HES-SO Valais-Wallis
  • Sierre, Valais, Switzerland
Recent publications
In this paper, we present the characteristics of current, electric fields and modeling approaches of lightning M-component mode of charge transfer. We consider both the classical M-components (occurring after return strokes) and M-component-type ICC (Initial Continuous Current) pulses occurring during the initial (ICC) phase of upward flashes. M-component-type ICC pulses can be distinguished from mixed-mode pulses using different criteria: (i) the 10–90% current risetime at the channel-base with respect to an 8-µs risetime; (ii) the time lag between the onset of the current and electric fields with a respect to a threshold of 10 µs; (iii) an asymmetrical waveform coefficient (AsWc) with respect to a value of 0.8; (iv) the relative height of the junction or connection points on the grounded channel above the ground. The features of M-component electric field waveforms are summarized for close, intermediate, and far distance ranges. The observed millisecond-scale slow-part pulse shows a polarity reversal from an initial-negative waveform at close range, to a full positive-flattening late-time response at intermediate range and a bipolar wave-shape at the far distance range. One or some microsecond-scale fast pulses (junction pulse) are observed to precede the millisecond-scale slow part pulse at intermediate and far distance ranges. The microsecond-scale fast pulses are dominated by unipolar pulses along with several cases of bipolar pulses exhibiting initial polarities of both signs. The main advantage of the guided wave model and its variations is their simplicity and straightforward implementation. The guided wave model is also able to reproduce reasonably well the observed slow electric fields. The nonlinear models are more physics-based compared to the guided wave models. They are based on an important number of adjustable parameters, many of which cannot be directly inferred from experimental observations. The significance of M-components is reviewed according to practical aspects in transformer secondary, surge protective devices (SPD), grounding systems.
This paper addresses the issue of visualizing the right information among large data sets by proposing to represent raw data as a set of mathematically-based implicit curves. Implicit curves are proving to be a powerful yet underused tool. The methodology we propose not only allows a more relevant visualization of information, but also a faster and efficient access to it: (1) since curves are extracted and compressed during precomputation, real-time rendering is possible on the end-user’s computer, even for very large datasets; (2) this property can be extended by enabling real-time data access and transfer at the server level – i.e. simultaneously saving local storage costs and increasing raw data security. Our proposal also achieved a high compression ratio (3%) while maintaining the visual significance of the data and reducing discrete artifacts such as curve gaps and pixel aliasing. We based our tests using two-dimensional height maps, but extending it to more dimensions is not a problem since we can consider any two-dimensional slice in these data. KeywordsInformation visualizationDatacubeEarth observationGPGPUWebGLFourier seriesSplines
In this paper we tackle the challenge of visualizing large matrices, also called datacubes, in real time (RT) using Web technologies. The most critical issue is to achieve this for arrays of up to several billion floats. For this purpose, it is necessary to implement models running on CPU-based or dedicated graphic processor unit (GPU). We propose a convenient selection of volume-rendering models for the scientific community and especially data scientists. To this end we oriented our approach to an integration of these models in Jupyter Notebook. The rendering of these datacubes is made possible thanks to an improved raycasting algorithm supporting datacubes with sizes of 163, 643, 2563, and up to 10243, corresponding to a billion cells. We designed three different rendering models: (1) an X-Ray model for 3D datacubes in a (x, y, z) space; (2) a model simulating the implicit surfaces of 3D datacubes in a (x, y, z) space; (3) and an original model, we named Derived-rendering, for 3D datacubes in a (x, y, t) space where t represents time. We also introduce solutions to reduce the memory footprint and load on the GPU side. Tested with a recent hardware configuration, our proposal demonstrates we can even reach RT rendering for a billion-cell datacube.
