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The floc size distribution of fine cohesive sediments in estuaries varies spatiotemporally within assorted physical, chemical, and biological factors. However, the distribution of different floc fractions that are affected by shear stress and salinity stratification has not yet been thoroughly investigated. This study intends to clarify the floc size distribution within the influences of turbulent shear rate and salinity stratification, and the implications for the flocculation process during the dry season in the Modaomen Estuary of the Pearl River. The decomposition of multimodal floc size distributions (FSDs) indicates that the floc fractions were composed of macroflocs (Macro), microflocs (Micro), Flocculi, and primary particles (Pp). Macro generally existed among the upper and middle layers, but smaller flocs, i.e., Micro, Flocculi, and Pp, were mostly concentrated in the bottom layer. The results agreed that the flocculation and deflocculation processes were dominant in the upper and bottom layers, respectively. In response to strong turbulent shear rates, FSDs in the bottom layer skewed toward small sizes and had a dual-peak tendency with frequent floc exchanges between Pp and Micro, then being Pp-dominant but converting to Micro when turbulent shear rates decreased. With impeded vertical mixing by salinity stratification, the FSDs in the upper or middle layers skewed toward a larger particle size with single peaks and lack of exchange among different floc fractions, leading to Macro dominance with a larger volume concentration and median size. In addition, turbulence mixing dramatically interfered with the good mixing of floc fractions amidst the vertical water column, with a low-salinity condition greatly affecting the formation of Macro in the bottom layer within proper turbulent shear rates. This study explores the effects of shear stress and salinity stratification on the flocculation process in the Modaomen Estuary, which contributes to a better understanding of sediment movement in a complex estuarine environment.

ObjectiveTo evaluate the clinical correlation of epithelial-mesenchymal transition (EMT) with PRL-3 and MMP9 expression in the circulating tumor cells (CTCs) of patients with colorectal cancer (CRC).Materials and MethodsBetween January 2016 and December 2018, the EMT phenotype-based subsets of CTCs and the expression levels of PRL-3 and MMP9 in CTCs were identified, and their clinical values in 172 patients were evaluated. The CTCs were isolated, classified, and counted using the CanPatrol™ CTC filtration system. The CTC subsets (epithelial cells, mesenchymal cells and biphenotypic cells), as well as PRL-3 and MMP9 expression, were detected by RNA in situ hybridization.ResultsCTCs were detected in 93.0% (160/172) of the included patients with CRC. Positive PRL-3 and MMP9 expression in CTC and M-CTC was found in 75.0% (102/136) and 80.8% (97/120) of the patients, respectively. The proportion of patients with positive PRL-3 and MMP9 expression in M-CTC was significantly associated with distant metastasis (p

Random forwarding networks play a significant role in solving security and load balancing problems. As a random quantity easily obtained by both sender and receiver, the end-to-end delay of random forwarding networks can be utilized as an effective random source for cryptography-related applications. In this paper, we propose a mathematical model of Random forwarding networks and give the calculation method of end-to-end delay distribution. In exploring the upper limit of the randomness of end-to-end delay, we find that the end-to-end delay collision of different forwarding routes is the main reason for the decrease of end-to-end delay randomness. Some of these collisions can be optimized by better network deployment, while others are caused by some interesting network topology, which is unavoidable. For further analysis, we propose an algorithm to calculate the inevitable collision in random forwarding networks skillfully by using Symbol Matrix, and we give the optimal node forwarding strategy with the maximum randomness of the end-to-end delay for a given number of middle forwarding nodes and forwarding times. Finally, we introduce a specific application of generating symmetric keys by using the randomness of the end-to-end delay.

Background: Anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors (TKIs) have significantly improved the clinical outcomes of patients with ALK-positive non-small cell lung cancer (NSCLC). However, reliable biomarkers to predict the prognostic role of this treatment are lacking. The Pan-Immune-Inflammation Value (PIV) has recently been demonstrated as a novel comprehensive biomarker to predict survival of patients with solid tumors. Our study aimed to evaluate the prognostic power of PIV in this group of patients. Patients and methods: 94 patients with advanced ALK-positive NSCLC who received first-line ALK inhibitors were enrolled in this study. PIV was calculated as the product of peripheral blood neutrophil, monocyte, and platelet counts divided by lymphocyte count. Kaplan-Meier method and Cox hazard regression models were used for survival analyses. Results: The 1-year progression-free survival (PFS) was 63.5%, and the 5-year overall survival (OS) rate was 55.1%. Patients with higher PIV, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune inflammation index (SII) had worse PFS in univariate analysis, but only the PIV (hazard ratio [HR] = 2.90, 95% confidence interval [CI]: 1.79–4.70, p < 0.001) was an independent prognostic factor in multivariate analysis. Similarly, patients with higher PIV, NLR, PLR, and SII had a worse OS in the univariate analysis, but only the PIV (HR = 4.70, 95% CI: 2.00–11.02, p < 0.001) was significantly associated with worse OS in multivariate analysis. Conclusion: PIV is a comprehensive and convenient predictor of both PFS and OS in patients with ALK-positive advanced NSCLC who received first-line ALK TKIs. Prospective clinical trials are required to validate the value of this new parameter.

