Effect of surface carbonates on the cyclability of LiNbO3_{3}-coated NCM622 in all-solid-state batteries with lithium thiophosphate electrolytes

While still premature as an energy storage technology, bulk solid-state batteries are attracting much attention in the academic and industrial communities lately. In particular, layered lithium metal oxides and lithium thiophosphates hold promise as cathode materials and superionic solid electrolytes, respectively. However, interfacial side reactions between the individual components during battery operation usually result in accelerated performance degradation. Hence, effective surface coatings are required to mitigate or ideally prevent detrimental reactions from occurring and having an impact on the cyclability. In the present work, we examine how surface carbonates incorporated into the sol–gel-derived LiNbO$_{3}$ protective coating on NCM622 [Li$_{1+x}$(Ni$_{0.6}$Co$_{0.2}$Mn$_{0.2}$)$_{1-x}$O2] cathode material affect the efficiency and rate capability of pellet-stack solid-state battery cells with β-Li$_{3}$PS$_{4}$ or argyrodite Li$_{6}$PS$_{5}$Cl solid electrolyte and a Li$_{4}$Ti$_{5}$O$_{12}$ anode. Our research data indicate that a hybrid coating may in fact be beneficial to the kinetics and the cycling performance strongly depends on the solid electrolyte used

Short-term effects of dietary selenium on lactating sows to improve litter performance, milk composition and tissue selenium retention in piglets

Objective This study was conducted to evaluate the short-term effects of dietary selenium supplementation on lactating sows on the physiological response, litter performance, milk composition, and tissue selenium retention in piglets when selenium was provided by different sources and at different levels in a lactation diet. Methods A total of 48 multiparous sows (Yorkshire×Landrace) with average body weight, backfat thickness, and parity were assigned to one of the four treatments with 12 sows per treatment using a 2×2 factorial arrangement in a completely randomized design. Inorganic or organic Se sources were added to the diet at 0.30 ppm and 0.50 ppm Se. Treatments were as follows: i) IS30, basal diet + inorganic Se 0.30 ppm; ii) IS50, basal diet + inorganic Se 0.50 ppm; iii) OS30, basal diet + organic Se 0.30 ppm; and iv) OS50: basal diet + organic Se 0.50 ppm. Results At Day 21 of lactation, a high tendency of litter weight (p = 0.08) and litter weight gain (p = 0.09) were observed when sows were fed an organic Se source. The milk Se concentration in the organic Se treatment was higher than that in the inorganic Se treatment at Day 21 of lactation (p<0.05). The serum Se concentrations of sows and piglets at Day 21 of lactation were significantly higher when lactating sows were fed organic Se instead of inorganic Se (p<0.01). During the suckling period, the kidney and muscle Se concentrations of piglets at Day 21 of lactation were significantly higher when the sow dietary Se source was organic (p<0.05). Liver Se concentrations were affected by Se source and level (p<0.05). This also resulted in an interaction response at 21 days of lactation (p<0.05). Conclusion The supplementation of dietary organic Se in a lactating diet could improve sow feed consumption, piglet performance, milk Se level, and the Se status of sows and piglets

Predicting Chemical Ocular Toxicity Using a Combinatorial QSAR Approach

Regulatory agencies require testing of chemicals and products to protect workers and consumers from potential eye injury hazards. Animal screening, such as the rabbit Draize test, for potential environmental toxicants is time-consuming and costly. Therefore, virtual screening using computational models to tag potential ocular toxicants is attractive to toxicologists and policy makers. We have developed quantitative structure-activity relationship (QSAR) models for a set of small molecules with animal ocular toxicity data compiled by the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods. The data set was initially curated by removing duplicates, mixtures, and inorganics. The remaining 75 compounds were used to develop QSAR models. We applied both k nearest neighbor and random forest statistical approaches in combination with Dragon and Molecular Operating Environment descriptors. Developed models were validated on an external set of 34 compounds collected from additional sources. The external correct classification rates (CCR) of all individual models were between 72 and 87%. Furthermore, the consensus model, based on the prediction average of individual models, showed additional improvement (CCR = 0.93). The validated models could be used to screen external chemical libraries and prioritize chemicals for in vivo screening as potential ocular toxicants

HairBrush for Immersive Data-Driven Hair Modeling

International audienceWhile hair is an essential component of virtual humans, it is also one of the most challenging digital assets to create. Existing automatic techniques lack the generality and flexibility to create rich hair variations, while manual authoring interfaces often require considerable artistic skills and efforts, especially for intricate 3D hair structures that can be difficult to navigate. We propose an interactive hair modeling system that can help create complex hairstyles in minutes or hours that would otherwise take much longer with existing tools. Modelers, including novice users, can focus on the overall hairstyles and local hair deformations, as our system intelligently suggests the desired hair parts. Our method combines the flexibility of manual authoring and the convenience of data-driven automation. Since hair contains intricate 3D structures such as buns, knots, and strands, they are inherently challenging to create using traditional 2D interfaces. Our system provides a new 3D hair author-ing interface for immersive interaction in virtual reality (VR). Users can draw high-level guide strips, from which our system predicts the most plausible hairstyles via a deep neural network trained from a professionally curated dataset. Each hairstyle in our dataset is composed of multiple variations, serving as blend-shapes to fit the user drawings via global blending and local deformation. The fitted hair models are visualized as interactive suggestions that the user can select, modify, or ignore. We conducted a user study to confirm that our system can significantly reduce manual labor while improve the output quality for modeling a variety of head and facial hairstyles that are challenging to create via existing techniques

