concept to demonstrate the capability of automatic drones to provide data of sufficient quality and reliability on a routine operational basis. Over 6 months, Meteodrones MM-670 were operated automatically eight times per night at Payerne, Switzerland. In total, 864 meteorological profiles were measured and compared to co-located standard measurements, including radiosoundings and remote sensing instruments. To our knowledge, this is the first time that Meteodrone's atmospheric profiles have been evaluated in such an extensive campaign. The paper highlights two case studies that showcase the performance and challenges of measuring temperature, humidity, and wind with a Meteodrone. It also focuses on the overall quality of the drone measurements. Throughout the campaign, the availability of Meteodrone measurements was 75.7%, with 82.2% of the flights reaching the nominal altitude of 2000 m above sea level. The quality of the measurements was assessed against the WMO's (World Meteorological Organization) requirements. The temperature measurements gathered by the Meteodrone met the "breakthrough" target, while the humidity and wind profiles met the "threshold" target for high-resolution numerical weather prediction. The temperature measurement quality was comparable to that of a microwave radiometer, and the humidity quality was similar to that obtained from a Raman LiDAR. However, the wind measurements gathered by a Doppler LiDAR were more accurate than the estimation provided by the Meteodrone. This campaign marks a significant step towards the operational use of automatic drones for meteorological applications. [ABSTRACT FROM AUTHOR]

The impact of corporate intangibles on a company's market value has been a widely debated topic. A large body of literature has separately examined the industry's effect- or firm-specific attributes, such as industry type, company size, company age, or indebtedness and profitability, on the motivation to disclose information on intangible assets, but without considering a comprehensive view. This paper examines the role intangible assets play in a firm's market valuation besides other firm-specific characteristics. The reducted dataset we use in this study comprises 250 publicly traded companies operating in four different business sectors in France, Germany, and Switzerland for the ten years from 2009 to 2018. Based on the panel data regression models, the study provides an extension of previous knowledge about the effect intangible assets may have on the investors' view of a company's value, where the value added of this paper is the empirical evidence of a possible link between the intangible assets' disclosure and the market value of German, French, and Swiss enterprises. The importance of our contribution lies in a comparative analysis carried out to reveal substantial differences in the impact of intangible assets and innovation activity on the market value firms in three European countries and across four industry sectors. Although the results show the positive impact of intangible assets on the companies' market value, we suggest that investors still assess companies based on their profitability rather than considering the information on intangible assets the enterprises disclose in their financial statements. [ABSTRACT FROM AUTHOR]

Radon is a natural and radioactively well-known carcinogenic indoor air pollutant. Since 2020, a radon short-term proactive methodology has been proposed by Swiss authorities, which aims to evaluate the probability of overpassing the national reference value. This study aims to assess the influence of different weather parameters on indoor radon levels monitored using this methodology. To this end, different statistical tools are used, such as correlations, auto-correlations, cross-correlations, and multiple linear regressions between meteorological parameters and indoor radon levels. We show a strong influence of weather conditions on indoor radon levels in occupied, but especially unoccupied spaces. Outdoor air temperature, followed by atmospheric pressure, was identified as the most significant parameter impacting indoor radon levels. Moreover, meteorological conditions monitored five days prior to the beginning of the radon measurements might affect radon levels. We come to the conclusion that it is of paramount importance to take these meteorological conditions into account when analyzing the results of short-term measurements, and more specifically, to consider the evolution of the weather conditions five days prior to the radon measurement. This paper helps to ensure the relevance of this short-term measurement method available in Switzerland. [ABSTRACT FROM AUTHOR]

Creativity has been studied for a long time and it has become a more significant topic of research in educational fields in recent decades. The present paper outlines a multivariate approach to creativity and substantiates this approach by investigating the creative process and multivariate factors through a creative course for master's students at the University of Teacher Education in Switzerland. Our goal is to examine more specifically the stages of the creative process and the emerging multivariate factors in different creative activities. The article reports findings from the analysis of students' creative report process diaries as well as semi-structured interviews. Drawing on experiential learning, this pilot study was conducted in collaboration with master's student teachers (n = 10). The results show that the different microlevels of the creative process are the subject of variations from one creative experience to another. Most factors of the multivariate approach emerge from this kind of creative training. The discussion will allow for a review of the research results and also a better understanding of the creative process in the pedagogy of creativity. [ABSTRACT FROM AUTHOR]