Seasonal variations of environmental factors generally result in considerable changes in microbiomes, yet we still lack a clear understanding of how microbial communities maintain their ecological stability. Here, we analyze a long-term (nine years) high-throughput sequencing dataset by network analysis to illustrate how the microbial stability varies among seasons in lake ecosystems. The results showed that the microbial networks were distinctly different among seasons, and the most complex network in autumn exhibited the highest stability. We found that the strong connecting structures among microbes (large modules) were significantly (P

Dipeptidyl-peptidase IV (DPP4), originally identified as an aminopeptidase in 1960s, is an ubiquitously expressed protease presented as either a membrane-bound or soluble form. DPP4 cleaves dipeptide off from the N-terminal of its substrates, altering the bioactivity of its substrates. Subsequent studies reveal that DPP4 is also involved in various cellular processes by directly binding to a number of ligands, including adenosine deaminase, CD45, fibronectin, plasminogen, and caveolin-1. In recent years, many novel functions of DPP4, such as promoting fibrosis and mediating virus entry, have been discovered. Due to its implication in fibrotic response and immunoregulation, increasing studies are focusing on the potential role of DPP4 in inflammatory disorders. As a moonlighting protein, DPP4 possesses multiple functions in different types of cells, including both enzymatic and non-enzymatic functions. However, most of the review articles on the role of DPP4 in autoimmune disease were focused on the association between DPP4 enzymatic inhibitors and the risk of autoimmune disease. An updated comprehensive summary of DPP4’s immunoregulatory actions including both enzymatic dependent and independent functions is needed. In this article, we will review the recent advances of DPP4 in immune regulation and autoimmune rheumatic disease.

Background Phosphorus (P) is abundant in soils, including organic and inorganic forms. Nevertheless, most of P compounds cannot be absorbed and used by plants. Aspergillus niger v. Tiegh is a strain that can efficiently degrade P compounds in soils. Methods In this study, A. niger xj strain was mutated using Atmospheric Room Temperature Plasma (ARTP) technology and the strains were screened by Mo-Sb Colorimetry with strong P-solubilizing abilities. Results Compared with the A. niger xj strain, setting the treatment time of mutagenesis to 120 s, four positive mutant strains marked as xj 90–32, xj120–12, xj120–31, and xj180–22 had higher P-solubilizing rates by 50.3%, 57.5%, 55.9%, and 61.4%, respectively. Among them, the xj120–12 is a highly efficient P solubilizing and growth-promoting strain with good application prospects. The growth characteristics such as plant height, root length, and dry and fresh biomass of peanut (Arachis hypogaea L.) increased by 33.5%, 43.8%, 43.4%, and 33.6%, respectively. Besides available P, the chlorophyll and soluble protein contents also vary degrees of increase in the P-solubilizing mutant strains. Conclusions The results showed that the ARTP mutagenesis technology can improve the P solubilization abilities of the A. niger mutant strains and make the biomass of peanut plants was enhanced of mutant strains.

New buffer layer materials RESbO3 (RE = Y, Sm, Dy, and Ho), Gd1−xCaxBiO3, Gd1−xPbxBiO3, and Eu1−xCaxBiO3 for coated conductors were deposited on a single crystal LaAlO3 substrate through the self-developed polymer-assisted chemical solution deposition method, and YSbO3 was also deposited on CeO2/NiW. Then, the results of x-ray diffraction patterns and SEM indicate high c-axis oriented, smooth, compact, and seamless properties of fabricated new buffer layers, which satisfied the subsequent growth of the superconducting layer. This work offers an effective method to prepare new buffer layers for coated conductors and may provide a new way to search materials with minimal mismatched lattice.

Listeria monocytogenes, as a model organism, is a causative agent of enteric pathogen that causes systemic infection. However, the interaction of L. monocytogenes and small intestinal epithelium has not been fully elucidated yet. In this study, mice and intestinal organoids were chosen as the models to investigate the influence of L. monocytogenes infection on the intestinal secretory cells and its differentiation-related pathways. Results confirmed the phenomenon of intestinal damage that L. monocytogenes infection could lead to villi damage in mice, which was accompanied by the increase of TNF-α production in jejunum as well as lipopolysaccharide (LPS) secretion in serum. Moreover, it was demonstrated that L. monocytogenes infection increased the number of goblet and Paneth cells in mice and intestinal organoids and upregulated the expression of Muc2 and Lyz. Furthermore, L. monocytogenes decreased the relative expression of Notch pathway-related genes (Jag1, Dll4, Notch1, and Hes1) while upregulating the relative expression of Math1 gene in mice and intestinal organoids. This indicated that L. monocytogenes infection caused the inhibition of Notch pathway, which may be the reason for the increased number of goblet and Paneth cells in the intestine. Collectively, these results are expected to provide more information on the mechanism of L. monocytogenes infection in the intestine.

