Automatic C-arm pose estimation via 2D/3D hybrid registration of a radiographic fiducial

ABSTRACT Motivation: In prostate brachytherapy, real-time dosimetry would be ideal to allow for rapid evaluation of the implant quality intra-operatively. However, such a mechanism requires an imaging system that is both real-time and which provides, via multiple C-arm fluoroscopy images, clear information describing the three-dimensional position of the seeds deposited within the prostate. Thus, accurate tracking of the C-arm poses proves to be of critical importance to the process. Methodology: We compute the pose of the C-arm relative to a stationary radiographic fiducial of known geometry by employing a hybrid registration framework. Firstly, by means of an ellipse segmentation algorithm and a 2D/3D feature based registration, we exploit known FTRAC geometry to recover an initial estimate of the C-arm pose. Using this estimate, we then initialize the intensity-based registration which serves to recover a refined and accurate estimation of the C-arm pose. Results: Ground-truth pose was established for each C-arm image through a published and clinically tested segmentation-based method. Using 169 clinical C-arm images and a ±10° and ±10 mm random perturbation of the ground-truth pose, the average rotation and translation errors were 0.68° (std = 0.06°) and 0.64 mm (std = 0.24 mm). Conclusion: Fully automated C-arm pose estimation using a 2D/3D hybrid registration scheme was found to be clinically robust based on human patient data

Precision mass measurements of magnesium isotopes and implications on the validity of the Isobaric Mass Multiplet Equation

If the mass excess of neutron-deficient nuclei and their neutron-rich mirror partners are both known, it can be shown that deviations of the Isobaric Mass Multiplet Equation (IMME) in the form of a cubic term can be probed. Such a cubic term was probed by using the atomic mass of neutron-rich magnesium isotopes measured using the TITAN Penning trap and the recently measured proton-separation energies of $^{29}$Cl and $^{30}$Ar. The atomic mass of $^{27}$Mg was found to be within 1.6$\sigma$ of the value stated in the Atomic Mass Evaluation. The atomic masses of $^{28,29}$Mg were measured to be both within 1$\sigma$, while being 8 and 34 times more precise, respectively. Using the $^{29}$Mg mass excess and previous measurements of $^{29}$Cl we uncovered a cubic coefficient of $d$ = 28(7) keV, which is the largest known cubic coefficient of the IMME. This departure, however, could also be caused by experimental data with unknown systematic errors. Hence there is a need to confirm the mass excess of $^{28}$S and the one-neutron separation energy of $^{29}$Cl, which have both come from a single measurement. Finally, our results were compared to ab initio calculations from the valence-space in-medium similarity renormalization group, resulting in a good agreement.Comment: 7 pages, 3 figure

Experimental Validation of a Forward Looking Interferometer for Detection of Clear Air Turbulence due to Mountain Waves

The Forward-Looking Interferometer (FLI) is an airborne sensor concept for detection and estimation of potential atmospheric hazards to aircraft. The FLI concept is based on high-resolution Infrared Fourier Transform Spectrometry technologies that have been developed for satellite remote sensing. The FLI is being evaluated for its potential to address multiple hazards, during all phases of flight, including clear air turbulence, volcanic ash, wake vortices, low slant range visibility, dry wind shear, and icing. In addition, the FLI is being evaluated for its potential to detect hazardous runway conditions during landing, such as wet or icy asphalt or concrete. The validation of model-based instrument and hazard simulation results is accomplished by comparing predicted performance against empirical data. In the mountain lee wave data collected in the previous FLI project, the data showed a damped, periodic mountain wave structure. The wave data itself will be of use in forecast and nowcast turbulence products such as the Graphical Turbulence Guidance and Graphical Turbulence Guidance Nowcast products. Determining how turbulence hazard estimates can be derived from FLI measurements will require further investigation

A mechanism for the inhibition of DNA-PK-mediated DNA sensing by a virus

The innate immune system is critical in the response to infection by pathogens and it is activated by pattern recognition receptors (PRRs) binding to pathogen associated molecular patterns (PAMPs). During viral infection, the direct recognition of the viral nucleic acids, such as the genomes of DNA viruses, is very important for activation of innate immunity. Recently, DNA-dependent protein kinase (DNA-PK), a heterotrimeric complex consisting of the Ku70/Ku80 heterodimer and the catalytic subunit DNA-PKcs was identified as a cytoplasmic PRR for DNA that is important for the innate immune response to intracellular DNA and DNA virus infection. Here we show that vaccinia virus (VACV) has evolved to inhibit this function of DNA-PK by expression of a highly conserved protein called C16, which was known to contribute to virulence but by an unknown mechanism. Data presented show that C16 binds directly to the Ku heterodimer and thereby inhibits the innate immune response to DNA in fibroblasts, characterised by the decreased production of cytokines and chemokines. Mechanistically, C16 acts by blocking DNA-PK binding to DNA, which correlates with reduced DNA-PK-dependent DNA sensing. The C-terminal region of C16 is sufficient for binding Ku and this activity is conserved in the variola virus (VARV) orthologue of C16. In contrast, deletion of 5 amino acids in this domain is enough to knockout this function from the attenuated vaccine strain modified vaccinia virus Ankara (MVA). In vivo a VACV mutant lacking C16 induced higher levels of cytokines and chemokines early after infection compared to control viruses, confirming the role of this virulence factor in attenuating the innate immune response. Overall this study describes the inhibition of DNA-PK-dependent DNA sensing by a poxvirus protein, adding to the evidence that DNA-PK is a critical component of innate immunity to DNA viruses