In the development of deep geological repositories (DGRs), performance assessment modeling is used to evaluate the integrity and performance of the engineered and geological barriers for thousands or millions of years of evolution of the disposal system. To evaluate the suitability of a site for a DGR, geoscientific data from dedicated site investigation programs are integrated into site-specific assessments. This paper presents the development and implementation of a modeling workflow aimed at comparing three potential siting areas for a DGR in Switzerland from the viewpoint of long-term safety and technical feasibility. The workflow follows the guidelines of the national regulator addressing safety relevant criteria such as the barrier efficiency of the host rock and its mechanical and chemical integrity in response to repository-induced influences and the long-term stability of the repository site over geological scales. In the regulatory requirements, the role of parametric, conceptual, and scenario uncertainty has been identified as an issue of special importance in the site selection process. The assessment approach comprises a portfolio of numerical models for the simulation of solute, gas and heat transport in the repository nearfield. The modeling was performed with deterministic as well as probabilistic variants integrated in an indicator-based approach that allows the consistent comparison of the candidate sites using quantitative dimensionless performance indices. The model-based assessment of the sites allows a traceable, transparent, and verifiable implementation of the site selection process. [ABSTRACT FROM AUTHOR]

The world of electrical distribution is rapidly changing and is seeing more and more distributed production and steerable flexibilities. Energy communities are seen as an important innovation for the optimization of electrical consumption at a local level. A central need of the local energy markets inside energy communities is the exchange and circulation of production and consumption data, and therefore the problem of the potential leak of sensitive data must be addressed. In this paper, the context of the Lugaggia Innovation Community, a Self Consumption Community pilot project in southern Switzerland, is introduced together with the blockchain framework that was created for its internal market interaction and the rules designed for its local energy market. A cryptographic protocol from the literature, based on homomorphic encryption, is then proposed for the anonymous aggregation of production and consumption data of the individual households at a resolution of 15 min. The computational overhead associated with the protocol is then experimented and analyzed. [ABSTRACT FROM AUTHOR]

A seismic swarm is a series of earthquakes that occur in a small area over a short period of time. A sequence of earthquakes of this magnitude is unusual in Switzerland, and it is impossible to anticipate how it may unfold in the future.The seismic activity of such an event usually fades after a few days or weeks. Significantly greater earthquakes are likely to occur during the next several days, with up to a chance of 5 to 10%. For these reasons, the underground research facilities need tools to provide data on the impact of these events on their experiments. The paper presents the techniques implemented at The European Organization for Nuclear Research (CERN) to allow the tracking and monitoring of these unusual events. Additionally, the real effect of such an unusual event is presented together with the statistical approach to monitoring and effect evaluation. Considering the collision energy of the beams at 14 TeV, the energy stored in the magnets at 10 GJ (2400 kg of TNT), and the energy carried by the two beams at 724 MJ (173 kg of TNT), prolonged exposure to vibration close to or above the set alarm levels may result in serious safety issues. The presented evaluation of earthquake swarm impact on underground facilities together with the approach for data evaluation can be used for the design of future detectors and accelerators. Additionally, it provides tools for facilities users to present the data in an easy to understand way. This includes the Future Circular Collider, whose purpose is to significantly expand the energy and intensity frontiers of planned particle colliders, with the goal of reaching collision energies of 100 TeV in the quest for novel physics. As a result, even greater standards for beam size and stability will be required. [ABSTRACT FROM AUTHOR]