BackgroundIntravenous immunoglobulin (IVIG) showed its therapeutic efficacy on Kawasaki disease (KD). However, the mechanisms by which it reduces systemic inflammation are not completely understood. Dendritic cells (DCs) and T cells play critical roles in the pathogenic processes of immune disorders. Assessing the quantity of DC subsets and T cells and identifying functional molecules present on these cells, which provide information about KD, in the peripheral blood may provide new insights into the mechanisms of immunoglobulin therapy.MethodsIn total, 54 patients with KD and 27 age-matched healthy controls (HCs) were included in this study. The number, percentage, and phenotype of DC subsets and CD4+ T cells in peripheral blood were analyzed through flow cytometry.ResultsPatients with KD exhibited fewer peripheral DC subsets and CD4+ T cells than HCs. Human leucocyte antigen-DR (HLA-DR) expression was reduced on CD1c+ myeloid DCs (CD1c+ mDCs), whereas that on plasmacytoid DCs (pDCs) did not change significantly. Both pDCs and CD1c+ mDCs displayed significantly reduced expression of co-stimulatory molecules, including CD40, CD86. pDCs and CD1c+ mDCs presented an immature or tolerant phenotype in acute stages of KD. Number of circulating pDC and CD1c+ mDC significantly inversely correlated with plasma interleukin-6 (IL-6) levels in KD patients pre-IVIG treatment. No significant differences were found concerning the DC subsets and CD4+ T cells in patients with KD with and without coronary artery lesions. Importantly, these altered quantity and phenotypes on DC subsets and CD4+ T cells were restored to a great extent post-IVIG treatment. T helper (Th) subsets including Th1 and Th2 among CD4+ T cells did not show alteration pre- and post-IVIG treatment, although the Th1-related cytokine IFN-γ level in plasma increased dramatically in patients with KD pre-IVIG treatment.ConclusionspDCs and CD1c+ mDCs presented an immature or tolerant phenotype in acute stages of KD, IVIG treatment restored the quantity and functional molecules of DCs and CD4+ T cells to distinct levels in vivo, indicating the involvement of DCs and CD4+ T cells in the inflammation in KD. The findings provide insights into the immunomodulatory actions of IVIG in KD.

ObjectivesDoxorubicin (Dox), a chemotherapeutic anthracycline agent for the treatment of a variety of malignancies, has a limitation in clinical application for dose-dependent cardiotoxicity. The purpose of this study was to explore the relationship between the composition/function of the gut microbiota and Dox-induced cardiotoxicity (DIC).MethodsC57BL/6J mice were injected intraperitoneally with 15 mg/kg of Dox, with or without antibiotics (Abs) administration. The M-mode echocardiograms were performed to assess cardiac function. The histopathological analysis was conducted by H&E staining and TUNEL kit assay. The serum levels of creatine kinase (CK), CK-MB (CK-MB), lactic dehydrogenase (LDH), and cardiac troponin T (cTnT) were analyzed by an automatic biochemical analyzer. 16S rRNA gene and metagenomic sequencing of fecal samples were used to explore the gut microbiota composition and function.Key FindingsDox caused left ventricular (LV) dilation and reduced LV contractility. The levels of cardiomyocyte apoptosis and myocardial enzymes were elevated in Dox-treated mice compared with the control (Con) group. 16S rRNA gene sequencing results revealed significant differences in microbial composition between the two groups. In the Dox group, the relative abundances of Allobaculum, Muribaculum, and Lachnoclostridium were significantly decreased, whereas Faecalibaculum, Dubosiella, and Lachnospiraceae were significantly increased compared with the Con group at the genus level. Functional enrichment with Cluster of orthologous groups of proteins (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that the Dox mice displayed different clusters of cellular processes and metabolism from the Con mice. The different species and their functions between the two groups were associated with the clinical factors of cardiac enzymes. Moreover, depletion of the gut microbiota could alleviate Dox-induced myocardial injury and cardiomyocyte apoptosis.ConclusionsThe study here shows that composition imbalance and functional changes of the gut microbiota can be one of the etiological mechanisms underlying DIC. The gut microbiota may serve as new targets for the treatment of cardiotoxicity and cardiovascular diseases.