Trembling Shear Behavior of a Modified-Chitosan Dispersed Suspension under an Electric Field and its Model Study

An electro-rheological (ER) fluid showing trembling shear behavior was fabricated with chitosan particles that had benzene, amine and azo-pendent side groups. This modified-chitosan dispersed suspension showed four regions in a plot of shear stress against shear rate at high electric field. We analyzed this specific behavior with our suggested model. The model was developed with the spring-damper model. Our suggested model equation treated the wide range of shear rate and specific behaviors of shear stress in ER fluids. In this study, we successfully obtained various ER fluids showing different behaviors just by changing the side functional groups of the particles in the ER fluids. All of the curves of the shear stress plotted against shear rate were fitted well by our spring-damper model.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58575/1/890_ftp.pd

Preoperative CT-guided ICG injection locating SPNs

Background: Localization of small pulmonary nodules (SPNs) is challenging in minimally invasive pulmonary resection, and it is unknown whether computer tomography (CT) guided by indocyanine green (ICG) can provide accurate localization with minimal complications. Methods: We performed a retrospective study of patients who underwent thoracoscopic resection of pulmonary nodules after CT-guided preoperative localization with ICG from May 2019 to May 2020. Demographics, procedural data, postoperative complications, and pathologic information, were collected, and an analysis of the accuracy and complications after surgery was conducted. Results: In 471 patients, there was a total of 512 peripheral pulmonary nodules that were ≤2 cm in size. The average time for CT-guided percutaneous ICG injection for localization was 18 minutes, and 98.4% (504/512) of the nodules were successfully localized. The average size of the nodules was 9.1 mm, and the average depth from the pleural surface was 8.9 mm. Overall, 5.9% (28/471) of the patients had asymptomatic pneumothorax after localization, but none needed a tube thoracostomy. All the nodules were resected using video-assisted thoracoscopy technique. Conclusions: Preoperative CT-guided transthoracic ICG injection is safe and feasible for localization of small lung nodules for minimally invasive pulmonary resection. This technique should be considered for preoperative CT-guided localization of small lung nodules

Distinct signalling pathways regulate sprouting angiogenesis from the dorsal aorta and the axial vein

Angiogenesis, the formation of new blood vessels from preexisting vessels, is critical to most physiological processes and many pathological conditions. During zebrafish development, angiogenesis expands the axial vessels into a complex vascular network that is necessary for efficient oxygen delivery. Although the dorsal aorta (DA) and the axial vein (AV) are spatially juxtaposed, the initial angiogenic sprouts from these vessels extend in opposite directions, suggesting that distinct cues may regulate angiogenesis of the axial vessels. In this report, we found that angiogenic sprouts from the DA are dependent on Vegf-A signaling, and do not respond to Bmp signals. In contrast, sprouts from the AV are regulated by Bmp signaling independent of Vegf-A signals, suggesting that Bmp is a vein-specific angiogenic cue during early vascular development. Our results support a paradigm, whereby different signals regulate distinct programs of sprouting angiogenesis from the AV and DA, and suggest that signaling heterogeneity contributes to the complexity of vascular networks

Network analysis of large-scale ImmGen and Tabula Muris datasets highlights metabolic diversity of tissue mononuclear phagocytes

The diversity of mononuclear phagocyte (MNP) subpopulations across tissues is one of the key physiological characteristics of the immune system. Here, we focus on understanding the metabolic variability of MNPs through metabolic network analysis applied to three large-scale transcriptional datasets: we introduce (1) an ImmGen MNP open-source dataset of 337 samples across 26 tissues; (2) a myeloid subset of ImmGen Phase I dataset (202 MNP samples); and (3) a myeloid mouse single-cell RNA sequencing (scRNA-seq) dataset (51,364 cells) assembled based on Tabula Muris Senis. To analyze such large-scale datasets, we develop a network-based computational approach, genes and metabolites (GAM) clustering, for unbiased identification of the key metabolic subnetworks based on transcriptional profiles. We define 9 metabolic subnetworks that encapsulate the metabolic differences within MNP from 38 different tissues. Obtained modules reveal that cholesterol synthesis appears particularly active within the migratory dendritic cells, while glutathione synthesis is essential for cysteinyl leukotriene production by peritoneal and lung macrophages