Biotinidase deficiency (BD) is a rare autosomal recessive metabolic disease. Previously the disease was identified only by clinical signs and symptoms, and since recently, it has been included in newborn screening programs (NBS) worldwide, though not commonly. In Europe, BD prevalence varies highly among different countries, e.g., from 1:7 116 in Turkey to 1:75 842 in Switzerland. This paper aimed to present the molecular spectrum of BD (profound and partial forms) in Polish patients diagnosed within the national NBS of 1,071,463 newborns. The initial suspicion of BD was based on an abnormal biotinidase activity result determined in a dry blood spot (DBS) by colorimetric and by fluorimetric methods while biochemical verification was determined by serum biotinidase activity (as quantitative analysis). The final diagnosis of BD was established by serum enzyme activity and the BTD gene direct sequencing. The obtained results allowed for the estimation of disease prevalence (1:66,966 births, while 1:178,577 for profound and 1:107,146 for partial forms), and gave novel data on the molecular etiology of BD. [ABSTRACT FROM AUTHOR]

Radon is a natural and radioactive gas that can accumulate in indoor environments. Indoor radon concentration (IRC) is influenced, among other factors, by meteorology, which is the subject of this paper. Weather parameters impact indoor radon levels and have already been investigated, but rarely in Switzerland. Moreover, there is a strong need for a better understanding of the radon behaviour inside buildings in Switzerland for public health concerns as Switzerland is a radon prone area. Based on long-term, continuous, and hourly radon measurements, radon distributions classified according to different weather event definitions were investigated and then compared at three different study sites in Western Switzerland. Outdoor temperature influences the most indoor radon, and it is globally anti-correlated. Wind influences indoor radon, but it strongly depends on intensity, direction, and building characteristics. Precipitation influences periodically indoor radon levels relatively to their intensity. Atmospheric pressure and relative humidity do not seem to be huge determinants on IRC. Our results are in line with previous findings and provide a vivid example in Western Switzerland. This paper underlines the different influence complexities of radon, and the need to communicate about it within the broader public and with construction professionals, to raise awareness. [ABSTRACT FROM AUTHOR]

This paper attempts to illustrate the complexity of thermal infrared (TIR) data analysis for urban heat island studies. While a certain shift regarding the use of correct scientific nomenclature (using the term "surface urban heat island") could be observed, the literature is full of incorrect conclusions and results using erroneous terminology. This seems to be the result of the ease of such literature implicitly suggesting that "warm surfaces" result in "high air temperatures", ultimately drawing conclusions for urban planning authorities. It seems that the UHI is easy to measure, easy to explain, easy to find, and easy to illustrate—simply take a TIR-image. Due to this apparent simplicity, many authors seem to jump into UHI studies without fully understanding the nature of the phenomenon as far as time and spatial scales, physical processes, and the numerous methodological pitfalls inherent to UHI studies are concerned. This paper attempts to point out some of the many pitfalls in UHI studies, beginning with a proper correction of longwave emission data, the consideration of the source area of a thermal signal in an urban system—which is predominantly at the roof level—demonstrating the physics and interactions of radiation and heat fluxes, especially in relation to the importance of urban storage heat flux, and ending with an examination of examples from the Basel study area in Switzerland. Attention is then turned to the analysis of spatially distributed net radiation in the day- and at nighttime as a minimum requirement for urban heat island studies. The integration of nocturnal TIR images is notably recommended, as satellite data and the UHI-phenomenon cover the same time period. [ABSTRACT FROM AUTHOR]

In this paper, experiences of the last 20 years with the PERALS-technique are described. PERALS stands for photo electron-rejecting alpha liquid scintillation. This liquid scintillation technique was developed by Jack McDowell in the 1970s and is a powerful technique for the analyses of many natural alpha nuclides and also the beta nuclide 90Sr. The principle is based on a selective extraction of the radionuclide from the water phase by means of a complexing or ion pair reagent. The extractant contains also a cocktail suitable for scintillation counting. Therefore, the extract can be analyzed directly after the extraction step. After removing quenchers, such as oxygen, and the proper setting of a pulse shape discriminator, alpha pulses can be counted with a photomultiplier. This paper describes the development of robust analysis schemes for the determination of traces of polonium, thorium, uranium and other actinides in water samples (groundwater, rain water, river water, drinking water, mineral water, sea water). For radon and radium, the enrichment in the extract is poor. Therefore, PERALS methods are not suitable for trace analyses of these analytes. In addition, the extraction of the beta-emitter 90Sr with a PERALS cocktail is discussed, even though its beta spectrum is not analyzed with a PERALS counter. Results from the survey of drinking water and mineral water in Switzerland are presented for every radio element. [ABSTRACT FROM AUTHOR]

