The Fundamental Aspects of TEMOM Model for Particle Coagulation due to Brownian Motion—Part II: In the Continuum Regime

The fundamental aspects of the Taylor-series expansion method of moment (TEMOM) model proposed to model the aerosol population balance equation due to Brownian coagulation in the continuum regime is shown in this study, such as the choice of the expansion point u, the relationship between asymptotic behavior and analytical solution, and the error of the high-order moment equations. All these analyses will contribute to the buildup of the theoretical system of the TEMOM model

Keeping speed and distance for aligned motion

The cohesive collective motion (flocking, swarming) of autonomous agents is ubiquitously observed and exploited in both natural and man-made settings, thus, minimal models for its description are essential. In a model with continuous space and time we find that if two particles arrive symmetrically in a plane at a large angle, then (i) radial repulsion and (ii) linear self-propelling toward a fixed preferred speed are sufficient for them to depart at a smaller angle. For this local gain of momentum explicit velocity alignment is not necessary, nor are adhesion/attraction, inelasticity or anisotropy of the particles, or nonlinear drag. With many particles obeying these microscopic rules of motion we find that their spatial confinement to a square with periodic boundaries (which is an indirect form of attraction) leads to stable macroscopic ordering. As a function of the strength of added noise we see – at finite system sizes – a critical slowing down close to the order-disorder boundary and a discontinuous transition. After varying the density of particles at constant system size and varying the size of the system with constant particle density we predict that in the infinite system size (or density) limit the hysteresis loop disappears and the transition becomes continuous. We note that animals, humans, drones, etc. tend to move asynchronously and are often more responsive to motion than positions. Thus, for them velocity-based continuous models can provide higher precision than coordinate-based models. An additional characteristic and realistic feature of the model is that convergence to the ordered state is fastest at a finite density, which is in contrast to models applying (discontinuous) explicit velocity alignments and discretized time. In summary, we find that the investigated model can provide a minimal description of flocking

Fecal microbial and metabolic characteristics of swine from birth to market

IntroductionRecently, the research on pig intestinal microbiota has become a hot topic in the field of animal husbandry. There are few articles describing the dynamic changes of porcine fecal microbiota and metabolites at different time points from birth to market.MethodsIn the present study, 381 fecal samples were collected from 633 commercial pigs at 7 time points, including the 1st day, the 10th day, the 25th day, the 45th day, the 70th day, the 120th day, and the 180th day after the birth of swine, were used for microbiome analysis by Illumina MiSeq sequencing methods while 131 fecal samples from 3 time points, the 10th day, the 25th day, and 70th day after birth, were used for metabolome analysis by LC–MS methods.ResultsFor the microbiome analysis, the fecal microbial richness increased over time from day 1 to 180 and the β-diversity of fecal microbiota was separated significantly at different time points. Firmicutes were the main phyla from day 10 to 180, followed by Bacteroides. The abundance of Lactobacillus increased significantly on day 120 compared with the previous 4 time points. From day 120 to day 180, the main porcine fecal microbes were Lactobacillus, Clostridium_sensu_stricto_1, Terrisporobacter and Streptococcus. Clostridium_sensu_stricto_1 and Terrisporobacter increased over time, while Lactobacillus, Escherichia-Shigella, Lachnoclostridium decreased with the time according to the heatmap, which showed the increase or decrease in microbial abundance over time. For the metabolome analysis, the PLS-DA plot could clearly distinguish porcine fecal metabolites on day 10, 25, and 70. The most different metabolic pathways of the 3 time points were Tryptophan metabolism, Sphingolipid signaling pathway, Protein digestion and absorption. Some metabolites increased significantly over time, such as Sucrose, L-Arginine, Indole, 2,3-Pyridinedicarboxylic acid and so on, while D-Maltose, L-2-Aminoadipic acid, 2,6-diaminohexanoic acid, L-Proline were opposite. The correlation between fecal metabolites and microbiota revealed that the microbes with an increasing trend were positively correlated with the metabolites affecting the tryptophan metabolic pathway from the overall trend, while the microbes with a decreasing trend were opposite. In addition, the microbes with an increasing trend were negatively correlated with the metabolites affecting the lysine pathway.DiscussionIn conclusion, this study elucidated the dynamic changes of porcine fecal microbiota and metabolites at different stages from birth to market, which may provide a reference for a comprehensive understanding of the intestinal health status of pigs at different growth stages

Research progress and development tendency of polymer drilling fluid technology for unconventional gas drilling