Bodyweight Perceptions among Texas Women: The Effects of Religion, Race/Ethnicity, and Citizenship Status

Despite previous work exploring linkages between religious participation and health, little research has looked at the role of religion in affecting bodyweight perceptions. Using the theoretical model developed by Levin et al. (Sociol Q 36(1):157–173, 1995) on the multidimensionality of religious participation, we develop several hypotheses and test them by using data from the 2004 Survey of Texas Adults. We estimate multinomial logistic regression models to determine the relative risk of women perceiving themselves as overweight. Results indicate that religious attendance lowers risk of women perceiving themselves as very overweight. Citizenship status was an important factor for Latinas, with noncitizens being less likely to see themselves as overweight. We also test interaction effects between religion and race. Religious attendance and prayer have a moderating effect among Latina non-citizens so that among these women, attendance and prayer intensify perceptions of feeling less overweight when compared to their white counterparts. Among African American women, the effect of increased church attendance leads to perceptions of being overweight. Prayer is also a correlate of overweight perceptions but only among African American women. We close with a discussion that highlights key implications from our findings, note study limitations, and several promising avenues for future research

The Beta-decay Paul Trap Mk IV: Design and commissioning

The Beta-decay Paul Trap is an open-geometry, linear trap used to measure the decays of $^8$Li and $^8$B to search for a tensor contribution to the weak interaction. In the latest $^8$Li measurement of Burkey et al. (2022), $\beta$ scattering was the dominant experimental systematic uncertainty. The Beta-decay Paul Trap Mk IV reduces the prevalence of $\beta$ scattering by a factor of 4 through a redesigned electrode geometry and the use of glassy carbon and graphite as electrode materials. The trap has been constructed and successfully commissioned with $^8$Li in a new data campaign that collected 2.6 million triple coincidence events, an increase in statistics by 30% with 4 times less $\beta$ scattering compared to the previous $^8$Li data set.Comment: 17 pages, 7 figure

A repeated measures experiment of school playing environment to increase physical activity and enhance self esteem in UK school children

School playtime provides daily opportunities for children to be active outdoors, but only makes small contributions to physical activity (PA) requirements. Natural environments facilitate unstructured PA and children report a preference for play in nature. Thus, play on the school field might encourage children to be more active during playtime. The primary aim of this study was to examine the impact of the school playing environment on children's PA. Descriptive data and fitness were assessed in 25 children aged 8–9 years from a single primary school. Over two consecutive weeks participants were allocated to either play on the school field or playground during playtime. The order of play in the two areas was randomised and counterbalanced. Moderate to vigorous PA (MVPA) was assessed during playtime on the last two days of each week using accelerometers. There was a significant interaction of environment and sex on MVPA during morning play (F(1,22) = 6.27; P0.05; np2 = 0.060) or all of playtime combined (P>0.05; np2 = 0.140). During morning play boys were significantly more active than girls on the playground (t(23) = 1.32; P0.05; n2 = 0.071). For lunch (F(1,22) = 24,11; P<0.001; np2 = 0.523) and all of playtime combined (F(1,22) = 33.67; P<0.001; np2 = 0.616) there was a significant effect of environment. There was also a significant main effect of sex during lunch (F(1,22) = 11.56; P<0.01; np2 = 0.344) and all of playtime combined (F(1,22) = 12.37; P<0.01; np2 = 0.371). MVPA was higher on the field and boys were more active than girls. Play on the field leads to increases in MVPA, particularly in girls. The promising trend for the effect of the natural environment on MVPA indicates that interventions aimed at increasing MVPA should use the natural environment and that schools should encourage greater use of their natural areas to increase PA

A New Measure of Centrality for Brain Networks

Recent developments in network theory have allowed for the study of the structure and function of the human brain in terms of a network of interconnected components. Among the many nodes that form a network, some play a crucial role and are said to be central within the network structure. Central nodes may be identified via centrality metrics, with degree, betweenness, and eigenvector centrality being three of the most popular measures. Degree identifies the most connected nodes, whereas betweenness centrality identifies those located on the most traveled paths. Eigenvector centrality considers nodes connected to other high degree nodes as highly central. In the work presented here, we propose a new centrality metric called leverage centrality that considers the extent of connectivity of a node relative to the connectivity of its neighbors. The leverage centrality of a node in a network is determined by the extent to which its immediate neighbors rely on that node for information. Although similar in concept, there are essential differences between eigenvector and leverage centrality that are discussed in this manuscript. Degree, betweenness, eigenvector, and leverage centrality were compared using functional brain networks generated from healthy volunteers. Functional cartography was also used to identify neighborhood hubs (nodes with high degree within a network neighborhood). Provincial hubs provide structure within the local community, and connector hubs mediate connections between multiple communities. Leverage proved to yield information that was not captured by degree, betweenness, or eigenvector centrality and was more accurate at identifying neighborhood hubs. We propose that this metric may be able to identify critical nodes that are highly influential within the network