Background: Ticagrelor belongs to a new class of P2Y12 receptor inhibitor that has been widely used for antiplatelet therapy. This study aimed to explore the effect of single nucleotide polymorphisms (SNPs) in metabolic enzymes, transporters, and other relevant variants on the pharmacokinetics (PK) of ticagrelor and its active metabolite, AR-C124910XX.Methods: The study population comprised 68 healthy Chinese volunteers who were enrolled in a ticagrelor bioequivalence clinical trial. The PK profile of ticagrelor was evaluated after orally administering a single 90-mg dose of ticagrelor in tablet form. The plasma concentrations of ticagrelor and AR-C124910XX were determined through liquid chromatography–tandem mass spectrometry. Plasma DNA samples were used to explore the effect of gene polymorphisms on the PK of ticagrelor and AR-C124910XX with whole-exome sequencing.Results: Female participants had a higher maximum plasma concentration/weight ratio (Cmax/W; p

Reliable lasers on Si with large bandwidth are desirable for high-performance data communication systems on Si-photonics platforms. Here, we report short optical pulses generated by gain-switched InP-based 1.55 µm quantum dash (Qdash) lasers directly grown on (001) Si. The laser performance and related physical parameters were investigated by carrying out a gain-switching test for lasers on both Si and native InP substrates. The shortest pulses obtained were 217 and 252 ps for the lasers on InP and Si, respectively. By varying the electrical bias and pulse duration systematically, the evolution of the generated optical pulse duration and peak power was studied. The impact of cavity size on the optical pulse was also examined. Parameters were extracted using established equations fitted with our measurement results to gain insight into the underlying physics and correlation with the observed behavior. The obtained results indicate that the pulse width is limited by the low differential gain and strong gain compression of the active material. Our results indicate that Qdash lasers on Si can demonstrate comparable performance to those on a native InP substrate and manifest its potential application in an Si-based photonics chip for optical on-chip communications.

Overflow water is an important part of the Atlantic Meridional Overturning Circulation, yet how it reaches the Greenland-Scotland Ridge is not fully known. Here, the authors show that the interior of the Greenland Sea gyre is the primary wintertime source of the densest portion of both Denmark Strait and Faroe Bank Channel overflows.

Abstract Background The pan‐cancer analysis has recently brought us into a novel level of cancer research. Nowadays, the Circular RNAs (circRNAs) is becoming increasingly important in the occurrence and progression of tumors. Nevertheless, the specific expression patterns and functions of circRNAs in the pan‐cancer remains unclear. Here we aimed to explore the expression patterns and functions of circRNAs in pan‐cancer. Methods We combined our microarray with seven circRNA arrays from the Gene Expression Omnibus (GEO) database and transcriptome profiles were acquired from The Cancer Genome Atlas (TCGA) database. A circRNA‐miRNA‐mRNA network was created and analyzed using multiple bioinformatic approaches including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, Search Tool for the Retrieval of Interacting Genes (STRING) database, cytoHubba and MCODE app. Cell function assays including CCK‐8 analysis, colony formation, and transwell assay were used to explore pan‐circRNAs’ functions. Results A panel of 6 circRNAs, 11 miRNAs, and 318 mRNAs was found to be differentially expressed (DE) in pan‐cancer. A circRNA‐miRNA‐mRNA network was also constructed. Then, a circRNA‐miRNA‐hub gene network was created according to 5 pan‐circRNAs, 8 pan‐miRNAs, and 16 pan‐mRNAs. Enrichment analysis pointed out the possible association of DEmRNAs with pan‐cancer is transcriptional misregulation in cancer. Overexpression of hsa_circ_0004639 and silence of hsa_circ_0008310 can inhibit the malignant biological properties of cancer cells. Conclusions Six pan‐circRNAs were discovered and their regulating mechanisms were predicted. Those findings together will give a new insight into pan‐cancer research and present potential therapy targeting as well as promising biomarkers.

The emergence of tumour adaptive radioresistance can limit the success of radiation therapy and immunotherapy in breast cancer. In this study, the authors demonstrate that CD47 and HER2 are coordinating in tumor response to radiation and that co-blockage of both receptors can eliminate radiorestistant breast cancer cells.

Abstract The dynamics of the community structure and composition of the dairy cow fecal bacterial communities during early lactation is unclear, therefore this study was conducted to characterize the fecal bacterial communities in dairy cows during early lactation using 16S rRNA gene sequencing. Feces were sampled from 20 healthy fresh Holstein dairy cows on day 1 (Fresh1d group) and day 14 (Fresh14d group) after calving. After calving, cows were fed the same fresh diet. The dominant phyla Firmicutes and Proteobacteria were decreased (P ≤ 0.01) with lactating progress and phyla Bacteroidetes were increased (P = 0.008) with lactating progress and dietary transition. At family level, the predominant families were Ruminococcaceae (35.23%), Lachnospiraceae (11.46%), Rikenellaceae (10.44%) and Prevotellaceae (6.89%). A total of 14 genera were different between fecal samples from Fresh1d and Fresh14d, included the predominant genera, such as Ruminococcaceae_UCG-005 (P = 0.008), Rikenellaceae_RC9_gut_group (P = 0.043) and Christensenellaceae_R-7_group (P = 0.008). All fecal bacterial communities shared members of the genera Ruminococcaceae_UCG-005, Bacteroides and Rikenellaceae_RC9_gut_group. These findings help to improve our understanding of the composition and structure of the fecal microbial community in fresh cows and may provide insight into bacterial adaptation time and dietary in lactating cows.

