Role of Internal Motions and Molecular Geometry on the NMR Relaxation of Hydrocarbons

The role of internal motions and molecular geometry on $^1$H NMR relaxation times $T_{1,2}$ in hydrocarbons is investigated using MD (molecular dynamics) simulations of the autocorrelation functions for in{\it tra}molecular $G_R(t)$ and in{\it ter}molecular $G_T(t)$ $^1$H-$^1$H dipole-dipole interactions arising from rotational ($R$) and translational ($T$) diffusion, respectively. We show that molecules with increased molecular symmetry such as neopentane, benzene, and isooctane show better agreement with traditional hard-sphere models than their corresponding straight-chain $n$-alkane, and furthermore that spherically-symmetric neopentane agrees well with the Stokes-Einstein theory. The influence of internal motions on the dynamics and $T_{1,2}$ relaxation of $n$-alkanes are investigated by simulating rigid $n$-alkanes and comparing with flexible (i.e. non-rigid) $n$-alkanes. Internal motions cause the rotational and translational correlation-times $\tau_{R,T}$ to get significantly shorter and the relaxation times $T_{1,2}$ to get significantly longer, especially for longer-chain $n$-alkanes. Site-by-site simulations of $^1$H's along the chains indicate significant variations in $\tau_{R,T}$ and $T_{1,2}$ across the chain, especially for longer-chain $n$-alkanes. The extent of the stretched (i.e. multi-exponential) decay in the autocorrelation functions $G_{R,T}(t)$ are quantified using inverse Laplace transforms, for both rigid and flexible molecules, and on a site-by-site bases. Comparison of $T_{1,2}$ measurements with the site-by-site simulations indicate that cross-relaxation (partially) averages-out the variations in $\tau_{R,T}$ and $T_{1,2}$ across the chain of long-chain $n$-alkanes. This work also has implications on the role of nano-pore confinement on the NMR relaxation of fluids in the organic-matter pores of kerogen and bitumen

A Novel Noise Injection-based Training Scheme for Better Model Robustness

Noise injection-based method has been shown to be able to improve the robustness of artificial neural networks in previous work. In this work, we propose a novel noise injection-based training scheme for better model robustness. Specifically, we first develop a likelihood ratio method to estimate the gradient with respect to both synaptic weights and noise levels for stochastic gradient descent training. Then, we design an approximation for the vanilla noise injection-based training method to reduce memory and improve computational efficiency. Next, we apply our proposed scheme to spiking neural networks and evaluate the performance of classification accuracy and robustness on MNIST and Fashion-MNIST datasets. Experiment results show that our proposed method achieves a much better performance on adversarial robustness and slightly better performance on original accuracy, compared with the conventional gradient-based training method

Changes of predominant species/biovars and sequence types of Brucellaisolates, Inner Mongolia, China

BACKGROUND: Human brucellosis incidence in China was divided into 3 stages, high incidence (1950-1960s), decline (1970-1980s) and re-emergence (1990-2000s). Human brucellosis has been reported in all the 32 provinces, of which Inner Mongolia has the highest prevalence, accounting for over 40% of the cases in China. To investigate the etiology alteration of human brucellosis in Inner Mongolia, the species, biovars and genotypes of 60 Brucella isolates from this province were analyzed. METHODS: Species and biovars of the Brucella strains isolated from outbreaks were determined based on classical identification procedures. Strains were genotyped by multi locus sequence typing (MLST). Sequences of 9 housekeeping genes were obtained and sequence types were defined. The distribution of species, biovars and sequence types (STs) among the three incidence stages were analyzed and compared. RESULTS: The three stages of high incidence, decline and re-emergence were predominated by B. melitensis biovar 2 and 3, B. abortus biovar 3, and B. melitensis biovar 1, respectively, implying changes in the predominant biovars. Genotyping by MLST revealed a total of 14 STs. Nine STs (from ST28 to ST36), accounting for 64.3% of all the STs, were newly defined and different from those observed in other countries. Different STs were distributed among the three stages. ST8 was the most common ST in 1950-1960s and 1990-2000s, while ST2 was the most common in 1970-1980s. CONCLUSIONS: The prevalence of biovars and sequence types of Brucella strains from Inner Mongolia has changed over time in the three stages. Compared with those from other countries, new sequence types of Brucella strains exist in China

Seasonal Variability of the Labrador Current and Shelf Circulation off Newfoundland