As a result of the limited knowledge on eluviation/illuviation and bioturbation rates, these two processes of soil particles translocation are qualitatively described either as synergic or competing processes. Here we take the opportunity of the recent development of an image analysis procedure to quantify illuvial clay and earthworm’s porosity to quantify the intensity of illuviation and bioturbation cumulated over soil formation in a temperate cultivated Luvisol. The key objectives of the study are i) to quantify the total intensity of illuviation and bioturbation and their depth distributions and ii) to assess the possibility for bioturbation to limit or compensate the depletion of the clay-sized fraction in topsoil horizons due to eluviation. The total quantity of illuvial clay is 1,100 t.ha−1 while the estimated annual amount of clay-sized fraction translocated by eluviation is between 0.08 and 1 t ha−1 yr−1. This is comparable to the annual loss of land by water erosion (between 1 and 5 t ha−1 yr−1) or by arable erosion (3.3 t ha−1 yr−1). Eluviation/illuviation is thus a discrete and active form of soil loss. With approximately 1,900 t.ha−1 of clay-sized fraction, the amount of fine particles displaced at least once by bioturbation is higher than the one related to eluviation/illuviation. At first sight, it therefore seems possible for biological activity to compensate for vertical transfers of the clay-sized fraction by eluviation/illuviation. However, our study shows that a considerable amount of the clay-sized fraction will never be brought up by the bioturbation and will remain definitively lost for the surface horizons as bioturbation decreases non-linearly with depth. Consequently, a preventive management of the depletion of the clay-sized fraction in topsoil horizons by eluviation/illuviation should be preferred to the curative management of its consequences by bioturbation.
There exists a wide range of optimization models in the Operations Management (OM) community to solve complex problems such as lot sizing. However, their practical performance is often criticized due to the complexity of implementation and insufficient applicability in real-world decision processes. These theory-driven approaches are either simple to compute, but only focus on single aspects of the decision without being able to capture the practical problem comprehensively, or are complex computational models with limited practicability. We apply a Design Science Research approach to resolve this issue and show how lot size decision-making models should be designed to thoroughly support managers. Our innovative model combines Discrete Event Simulation (DES) with OM methods and is developed and tested in a case study in the metal processing industry. Results reveal that the model is suitable to provide transparency about effects and a range of efficient solutions. Open Access: https://www.tandfonline.com/doi/full/10.1080/21693277.2022.2092564
Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of the hottest server components (i.e., cores and cache). Previous methods focused on either improving energy efficiency by adopting new hybrid-cache architectures including the resistive random-access memory (RRAM) and static random-access memory (SRAM) at the hardware level, or exploring trade-offs between lifetime limitation and performance of multi-core processors under stable workloads conditions. Therefore, no work has so far proposed a co-optimization method with hybrid-cache-based server architectures for real-life dynamic scenarios taking into account scalability, performance, lifetime reliability, and energy efficiency at the same time. In this paper, we first formulate a reliability model for the hybrid-cache architecture to enable precise lifetime reliability management and energy efficiency optimization. We also include the performance and energy overheads of cache switching, and optimize the benefits of hybrid-cache usage for better energy efficiency and performance. Then, we propose a runtime Q-Learning-based reliability management and performance optimization approach for multi-core microprocessors with the hybrid-cache architecture, jointly incorporated with a dynamic preemptive priority queue management method to improve the overall tasks’ performance by targeting to respect their end time limits. Experimental results show that our proposed method achieves up to 44% average performance (i.e., tasks execution time) improvement, while maintaining the whole system design lifetime longer than 5 years, when compared to the latest state-of-the-art energy efficiency optimization and reliability management methods for computing servers.
Background: Currently, very little is known about the effects of an endurance high intensity interval training (HIIT) in chronic low back pain patients. Therefore, the feasibility and safety of the HIIT must be assessed first before Currently, very little is known about the effects of an endurance high intensity interval training in chronic low back pain patients. Therefore, the feasibility and safety of the HIIT has to be assessed first before it can be integrated safely into research and daily practice it can be integrated safely into research and daily practice. This study aims to answers the question if high intensity interval training and moderate intensity continuous training (MICT) have comparable adherence and feasibility. Methods: Participants (age from 29 to 69 years) with non-specific chronic low back pain were recruited in this randomised, single-blinded, allocation concealed, feasibility study. The participants trained 30 min on a cycle ergometer for 12 weeks. One group had HIIT and the other MICT. Results: Of 45 screened subjects 30 participated. The adherence rate was 94% in the HIIT group (median 0.94, IQR 0.23) versus 96% in the MICT group (median 0.96, IQR 0.08), without between-group differences: estimated median of the difference of - 0,01 [95% CI, - 0.11 to 0.06; p = 0.76]. Similar results in enjoyability (median 3, IQR 1 vs median 2, IQR 1.8) and willingness to continue the training (median 3, IQR 1 vs median 3, IQR 0.4). Both groups improved in pain and disability, without between-group differences in pain [median of the difference, 0.5; 95% CI, - 1 to 2; p = 0.95] nor in disability [median of the difference, 1.78; 95% CI, - 6.44 to 9.56; p = 0.64]. Conclusion: There were no differences in adherence rates. HIIT is as feasible as MICT in non-specific chronic low back pain and can be used in future larger trials to deepen the knowledge about HIIT in this specific population. Trial registration: ClinicalTrials.gov, NCT04055545 . Registered 13 August 2019.