Abstract It is unclear about the functional role of microRNA-133a-3p (miR-133a-3p) in intracranial aneurysm (IA). Hence, the aim of the present study was to investigate the regulatory role of miR-133a-3p on the regulation of vascular endothelial injury-induced IA through phosphoserine aminotransferase 1 (PSAT1)/glycogen synthase kinase 3β (GSK3β)/β-catenin signaling pathway. Normal intracranial arteriole tissues and IA tissues were gathered from patients with brain trauma and IA. The expression of miR-133a-3p, PSAT1, GSK3β, and β-catenin in tissues was determined by RT-qPCR and western blot analysis. The endothelial cells (ECs) of the human IA were cultured and treated with miR-133a-3p mimic and si-PSAT1 to determine their functions in endothelial cell migration, apoptosis, and proliferation. The expression of miR-133a-3p, PSAT1, GSK3β, β-catenin, Ki-67, CyclinD1, Bax, and Bcl-2 in ECs were tested by RT-qPCR or western blot analysis. Moreover, IA rat model was established to detect the pathological changes and the expression of miR-133a-3p, PSAT1, GSK3β, β-catenin, VEGF, and MMP-9 in IA tissues in vivo. Expression of miR-133a-3p was related to the number and size of IA. MiR-133a-3p expression was deceased and the PSAT1, GSK3β, and β-catenin expression was raised in IA. Restored miR-133a-3p and depleted PSAT1 alleviated the pathological change; reduced PSAT1, GSK3β, and β-catenin expression in IA; suppressed apoptosis and advanced proliferation and migration of IA ECs, as well as reduced VEGF and MMP-9 expression in IA tissues in vivo. Our study suggests that overexpression of miR-133a-3p or downregulation of PSAT1 restrains endothelial cell damage and advances endothelial cell proliferation via inhibiting the GSK3β/β-catenin pathway in IA. MiR-133a-3p might be a potential candidate marker and therapeutic target for IA.

Abstract This paper investigated the working behavior characteristics of six reinforcement concrete (RC) beams subjected to bending based on the numerical shape function (NSF) method and structural stressing state theory. Firstly, the structural stressing state mode is expressed based on the generalized strain energy density (GSED) derived from the measured strain data. Then, one of the Carbon Fiber Reinforced Plastic (CFRP)-strengthened RC beams is taken as an example and the leap characteristics of RC beam’s stressing state are detected by applying the Mann–Kendall (M–K) criterion, updating the existing definition of the structural failure load. Accordingly, the stressing state modes and strain fields of the CFRP-strengthened RC beam are proposed to reveal their leap characteristics. Furthermore, through comparing the working performance of six RC beams, the effects of different strengths and different reinforcement ratios on CFRP strengthening performance are investigated. Finally, the NSF method is applied to reasonably interpolate the limited strain data for further revealing the stressing state characteristics of the RC beams. The research results explore a new analysis method to conduct an accurate estimation of the structural failure load and provide a reference for the future design of CFRP-strengthened RC beams.

In the ultra dense network (UDN),the pilot reuse scheme would produce significant interference,which will affect the accuracy of channel estimation.To solve this problem,an interference avoidance strategy for UDN with pilot reuse was proposed.An interference model of subcarriers for UDN was provided and the interference probability of subcarriers was derived.Then,based on the model,a pilot position selection model was proposed and an interference avoidance strategy for UDN with pilot reuse was provided.The simulation results show that compared with the traditional channel estimation algorithm,the channel estimation with proposed interference avoidance strategy can effectively avoid the interference and ensure the accuracy of channel estimation in UDN with pilot reuse.

Abstract Background Hypotrichia are a group with the most complex morphology and morphogenesis within the ciliated protists. The classification of Gastrostyla-like species, a taxonomically difficult group of hypotrichs with a common ventral cirral pattern but various dorsal and ontogenetic patterns, is poorly understood. Hence, systematic relationships within this group and with other taxa in the subclass Hypotrichia remain unresolved. Results 18S rRNA gene sequence of a new Gastrostyla-like taxon was obtained. Phylogenetic analyses based on the 18S rRNA gene sequences indicate that this ciliate represents a new genus that is closely related to Heterourosomoida and Kleinstyla within the oxytrichid clade of the Hypotrichia. However, the position of this cluster remains unresolved. All three genera deviate from the typical oxytrichids by their incomplete (or lack of) dorsal kinety fragmentation during morphogenesis. Morphology and morphogenesis of this newly discovered form, Heterogastrostyla salina nov. gen., nov. spec., are described. Heterogastrostyla nov. gen., is characterised as follows: more than 18 fronto-ventral-transverse cirri, cirral anlagen V and VI develop pretransverse cirri, and dorsal ciliature in Urosomoida-like pattern. Conclusions Similar to the CEUU-hypothesis about convergent evolution of urostylids and uroleptids, we speculate that the shared ventral cirral patterns of Gastrostyla-like taxa might have resulted from convergent evolution.

