On the impact of covariance functions in multi-objective Bayesian optimization for engineering design

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordMulti-objective Bayesian optimization (BO) is a highly useful class of methods that can effectively solve computationally expensive engineering design optimization problems with multiple objectives. However, the impact of covariance function, which is an important part of multi-objective BO, is rarely studied in the context of engineering optimization. We aim to shed light on this issue by performing numerical experiments on engineering design optimization problems, primarily low-fidelity problems so that we are able to statistically evaluate the performance of BO methods with various covariance functions. In this paper, we performed the study using a set of subsonic airfoil optimization cases as benchmark problems. Expected hypervolume improvement was used as the acquisition function to enrich the experimental design. Results show that the choice of the covariance function give a notable impact on the performance of multi-objective BO. In this regard, Kriging models with Matern-3/2 is the most robust method in terms of the diversity and convergence to the Pareto front that can handle problems with various complexities.Natural Environment Research Council (NERC

A Specific Haplotype Framework Surrounds the Omani Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) Mutation S549R

Abstract Cystic Fibrosis (CF) is an autosomal recessive disorder affecting the chloride transport in mucus-producing epithelial cells. The disease is caused by mutations in the Cystic Fibrosis Transmembrane conductance Regulator (CFTR), which is responsible for trans-epithelial chloride transport. Approximately 1900 mutations and gene variants of the CFTR have been described. The spectrum of major White-European mutations includes F508del, G542X, G551D and N1303K. F508del is the most common CF-causing mutation, found in approximately 70% of all CF patients worldwide. The spectrum of CF mutations of Arab populations is under-investigated. However, initial molecular-epidemiological studies indicate the existence of specific CF mutation clusters within geographical regions in the Middle East, suggesting specific distributions of CF mutation carrying chromosomes in this part of the world. We showed that the world-wide rare CF mutation S549R is the predominant disease causing mutation in the Omani population. We reported that S549R, together with two other identified mutations, F508del and the rare private mutation V392G, are genetically linked to the exonic methionine polymorphism c.1408A>G; p.Met470Val at exon 10 and the intronic dimorphic 4-bp GATT 6-repeat at intron 6, c.744_33GATT [6_8]. We detected three haplotypes in 28 alleles of the Omani CF cohort and 408 alleles of our control cohort of unrelated and unaffected Omani volunteers. The CF disease associated haplotype consisting of an M allele and a 6-repeat expansion, occurred with an allele frequency of only 0.174 in the normal Omani population. The discriminative power of the haplotype was attributed to the intronic dimorphic 4-bp GATT 6-repeat. Furthermore, we found only one mutation, c.1733_1734delTA in the Omani CF cohort which deviated from the rule and shared the most common haplotype, a V allele and a 7-repeat extension, with the normal population

Multi-objective optimization using Deep Gaussian Processes: Application to Aerospace Vehicle Design

International audienceThis paper is focused on the problem of constrained multi-objective design optimization of aerospace vehicles. The design of such vehicles often involves disciplinary legacy models considered as black-box and computationally expensive simulations characterized by a possible non-stationary behavior (an abrupt change in the response or a different smoothness along the design space). The expensive cost of an exact function evaluation makes the use of classical evolutionary multi-objective algorithms not tractable. While Bayesian Optimization based on Gaussian Process regression can handle the expensive cost of the evaluations, the non-stationary behavior of the functions can make it inefficient. A recent approach consisting of coupling Bayesian Optimization with Deep Gaussian Processes showed promising results for single-objective non-stationary problems. This paper presents an extension of this approach to the multi-objective context. The efficiency of the proposed approach is assessed with respect to classical optimization methods on an analytical test-case and on an aerospace design problem

Repeatability of Corticospinal and Spinal Measures during Lengthening and Shortening Contractions in the Human Tibialis Anterior Muscle