The digitalization of clinical workflows and the increasing performance of deep learning algorithms are paving the way towards new methods for tackling cancer diagnosis. However, the availability of medical specialists to annotate digitized images and free-text diagnostic reports does not scale with the need for large datasets required to train robust computer-aided diagnosis methods that can target the high variability of clinical cases and data produced. This work proposes and evaluates an approach to eliminate the need for manual annotations to train computer-aided diagnosis tools in digital pathology. The approach includes two components, to automatically extract semantically meaningful concepts from diagnostic reports and use them as weak labels to train convolutional neural networks (CNNs) for histopathology diagnosis. The approach is trained (through 10-fold cross-validation) on 3’769 clinical images and reports, provided by two hospitals and tested on over 11’000 images from private and publicly available datasets. The CNN, trained with automatically generated labels, is compared with the same architecture trained with manual labels. Results show that combining text analysis and end-to-end deep neural networks allows building computer-aided diagnosis tools that reach solid performance (micro-accuracy = 0.908 at image-level) based only on existing clinical data without the need for manual annotations.
We investigate synthesis, phase evolution, hollow and porous structure and magnetic properties of quasi-amorphous intermediate phase (QUAIPH) and hematite (α-Fe2O3) nanostructure synthesized by annealing of akaganeite (β-FeOOH) nanorods. It is found that the annealing temperature determines the phase composition of the products, the crystal structure/size dictates the magnetic properties whereas the final nanorod morphology is determined by the starting material. Annealing of β-FeOOH at ∼300 °C resulted in the formation of hollow QUAIPH nanorods. The synthesized material shows low-cytotoxicity, superparamagnetism and good transverse relaxivity, which is rarely reported for QUAIPH. The QUAIPH nanorods started to transform to porous hematite nanostructures at ∼350 °C and phase transformation was completed at 600 °C. During the annealing, the crystal structure changed from monoclinic (akaganeite) to quasi-amorphous and rhombohedral (hematite). Unusually, the crystallite size first decreased (akaganeite → QUAIPH) and then increased (QUAIPH → hematite) during annealing whereas the nanorods retained particle shape. The magnetic properties of the samples changed from antiferromagnetic (akaganeite) to superparamagnetic with blocking temperature TB = 84 K (QUAIPH) and finally to weak-ferromagnetic with the Morin transition at TM = 244 K and high coercivity HC = 1652 Oe (hematite). The low-cytotoxicity and MRI relaxivity (r2 = 5.80 mM⁻¹ s⁻¹ (akaganeite), r2 = 4.31 mM⁻¹ s⁻¹ (QUAIPH) and r2 = 5.17 mM⁻¹ s⁻¹ (hematite)) reveal potential for biomedical applications.
Background In healthcare there is a call to provide cost-efficient and safe care. This can be achieved through evidence-based practice (EBP), defined as the use of evidence from research, context, patient preferences, and clinical expertise. However, the contemporary and process-integrated supply of evidence-based knowledge at the point of care is a major challenge. An integrative knowledge management system supporting practicing clinical nurses in their daily work providing evidence-based knowledge at the point of care is required. The aim of this study was (1) to map standardized and structured nursing interventions classification and evidence on a knowledge platform to support evidence-based knowledge at the point of care, and (2) to explore the challenge of achieving interoperability between the source terminology of the nursing interventions classification (LEP Nursing 3) and the target format of the evidence provided on the knowledge platform (FIT-Nursing Care). Methods In an iterative three-round mapping process, three raters, nurses with clinical and nursing informatics or EBP experience, matched nursing interventions from the LEP Nursing 3 classification and evidence provided from Cochrane Reviews summarized on FIT-Nursing Care as so-called study synopses. We used a logical mapping method. We analysed the feasibility using thematic analysis. Results In the third and final mapping round, a total of 47.01% (252 of 536) of nursing interventions from LEP Nursing 3 were mapped to 92.31% (300 of 325) of synopses from FIT-Nursing Care. The interrater reliability of 77.52% suggests good agreement. The experience from the whole mapping process provides important findings: (1) different content orientations—because both systems pursue different purposes (content validity), (2) content granularity—differences regarding the structure and the level of detail in both systems, and (3) operationalization of knowledge. Conclusion Mapping of research evidence to nursing classification seems feasible; however, three specific challenges were identified: different content orientation; content granularity; and operationalization of knowledge. The next step for this integrative knowledge management system will now be testing at the point of care.