Abstract Background The relationship between transcription and the 3D chromatin structure is debated. Multiple studies have shown that transcription affects global Cohesin binding and 3D genome structures. However, several other studies have indicated that inhibited transcription does not alter chromatin conformations. Results We provide the most comprehensive evidence to date to demonstrate that transcription plays a relatively modest role in organizing the local, small-scale chromatin structures in mammalian cells. We show degraded Pol I, Pol II, and Pol III proteins in mESCs cause few or no changes in large-scale 3D chromatin structures, selected RNA polymerases with a high abundance of binding sites or active promoter-associated interactions appear to be relatively more affected after the degradation, transcription inhibition alters local, small loop domains, as indicated by high-resolution chromatin interaction maps, and loops with bound Pol II but without Cohesin or CTCF are identified and found to be largely unchanged after transcription inhibition. Interestingly, Pol II depletion for a longer time significantly affects the chromatin accessibility and Cohesin occupancy, suggesting that RNA polymerases are capable of affecting the 3D genome indirectly. These direct and indirect effects explain the previous inconsistent findings on the influence of transcription inhibition on the 3D genome. Conclusions We conclude that Pol I, Pol II, and Pol III loss alters local, small-scale chromatin interactions in mammalian cells, suggesting that the 3D chromatin structures are pre-established and relatively stable.

Aiming at the problem of poor performance of the classification model in the case of unintentional phase modulation on pulse (UPMOP) to achieve radar specific emitter identification,a method for radar specific emitter identification with long and short-term memory and full convolutional networks (LSTM-FCN) was proposed.Firstly,a simplified observation model of the intrapulse signal phase considering the intentional modulation was presented,and the observation phase sequence was deramp to extract the noisy estimate of the UPMOP.Then Bezier curve was utilized to fit the UPMOP to reduce the influence of noise and obtain a more accurate description of UPMOP.Finally,the LSTM-FCN was used to extract the joint features of UPMOP sequence to realize the radar specific emitter automatic identification.Both the simulation experiments and the measured data experiments verify the feasibility and effectiveness of the proposed algorithm.Moreover,the proposed algorithm has high identification accuracy and short time consumption.

Abstract Dysregulation of circadian rhythms associates with cardiovascular disorders. It is known that deletion of the core circadian gene Bmal1 in mice causes dilated cardiomyopathy. However, the biological rhythm regulation system in mouse is very different from that of humans. Whether BMAL1 plays a role in regulating human heart function remains unclear. Here we generated a BMAL1 knockout human embryonic stem cell (hESC) model and further derived human BMAL1 deficient cardiomyocytes. We show that BMAL1 deficient hESC-derived cardiomyocytes exhibited typical phenotypes of dilated cardiomyopathy including attenuated contractility, calcium dysregulation, and disorganized myofilaments. In addition, mitochondrial fission and mitophagy were suppressed in BMAL1 deficient hESC-cardiomyocytes, which resulted in significantly attenuated mitochondrial oxidative phosphorylation and compromised cardiomyocyte function. We also found that BMAL1 binds to the E-box element in the promoter region of BNIP3 gene and specifically controls BNIP3 protein expression. BMAL1 knockout directly reduced BNIP3 protein level, causing compromised mitophagy and mitochondria dysfunction and thereby leading to compromised cardiomyocyte function. Our data indicated that the core circadian gene BMAL1 is critical for normal mitochondria activities and cardiac function. Circadian rhythm disruption may directly link to compromised heart function and dilated cardiomyopathy in humans.

With the rapid development of core network technology,network structures have become increasingly complicated.Nowadays,it is urgent to transform from the traditional CT core network to IT core network.Widely used in the IT field,SRE model provided core network maintenance personnel with an applicable transformation way.The feasibility of SRE model through the CT maintenance point of view was analyzed,emphasizing on the comparison of IT maintenance with CT maintenance in reality with principles mentioned in SRE.Moreover,cases were expounded in the thesis to demonstrate an effective transformation strategy with the help of SRE model.

Based on the vision on the 6G wireless communication network,i.e.,global coverage,all spectrums and all applications,we comprehensively survey 6G related wireless channel measurements,channel characteristics,and channel models for all frequency bands and all scenarios.Millimeter wave (mmWave),terahertz (THz),optical band,satellite,unmanned aerial vehicle (UAV),maritime,underwater acoustic,high-speed train (HST),vehicle-to-vehicle (V2V),massive/ultra-massive multiple-input multiple-output (MIMO),orbital angular momentum (OAM),and industry Internet of things (IoT) communication channels were particularly investigated.The related 6G channel measurement and modeling results were also given.Finally,future research challenges on 6G channel measurements and modeling were pointed out.

