Diffusive MASS NMR Studies of Transport in Porous Materials

NMR methods are widely used to probe the structure and fluid dynamics of porous materials including such diverse materials as cheese and chocolate, cosmetics and pharmaceuticals, solvents in resins and soft matter, biological tissue, and for oil exploration. NMR measurements are uniquely suited to these studies since it records the correlation of changing local magnetic fields over a time scale of ms to seconds. The local magnetic fields are established by local variations in the bulk magnetic susceptibility of the sample (and so are directly tied to the sample's local structure). The fluctuation in field that a spin sees is due to molecular transport (including molecular diffusion) through these local fields, and so reports on the length scales of structures and impediments to transport. In the past this information has primarily been employed via empirical relations that relate bulk measurements of relaxation times or diffusion to some microscopic property (pore size, throat size, S/V, and surface relaxivity, etc.). These empirical relationships, while useful, hide the underlying complexity of spin dynamics in confining geometries. We have developed a new set of methods to provide a means of systematically varying the reflective time scale of the measurement and thus the reflective length scale. This new handle permits a detailed, microscopic picture of the structure and dynamics

Resonance Analysis of a Transmission Power System and Possible Consequences of its Undergrounding

Presently there is a great interest in underground cable transmission lines in extra high and high voltage level networks. The undergrounding of the transmission system can lead to the decrease of the resonance frequencies resulting in high overvoltages and possible power system component damages. It is therefore necessary to analyze possible resonance problems in the mixed power transmission system. In this work a frequency dependent model for transmission systems is implemented and the frequency scan results are presented. In order to gain a better understanding of the nature and extent of the resonance, a resonance mode analysis is also executed. The proposed procedure is tested on two examples: a ten-node power system and the Swiss extra high voltage (EHV) power transmission system. Power systems comprising solely overhead lines and different variations of mixed power system are examined

Introduction to and Screening Visit Results of the Multicenter Pediatric Crohn's Disease Growth Study.

BackgroundStatural growth impairment is more common in males with Crohn's disease (CD). We assessed sex differences in height Z score differences and bone age (BA) Z scores and characterized age of menarche in a novel contemporary cohort of pediatric CD patients undergoing screening for enrollment in the multicenter longitudinal Growth Study.MethodsCrohn's disease patients (females with chronological age [CA] 5 years and older and younger than 14 years; males with CA 6 years and older and younger than 16 years) participated in a screening visit for the Growth Study. Height BA-Z scores are height Z scores calculated based on BA. Height CA-Z scores are height Z scores calculated based on CA. The height Z score difference equals height CA-Z score minus height BA-Z score.ResultsOne hundred seventy-one patients (60% male) qualified for this analysis. Mean CA was 12.2 years. Mean height CA-Z score was -0.4, and mean height BA-Z score was 0.4 in females. Mean height CA-Z score was -0.1, and mean height BA-Z score was 0.2 in males. The absolute value of the mean height Z score difference was significantly greater in females (0.8) than males (0.3; P = 0.005). The mean BA-Z score in females (-1.0) was significantly lower than in males (-0.2; P = 0.002). The median CA at menarche was 13.6 (95% CI, 12.6-14.6) years.ConclusionsOur screening visit data suggest that standardized height gain is lower in males with skeletal maturation and delayed puberty is common in females in CD. We are investigating these findings in the ongoing Growth Study

Diversity and origins of bacterial and archaeal viruses on sinking particles reaching the abyssal ocean

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Luo, E., Leu, A. O., Eppley, J. M., Karl, D. M., & DeLong, E. F. Diversity and origins of bacterial and archaeal viruses on sinking particles reaching the abyssal ocean. ISME Journal, 16, : 1627–1635, https://doi.org/10.1038/s41396-022-01202-1.Sinking particles and particle-associated microbes influence global biogeochemistry through particulate matter export from the surface to the deep ocean. Despite ongoing studies of particle-associated microbes, viruses in these habitats remain largely unexplored. Whether, where, and which viruses might contribute to particle production and export remain open to investigation. In this study, we analyzed 857 virus population genomes associated with sinking particles collected over three years in sediment traps moored at 4000 m in the North Pacific Subtropical Gyre. Particle-associated viruses here were linked to cellular hosts through matches to bacterial and archaeal metagenome-assembled genome (MAG)-encoded prophages or CRISPR spacers, identifying novel viruses infecting presumptive deep-sea bacteria such as Colwellia, Moritella, and Shewanella. We also identified lytic viruses whose abundances correlated with particulate carbon flux and/or were exported from the photic to abyssal ocean, including cyanophages. Our data are consistent with some of the predicted outcomes of the viral shuttle hypothesis, and further suggest that viral lysis of both autotrophic and heterotrophic prokaryotes may play a role in carbon export. Our analyses revealed the diversity and origins of prevalent viruses found on deep-sea sinking particles and identified prospective viral groups for future investigation into processes that govern particle export in the open ocean.This project is funded by grants from the Simons Foundation (#329108 to EFD and DMK, #721223 to EFD, and #721252 to DMK) and the Gordon and Betty Moore Foundation (GBMF3777 to EFD and GBMF3794 to DMK). Partial support for EL was provided by the Natural Sciences and Engineering Research Council of Canada (PGSD3-487490-2016)