This paper presents a small signal stability analysis to assess the stability issues facing PV (photovoltaic) inverters connected to a weak grid. It is revealed that the cause of the transient instabilities, either high-frequency or low-frequency oscillations, is dominated by the outer control loops and the grid strength. However, most challenging oscillations are low-frequency oscillations induced by coupling interaction between the outer loop controller and PLL (Phase-Locked Loop) when the inverter is connected to a weak grid. Therefore, the paper proposes a low-frequency damping methodology in order to enhance the high system integration, while maintaining the stability of the system. The control method uses a DC link voltage error to modulate the reference reactive current. The proposed control reduces the low-frequency coupling between the DVC (DC link voltage controller), AVC (AC voltage controller) and PLL (Phase-locked loop). According to this study's results, the performance capability of the grid-connected PV inverter is improved and flexibility in the outer loop controller design is enhanced. The control strategy proposed in this paper is tested using the PLECS simulation software (Plexim GmbH, Zurich Switzerland) and the results are compared with the conventional method. [ABSTRACT FROM AUTHOR]

The Global Climate Observing System (GCOS) was established in 1992 to ensure that the observations necessary to address climate-related issues are defined, obtained and made available, to all potential users. The Swiss GCOS Office at the Federal Office of Meteorology and Climatology MeteoSwiss has the task of coordinating all climate relevant measurements in Switzerland (GCOS Switzerland). As such, the Swiss GCOS Office also fosters the exploration of new measurement techniques and methods, in particular through the use of satellite-based data, to complement the long-term in situ observations in Switzerland. In this paper, the role of satellites is presented for climatological studies of atmospheric and terrestrial Essential Climate Variables in Switzerland. For the atmospheric domain, the 10-year climatology March 2000-February 2010 of cloud cover from MODIS is shown for Switzerland, in low (1° x 1°) and high (0.05° x 0.05°) resolution, and compared to ground-based synop observations. For the terrestrial domain, the satellite-derived Swiss glacier inventory from 1998/99 and the new Alpine-wide inventory from 2003 is presented along with area changes derived from a comparison with previous inventories. [ABSTRACT FROM AUTHOR]

Profound changes driven by decarbonization, decentralization, and digitalization are disrupting the energy industry, bringing new challenges to its key stakeholders. In the attempt to address the climate change issue, increasing penetration of renewables and mobility electrification augment the complexity of the electric grid, thus calling for new management approaches to govern energy exchanges while ensuring reliable and secure operations. The emerging blockchain technology is regarded as one of the most promising solutions to respond to the matter in a decentralized, efficient, fast, and secure way. In this work, we propose an Ethereum-based charging management framework for electric vehicles (EVs), tightly interlinked with physical and software infrastructure and implemented in a real-world demonstration site. With a specifically designed solidity-based smart contract governing the charging process, the proposed framework enables secure and reliable accounting of energy exchanges in a network of trustless peers, thus facilitating the EVs' deployment and encouraging the adoption of blockchain technology for everyday tasks such as EV charging through private and semi-private charging infrastructure. The results of a multi-actor implementation case study in Switzerland demonstrate the feasibility of the proposed blockchain framework and highlight its potential to reduce costs in a typical EV charging business model. Moreover, the study shows that the suggested framework can speed up the charging and billing processes for EV users, simplify the access to energy markets for charging station owners, and facilitate the interaction between the two through specifically designed mobile and web applications. The implementation presented in this paper can be used as a guideline for future blockchain applications for EV charging and other smart grid projects. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the potentials of distributed generation (DG) in a medium-sized Swiss city. We show the role of private households in the sustainable energy transition process induced by Swiss energy policy. For the analysis, we define six scenarios that enable us to study the potentials and impacts of different combinations of DG technologies in terms of costs, CO2 emissions, and amounts and shares of DG provided by non-industrial end-users (essentially private households and the services sector). Three variants are investigated, one with real electricity costs and CO2 emissions, one with increased electricity costs (e.g., construction of new power plants), and one with increased CO2 emissions (e.g., due to the planned nuclear phase-out in Switzerland). We find that non-industrial entities can play an important role as prosumers. They mitigate the need for centralized generation. Within a scenario where the non-industrial energy end-users install water-water heat pumps and photovoltaics, a total reduction of the gas procurement from the grid is possible whereas the electricity demand from the grid increases by 24%. This scenario reveals higher DG electricity costs in comparison to conventional electricity supply, but the total costs of energy supply decrease due to the elimination of gas supply, and the CO2 emissions can be reduced by 68%. [ABSTRACT FROM AUTHOR]