Cancer radiotherapy (RT) demonstrates the benefit of local control with fewer side-effects compared to chemotherapy. To further improve the overall efficacy of RT and RT-combined therapies, studies revealing the mechanisms involved in tumor response to radiation are required. Accumulating new evidence has demonstrated that the microenvironment of solid tumors, such as cancers in lung, breast, and liver, holds a highly heterogenic population of tumor cells, an array of stromal cells with different functions, as well as non-cellular components. The observed tumor responses to cancer radiotherapy are pooled signals generated from the heterogenic cell populations such as the survival of radioresistant tumor cells and the infiltrated immune cells. Thus, further elucidation of key dynamics in irradiated tumor microenvironment (ITME), including repopulation of cancer stem cells, metabolic shifting, and radiation-induced tumor immunogenicity, will be necessary to significantly enhance the outcome of RT or RT-combined immunotherapy. This review summarizes the current experimental and clinical results of these three dynamics in ITME.

Objective It is unclear if biosimilars of biologics for inflammatory arthritis are realizing their promise to increase competition and improve accessibility. This study evaluates biosimilar tumor necrosis factor inhibitor (TNFi) utilization across rheumatology practices in the United States and compares whether patients initiating biosimilars remain on these treatments at least as long as new initiators of bio‐originators. Methods We identified a cohort of patients initiating a TNFi biosimilar between January 2017 and September 2018 from an electronic health record registry containing data from 218 rheumatology practices and over 1 million rheumatology patients in the United States. We also identified a cohort of patients who initiated the bio‐originator TNFi during the same period. We calculated the proportion of biosimilar prescriptions compared with other TNFi's and compared persistence on these therapies, adjusting for age, sex, diagnoses codes, and insurance type. Results We identified 909 patients prescribed the biosimilar infliximab‐dyyb, the only biosimilar prescribed, and 4413 patients with a new prescription for the bio‐originator infliximab. Biosimilar patients tended to be older, have a diagnosis code for rheumatoid arthritis, and covered by Medicare insurance. Over the study period, biosimilar prescriptions reached a maximum of 3.5% of all TNFi prescriptions. Patients persisted on the biosimilar at least as long as the bio‐originator infliximab (hazard ratio [HR] 0.83, P = 0.07). Conclusion The uptake of biosimilars in the United States remains low despite persistence on infliximab‐dyyb being similar to the infliximab bio‐originator. These results add to clinical studies that should provide greater confidence to patients and physicians regarding biosimilar use.

In the era of big data, multiple data sources have been employed in the study of land use and transportation for urban and regional planning purposes. This paper offers an example of how multiple data sources (e.g., mobile signalling data, taxi trips and transit trips from smartcard data) can be used to estimate the spatial pattern of commute mode preference in Beijing, China. The comparative analysis investigates the spatial pattern of commute mode preference by taxi at a fine resolution in Beijing. This work indicates how the preference for taxis can be seen in the north-east of the inner city, but not around employment centres. Equally, a complementary relationship is found between a preference for taxis and public transit that provides useful insights into modal choice at an intra-urban scale. These findings are useful in urban planning and transport management.

This paper mainly studies the obstacle avoidance and rapid reconstruction of UAV formations. A hybrid trajectory planning algorithm based on potential field fluid dynamic model and bidirectional fast search random tree is proposed to improve the ability of UAV formation to adapt to complex dynamic environment. Firstly, a dynamic system mathematical model based on fluid potential energy field is proposed; and the obstacle potential energy function and potential energy function between the formations modify the disturbance flow field. Secondly, IBi-directional Rapidly Exploring Random Tree (IBi-RRT) algorithm with adaptive step size is scheduled to solve the dispersive and convergent streamlines of disturbed flow field and to plan the trajectory. This method can clarify the flow field streamlines by adaptive step size combined with rolling detection method, which greatly improves the formation's ability to avoid dynamic threats. The experimental results show that the proposed improved fluid potential energy field dynamic system and IBi-RRT hybrid trajectory planning algorithm with adaptive step size can effectively improve the adaptive ability of UAV formation to the dynamic environment, and can plan the ideal trajectory in response to unexpected situations.

Vessel Monitoring Systems (VMS) are extensively used in the world to provide information on the vessel's spatiotemporal distribution, monitor the fishing activities of marine fishery and manage the safety of vessel navigation. In the traditional VMS, there are some deficiencies in the interaction and real-time communication between the land system and marine vessel. We present an edge computing-based adaptable trajectory transmission policy (EC-ATT) for VMS to improve the communication efficiency in this paper. Firstly, a novel VMS framework named EC-VMS is proposed which composed of four layers. Each vessel has an edge computing intelligent node to collect data, process and transmit data. Meanwhile, the edge computing server is set up to enhance collaborative computing between the cloud and the edge, that transmits data through the Beidou navigation satellite system. Secondly, the EC-ATT utilizes the computing power of edge nodes to establish an adaptive data transmission mechanism, which reduces redundant data and satellite communication frequency. Besides, the packet loss feedback mechanism and error checking strategy are used to ensure the reliability of data transmission. The experimental results show that EC-ATT has better performance in typical cases, which not only reduces the average communication time but also strengthens the real-time availability of the VMS.