Three-dimensional finite element models were established for the Newfoundland and Labrador Shelf to investigate climatological monthly mean wind- and density-driven circulation. The model was forced using wind stresses from the National Center for Environmental Prediction-National Center for Atmospheric Research reanalysis data prescribed at the sea surface, large-scale remote forcing determined from a North Atlantic model, monthly mean temperature and salinity climatology, and M2 tide on the open boundary. The model results were examined against various in situ observations (moored current meter, tide gauge, and vessel-mounted acoustic Doppler current profiler data) and satellite drift measurements and discussed together with literature information. The seasonal mean circulation solutions were investigated in terms of relative importance of wind to density forcing for the Labrador Current. The model results indicate significant seasonal and spatial variations, consistent generally with previous study results and in approximate agreement with observations for the major currents. The region is dominated by the equatorward flowing Labrador Current along the shelf edge and along the Labrador and Newfoundland coasts. The Labrador Current is strong in the fall/winter and weak in the spring/summer. The mean transport of the shelf edge Labrador Current is 7.5 Sv at the Seat Island transect and 5.5 Sv through the Flemish Pass. The seasonal ranges are 4.5 and 5.2 Sv at the two sections, respectively. Density- and wind-driven components are both important in the inshore Labrador Current. The density-driven component dominates the mean component of the shelf edge Labrador Current while the large-scale wind-forcing contributes significantly to its seasonal variability

Immunization of Mice with Recombinant Protein CobB or AsnC Confers Protection against Brucella abortus Infection

Due to drawbacks of live attenuated vaccines, much more attention has been focused on screening of Brucella protective antigens as subunit vaccine candidates. Brucella is a facultative intracellular bacterium and cell mediated immunity plays essential roles for protection against Brucella infection. Identification of Brucella antigens that present T-cell epitopes to the host could enable development of such vaccines. In this study, 45 proven or putative pathogenesis-associated factors of Brucella were selected according to currently available data. After expressed and purified, 35 proteins were qualified for analysis of their abilities to stimulate T-cell responses in vitro. Then, an in vitro gamma interferon (IFN-γ) assay was used to identify potential T-cell antigens from B. abortus. In total, 7 individual proteins that stimulated strong IFN-γ responses in splenocytes from mice immunized with B. abortus live vaccine S19 were identified. The protective efficiencies of these 7 recombinant proteins were further evaluated. Mice given BAB1_1316 (CobB) or BAB1_1688 (AsnC) plus adjuvant could provide protection against virulent B. abortus infection, similarly with the known protective antigen Cu-Zn SOD and the license vaccine S19. In addition, CobB and AsnC could induce strong antibodies responses in BALB/c mice. Altogether, the present study showed that CobB or AsnC protein could be useful antigen candidates for the development of subunit vaccines against brucellosis with adequate immunogenicity and protection efficacy

Magnetic-field-induced electronic instability of Weyl-like fermions in compressed black phosphorus

Revealing the role of Coulomb interaction in topological semimetals with Dirac/Weyl-like band dispersion shapes a new frontier in condensed matter physics. Topological node-line semimetals (TNLSMs), anticipated as a fertile ground for exploring electronic correlation effects due to the anisotropy associated with their node-line structure, have recently attracted considerable attention. In this study, we report an experimental observation for correlation effects in TNLSMs realized by black phosphorus (BP) under hydrostatic pressure. By performing a combination of nuclear magnetic resonance measurements and band calculations on compressed BP, a magnetic-field-induced electronic instability of Weyl-like fermions is identified under an external magnetic field parallel to the so-called nodal ring in the reciprocal space. Anomalous spin fluctuations serving as the fingerprint of electronic instability are observed at low temperatures, and they are observed to maximize at approximately 1.0 GPa. This study presents compressed BP as a realistic material platform for exploring the rich physics in strongly coupled Weyl-like fermions.Comment: 10 pages, 4 figure

Construction of a Medical Micro-Object Cascade Network for Automated Segmentation of Cerebral Microbleeds in Susceptibility Weighted Imaging

Aim: The detection and segmentation of cerebral microbleeds (CMBs) images are the focus of clinical diagnosis and treatment. However, segmentation is difficult in clinical practice, and missed diagnosis may occur. Few related studies on the automated segmentation of CMB images have been performed, and we provide the most effective CMB segmentation to date using an automated segmentation system.Materials and Methods: From a research perspective, we focused on the automated segmentation of CMB targets in susceptibility weighted imaging (SWI) for the first time and then constructed a deep learning network focused on the segmentation of micro-objects. We collected and marked clinical datasets and proposed a new medical micro-object cascade network (MMOC-Net). In the first stage, U-Net was utilized to select the region of interest (ROI). In the second stage, we utilized a full-resolution network (FRN) to complete fine segmentation. We also incorporated residual atrous spatial pyramid pooling (R-ASPP) and a new joint loss function.Results: The most suitable segmentation result was achieved with a ROI size of 32 × 32. To verify the validity of each part of the method, ablation studies were performed, which showed that the best segmentation results were obtained when FRN, R-ASPP and the combined loss function were used simultaneously. Under these conditions, the obtained Dice similarity coefficient (DSC) value was 87.93% and the F2-score (F2) value was 90.69%. We also innovatively developed a visual clinical diagnosis system that can provide effective support for clinical diagnosis and treatment decisions.Conclusions: We created the MMOC-Net method to perform the automated segmentation task of CMBs in an SWI and obtained better segmentation performance; hence, this pioneering method has research significance