In this paper, a mathematical model based on the one-parameter Mittag-Leffler function is proposed to be used for the first time to describe the relation between the unemployment rate and the inflation rate, also known as the Phillips curve. The Phillips curve is in the literature often represented by an exponential-like shape. On the other hand, Phillips in his fundamental paper used a power function in the model definition. Considering that the ordinary as well as generalised Mittag-Leffler function behave between a purely exponential function and a power function it is natural to implement it in the definition of the model used to describe the relation between the data representing the Phillips curve. For the modelling purposes the data of two different European economies, France and Switzerland, were used and an "out-of-sample" forecast was done to compare the performance of the Mittag-Leffler model to the performance of the power-type and exponential-type model. The results demonstrate that the ability of the Mittag-Leffler function to fit data that manifest signs of stretched exponentials, oscillations or even damped oscillations can be of use when describing economic relations and phenomenons, such as the Phillips curve. [ABSTRACT FROM AUTHOR]

The number of scholarly publications on the topic of biosensors has increased rapidly; as a result, it is no longer easy to build an informed overview of the developments solely by manual means. Furthermore, with many new research results being continually published, it is useful to form an up-to-date understanding of the recent trends or emergent directions in the field. This paper utilizes bibliometric methods to provide an overview of the developments in the topic based on scholarly publications. The results indicate an increasing interest in the topic of biosensor(s) with newly emerging sub-topics. The US is identified as the country with highest total contribution to this area, but as a collective, EU countries top the list of total contributions. An examination of trends over the years indicates that in recent years, China-based authors have been more productive in this area. If research contribution per capita is considered, Singapore takes the top position, followed by Sweden, Switzerland and Denmark. While the number of publications on biosensors seems to have declined in recent years in the PubMed database, this is not the case in the Web of Science database. However, there remains an indication that the rate of growth in the more recent years is slowing. This paper also presents a comparison of the developments in publications on biosensors with the full set of publications in two of the main journals in the field. In more recent publications, synthetic biology, smartphone, fluorescent biosensor, and point-of-care testing are among the terms that have received more attention. The study also identifies the top authors and journals in the field, and concludes with a summary and suggestions for follow up research. [ABSTRACT FROM AUTHOR]

The Benedictine Convent of Saint John at Müstair is a UNESCO World Heritage Site located in the eastern part of Switzerland close to South Tyrol's border (Italy). Known as a well-preserved Carolingian building complex housing Carolingian and Romanesque frescoes, the convent has received much academic attention. However, all research activities so far have been concentrated on the area enclosed by the convent's walls, even though the neighbouring fields to the east and south are also part of the convent's property. This paper reports on the archaeological magnetic and ground-penetrating radar surveys of these areas, executed as part of a pilot project exploring the convent's immediate environment. At present, these fields are used for agriculture and located on a massive alluvial fan of the mountain stream Valgarola. Dense geophysical sampling revealed an intricate network of distributary channels with stream and mudflow deposits, constituting a natural border of the convent's territory. In addition to different field systems, a newly discovered broad pathway appears to be an original Roman road. Numerous structural elements, mapped within the convent's walls, could be attributed to specific building phases. Over 40 large and deep burial shafts, arranged in three rows, were discovered outside the convent's burial ground. Their specific design and arrangement are characteristic of early medieval burials, such as those of the 6th century Lombards on the edge of the eastern Alps. [ABSTRACT FROM AUTHOR]

