Comparison of diagnostic methods for detection of BRAFV600E mutation in ameloblastoma.

BACKGROUND: Ameloblastoma is an aggressively growing, highly recurrent odontogenic jaw tumor. Its association with BRAFV600E mutation is an indication for BRAFV00E-inhibitor therapy The study objective was to identify a sensitive low-cost test for BRAFV600E-positive ameloblastoma. We hypothesized that immunohistochemical staining of formalin-fixed paraffin-embedded tissues for BRAFV600E mutation is a low-cost surrogate for BRAFV600E gene sequencing when laboratory resources are inadequate for molecular testing. METHODS: Tissues from 40 ameloblastoma samples were retrieved from either formalin-fixed paraffin-embedded blocks, RNAlater™ stabilization solution or samples inadvertently pre-fixed in formalin before transfer to RNAlater™. BRAFV600E mutation was assessed by Direct Sanger sequencing, Amplification Refractory Mutation System-PCR and immunohistochemistry (IHC). RESULTS: BRAFV600E mutation was detected by IHC, Amplification Refractory Mutation System-PCR and Direct Sanger sequencing in 93.33%, 52.5% and 30% of samples respectively. Considering Direct Sanger sequencing as standard BRAFV600E detection method, there was significant difference between the three detection methods (𝜒2 (2) = 31.34, p < 0.0001). Sensitivity and specificity of IHC were 0.8 (95% CI: 0.64-0.90) and 0.9 (95% CI: 0.75-0.99) respectively, while positive predictive value and negative predictive value (NPV) were 0.9 and 0.8 (Fischer's test, p < 0.0001) respectively. Sensitivity and specificity of Amplification Refractory Mutation System-PCR detection method were 0.7 (95% CI: 0.53-0.80) and 0.9 (95% CI = 0.67-0.98) respectively, while PPV and NPV were 0.9 and 0.6 respectively (Fischer's test, p < 0.0001). CONCLUSION: Low-cost and less vulnerability of IHC to tissue quality make it a viable surrogate test for BRAFV600E detection in ameloblastoma. Sequential dual IHC and molecular testing for BRAFV600E will reduce equivocal results that could exclude some patients from BRAFV600E-inhibitor therapies.

A Robust Cubature Kalman Filter with Abnormal Observations Identification Using the Mahalanobis Distance Criterion for Vehicular INS/GNSS Integration.

INS/GNSS (inertial navigation system/global navigation satellite system) integration is a promising solution of vehicle navigation for intelligent transportation systems. However, the observation of GNSS inevitably involves uncertainty due to the vulnerability to signal blockage in many urban/suburban areas, leading to the degraded navigation performance for INS/GNSS integration. This paper develops a novel robust CKF with scaling factor by combining the emerging cubature Kalman filter (CKF) with the concept of Mahalanobis distance criterion to address the above problem involved in nonlinear INS/GNSS integration. It establishes a theory of abnormal observations identification using the Mahalanobis distance criterion. Subsequently, a robust factor (scaling factor), which is calculated via the Mahalanobis distance criterion, is introduced into the standard CKF to inflate the observation noise covariance, resulting in a decreased filtering gain in the presence of abnormal observations. The proposed robust CKF can effectively resist the influence of abnormal observations on navigation solution and thus improves the robustness of CKF for vehicular INS/GNSS integration. Simulation and experimental results have demonstrated the effectiveness of the proposed robust CKF for vehicular navigation with INS/GNSS integration.

Prevalence and its risk factors for low back pain among operation and maintenance personnel in wind farms.

BACKGROUND: With the increasingly severe energy shortage and climate change problems, developing wind power has become a key energy development strategy and an inevitable choice to protect the ecological environment worldwide. The purpose of this study was to investigate the prevalence of low back pain (LBP) and analyze its risk factors among operation and maintenance personnel in wind farms (OMPWF). METHODS: A cross-sectional survey of 151 OMPWF was performed, and a comprehensive questionnaire, which was modified and combined from Nordic Musculoskeletal Questionnaires (NMQ), Washington State Ergonomics Tool (WSET) and Syndrome Checklist-90(SCL-90) was used to assess the prevalence and risk factors of LBP among OMPWF. RESULTS: The prevalence of LBP was 88.74 % (134/151) among OMPWF. The multivariable model highlighted four related factors: backrest, somatization, squatting and lifting objects weighing more than 10 lb more than twice per minute. CONCLUSIONS: The prevalence of LBP among OMPWF appears to be high and highlights a major occupational health concern.

Real-time haptic characterisation of Hunt-Crossley model based on radial basis function neural network for contact environment.