This article documents the beginning of the intellectual companionship between the founder of ethnomethodology, Harold Garfinkel, and Edward Rose, who is most often associated with his program of “ethno‐inquiries.” I present results from archival research focusing on the contacts and collaborations between Rose and Garfinkel in the years 1955–1965. First, I describe the review process for Rose and Felton's paper, submitted to the American Sociological Review in 1955, which Garfinkel reviewed and after Rose's rebuttal recommended for publication. The paper induced Garfinkel to write an extensive commentary that has remained unpublished. Second, I discuss the 1958 New Mexico conference sponsored by the Air Force, which was an opportunity for Rose and Garfinkel to work together on topics related to common‐sense knowledge and scientific knowledge. Third, I give an overview of the ethnomethodological conferences in 1962 and 1963, supported by an Air Force grant written collaboratively by Rose and Garfinkel. Here I focus primarily on Rose's research on “small languages,” which stimulated many discussions among the early ethnomethodologists. Rose's work and exchanges with Garfinkel demonstrate the former's affinity for miniaturization as a research approach and search for ways to empiricize topics of sociological theory in locally observable settings.
According to the social cognitive view, the organization of sports team behavior is underpinned by the existence of shared knowledge. This study considers tactical position knowledge as an example of shared macro-level plans involved in organizing team behavior. A coach- and a team-referenced measure of sharedness in tactical knowledge are introduced to test whether expert sport teams share knowledge to a higher degree than weaker sport teams (RQ1), whether the time spent performing a common task predicts shared knowledge (RQ2), whether role-specific specializations are mirrored in the degree to which athletes share tactical knowledge (RQ3) and whether tactical knowledge is shared to different degrees in defensive as opposed to offensive game situations (RQ4). Members of 17 football teams (N = 296) participating in championships at different levels of the Swiss National Football Federation took part in the scenario-based, cross-sectional study. Participants marked the positions of their team members according to their tactical playing strategy. Data were analyzed using multiple regression and mixed linear model procedures. Teams playing at the professional level had significantly more consistent ideas about their teams’ tactical positions than those at the amateur level. Within the amateur level, no consistent pattern of increasing consensus as the playing level increased was found. Sharedness in tactical knowledge increased with the duration of team membership when considering the team-referenced congruency measure. However, the effect was low. Overall, there was a pattern of defenders and midfielders agreeing with their team reference positions more than did goal keepers and forwards. Sharedness was generally higher in defensive situations than in offensive situations. The presented approach to measuring shared knowledge offers new insights into a yet under-researched field. It can be adopted to answering research questions in other sports and situations involving other measures of team performance assumed to be affected by shared knowledge.
We develop new theoretical results on matrix perturbation to shed light on the impact of architecture on the performance of a deep network. In particular, we explain analytically what deep learning practitioners have long observed empirically: the parameters of some deep architectures (e.g., residual networks, ResNets, and Dense networks, DenseNets) are easier to optimize than others (e.g., convolutional networks, ConvNets). Building on our earlier work connecting deep networks with continuous piecewise-affine splines, we develop an exact local linear representation of a deep network layer for a family of modern deep networks that includes ConvNets at one end of a spectrum and ResNets, DenseNets, and other networks with skip connections at the other. For regression and classification tasks that optimize the squared-error loss, we show that the optimization loss surface of a modern deep network is piecewise quadratic in the parameters, with local shape governed by the singular values of a matrix that is a function of the local linear representation. We develop new perturbation results for how the singular values of matrices of this sort behave as we add a fraction of the identity and multiply by certain diagonal matrices. A direct application of our perturbation results explains analytically why a network with skip connections (such as a ResNet or DenseNet) is easier to optimize than a ConvNet: thanks to its more stable singular values and smaller condition number, the local loss surface of such a network is less erratic, less eccentric, and features local minima that are more accommodating to gradient-based optimization. Our results also shed new light on the impact of different nonlinear activation functions on a deep network’s singular values, regardless of its architecture.
