Improved Ductility of Boron Carbide by Microalloying with Boron Suboxide

Boron carbide (B_4C) is the third hardest material in nature, but applications are hindered by its brittle failure under impact. We found that this brittle failure of B_4C arises from amorphous shear band formation due to deconstruction of icosahedral clusters, and on the basis of this model we suggest and validate with quantum mechanics (QM, PBE flavor of density function theory) that a laminated B_4C–B_6O composite structure will eliminate this brittle failure. Using QM to apply shear deformations along various slip systems, we find that the (001)/[100] slip system has the lowest maximum shear strength, indicating it to be the most plausible slip system. We find that this composite structure has a shear strength of 38.33 GPa, essentially the same as that of B_4C (38.97 GPa), indicating the same intrinsic hardness as B4C. However, the critical failure strain for (001)/[100] slip in the composite is 0.465, which is 41% higher than B_4C, indicating a dramatically improvement on ductility. This arises because incorporation of B_6O prevents the failure mechanism of B_4C in which the carbene formed during shear deformation reacts with the C–B–C chains. This suggests a new strategy for designing ductile superhard ceramics

ASTROD, ASTROD I and their gravitational-wave sensitivities

ASTROD (Astrodynamical Space Test of Relativity using Optical Devices) is a mission concept with three spacecraft -- one near L1/L2 point, one with an inner solar orbit and one with an outer solar orbit, ranging coherently with one another using lasers to test relativistic gravity, to measure the solar system and to detect gravitational waves. ASTROD I with one spacecraft ranging optically with ground stations is the first step toward the ASTROD mission. In this paper, we present the ASTROD I payload and accelerometer requirements, discuss the gravitational-wave sensitivities for ASTROD and ASTROD I, and compare them with LISA and radio-wave PDoppler-tracking of spacecraft.Comment: presented to the 5th Edoardo Amaldi Conference (July 6-11, 2003) and submitted to Classical and Quantum Gravit

The co-crystal of TNT/CL-20 leads to decreased sensitivity toward thermal decomposition from first principles based reactive molecular dynamics

To gain an atomistic-level understanding of the experimental observation that the cocrystal TNT/CL-20 leads to decreased sensitivity, we carried out reactive molecular dynamics (RMD) simulations using the ReaxFF reactive force field. We compared the thermal decomposition of the TNT/CL-20 cocrystal with that of pure crystals of TNT and CL-20 and with a simple physical mixture of TNT and CL-20. We find that cocrystal has a lower decomposition rate than CL-20 but higher than TNT, which is consistent with experimental observation. We find that the formation of carbon clusters arising from TNT, a carbon-rich molecule, plays an important role in the thermal decomposition process, explaining the decrease in sensitivity for the cocrystal. At low temperature and in the early stage of chemical reactions under high temperature, the cocrystal releases energy more slowly than the simple mixture of CL-20–TNT. These results confirm the expectation that co-crystallization is an effective way to decrease the sensitivity for energetic materials while retaining high performance

Hybrid Equation/Agent-Based Model of Ischemia-Induced Hyperemia and Pressure Ulcer Formation Predicts Greater Propensity to Ulcerate in Subjects with Spinal Cord Injury

Pressure ulcers are costly and life-threatening complications for people with spinal cord injury (SCI). People with SCI also exhibit differential blood flow properties in non-ulcerated skin. We hypothesized that a computer simulation of the pressure ulcer formation process, informed by data regarding skin blood flow and reactive hyperemia in response to pressure, could provide insights into the pathogenesis and effective treatment of post-SCI pressure ulcers. Agent-Based Models (ABM) are useful in settings such as pressure ulcers, in which spatial realism is important. Ordinary Differential Equation-based (ODE) models are useful when modeling physiological phenomena such as reactive hyperemia. Accordingly, we constructed a hybrid model that combines ODEs related to blood flow along with an ABM of skin injury, inflammation, and ulcer formation. The relationship between pressure and the course of ulcer formation, as well as several other important characteristic patterns of pressure ulcer formation, was demonstrated in this model. The ODE portion of this model was calibrated to data related to blood flow following experimental pressure responses in non-injured human subjects or to data from people with SCI. This model predicted a higher propensity to form ulcers in response to pressure in people with SCI vs. non-injured control subjects, and thus may serve as novel diagnostic platform for post-SCI ulcer formation. © 2013 Solovyev et al

Neutralization of Diverse Human Cytomegalovirus Strains Conferred by Antibodies Targeting Viral gH/gL/pUL128-131 Pentameric Complex

