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BackgroundDue to the axial elongation–associated changes in the optic nerve and retina in high myopia, traditional methods like optic disc evaluation and visual field are not able to correctly differentiate glaucomatous lesions. It has been clinically challenging to detect glaucoma in highly myopic eyes. ObjectiveThis study aimed to develop a neural network to adjust for the dependence of the peripapillary retinal nerve fiber layer (RNFL) thickness (RNFLT) profile on age, gender, and ocular biometric parameters and to evaluate the network’s performance for glaucoma diagnosis, especially in high myopia. MethodsRNFLT with 768 points on the circumferential 3.4-mm scan was measured using spectral-domain optical coherence tomography. A fully connected network and a radial basis function network were trained for vertical (scaling) and horizontal (shift) transformation of the RNFLT profile with adjustment for age, axial length (AL), disc-fovea angle, and distance in a test group of 2223 nonglaucomatous eyes. The performance of RNFLT compensation was evaluated in an independent group of 254 glaucoma patients and 254 nonglaucomatous participants. ResultsBy applying the RNFL compensation algorithm, the area under the receiver operating characteristic curve for detecting glaucoma increased from 0.70 to 0.84, from 0.75 to 0.89, from 0.77 to 0.89, and from 0.78 to 0.87 for eyes in the highest 10% percentile subgroup of the AL distribution (mean 26.0, SD 0.9 mm), highest 20% percentile subgroup of the AL distribution (mean 25.3, SD 1.0 mm), highest 30% percentile subgroup of the AL distribution (mean 24.9, SD 1.0 mm), and any AL (mean 23.5, SD 1.2 mm), respectively, in comparison with unadjusted RNFLT. The difference between uncompensated and compensated RNFLT values increased with longer axial length, with enlargement of 19.8%, 18.9%, 16.2%, and 11.3% in the highest 10% percentile subgroup, highest 20% percentile subgroup, highest 30% percentile subgroup, and all eyes, respectively. ConclusionsIn a population-based study sample, an algorithm-based adjustment for age, gender, and ocular biometric parameters improved the diagnostic precision of the RNFLT profile for glaucoma detection particularly in myopic and highly myopic eyes.

Abstract We revisit the masses of heavy quarkonium double-gluon hybrid mesons with exotic quantum numbers J PC = 1−+ and 2+− in the framework of the QCD sum rules. Considering the double-gluon hybrid meson operators in the octet-octet color structure, we have constructed two independent interpolating currents with J PC = 1−+ and five independent currents with J PC = 2+−. For the interpolating currents with antisymmetric glueball operator, there exist non-local divergences in one kind of additional Feynman diagrams of the tri-gluon condensate, which will give important contributions to the sum rule stabilities and mass predictions. We use the diagrammatic renormalization to cancel out such divergences. At the leading order of α s , the two-point correlation functions and spectral densities can be expressed in the analytic form of the generalized hypergeometric functions and Meijer’s G-functions. After performing the numerical analysis, we predict the masses of the 1−+ and 2+− charmonium double-gluon hybrid mesons to be around 6.1 − 7.2 GeV and 6.3 − 6.4 GeV, respectively. For the bottomonium systems, their masses are predicted to be 13.7 − 14.3 GeV and 12.6 − 13.3 GeV for the 1−+ and 2+− channels, respectively. Besides, it is possible to hunt for these charmonium hybrids in the radiative decays of bottomonium mesons in BelleII experiment. Further investigations on these hybrid states in various theoretical and phenomenological methods are also anticipated in the future.

Abstract Due to their responsiveness to modulation by external direct current fields, dielectric tunable materials are extensively utilized in integrated components, such as ferroelectric phase shifters. Barium strontium titanate ceramics have been considered the most potential tunable materials for a long time. However, the significant dielectric loss and high voltage drive have limited their further applications. Recently, Bi6Ti5WO22 ceramic has regained attention for its high dielectric tunability with low loss. In this study, we judiciously introduce Nb5+ with a larger ionic radius, replacing Ti4+ and W6+. This successful substitution enables the modulation of the phase transition temperature of Bi6Ti5WO22 ceramics to room temperature, resulting in superior tunable properties. Specifically, the 0.7Bi6Ti5WO22−0.3Bi6Ti4Nb2O22 ceramics exhibit giant tunability (~75.6%) with ultralow loss (

Total thrust and torque are two key indicators of shield movement performance. Most existing data-driven machine learning studies focus on developing more accurate models for predicting total thrust and torque but overlook the interpretability of the models. To address this black-box issue, this study proposes an interpretable probabilistic prediction algorithm for the shield movement performance. The algorithm uses the natural gradient boosting (NGBoost) model to iteratively update the parametric probability distributions (e.g., mean and variance) and achieve probabilistic predictions of the total thrust and torque. The impact of each feature on the prediction values and uncertainty is quantified by extending the importance analysis of a single deterministic predictive value to both the mean and variance. The feature interactions are analyzed and their predictive contributions are quantified by the shapley additive explanations (SHAP) method. The transparency of the NGBoost model is improved through the visualization of the decision-making process. A shield tunneling project in Hangzhou is used to validate the effectiveness of the proposed algorithm. The results indicate that the NGboost model outperforms other five models in terms of accuracy. The prediction results are interpretable, and the interpretable probabilistic model provides decision-makers with a more intuitive and reliable reference.

We develop an analytical model for estimating the equilibrium quantities, such as electron temperature and number density, in an electron beam–plasma interaction system. This model provides a convenient way to calculate the effective electron temperature and density by considering the energy balance of the bulk cold electrons. Six energy sources/losses terms relevant to the cold electrons are accounted for, where quasi-linear theory is applied for estimating wave heating at equilibrium. We compare this calculation with the particle-in-cell (PIC) simulation results and find good agreement. Based on these results, we then consider two situations where we can simplify our model. The first is dominated by the balance between electron–electron Coulomb collisions and loss to the anode, which is mostly relevant to the conduction phase of plasma switches. The second is dominated by wave heating balanced by the anode loss, relevant to the electron beam–plasma discharge systems. We then couple our simplified energy balance model with the ion diffusion model and solve both the number density and the electron temperature as functions of the current density, electrode distance, pressure, and applied voltage, where a nice agreement is also obtained when comparing to PIC simulations. [ABSTRACT FROM AUTHOR]

[C20H34F12N4P2], triclinic, P1‾ $P\overline{1}$ (no. 2), a = 8.4322(10) Å, b = 13.6360(16) Å, c = 13.8381(16) Å, α = 89.9960(10)°, β = 105.5320(10)°, γ = 90.0150(10)°, V = 1533.0(3) Å3, Z = 2, Rgt (F) = 0.0613, wRref (F 2) = 0.1966, T = 296(2) K.