Despite considerable growth in understanding of various aspects of sporting and exercise embodiment over the last decade, in-depth investigations of embodied affectual experiences in running remain limited. Furthermore, within the corpus of literature investigating pleasure and the hedonic dimension in running, much of this research has focused on experiences of pleasure in relation to performance and achievement, or on specific affective states, such as enjoyment, derived after completing a run. We directly address this gap in the qualitative literature on sporting and exercise embodiment by contributing novel insights on the mind-body pleasures of running via focusing analytic attention towards the pleasures recalled by runners as experienced during positive, rewarding running experiences. Applying conceptual insights drawn from sociological phenomenology, we analyse data from an in-depth, event-focused interview study with distance runners who reported positive, rewarding experiences in recent recreational runs. Through reflexive thematic analysis, we present findings in relation to three themes: (1) ‘running feels like it should’; (2) sensory engagements; and (3) time out. The study contributes fresh perspectives, both conceptually and in relation to data-collection approach, to a small literature on the lived experience of pleasure in sport, exercise and physical cultures.
Background The COVID-19 pandemic has not only impacted intensive care units, but all healthcare services generally. This PsyGipo2C project specifically investigates how psychiatry and mental health professionals have been affected by the reorganizations and constraints imposed, which have reshaped their often already difficult working conditions. Methods Our research combined quantitative and qualitative methods, surveying and interviewing health professionals of all occupations working in psychiatric and mental health services. A questionnaire was completed by 1241 professionals from 10 European countries, and 13 group interviews were conducted across 5 countries. In addition to this, 31 individual interviews were conducted in Belgium and France. Results Among the questionnaire respondents, 70.2% felt that their workload had increased, particularly due to their tasks being diversified and due to increased complexity in the provision of care. 48.9% felt that finding a work-life balance had become more difficult, and 59.5% felt their health had been affected by the crisis. The impact of the health crisis nevertheless varied across professions: our data provides insight into how the health measures have had a differential impact on professional tasks and roles across the various categories of occupations, obliging professionals to make various adaptations. The distress incurred has been linked not only to these new constraints in their work, but also to the combination of these with other pressures in their personal lives, which has consequently compromised their well-being and their ability to cope with multiple demands. Discussion The COVID-19 health crisis has had varying impacts depending on the profession and access to remote work, sometimes leading to conflicts within the teams. The suffering expressed by the professionals was tied to their values and patterns of investment in work. Our research also highlights how these professionals made little use of the psychological supports offered, probably due to a reluctance to acknowledge that their mental health was affected.
Introduction and literature review Abiotic resources are extensively used in industrialized societies to deliver multiple services that contribute to human well-being. Their increased extraction and use can potentially reduce their accessibility, increase competition among users, and ultimately lead to a deficit of those services. Life cycle assessment is a relevant tool to assess the potential damages of dissipating natural resources. Building on the general consensus recommending evaluating the damages on the instrumental value of resources to humans in order to assess the consequences of resources dissipation, this research work proposes a novel conceptual framework to assess the potential loss of services provided by abiotic resources, which when facing unmet demand can lead to a deficit to human users and have consequences on human well-being. Results A framework is proposed to describe the mechanisms that link human intervention on the resources in the accessible stock to competition among users. Users facing the deficit of resource services are assumed to have to pay to recover the services, using backup technologies. The mechanisms that are proposed to be characterized are dissipation and degradation. Data needed to later operationalize the framework for abiotic resources are identified. It also proposes a framework at the life cycle inventory level to harmonize life cycle inventories with the current impact assessment framework to fully characterize impacts on resource services. It regards ensuring mass balances of elements between inputs and outputs of life cycle inventory datasets as well as including the functionality of resource flows. Discussion and conclusions The framework provides recommendations for the development of operational life cycle impact assessment (LCIA) methods for resource services deficit assessment. It establishes the impact pathway to damage on the area of protection “Resource Services”, data needed to feed the model and recommendations to improve the current state of life cycle inventories to be harmonized with the LCIA framework. Graphical Abstract
Despite decades of prevention, tobacco addiction is still a widespread health concern responsible for around 8 million deaths per year. Existing digital smoking cessation solutions such as social media are becoming increasingly popular and represent a novel approach to find community support. However, little is known about how they affect smoking behavior. This research aims to understand what motivates people to join online communities and how their participation affects their attitudes and behaviors. To do so, this article conducts an in-depth analysis of the popular Reddit r/StopSmoking thread through three complementary studies. Using the transtheoretical model and the uses and gratification theory, Study 1 aims at understanding the link between motivation factors, engagement and outcomes through a user survey. Study 2 aims at understanding the engagement by analyzing the content of 10 years of user interaction data. Study 3 attempts to gain further knowledge of interactions by examining the reaction of the community to a crisis situation such as that of the recent COVID-19 pandemic. Findings convey the fact that participation in such communities has a favorable impact on the change process towards quitting. Results show that providing social support to others is the biggest contributing factor for participating in the community. User interactions analysis confirmed that survey responses were accurate reflections of actual user activity. Regarding the impact of the COVID-19 crisis, results suggest that it increased levels of stress and depression in the community while decreasing active engagement, indicating that there may be opportunities for improvement in dealing with tough situations.