Human cytomegalovirus (HCMV) is the leading cause of congenital viral infection, and developing a prophylactic vaccine is of high priority to public health. We recently reported a replication-defective human cytomegalovirus with restored pentameric complex glycoprotein H (gH)/gL/pUL128-131 for prevention of congenital HCMV infection. While the quantity of vaccine-induced antibody responses can be measured in a viral neutralization assay, assessing the quality of such responses, including the ability of vaccine-induced antibodies to cross-neutralize the field strains of HCMV, remains a challenge. In this study, with a panel of neutralizing antibodies from three healthy human donors with natural HCMV infection or a vaccinated animal, we mapped eight sites on the dominant virus-neutralizing antigen-the pentameric complex of glycoprotein H (gH), gL, and pUL128, pUL130, and pUL131. By evaluating the site-specific antibodies in vaccine immune sera, we demonstrated that vaccination elicited functional antiviral antibodies to multiple neutralizing sites in rhesus macaques, with quality attributes comparable to those of CMV hyperimmune globulin. Furthermore, these immune sera showed antiviral activities against a panel of genetically distinct HCMV clinical isolates. These results highlighted the importance of understanding the quality of vaccine-induced antibody responses, which includes not only the neutralizing potency in key cell types but also the ability to protect against the genetically diverse field strains. IMPORTANCE HCMV is the leading cause of congenital viral infection, and development of a preventive vaccine is a high public health priority. To understand the strain coverage of vaccine-induced immune responses in comparison with natural immunity, we used a panel of broadly neutralizing antibodies to identify the immunogenic sites of a dominant viral antigen-the pentameric complex. We further demonstrated that following vaccination of a replication-defective virus with the restored pentameric complex, rhesus macaques can develop broadly neutralizing antibodies targeting multiple immunogenic sites of the pentameric complex. Such analyses of site-specific antibody responses are imperative to our assessment of the quality of vaccine-induced immunity in clinical studies

Cocaine Use Prediction with Tensor-based Machine Learning on Multimodal MRI Connectome Data

This paper considers the use of machine learning algorithms for predicting cocaine use based on magnetic resonance imaging (MRI) connectomic data. The study utilized functional MRI (fMRI) and diffusion MRI (dMRI) data collected from 275 individuals, which was then parcellated into 246 regions of interest (ROIs) using the Brainnetome atlas. After data preprocessing, the datasets were transformed into tensor form. We developed a tensor-based unsupervised machine learning algorithm to reduce the size of the data tensor from $275$ (individuals) $\times 2$ (fMRI and dMRI) $\times 246$ (ROIs) $\times 246$ (ROIs) to $275$ (individuals) $\times 2$ (fMRI and dMRI) $\times 6$ (clusters) $\times 6$ (clusters). This was achieved by applying the high-order Lloyd algorithm to group the ROI data into 6 clusters. Features were extracted from the reduced tensor and combined with demographic features (age, gender, race, and HIV status). The resulting dataset was used to train a Catboost model using subsampling and nested cross-validation techniques, which achieved a prediction accuracy of 0.857 for identifying cocaine users. The model was also compared with other models, and the feature importance of the model was presented. Overall, this study highlights the potential for using tensor-based machine learning algorithms to predict cocaine use based on MRI connectomic data and presents a promising approach for identifying individuals at risk of substance abuse

Telescope Alignment From Sparsely Sampled Wavefront Measurements Over Pupil Subapertures

Alignment of two-element telescopes is a classic problem. During recent integration and test of the Space Interferometry Mission s (SIM s) Astrometric Beam Combiner (ABC), the innovators were faced with aligning two such telescope subsystems in the presence of a further complication: only two small subapertures in each telescope s pupil were accessible for measuring the wavefront with a Fizeau interferometer. This meant that the familiar aberrations that might be interpreted to infer system misalignments could be viewed only over small sub-regions of the pupil, making them hard to recognize. Further, there was no contiguous surface of the pupil connecting these two subapertures, so relative phase piston information was lost; the underlying full-aperture aberrations therefore had an additional degree of ambiguity. The solution presented here is to recognize that, in the absence of phase piston, the Zygo measurements primarily provide phase tilt in the subaperture windows of interest. Because these windows are small and situated far from the center of the (inaccessible) unobscured full aperture, any aberrations that are higher-order than tilt will be extremely high-order on the full aperture, and so not necessary or helpful to the alignment. Knowledge of the telescope s optical prescription allows straightforward evaluation of sensitivities (subap mode strength per unit full-aperture aberration), and these can be used in a predictive matrix approach to move with assurance to an aligned state. The technique is novel in every operational way compared to the standard approach of alignment based on full-aperture aberrations or searching for best rms wavefront. This approach is closely grounded in the observable quantities most appropriate to the problem. It is also more intuitive than inverting full phase maps (or subaperture Zernike spectra) with a ray-tracing program, which must certainly work in principle, but in practice met with limited success. Even if such classical alignment techniques became practical, the techniques reported here form a reassuringly transparent and intuitive check on the course of the alignment with very little computational effort