Hyperfine structure and hyperfine transitions of helium-3

The hyperfine structure of 3He with an external magnetic field is precisely calculated by using double basis set wave functions. The comparison with available experiments effectively tests the theory of hyperfine structure. An exact diagonalization provides a comprehensive interpretation of the results across the complete range of hyperfine coupling strengths of 3He. The theoretical investigation shows that suppression of the hyperfine transitions is caused mainly by strong hyperfine mixing and accidental cancellation between two hyperfine states. An IS coupling model can also qualitatively interpret the suppression of the hyperfine transitions. However, this work has shown that the IS model will become more accurate as the hyperfine transitions occur between 23S1 and n 3PJ states with higher values of principal quantum number n. An unexpected result of this work is that even for the low-Z isotope 3He, hyperfine-induced transitions are still important. This originates from strong hyperfine mixing between singlet and triplet states

Hyperfine structure for the Rydberg states of helium-3.

A comprehensive study is made of the hyperfine structure of the helium isotope 3He for all states up to n = 10 and L = 7. High precision values of the hyperfine structure parameters CSS\u27, DS, and ESS\u27 are calculated using the doubled-basis-set Hylleraas-type wave functions developed by Drake. In this calculation, the singlet-triplet states mixing, the Breit relativistic, QED and finite nuclear size effects are included. Hyperfine splittings and hyperfine shifts have been calculated by diagonalizing the complete fine and hyperfine interaction matrix. Our results nicely agree with the available experimental ones. One of the applications of the calculated hyperfine shift is to determine the nuclear radius of 3He. This work forms a complete description of hyperfine structure of 3 He. Source: Masters Abstracts International, Volume: 43-05, page: 1740. Adviser: G. W. F. Drake. Thesis (M.Sc.)--University of Windsor (Canada), 2004

Optimization of Treatment Geometry to Reduce Normal Brain Dose in Radiosurgery of Multiple Brain Metastases with Single-Isocenter Volumetric Modulated Arc Therapy

Treatment of patients with multiple brain metastases using a single-isocenter volumetric modulated arc therapy (VMAT) has been shown to decrease treatment time with the tradeoff of larger low dose to the normal brain tissue. We have developed an efficient Projection Summing Optimization Algorithm to optimize the treatment geometry in order to reduce dose to normal brain tissue for radiosurgery of multiple metastases with single-isocenter VMAT. The algorithm: (a) measures coordinates of outer boundary points of each lesion to be treated using the Eclipse Scripting Application Programming Interface, (b) determines the rotations of couch, collimator, and gantry using three matrices about the cardinal axes, (c) projects the outer boundary points of the lesion on to Beam Eye View projection plane, (d) optimizes couch and collimator angles by selecting the least total unblocked area for each specific treatment arc, and (e) generates a treatment plan with the optimized angles. The results showed significant reduction in the mean dose and low dose volume to normal brain, while maintaining the similar treatment plan qualities on the thirteen patients treated previously. The algorithm has the flexibility with regard to the beam arrangements and can be integrated in the treatment planning system for clinical application directly

Hyperfine Suppression of 23S1−33PJ2^3{\rm S}_1 - 3^3{\rm P}_J Transitions in 3^3He

Two anomalously weak transitions within the $2 ^3{\rm S}_1~-~3 ^3{\rm P}_J$ manifolds in $^3$He have been identified. Their transition strengths are measured to be 1,000 times weaker than that of the strongest transition in the same group. This dramatic suppression of transition strengths is due to the dominance of the hyperfine interaction over the fine structure interaction. An alternative selection rule based on \textit{IS}-coupling (where the nuclear spin is first coupled to the total electron spin) is proposed. This provides qualitative understanding of the transition strengths. It is shown that the small deviations from the \textit{IS}-coupling model are fully accounted for by an exact diagonalization of the strongly interacting states.Comment: 4 Pages, 2 figures, 1 table. Accepted for publication in PR

Energy Levels for the stable isotopes of atomic helium (4He I and 3He I)

NRC publication: Ye

Nuclear charge radius for 3He

NRC publication: Ye

Accumulated Dose Estimation in Lung Stereotactic Body Radiation Therapy using Deformable Image Registration Algorithm

