Thermal effects compensation and associated uncertainty for large magnet assembly precision alignment

Big science and ambitious industrial projects continually push technical requirements forward beyond the grasp of conventional engineering techniques. An example of these are the extremely tight micrometric assembly and alignment tolerances required in the field of celestial telescopes, particle accelerators, and the aerospace industry. Achieving such extreme requirements for large assemblies is limited, largely by the capability of the metrology used, namely, its uncertainty in relation to the alignment tolerance required. The current work described here was done as part of Maria Curie European research project held at CERN, Geneva. This related to future accelerators requiring the spatial alignment of several thousand, metre-plus large assemblies to a common datum within a targeted combined standard uncertainty (uctg(y)) of 12 μm. The current work has found several gaps in knowledge limiting such a capability. Among these was the lack of uncertainty statements for the thermal error compensation applied to correct for the assembly's dimensional instability, post metrology and during assembly and alignment. A novel methodology was developed by which a mixture of probabilistic modelling and high precision traceable reference measurements were used to quantify the uncertainty of the various thermal expansion models used namely: Empirical, Finite Element Method (FEM) models and FEM metamodels. Results have shown that the suggested methodology can accurately predict the uncertainty of the thermal deformation predictions made and thus compensations. The analysis of the results further showed how using this method a ‘digital twin’ of the engineering structure can be calibrated with known uncertainty of the thermal deformation behaviour predictions in the micrometric range. Namely, the Empirical, FEM and FEM metamodels combined standard uncertainties ( uc(y) ) of prediction were validated to be of maximum: 8.7 μm, 11.28 μm and 12.24 μm for the studied magnet assemblies

A Unifying Variational Framework for Gaussian Process Motion Planning

To control how a robot moves, motion planning algorithms must compute paths in high-dimensional state spaces while accounting for physical constraints related to motors and joints, generating smooth and stable motions, avoiding obstacles, and preventing collisions. A motion planning algorithm must therefore balance competing demands, and should ideally incorporate uncertainty to handle noise, model errors, and facilitate deployment in complex environments. To address these issues, we introduce a framework for robot motion planning based on variational Gaussian processes, which unifies and generalizes various probabilistic-inference-based motion planning algorithms, and connects them with optimization-based planners. Our framework provides a principled and flexible way to incorporate equality-based, inequality-based, and soft motion-planning constraints during end-to-end training, is straightforward to implement, and provides both interval-based and Monte-Carlo-based uncertainty estimates. We conduct experiments using different environments and robots, comparing against baseline approaches based on the feasibility of the planned paths, and obstacle avoidance quality. Results show that our proposed approach yields a good balance between success rates and path quality

A randomized, placebo-controlled trial of repeated IV antibiotic therapy for Lyme encephalopathy

Background: Optimal treatment remains uncertain for patients with cognitive impairment that persists or returns after standard IV antibiotic therapy for Lyme disease. Methods: Patients had well-documented Lyme disease, with at least 3 weeks of prior IV antibiotics, current positive IgG Western blot, and objective memory impairment. Healthy individuals served as controls for practice effects. Patients were randomly assigned to 10 weeks of double-masked treatment with IV ceftriaxone or IV placebo and then no antibiotic therapy. The primary outcome was neurocognitive performance at week 12—specifically, memory. Durability of benefit was evaluated at week 24. Group differences were estimated according to longitudinal mixed-effects models. Results: After screening 3368 patients and 305 volunteers, 37 patients and 20 healthy individuals enrolled. Enrolled patients had mild to moderate cognitive impairment and marked levels of fatigue, pain, and impaired physical functioning. Across six cognitive domains, a significant treatment-by-time interaction favored the antibiotic-treated group at week 12. The improvement was generalized (not specific to domain) and moderate in magnitude, but it was not sustained to week 24. On secondary outcome, patients with more severe fatigue, pain, and impaired physical functioning who received antibiotics were improved at week 12, and this was sustained to week 24 for pain and physical functioning. Adverse events from either the study medication or the PICC line were noted among 6 of 23 (26.1%) patients given IV ceftriaxone and among 1 of 14 (7.1%) patients given IV placebo; these resolved without permanent injury. Conclusion: IV ceftriaxone therapy results in short-term cognitive improvement for patients with posttreatment Lyme encephalopathy, but relapse in cognition occurs after the antibiotic is discontinued. Treatment strategies that result in sustained cognitive improvement are needed

