Leak-Tight Welding Experience from the Industrial Assembly of the LHC Cryostats at CERN

The assembly of the approximately 1700 LHC main ring cryostats at CERN involved extensive welding of cryogenic lines and vacuum vessels. More than 6 km of welding requiring leak tightness to a rate better than 1.10-9 mbar.l.s-1 on stainless steel and aluminium piping and envelopes was made, essentially by manual welding but also making use of orbital welding machines. In order to fulfil the safety regulations related to pressure vessels and to comply with the leak-tightness requirements of the vacuum systems of the machine, welds were executed according to high qualification standards and following a severe quality assurance plan. Leak detection by He mass spectrometry was extensively used. Neon leak detection was used successfully to locate leaks in the presence of helium backgrounds. This paper presents the quality assurance strategy adopted for welds and leak detection. It presents the statistics of non-conformities on welds and leaks detected throughout the entire production and the advances in the use of alternative leak detection methods in an industrial environment

Influence of the elemental composition and crystal structure on the vacuum properties of Ti-Zr-V non-evaporable getter films

Non-evaporable thin film getters based on the elements of the 4th and 5th columns of the periodic table have been deposited by sputtering. Among the about 20 alloys studied to date, the lowest activation temperature (about 180 °C for a 24-hour heating) has been found for the Ti-Zr-V system in a well-defined composition range. The characterization of the activation behavior of such Ti-Zr-V films is presented. The evolution of the surface chemical composition during activation is monitored by Auger Electron Spectroscopy (AES) and the functional properties are evaluated by pumping speed measurements. The pumping speed characteristics are quite similar to those already measured for commercially available NEG materials, except for the much lower saturation coverage for CO. This inconvenience, which is due to the smooth surface structure of these films, can be counteracted by increasing the roughness of the substrate

Vacuum properties of TiZrV non-evaporable getter films

Sputter-deposited thin films of TiZrV are fully activated after 24 h "in situ" heating at 180 °C. This activation temperature is the lowest of some 18 different getter coatings studied so far, and it allows the use of the getter thin film technology with aluminium alloy vacuum chambers, which cannot be baked at temperatures higher than 200 °C.An updated review is given of the most recent results obtained on TiZrV coatings, covering the following topics: influence of the elemental composition and crystal structure on activation temperature, discharge gas trapping and degassing, dependence of pumping speed and surface saturation capacity on film morphology, ageing consequent to activation-air venting cycles and ultimate pressures. Furthermore, the results obtained when exposing a coated particle beam chamber to synchrotron radiation in a real accelerator environment (ESRF Grenoble) are presented and discussed

Periodic Bedrock Ridges at the ExoMars 2022 Landing Site: Evidence for a Changing Wind Regime

Wind-formed features are abundant in Oxia Planum (Mars), the landing site of the 2022 ExoMars mission, which shows geological evidence for a past wet environment. Studies of aeolian bedforms at the landing site were focused on assessing the risk for rover trafficability, however their potential in recording climatic fluctuations has not been explored. Here we show that the landing site experienced multiple climatic changes in the Amazonian, which are recorded by an intriguing set of ridges that we interpret as Periodic Bedrock Ridges (PBRs). Clues for a PBR origin result from ridge regularity, defect terminations, and the presence of preserved megaripples detaching from the PBRs. PBR orientation differs from superimposed transverse aeolian ridges pointing toward a major change in wind regime. Our results provide constrains on PBR formation mechanisms and offer indications on paleo winds that will be crucial for understanding the landing site geology

Martian environmental chamber: Dust system injection

NessunaThe aim of this work is to describe the development and implementation of an experimental setup able to reproduce some characteristics of the Martian atmosphere. The development of such setup fits into the context of MicroMED project, that foresees the development of an optical particle counter to be accommodated on the ExoMars 2020 Surface Platform, as part of the suite of sensors named Dust Complex. MicroMED will perform the first direct measurement of the size distribution of the powder close to Martian surface. The experimental setup is able to reproduce the characteristics of the Martian atmosphere: pressure, atmospheric composition, the actual temperature in which MicroMED will operate (from 20 C to 40 C) and the most important thing: the presence of suspended dust. The main result obtained in this work was the right configuration of an experimental setup in which to test sensors or instruments that work in Martian conditions. In particular, a dust injection system has been developed in order to obtain a dust distribution that was localized and without the formation of particles aggregates, for a correct calibration of the instrument