Dynamic soft tissue characterisation is an important element in robotic minimally invasive surgery. This paper presents a novel method by combining neural network with recursive least square (RLS) estimation for dynamic soft tissue characterisation based on the nonlinear Hunt-Crossley (HC) model. It develops a radial basis function neural network (RBFNN) to compensate for the error caused by natural logarithmic factorisation (NLF) of the HC model for dynamic RLS estimation of soft tissue properties. The RBFNN weights are estimated according to the maximum likelihood principle to evaluate the probability distribution of the neural network modelling residual. Further, by using the linearisation error modelled by RBFNN to compensate for the linearised HC model, an RBFNN-based RLS algorithm is developed for dynamic soft tissue characterisation. Simulation and experimental results demonstrate that the proposed method can effectively model the natural logarithmic linearisation error, leading to improved accuracy for RLS estimation of the HC model parameters.

Effect of nano h-BN particles on growth regularity and tribological behavior of PEO composite ceramic coating of ZL109 alloy.

A composite ceramic coating containing h-BN particles was prepared on the ZL109 alloy via plasma electrolytic oxidation. The h-BN particles were modified by Polyethylene glycol to improve the dispersibility. The results revealed that the h-BN particles in the electrolyte were inertly incorporated into the coating. Meanwhile, the incorporation of h-BN particles can reduce the porosity and slightly increase the roughness of the composite ceramic coating. Furthermore, the growth rate of the coating and the conversion of γ-Al2O3 and α-Al2O3 were promoted by the incorporation of h-BN particles via the change of the current. In addition, due to the presence of h-BN particles, the composite ceramic coating had a lower friction coefficient and a lower wear rate under dry sliding condition.

Effect of nickel-coated carbon nanotubes on the preparation and wear resistance of microarc oxidation ceramic coating on ZL109 aluminum alloy.

In order to adapt to the development of lightweight equipment, and further improve the wear resistance of ZL109 aluminum alloy, the influence of nickel-coated carbon nanotubes as an electrolyte additive on the preparation and wear resistance of microarc oxidation ceramic coatings on ZL109 aluminum alloy surface was investigated. In this work, 0.4 g/L, 0.8 g/L, 1.2 g/L, 1.6 g/L, and 2 g/L nickel-coated carbon nanotubes were added to the electrolyte respectively. The microarc oxidation ceramic coatings were prepared under bipolar pulse constant pressure mode, which were analyzed from the aspects of morphology, chemical composition, and wear resistance property. The results show that the nickel-coated carbon nanotubes possess a great influence on ceramic coatings. The morphology of ceramic coatings was significantly changed. In this work, the coating prepared by 1.2 g/L nickel-coated carbon nanotubes exhibits excellent wear resistance property.

Extended Kalman filter for online soft tissue characterization based on Hunt-Crossley contact model.

Real-time soft tissue characterization is significant to robotic assisted minimally invasive surgery for achieving precise haptic control of robotic surgical tasks and providing realistic force feedback to the operator. This paper presents a nonlinear methodology for online soft tissue characterization. An extended Kalman filter (EKF) is developed based on dynamic linearization of the nonlinear H-C contact model in terms of system state for online characterization of soft tissue parameters. To handle the resultant linearization modelling error, an innovation orthogonal EKF is further developed by incorporating an adaptive factor in the EKF filtering to adaptively adjust the innovation covariance according to the principle of innovation orthogonality. Simulation and experimental results as well as comparison analysis demonstrate that the proposed methodology can effectively characterize soft tissue parameters, leading to dramatically improved accuracy comparing to recursive least square estimation. Further, the proposed methodology also requires a smaller computational load and can achieve the real-time performance for soft tissue characterization.

Extended Kalman filter based on stochastic epidemiological model for COVID-19 modelling.

This paper presents a new stochastic-based method for modelling and analysis of COVID-19 spread. A new deterministic Susceptible, Exposed, Infectious, Recovered (Re-infected) and Deceased-based Social Distancing model, named SEIR(R)D-SD, is proposed by introducing the re-infection rate and social distancing factor into the traditional SEIRD (Susceptible, Exposed, Infectious, Recovered and Deceased) model to account for the effects of re-infection and social distancing on COVID-19 spread. The deterministic SEIRD(R)D-SD model is further converted into the stochastic form to account for uncertainties involved in COVID-19 spread. Based on this, an extended Kalman filter (EKF) is developed based on the stochastic SEIR(R)D-SD model to simultaneously estimate both model parameters and transmission state of COVID-19 spread. Simulation results and comparison analyses demonstrate that the proposed method can effectively account for the re-infection and social distancing as well as uncertain effects on COVID-19 spread, leading to improved accuracy for prediction of COVID-19 spread.

Anticorrosive non-crystalline coating prepared by plasma electrolytic oxidation for ship low carbon steel pipes.

A corrosion-resistant non-crystalline coating was fabricated by plasma electrolytic oxidation (PEO) on Q235 low carbon steel for ship pipes. The distribution and composition of chemical elements and phases of PEO coatings were analyzed by an orthogonal experiment, and the formation mechanism of PEO coatings was discussed. The corrosion current densities and corrosion potentials were measured. The results indicated that the formation of a transition layer mainly containing Fe3O4 was crucial for achieving an excellent coating quality. Furthermore, the corrosion current density of coated steel was reduced by 78% compared with the bare steel.