Unconventional gas includes tight sandstone gas, shale gas, coalbed methane, and natural gas hydrate. With huge reserves, unconventional gas has become the most important natural gas resource successor after the end of the “Easy Oil era.” The drilling fluid is an indispensable wellbore working fluid for unconventional gas drilling with multiple functions. The polymer drilling fluid (PDF) is the most common, longest developed, and most diverse drilling fluid type. With advantages of easily controlled rheology, convenient on-site performance maintenance, and specifically low cost and weak environment pollution, the PDF is gradually replacing the oil-based drilling fluid as the first choice for unconventional gas drilling. The invention of the non-disperse low-solid-content PDF in the 1960s shows that PDF technology has entered the stage of scientific development, and until now, its development has generally experienced five stages: beginning, developing, improving, re-developing, and re-improving. Dozens of polymer additives and PDF systems have been invented and applied, which have solved severe drilling problems, greatly improved drilling efficiency, and promoted exploration and development in difficult oil and gas resources. This paper first reviews the research progress of PDF technology according to the timeline by introducing the composition, feature, advantages, and disadvantages of some representative polymer additives and PDF systems, emphatically the function and mechanism of stabilizing wellbores, lubricating drilling tools, and protecting reservoirs of the biomimetic wellbore-strengthening PDF and amphiphobic high-efficiency PDF in unconventional gas drilling. Then, combining future global demands, especially China’s strategic needs of oil and gas exploration and development, the development tendency of PDF technology is critically illustrated by introducing several potential research directions including intelligent PDF, ecological PDF, and PDF for natural gas hydrate and deep layer gas resources

Construction and validation of a cuproptosis-related prognostic model for glioblastoma

BackgroundCuproptosis, a newly reported type of programmed cell death, takes part in the regulation of tumor progression, treatment response, and prognosis. But the specific effect of cuproptosis-related genes (CRGs) on glioblastoma (GBM) is still unclear.MethodsThe transcriptome data and corresponding clinical data of GBM samples were downloaded from the TCGA and GEO databases. R software and R packages were used to perform statistical analysis, consensus cluster analysis, survival analysis, Cox regression analysis, Lasso regression analysis, and tumor microenvironment analysis. The mRNA and protein expression levels of model-related genes were detected by RT-qPCR and Western blot assays, respectively.ResultsThe expression profile of CRGs in 209 GBM samples from two separate datasets was obtained. Two cuproptosis subtypes, CRGcluster A and CRGcluster B, were identified by consensus cluster analysis. There were apparent differences in prognosis, tumor microenvironment, and immune checkpoint expression levels between the two subtypes, and there were 79 prognostic differentially expressed genes (DEGs). According to the prognostic DEGs, two gene subtypes, geneCluster A and geneCluster B, were identified, and a prognostic risk score model was constructed and validated. This model consists of five prognostic DEGs, including PDIA4, DUSP6, PTPRN, PILRB, and CBLN1. Ultimately, to improve the applicability of the model, a nomogram was established. Patients with GBM in the low-risk cluster have a higher mutation burden and predict a longer OS than in the high-risk group. Moreover, the risk score was related to drug sensitivity and negatively correlated with the CSC index.ConclusionWe successfully constructed a cuproptosis-related prognostic model, which can independently predict the prognosis of GBM patients. These results further complement the understanding of cuproptosis and provide new theoretical support for developing a more effective treatment strategy

Keeping speed and distance for aligned motion

The cohesive collective motion (flocking, swarming) of autonomous agents is ubiquitously observed and exploited in both natural and man-made settings, thus, minimal models for its description are essential. In a model with continuous space and time we find that if two particles arrive symmetrically in a plane at a large angle, then (i) radial repulsion and (ii) linear self-propelling toward a fixed preferred speed are sufficient for them to depart at a smaller angle. For this local gain of momentum explicit velocity alignment is not necessary, nor are adhesion/attraction, inelasticity or anisotropy of the particles, or nonlinear drag. With many particles obeying these microscopic rules of motion we find that their spatial confinement to a square with periodic boundaries (which is an indirect form of attraction) leads to stable macroscopic ordering. As a function of the strength of added noise we see – at finite system sizes – a critical slowing down close to the order-disorder boundary and a discontinuous transition. After varying the density of particles at constant system size and varying the size of the system with constant particle density we predict that in the infinite system size (or density) limit the hysteresis loop disappears and the transition becomes continuous. We note that animals, humans, drones, etc. tend to move asynchronously and are often more responsive to motion than positions. Thus, for them velocity-based continuous models can provide higher precision than coordinate-based models. An additional characteristic and realistic feature of the model is that convergence to the ordered state is fastest at a finite density, which is in contrast to models applying (discontinuous) explicit velocity alignments and discretized time. In summary, we find that the investigated model can provide a minimal description of flocking

Detection of a superconducting phase in a two-atom layer of hexagonal Ga film grown on semiconducting GaN(0001)

The recent observation of superconducting state at atomic scale has motivated the pursuit of exotic condensed phases in two-dimensional (2D) systems. Here we report on a superconducting phase in two-monolayer crystalline Ga films epitaxially grown on wide band-gap semiconductor GaN(0001). This phase exhibits a hexagonal structure and only 0.552 nm in thickness, nevertheless, brings about a superconducting transition temperature Tc as high as 5.4 K, confirmed by in situ scanning tunneling spectroscopy, and ex situ electrical magneto-transport and magnetization measurements. The anisotropy of critical magnetic field and Berezinski-Kosterlitz-Thouless-like transition are observed, typical for the 2D superconductivity. Our results demonstrate a novel platform for exploring atomic-scale 2D superconductor, with great potential for understanding of the interface superconductivity