Event Related Electrical Potentials Recorded From The Brain Prior To The Initiation Of Speech

This research will explore the neurologic pathways that occur before the initiation of speech. The basis for this project and the research component will include the electrical potentials along the speech production pathway. The subjects will be given a target consonant-vowel (CV), and their speech production will be recorded simultaneously with their neural activity. We will be attempting to record the electrical signals from the cortex. Subjects will be neurotypical. Benefits of this research will include an increased understanding of normal neuro-electrical properties of the speech production pathway. The clinical benefit will include understanding variations from the norm with application to neuro-motor disorders

Deformation and spallation of shocked Cu bicrystals with Σ3 coherent and symmetric incoherent twin boundaries

We perform molecular dynamics simulations of Cu bicrystals with two important grain boundaries (GBs), Σ3 coherent twin boundaries (CTB), and symmetric incoherent twin boundaries (SITB) under planar shock wave loading. It is revealed that the shock response (deformation and spallation) of the Cu bicrystals strongly depends on the GB characteristics. At the shock compression stage, elastic shock wave can readily trigger GB plasticity at SITB but not at CTB. The SITB can induce considerable wave attenuation such as the elastic precursor decay via activating GB dislocations. For example, our simulations of a Cu multilayer structure with 53 SITBs (∼1.5-μm thick) demonstrate a ∼80% elastic shock decay. At the tension stage, spallation tends to occur at CTB but not at SITB due to the high mobility of SITB. The SITB region transforms into a threefold twin via a sequential partial dislocation slip mechanism, while CTB preserves its integrity before spallation. In addition, deformation twinning is a mechanism for inducing surface step during shock tension stage. The drastically different shock response of CTB and SITB could in principle be exploited for, or benefit, interface engineering and materials design

Left-right loading dependence of shock response of (111)//(112) Cu bicrystals: Deformation and spallation

We investigate with molecular dynamics the dynamic response of Cu bicrystals with a special asymmetric grain boundary (GB), (111)//(112)〈110〉, and its dependence on the loading directions. Shock loading is applied along the GB normal either from the left or right to the GB. Due to the structure asymmetry, the bicrystals demonstrate overall strong left-right loading dependence of its shock response, including compression wave features, compression and tensile plasticity, damage characteristics (e.g., spall strength), effective wave speeds and structure changes, except that spallation remains dominated by the GB damage regardless of the loading directions. The presence or absence of transient microtwinning also depends on the loading directions

Shock compression and spallation of single crystal tantalum

We present molecular dynamics simulations of shock-induced plasticity and spall damage in single crystal Ta described by a recently developed embedded-atom-method (EAM) potential and a volumedependent qEAM potential. We use impact or Hugoniotstat simulations to investigate the Hugoniots, deformation and spallation. Both EAM and qEAM are accurate in predicting, e.g., the Hugoniots and γ - surfaces. Deformation and spall damage are anisotropic for Ta single crystals. Our preliminary results show that twinning is dominant for [100] and [110] shock loading, and dislocation, for [111]. Spallation initiates with void nucleation at defective sites from remnant compressional deformation or tensile plasticity. Spall strength decreases with increasing shock strength, while its rate dependence remains to be explored

Unusual DNA Structure and DNA Damage Recognition: Structure and Dynamic Markers

Nucleic acids play a central role in many biological processes, including information storage, gene expression, serving as messengers or structural components and even catalysis. Their diverse roles have made them targets of interest to diagnose and treat an array of human disorders such as infections, degenerative diseases and cancer. Nature has evolved proteins and ligands that recognize specific nucleic acid sequences or structures and control their function, demonstrating that this can be efficiently accomplished. This has led to the development of wide variety of synthetic molecules that selectively bind to nucleic acids. In turn, this has precipitated numerous studies which showed that nucleic acid structures and their dynamic properties must be understood in order to efficiently target specific sequences or structures

Performance of a deep convolutional neural network for MRI-based vertebral body measurements and insufficiency fracture detection

OBJECTIVES The aim is to validate the performance of a deep convolutional neural network (DCNN) for vertebral body measurements and insufficiency fracture detection on lumbar spine MRI. METHODS This retrospective analysis included 1000 vertebral bodies in 200 patients (age 75.2 ± 9.8 years) who underwent lumbar spine MRI at multiple institutions. 160/200 patients had ≥ one vertebral body insufficiency fracture, 40/200 had no fracture. The performance of the DCNN and that of two fellowship-trained musculoskeletal radiologists in vertebral body measurements (anterior/posterior height, extent of endplate concavity, vertebral angle) and evaluation for insufficiency fractures were compared. Statistics included (a) interobserver reliability metrics using intraclass correlation coefficient (ICC), kappa statistics, and Bland-Altman analysis, and (b) diagnostic performance metrics (sensitivity, specificity, accuracy). A statistically significant difference was accepted if the 95% confidence intervals did not overlap. RESULTS The inter-reader agreement between radiologists and the DCNN was excellent for vertebral body measurements, with ICC values of > 0.94 for anterior and posterior vertebral height and vertebral angle, and good to excellent for superior and inferior endplate concavity with ICC values of 0.79-0.85. The performance of the DCNN in fracture detection yielded a sensitivity of 0.941 (0.903-0.968), specificity of 0.969 (0.954-0.980), and accuracy of 0.962 (0.948-0.973). The diagnostic performance of the DCNN was independent of the radiological institution (accuracy 0.964 vs. 0.960), type of MRI scanner (accuracy 0.957 vs. 0.964), and magnetic field strength (accuracy 0.966 vs. 0.957). CONCLUSIONS A DCNN can achieve high diagnostic performance in vertebral body measurements and insufficiency fracture detection on heterogeneous lumbar spine MRI. KEY POINTS • A DCNN has the potential for high diagnostic performance in measuring vertebral bodies and detecting insufficiency fractures of the lumbar spine