The Compact Muon Solenoid (CMS) is a particle physics experiment situated on the Large Hadron Collider (LHC) at CERN, Switzerland. The CMS upgrade (planned for 2025) involves installing a new advanced sensor system within the CMS tracker, the centre of the detector closest to the particle collisions. The increased heat load associated with these sensors has required the design of an enhanced cooling system that exploits the latent heat of 40 bar CO2. In order to minimise interaction with the incident radiation and improve the detector performance, the cooling pipes within this system need to be thin-walled (~100 μm) and strong enough to withstand these pressures. The purpose of this paper is to analyse the microstructure and mechanical properties of thin-walled cooling pipes currently in use in existing detectors to assess their potential for the tracker upgrade. In total, 22 different pipes were examined, which were composed of CuNi, SS316L, and Ti and were coated with Ni, Cu, and Au. The samples were characterised using computer tomography for 3D structural assessment, focused ion beam ring-core milling for microscale residual stress analysis, optical profilometry for surface roughness, optical microscopy for grain size analysis, and energy dispersive X-ray spectroscopy for elemental analysis. Overall, this examination demonstrated that the Ni- and Cu-coated SS316L tubing was optimal due to a combination of low residual stress (20 MPa axial and 5 MPa hoop absolute), low coating roughness (0.4 μm Ra), minimal elemental diffusion, and a small void fraction (1.4%). This result offers a crucial starting point for the ongoing thin-walled pipe selection, development, and pipe-joining research required for the CMS tracker upgrade, as well as the widespread use of CO2 cooling systems in general. [ABSTRACT FROM AUTHOR]

Since extreme values of climatic actions are commonly derived assuming the climate being stationary over time, engineering structures and infrastructures are designed considering design actions derived under this assumption. Owing to the increased relevance of the expected climate change effects and the correlated variations of climate actions extremes, ad hoc strategies for future adaption of design loads are needed. Moreover, as current European maps for climatic actions are generally based on observations collected more than 20 years ago, they should be updated. By a suitable elaboration of the projections of future climate changes, the evolution over time of climatic actions can be assessed; this basic and crucial information allows us to facilitate future adaptations of climatic load maps, thus improving the climate resilience of structures and infrastructures. In this paper, current trends of climatic actions in Europe, daily maximum and minimum temperatures, daily precipitation, and ground snow loads, are investigated based on available gridded datasets of observations (E-OBS) and regional reanalysis (Uncertainties in Ensembles of Regional Re-Analyses, UERRA), to assess their suitability to be used in the elaboration of maps for climatic actions. The results indicate that the E-OBS gridded datasets reproduce trends in extreme temperatures and precipitation well in the investigated regions, while reanalysis data, which include snow water equivalent, show biases in the assessment of ground snow load modifications over the years in comparison with measurements. As far as climate change effects are concerned, trends of variation of climatic actions are estimated considering subsequent time windows, 40 years in duration, covering the period 1950–2020. Results, in terms of factors of change, are critically discussed, also in comparison with the elaborations of reliable datasets of real observations, considering a case study covering Germany and Switzerland. [ABSTRACT FROM AUTHOR]