Purpose: To estimate accumulated dose to targets and OARs for lung cancer patients treated with SBRT. Methods: CBCT and planning CT (pCT) image datasets for lung cancer patients treated with SBRT (12Gyx4), were deformably registered. ITV-PTV margin was uniformly 5 mm. The pCT was deformed and resampled based on the displacement vector field (DVF) from the pCT/CBCT registration, so as to minimize HU issues associated with CBCT. Deformable image registration (DIR) was based on a multi-resolution b-spline algorithm with mutual-information as the similarity metric. Dose-ofthe- day was calculated on the deformed pCT datasets, for each of the four fractions, and dose was accumulated using an energy-mass-mapping algorithm. Results: Mean (standard deviation) of cumulative mean dose minus plan mean dose was -0.6% (1.2%) for the GTV, -0.9% (1.3%) for the PTV, -1.8% (1.2%) for the spinal cord, and -1.6% (4.1%) for total lung-PTV. Mean (standard deviation) of cumulative D95 minus plan D95 was -0.5% (1.3%) for the GTV and -2.9% (2.6%) for the PTV. Mean (standard deviation) of cumulative max. dose minus plan max. dose was -1.1% (1.0%) for the GTV, -1.1% (0.9%) for the PTV, 3.4% (11.7%) for the spinal cord, and 1.1% (2.0%) for total lung-PTV. Mean (standard deviation) of cumulative min. dose minus plan min. dose was 2.1% (3.5%) for the GTV and -14.2% (5.9%) for the PTV. Conclusion: Cumulative doses using deformable dose accumulation were found to be less than planned doses. The planned dose degradation is noted in the DVH shoulders, where min. differences \u3e10% are observed for the PTV, albeit with the GTV min. dose maintained within (2- 4%). OAR max. doses for critical structures such as the spinal cord are shown to increase \u3e10%, which is an important consideration for this serial organ, in the context of SBRT lung treatment

ADST: Forecasting Metro Flow Using Attention-Based Deep Spatial-Temporal Networks with Multi-Task Learning

Passenger flow prediction has drawn increasing attention in the deep learning research field due to its great importance in traffic management and public safety. The major challenge of this essential task lies in multiple spatiotemporal correlations that exhibit complex non-linear correlations. Although both the spatial and temporal perspectives have been considered in modeling, most existing works have ignored complex temporal correlations or underlying spatial similarity. In this paper, we identify the unique spatiotemporal correlation of urban metro flow, and propose an attention-based deep spatiotemporal network with multi-task learning (ADST-Net) at a citywide level to predict the future flow from historical observations. ADST-Net uses three independent channels with the same structure to model the recent, daily-periodic and weekly-periodic complicated spatiotemporal correlations, respectively. Specifically, each channel uses the framework of residual networks, the rectified block and the multi-scale convolutions to mine spatiotemporal correlations. The residual networks can effectively overcome the gradient vanishing problem. The rectified block adopts an attentional mechanism to automatically reweigh measurements at different time intervals, and the multi-scale convolutions are used to extract explicit spatial relationships. ADST-Net also introduces an external embedding mechanism to extract the influence of external factors on flow prediction, such as weather conditions. Furthermore, we enforce multi-task learning to utilize transition passenger flow volume prediction as an auxiliary task during the training process for generalization. Through this model, we can not only capture the steady trend, but also the sudden changes of passenger flow. Extensive experimental results on two real-world traffic flow datasets demonstrate the obvious improvement and superior performance of our proposed algorithm compared with state-of-the-art baselines

Associations Between Normal Lung Density Changes and Radiation-Induced Pneumonitis after Concurrent Chemoradiotherapy for Patients with Locally Advanced Stage Lung Cancer

Purpose: To investigate associations between normal lung CT density changes and radiation-induced pneumonitis (RP) after concurrent chemoradiotherapy for patients with lung cancer. Methods: Forty one patients with the stage III lung cancer were originally planned and treated using the AAA dose algorithm with prescription dose, 60-66 Gy in 2 Gy fractions. Planning was performed using IMRT or 3D-CRT techniques such that dose to normal organs was within tolerance levels. Planning CT images were rigidly registered to the follow-up CT datasets at 3 months after treatment, and dose distributions were mapped accordingly. Hounsfield Unit (HU) changes were assessed in the region encompassing V20, as well as the peri-tumoral region defined by a 3 cm uniform expansion around the ITV, in the ipsilateral lung. Clinical radiation pneumonitis was graded using CTCAE v4.03 by physicians who were blinded to HU changes in lung density (12 with grade 1 RP, 4 with grade 2 RP among 41 patients). Results: Significant correlations (Fig. 1-2) were observed between lung density changes and RP grade in the region encompassing V20 (r = 0.65, p \u3c 0.001), and the peri-tumoral region (r = 0.60, p \u3c 0.001). No significant correlations were found between V20, or MLD (defined by either both lungs or ipsilateral lung minus PTV) and RP, or between lung density change and RP in the region defining ipsilateral lung (Fig. 3-6). Population average lung density changes in dose bins 3-60 Gy for patients with RP grades 0-2 were comparable to the findings of others. Conclusion: Correlations noted between lung density changes in the region encompassing V20 and the peri-tumoral region with radiation pneumonitis grade could potentially be useful predictors of the risk of RP after concurrent chemoradiotherapy. A larger cohort of patients is needed to confirm these findings