A Region-Based Deep Learning Algorithm for Detecting and Tracking Objects in Manufacturing Plants

In today\u27s competitive production era, the ability to identify and track important objects in a near real-time manner is greatly desired among manufacturers who are moving towards the streamline production. Manually keeping track of every object in a complex manufacturing plant is infeasible; therefore, an automatic system of that functionality is greatly in need. This study was motivated to develop a Mask Region-based Convolutional Neural Network (Mask RCNN) model to semantically segment objects and important zones in manufacturing plants. The Mask RCNN was trained through transfer learning that used a neural network (NN) pre-trained with the MS-COCO dataset as the starting point and further fine-tuned that NN using a limited number of annotated images. Then the Mask RCNN model was modified to have consistent detection results from videos, which was realized through the use of a two-staged detection threshold and the analysis of the temporal coherence information of detected objects. The function of object tracking was added to the system for identifying the misplacement of objects. The effectiveness and efficiency of the proposed system were demonstrated by analyzing a sample of video footages

Action Recognition in Manufacturing Assembly using Multimodal Sensor Fusion

Production innovations are occurring faster than ever. Manufacturing workers thus need to frequently learn new methods and skills. In fast changing, largely uncertain production systems, manufacturers with the ability to comprehend workers\u27 behavior and assess their operation performance in near real-time will achieve better performance than peers. Action recognition can serve this purpose. Despite that human action recognition has been an active field of study in machine learning, limited work has been done for recognizing worker actions in performing manufacturing tasks that involve complex, intricate operations. Using data captured by one sensor or a single type of sensor to recognize those actions lacks reliability. The limitation can be surpassed by sensor fusion at data, feature, and decision levels. This paper presents a study that developed a multimodal sensor system and used sensor fusion methods to enhance the reliability of action recognition. One step in assembling a Bukito 3D printer, which composed of a sequence of 7 actions, was used to illustrate and assess the proposed method. Two wearable sensors namely Myo-armband captured both Inertial Measurement Unit (IMU) and electromyography (EMG) signals of assembly workers. Microsoft Kinect, a vision based sensor, simultaneously tracked predefined skeleton joints of them. The collected IMU, EMG, and skeleton data were respectively used to train five individual Convolutional Neural Network (CNN) models. Then, various fusion methods were implemented to integrate the prediction results of independent models to yield the final prediction. Reasons for achieving better performance using sensor fusion were identified from this study

Validation of vessel size imaging (VSI) in high-grade human gliomas using magnetic resonance imaging, image-guided biopsies, and quantitative immunohistochemistry.

To evaluate the association between a vessel size index (VSIMRI) derived from dynamic susceptibility contrast (DSC) perfusion imaging using a custom spin-and-gradient echo echoplanar imaging (SAGE-EPI) sequence and quantitative estimates of vessel morphometry based on immunohistochemistry from image-guided biopsy samples. The current study evaluated both relative cerebral blood volume (rCBV) and VSIMRI in eleven patients with high-grade glioma (7 WHO grade III and 4 WHO grade IV). Following 26 MRI-guided glioma biopsies in these 11 patients, we evaluated tissue morphometry, including vessel density and average radius, using an automated procedure based on the endothelial cell marker CD31 to highlight tumor vasculature. Measures of rCBV and VSIMRI were then compared to histological measures. We demonstrate good agreement between VSI measured by MRI and histology; VSIMRI = 13.67 μm and VSIHistology = 12.60 μm, with slight overestimation of VSIMRI in grade III patients compared to histology. rCBV showed a moderate but significant correlation with vessel density (r = 0.42, p = 0.03), and a correlation was also observed between VSIMRI and VSIHistology (r = 0.49, p = 0.01). The current study supports the hypothesis that vessel size measures using MRI accurately reflect vessel caliber within high-grade gliomas, while traditional measures of rCBV are correlated with vessel density and not vessel caliber

2-Bromo-5,7-dimeth­oxy-4-phenyl­quinoline

The title compound, C17H14BrNO2, was synthesized by the treatment of 5,7-dimeth­oxy-4-phenyl­quinolin-2-one with phosphoryl bromide in a Vilsmeier-type reaction. There are two independent mol­ecules (A and B) in the asymmetric unit which differ by 11.2° in the orientation of the 4-phenyl ring with respect to the planar quinoline ring system [dihedral angles = 55.15 (8) and 66.34 (8)° in mol­ecules A and B, respectively]. In the crystal structure, the independent mol­ecules are linked via C—H⋯N and C—H⋯O hydrogen bonds, forming centrosymmetric tetra­meric units which are cross-linked through C—H⋯π and C—Br⋯π inter­actions with Br⋯centroid distances of 3.4289 (8) and 3.5967 (8) Å