Dynamic growth of photovoltaic capacity in Poland encourages many entities to invest in photovoltaic systems. However, in the case of buildings with low roof-bearing capacity it can be problematic or even impossible to mount conventional PV modules due to their relatively high weight. Hence, the use of lightweight PV modules is a potential solution. In this paper four different prototype silicon lightweight modules of novel structure manufactured by the Xdisc S.A have been investigated in terms of their electrical and thermal features. The measurements showed that all prototypes have efficiency exceeding 19.5% and power in range of 214 to 242 Wp at standard test conditions. Their area density is about 3.5 kg/m2 which is typical for lightweight modules. In turn, the Power-to-Weight Ratio exceeds 40 W/kg threshold and in one case reaches almost 58 W/kg. Thanks to the measurements, the prototypes could be modelled in PVsyst (PVsyst SA, Satigny, Switzerland). The performed simulations of an example PV system revealed that installations based on prototypes have comparable performance to a conventional installation. Nevertheless, at current prices they are less profitable than the standard system and it shows the need for future cost reductions in the manufacturing process. The proposed materials selection may be the starting point for search of inexpensive substitutes of these materials which still conserve modules high performance. A system based on the prototypes can still prove advantageous when simplicity and promptness outweigh higher initial costs. [ABSTRACT FROM AUTHOR]

Energy efficiency programmes (EEPs) are schemes operated by utilities or other bodies in order to incentivize energy efficiency improvement, in particular by adoption of energy-efficient products and typically by means of an economic reward. Ample experience has been gained, especially in the U.S., where EEPs have been in use for decades, with the rationale of avoiding additional energy supply by improving energy efficiency. More recently, EEPs have been implemented in Europe and in Switzerland. This review paper presents insights from the U.S., the EU and especially from Switzerland, with a focus on levelised programme cost of saved energy (LPC) as a key performance indicator. These LPC values, which take the perspective of the programme operator, are typically low to very low compared to the cost of electricity supply, thereby representing an important argument in favour of their use. The country examples show that EEPs are being effectively and successfully put into practice, for example, in Switzerland both as (i) a national tender-based scheme (called ProKilowatt) and in the form of a (ii) utility-operated obligation-based scheme (in Geneva). EEPs not only call for diligent implementation but also for suitable legal settings, e.g., in the form of mandatory energy efficiency savings targets (as realised for energy efficiency obligations, EEOs) in combination with programme cost recovery. The main criticism of EEPs is the free-rider effect, which needs to be minimised. On the other hand, EEPs are accompanied by significant co-benefits (environmental, health-related and social) and spillover effects. In their currently prevalent form, EEPs allow one to effectively save energy at a (very) low cost ("low-hanging fruit"). They can hence play an important role in fostering the energy transition; however, they should be implemented as part of a policy portfolio, in combination with other policy instruments. [ABSTRACT FROM AUTHOR]

Epidemiology and public health research relating to solar ultraviolet (UV) exposure usually relies on dosimetry to measure UV doses received by individuals. However, measurement errors affect each dosimetry measurement by unknown amounts, complicating the analysis of such measurements and their relationship to the underlying population exposure and the associated health outcomes. This paper presents a new approach to estimate UV doses without the use of dosimeters. By combining new satellite-derived UV data to account for environmental factors and simulation-based exposure ratio (ER) modelling to account for individual factors, we are able to estimate doses for specific exposure periods. This is a significant step forward for alternative dosimetry techniques which have previously been limited to annual dose estimation. We compare our dose estimates with dosimeter measurements from skiers and builders in Switzerland. The dosimetry measurements are expected to be slightly below the true doses due to a variety of dosimeter-related measurement errors, mostly explaining why our estimates are greater than or equal to the corresponding dosimetry measurements. Our approach holds much promise as a low-cost way to either complement or substitute traditional dosimetry. It can be applied in a research context, but is also fundamentally well-suited to be used as the basis for a dose-estimating mobile app that does not require an external device. [ABSTRACT FROM AUTHOR]