Serious game development involves a multidisciplinary team of teachers and computer scientists. But the difference in computer competencies between the team members is a recurring difficulty in this collaboration. Authoring tools, which provide interfaces adapted to users' competencies, are promising solutions to overcome this difficulty. However, existing authoring tools are either limited in their functionalities (not powerful) or too complex for non-computer scientists (not usable). A comprehensive set of design principles to address this limitation does not yet exist. The objective of this research was to define a set of design principles for the development of powerful and usable authoring tools. To achieve this objective, we first defined a set of design principles. We then developed an authoring tool corresponding to these principles. Finally, we carried out test uses of that tool through the development of twelve serious games. Results show that this authoring tool enabled the development of a wide variety of serious games (powerful) by teams with heterogeneous computer skills (usable). Design principles defined in this research integrate and extend previous works. They allow to overcome the dilemma between the power and usability of authoring tools. This could unlock new possibilities for collaborative approaches in serious games developments.
Social media (SM) enables micro, small, and medium sized enterprises (SMEs) to improve brand awareness and to engage their audience, which can lead to referrals, repeat business, and increased sales. However, the existing literature offers limited insights into how the ability to leverage SM for commercial activities that are beyond transactions (relational social commerce capability) can affect performance outcomes for SMEs. Drawing on the existing literature and insights from in-depth interviews with six SME managers/owners, we developed a conceptual research model and examined it empirically by using a dataset collected from Slovenian SMEs. This study identifies relational social commerce capability and competitive advantage as important mediators when exploring the impact of SM use on business performance. More specifically, the findings reveal the mediating role of relational social commerce capability between SM use and competitive advantage, while SM use was not found to have a direct impact on competitive advantage. Furthermore, the findings illustrate business performance as a result of the competitive advantage derived from relational s-commerce capability.
The current paper discusses some selected developments for efficient management of the globally increasing quantity of waste. Incinerator bottom ash (IBA), the heavier ash generated during incineration of municipal waste, is currently utilised in two distinct ways. One pathway is not to fragment IBA and use it as a building material in road construction. This results in reduced landfilled residual but low metal recovery. The other way is to crush the mineral aggregate, thus maximising metal recovery but resulting in higher landfilled, end material. Here emphasis is placed on the second approach as implemented in Switzerland together with the economics and need for improvement of metal recovery from IBA and fly ash. The second theme reports on the viability of recycling mussel shells as a partial substitute for cement to stabilise dredged marine sediments mechanically. This can reduce the consumption of natural resources and lower the amount of binders used in sediment stabilisation practices. Finally, the adequacy of EU’s requirements regarding monitoring of groundwater pollution from landfills is assessed, and recommendations are provided to use bioindicators to determine the impact of landfills on surrounding vegetation.
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1,218 members
René Schumann
  • Bereich eEnergy
Roland Schegg
  • Institut für Tourismus
Pawel Matusz
  • Haute École de Santé
Lara Allet
  • Health - Physiotherapy
Roger Hilfiker
  • School of Health Sciences
Rue de l'Industrie 23, 1950, Sierre, Valais, Switzerland
Head of institution
François Seppey
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