Aeolian processes at the ExoMars 2022 landing site

Wind-formed features are abundant in Oxia Planum (Mars), the landing site of the 2022 ExoMars mission, which shows geological evidence for a past wet environment [1-4]. Here we show that the landing site experienced multiple climatic changes recorded by an intriguing set of ridges that we interpret as Periodic Bedrock Ridges (PBRs) [5, 6]. Clues for a PBR origin result from ridge regularity, defect terminations, and the presence of preserved megaripples detaching from the PBRs. PBR orientation differs from superimposed transverse aeolian ridges pointing toward a major change in wind regime. Superposition relationships of the PBRs with a dark-toned geological unit [4] indicate that such a change in the main wind condition likely occurred during the Amazonian. Active bedform migration from nearby craters (McLaughlin and Oyama) show winds coming from the North, matching the orientation of the wind streaks visible in the putative landing ellipse. Our results provide constrains on the wind regime in Oxia Planum and offer indications on present and past winds that will be crucial for understanding the landing site geology.For full details, see [1].[1] Silvestro, S. et al. 2021. Periodic Bedrock Ridges at the ExoMars 2022 landing site: Evidence for a Changing Wind Regime. GRL, 48, 4.[2] Favaro, E. et al. 2021. The Aeolian Environment of the Landing Site for the ExoMars Rosalind Franklin Rover in Oxia Planum, Mars. JGR, 126, 4.[3] Balme, M. et al. 2017. Surface-based 3D measurements of small aeolian bedforms on Mars and implications for estimating ExoMars rover traversability hazards. PSS, 153, 39-53.[4] Quantin, C. et al. Oxia Planum: The Landing Site for the ExoMars ''Rosalind Franklin'' Rover Mission: Geological Context and Prelanding Interpretation. Astrobiology, 21, 3.[5] Montgomery, D. R. et al. 2012. Periodic bedrock ridges on Mars. JGR, 117, E03005.[6] Hugenholtz, C. H. et al. 2015. Formation of periodic bedrock ridges on Earth. Aeolian Research, 18, 135-144

Discordant antibiotic therapy and length of stay in children hospitalized for urinary tract infection

BACKGROUND: Urinary tract infections (UTIs) are a common reason for pediatric hospitalizations. OBJECTIVE: To determine the effect of discordant antibiotic therapy (in vitro nonsusceptibility of the uropathogen to initial antibiotic) on clinical outcomes for children hospitalized for UTI. DESIGN/SETTING: Multicenter retrospective cohort study in children aged 3 days to 18 years, hospitalized at 5 children's hospitals with a laboratory‐confirmed UTI. Data were obtained from medical records and the Pediatric Hospital Information System (PHIS) database. PARTICIPANTS: Patients with laboratory‐confirmed UTI. MAIN EXPOSURE: Discordant antibiotic therapy. MEASUREMENTS: Length of stay and fever duration. Covariates included age, sex, insurance, race, vesicoureteral reflux, antibiotic prophylaxis, genitourinary abnormality, and chronic care conditions. RESULTS: The median age of the 216 patients was 2.46 years (interquartile range [IQR]: 0.27, 8.89) and 25% were male. The most common causative organisms were E. coli and Klebsiella species. Discordant therapy occurred in 10% of cases and most commonly in cultures positive for Klebsiella species, Enterobacter species, and mixed organisms. In adjusted analyses, discordant therapy was associated with a 1.8 day (95% confidence interval [CI]: 1.5, 2.1) longer length of stay [LOS], but not with fever duration. CONCLUSIONS: Discordant antibiotic therapy for UTI is common and associated with longer hospitalizations. Further research is needed to understand the clinical factors contributing to the increased LOS and to inform decisions for empiric antibiotic selection in children with UTIs. Journal of Hospital Medicine 2012; © 2012 Society of Hospital MedicinePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94298/1/1960_ftp.pd

Aeolian Landforms in the ExoMars Landing Site, a Regional Perspective

PBRs, TARs and dunes in the ExoMars landing site and its surrounding, evidence for regional winds and climatic changes

A Privacy-Preserving Distributed Architecture for Deep-Learning-as-a-Service

Deep-learning-as-a-service is a novel and promising computing paradigm aiming at providing machine/deep learning solutions and mechanisms through Cloud-based computing infrastructures. Thanks to its ability to remotely execute and train deep learning models (that typically require high computational loads and memory occupation), such an approach guarantees high performance, scalability, and availability. Unfortunately, such an approach requires to send information to be processed (e.g., signals, images, positions, sounds, videos) to the Cloud, hence having potentially catastrophic-impacts on the privacy of users. This paper introduces a novel distributed architecture for deep-learning-as-a-service that is able to preserve the user sensitive data while providing Cloud-based machine and deep learning services. The proposed architecture, which relies on Homomorphic Encryption that is able to perform operations on encrypted data, has been tailored for Convolutional Neural Networks (CNNs) in the domain of image analysis and implemented through a client-server REST-based approach. Experimental results show the effectiveness of the proposed architecture