Histoplasmosis is a well-known endemic fungal infection but experience in non-endemic regions is often limited, which may lead to delayed diagnosis and extensive testing. The diagnosis can be especially challenging, typically when the disease first presents with pulmonary nodules accompanied by hilar and mediastinal lymphadenopathy, suggesting a much more common malignant disease. In this situation, a greater FDG uptake in draining lymph nodes in comparison with the associated lung nodule seen in [18F]FDG-PET/CT, the so-called "flip-flop fungus" sign, can help to orientate further diagnostic measures. We report a case of a 56-year-old woman living in Switzerland, a non-endemic region, whose diagnosis of imported histoplasmosis was delayed since the findings had been initially misinterpreted as pulmonary malignancy. Further, histological workup was inconclusive due to lack of specific fungal staining, leading to ineffective treatment and non-resolving disease. This paper intends to highlight the pitfalls in diagnosing Histoplasma capsulatum and presents images of particularities of fungal infections in [18F]FDG-PET/CT, which in our case showed a "flip-flop fungus" sign. [ABSTRACT FROM AUTHOR]

Operating power systems with large amounts of renewables requires predicting future photovoltaic (PV) production with fine temporal and spatial resolution. State-of-the-art techniques combine numerical weather predictions with statistical post-processing, but their resolution is too coarse for applications such as local congestion management. In this paper we introduce computing methods for multi-site PV forecasting, which exploit the intuition that PV systems provide a dense network of simple weather stations. These methods rely entirely on production data and address the real-life challenges that come with them, such as noise and gaps. Our approach builds on graph signal processing for signal reconstruction and for forecasting with a linear, spatio-temporal autoregressive (ST-AR) model. It also introduces a data-driven clear-sky production estimation for normalization. The proposed framework was evaluated over one year on both 303 real PV systems under commercial monitoring across Switzerland, and 1000 simulated ones based on high-resolution weather data. The results demonstrate the performance and robustness of the approach: with gaps of four hours on average in the input data, the average daytime NRMSE over a six-hour forecasting horizon (in 15 min steps) and over all systems is 13.8% and 9% for the real and synthetic data sets, respectively. [ABSTRACT FROM AUTHOR]

The paper addresses the issue of modelling the demand for electricity in residential buildings with the use of artificial neural networks (ANNs). Real data for six houses in Switzerland fitted with measurement meters was used in the research. Their original frequency of 1 Hz (one-second readings) was re-sampled to a frequency of 1/600 Hz, which corresponds to a period of ten minutes. Out-of-sample forecasts verified the ability of ANNs to disaggregate electricity usage for specific applications (electricity receivers). Four categories of electricity consumption were distinguished: (i) fridge, (ii) washing machine, (iii) personal computer, and (iv) freezer. Both standard ANNs with multilayer perceptron architecture and newer types of networks based on deep learning were used. The simulations included over 10,000 ANNs with different architecture (number of neurons and structure of their connections), type and number of input variables, formulas of activation functions, training algorithms, and other parameters. The research confirmed the possibility of using ANNs to model the disaggregation of electricity consumption based on low frequency data, and suggested ways to build highly optimised models. [ABSTRACT FROM AUTHOR]

Ensemble flood forecasts are an established tool to provide information about the uncertainty of runoff predictions. However, their interpretation may not be straightforward, especially when dealing with extreme events; therefore, the development of new tools to enhance their understanding and visualization is necessary. Recently, the so-called "peak-box" approach has been developed to help decision makers in the interpretation and verification of peak-flow forecasts, receiving positive feedbacks within the hydrological community. However, this method has proven to be limited when multiple peak-flow events occur within the forecast, being unable to separate close discharge peaks. The aim of this paper is then to develop a new algorithm designed to accomplish this task. To do so, we consider runoff probabilistic forecasts obtained with a coupled hydrometeorological flood forecasting system formed by the high resolution meteorological Ensemble model COSMO-E and the hydrological model PREVAH, for the small Verzasca basin, Switzerland, during October and November 2018. The application of this new method, despite the limitation given by the small sample size considered in this study, indicates a successful implementation: the new algorithm is able to distinguish among different events and to provide sharper and more skillful forecasts, and its verification yields slightly better timing estimations compared to the former approach. [ABSTRACT FROM AUTHOR]