Multiphase modelling of tumour growth and extracellular matrix interaction: mathematical tools and applications

Resorting to a multiphase modelling framework, tumours are described here as a mixture of tumour and host cells within a porous structure constituted by a remodelling extracellular matrix (ECM), which is wet by a physiological extracellular fluid. The model presented in this article focuses mainly on the description of mechanical interactions of the growing tumour with the host tissue, their influence on tumour growth, and the attachment/detachment mechanisms between cells and ECM. Starting from some recent experimental evidences, we propose to describe the interaction forces involving the extracellular matrix via some concepts coming from viscoplasticity. We then apply the model to the description of the growth of tumour cords and the formation of fibrosis

Adsorption and reaction of CO on (Pd–)Al2O3 and (Pd–)ZrO2: vibrational spectroscopy of carbonate formation

γ-Alumina is widely used as an oxide support in catalysis, and palladium nanoparticles supported by alumina represent one of the most frequently used dispersed metals. The surface sites of the catalysts are often probed via FTIR spectroscopy upon CO adsorption, which may result in the formation of surface carbonate species. We have examined this process in detail utilizing FTIR to monitor carbonate formation on γ-alumina and zirconia upon exposure to isotopically labelled and unlabelled CO and CO2. The same was carried out for well-defined Pd nanoparticles supported on Al2O3 or ZrO2. A water gas shift reaction of CO with surface hydroxyls was detected, which requires surface defect sites and adjacent OH groups. Furthermore, we have studied the effect of Cl synthesis residues, leading to strongly reduced carbonate formation and changes in the OH region (isolated OH groups were partly replaced or were even absent). To corroborate this finding, samples were deliberately poisoned with Cl to an extent comparable to that of synthesis residues, as confirmed by Auger electron spectroscopy. For catalysts prepared from Cl-containing precursors a new CO band at 2164 cm−1 was observed in the carbonyl region, which was ascribed to Pd interacting with Cl. Finally, the FTIR measurements were complemented by quantification of the amount of carbonates formed via chemisorption, which provides a tool to determine the concentration of reactive defect sites on the alumina surface

Regional Cerebral Blood Flow and Metabolic Rate in Persistent Lyme Encephalopathy

Context: There is controversy regarding whether objective neurobiological abnormalities exist after intensive antibiotic treatment for Lyme disease. Objectives: To determine whether patients with a history of well-characterized Lyme disease and persistent cognitive deficit show abnormalities in global or topographic distributions of regional cerebral blood flow (rCBF) or cerebral metabolic rate (rCMR). Design: Case-controlled study. Setting: A university medical center. Participants: A total of 35 patients and 17 healthy volunteers (controls). Patients had well-documented prior Lyme disease, a currently reactive IgG Western blot, prior treatment with at least 3 weeks of intravenous cephalosporin, and objective memory impairment. Main Outcome Measures: Patients with persistent Lyme encephalopathy were compared with age-, sex-, and education-matched controls. Fully quantified assessments of rCBF and rCMR for glucose were obtained while subjects were medication-free using positron emission tomography. The CBF was assessed in 2 resting room air conditions (without snorkel and with snorkel) and 1 challenge condition (room air enhanced with carbon dioxide, ie, hypercapnia). Results: Statistical parametric mapping analyses revealed regional abnormalities in all rCBF and rCMR measurements that were consistent in location across imaging methods and primarily reflected hypoactivity. Deficits were noted in bilateral gray and white matter regions, primarily in the temporal, parietal, and limbic areas. Although diminished global hypercapnic CBF reactivity (P < .02) was suggestive of a component of vascular compromise, the close coupling between CBF and CMR suggests that the regional abnormalities are primarily metabolically driven. Patients did not differ from controls on global resting CBF and CMR measurements. Conclusions: Patients with persistent Lyme encephalopathy have objectively quantifiable topographic abnormalities in functional brain activity. These CBF and CMR reductions were observed in all measurement conditions. Future research should address whether this pattern is also seen in acute neurologic Lyme disease