Elements of the human central nervous system (CNS) constantly oscillate. In addition, there are also methodological factors and changes in muscle mechanics during dynamic muscle contractions that threaten the stability and consistency of transcranial magnetic stimulation (TMS) and perpherial nerve stimulation (PNS) measures

Dental Ergonomics to Combat Musculoskeletal Disorders: A Review

Musculoskeletal disorders (MSDs) are significant workplace problems affecting occupational health, productivity and the careers of dental professionals. The prevalence of MSDs is on the rise for all types of dental workers. In spite of different patterns of work culture, there are parallel levels of symptoms in dentists across nations. Risk factors for MSDs are multifactorial. Symptoms appear very early in careers, with higher prevalence of MSDs even during educational training. Ergonomics improvements, health promotion and organizational interventions are necessary to reduce the risk. An interdisciplinary approach with progressive efforts should be taken to address MSDs in dental professionals

Prevalence of bone loss surrounding dental implants as detected in cone beam computed tomography: a cross-sectional study

Objectives The objective of this study was to assess the prevalence of crestal, and apical bone loss (CBL & ABL) associated with dental implants in CBCT scans. The second objective was to assess the radiographic stage of implant disease and the visible predisposing factors. Materials and Methods The CBCT scans that were taken from January 2015 to January 2022 in King Saud Medical City were screened to examine the marginal and periapical condition of dental implants. Information related to demographic variables, stage of bone loss, and radiographically evident predisposing factors were collected. The results were analyzed using descriptive statistics, chi-square test, and logistic regression analysis. Results In total, 772 implant scans were analyzed. The prevalence of crestal bone loss and apical bone loss around the implants were 6.9% and 0.4% respectively. The amount of bone loss was moderate in 52.8% of cases of CBL and 100% mild in cases of ABL. The risk factors for CBL were patient age (p < 0.001), implant location (p < 0.001), bone loss in proximal teeth (p < 0.001), and adjacent edentulous sites (p < 0.001). The risk factors for ABL were adjacent periapical infection (p < 0.001) and endodontic therapy (p = 0.024). Conclusion The prevalence of CBL and ABL was low. The CBCT can be used as a diagnostic tool for studying the prevalence of bone loss associated with peri-implant disease and relevant risk factors. The implantation of CBCT to evaluate the success and the prognosis of dental implants or the treatment of peri-implant diseases can be further considered in future research

Evaluation of the Dentinal Shear Bond Strength and Resin Interface in Primary Molars after Pre-Treatment with Various Dentin Bio-Modifiers: An In Vitro Study

Dentine adhesives have demonstrated great success with permanent teeth. Though the results in primary teeth are not well documented, some studies have demonstrated lower values of bond strength in primary teeth than those found in permanent teeth. The aim of this study was to compare and evaluate the effect of grape seed extract (6.5%) (Herbal Bio Solutions, Delhi, India), glutaraldehyde (5%) (Loba Chemie PVT. LTD., Mumbai), hesperidin (0.5%) (Herbal Bio Solutions, Delhi, India), and casein phosphopeptide-amorphous calcium phosphate (tooth mousse) (GC Corporation, Alsip, IL, USA) on the shear bond strength of dentine of primary teeth and to evaluate the resin tags at the resin tooth interface. Seventy-five caries-free human primary molars were collected, and their occlusal surfaces were ground flat. Dentin surfaces were etched using phosphoric acid. Then teeth were randomly assigned in sequential order to five groups according to the dentinal treatment method: Group I (Control group) (no treatment), Group II (5% glutaraldehyde), Group III (6.5% grape seed extract), Group IV (0.5% hesperidin), and Group V (CPP-ACP). Ten teeth from each group were assigned for Shear Bond Strength and five for SEM analysis. ANOVA and a post hoc least significant difference test (p p p < 0.05). The use of dentin bio modifiers such as 5% glutaraldehyde, 6.5% grape seed extract, 0.5% hesperidin, and CPP-ACP in the bonding process for primary teeth did not improve the dentinal bond strength