This paper addresses the trajectory tracking problem for constrained high dynamic electro-hydraulic actuator in the presence of time-varying parameters, high frequency external load interference, measurement noise and some unmeasurable states. An adaptive robust optimal control scheme is proposed for the electro-hydraulic actuator in legged robot. The framework of our presented scheme is based on a linear time-varying model predictive controller (LTV-MPC) embedded with a multi-scale online estimator (MEKF). With fast- varying and slow- varying time scales, the MEKF part is used not only for measurable states filtering and unmeasurable states estimation, but also for time-varying parameters and external load interference estimation, which will be integrated into the mpc model in real time. The LTV-MPC part is a trajectory tracking controller designed by constrained MPC with an approximate high-precision real-time model and a rapidly solved cost function, which guarantees that the input and output constraints are satisfied during the receding horizon and optimal control process. Finally, with a series of highly dynamic conditions, the comparison experiment results show that the proposed controller has a simple design process, strong adaptive robust performance and trajectory tracking performance, which verifies the effectiveness of the control scheme.

In this paper, a novel Mobile-Coverage scheme is proposed to improve the coverage and lifetime of hybrid sensor networks, and thus the target region can be completely covered with minimum number of mobile sensor nodes and the energy consumption can be reduced in hybrid sensor networks at the same time. Our scheme is applied to a hybrid network comprising of both static and mobile sensor nodes, which are randomly deployed in a rectangle area. We derived the minimum number of sensor nodes as well as the mobile nodes required to cover the target region completely. Compared to the existing works, the minimum number of mobile sensor nodes required in this paper is significantly smaller, which implies that the movement distance and energy consumption of mobile nodes in our scheme is reduced. Moreover, we proved that the construction of our scheme based on the Virtual Force and Voronoi Graph (VFVG) is correct, and then derived the optimal trade-off between the coverage of the target region and energy consumption of mobile nodes. Our scheme can achieve the maximum coverage which is 98.7% by minimum number of mobile sensor nodes. Meanwhile, a connectivity rate of 76.84% can also be achieved by our connectivity evaluation method. Finally, a new topology construction algorithm-Topology Construction and Maintenance based on Trust (TCMT) is created to further increase the lifetime of the sensor network. We also evaluated the performance of our scheme in terms of coverage and lifetime, and carried out extensive experiments to compare the coverage and energy consumption in our scheme and several previous schemes. The experimental results showed that our scheme is more efficient than the previous schemes simulated.

In order to satisfy the real-time need of model-based controllers for model parameters and full states feedback, this paper has conducted in-depth research on the states and parameters estimation of electro-hydraulic actuator in legged robot with three problems for time-varying parameters estimation (including system parameters and external load force), non-measurable states estimation and measurable states filtering. The first-order trajectory sensitivity method based on the dynamic model is used to determine the parameter set to be estimated, and the parameter fast and slow characteristics are analyzed in detail to obtain the generalized states and slow-varying parameters. Then, the combined algorithm with a fast-varying time scale (composed of a fusion kalman filter and a fast-varying time scale extended kalman filter) and a slow-varying time scale (composed of a slow-varying time scale extended kalman filter) is innovatively proposed to realize the data-driven multi-scale online joint estimation of states and parameters for the actuator system. Finally, the results of three comparative experiments show that the proposed algorithm has better stability, faster convergence speed and more accurate estimation than the dual extended kalman filter algorithm, and the states and parameters estimated by the proposed algorithm accurately reflect the actual characteristics of actuator. Moreover, the algorithm has strong adaptability and robustness in different actuator hardware environment and strong convergence ability for different initial values of states and parameters.

The task priority planning problem is addressed in the task supervisor of null-space behavioral (NSB) control for multi-agent systems. Traditional methods rely on pre-defined logic-based or fuzzy rules to adjust task priority. In this work, a novel task supervisor is proposed using model predictive control (MPC) techniques. At each sampling instant, the task priority planning problem is formulated as a switching mode optimal control problem (OCP), which can be solved by efficient mixed-integer optimal control algorithms. The optimal task priority order is obtained based on current and predictive information of agents, without the need for a pre-defined rule. By explicitly introducing slack variables into constraints, the proposed MPC method is flexible to cope with dynamic obstacles in unknown environments. Simulations with static and dynamic obstacles show that the proposed method can provide significantly better control performance than the traditional logic-based method using less priority switchings.

This question combines virtual reality technology with video surveillance technology to realize an intelligent video surveillance system based on virtual reality technology in tourist attractions. It analyzes the technology and theory involved in the video surveillance system based on virtual reality technology and then designs the architecture and functions of the system. The system is divided into three parts, such as local monitoring client, streaming media server, and remote monitoring client. It detailed the design and implementation of each module. We use the OpenCV library and moving target detection algorithm to realize the intelligent analysis of surveillance video and use the OpenGL engine to render the surveillance video of VR panorama of tourist attractions to achieve the effect of virtual reality. The video surveillance system implemented is tested and analyzed in combination with the actual application of tourist attractions. The test results show that the system can operate stably and meet the design indicators. The remote monitoring delay is controlled within one second. The remote monitoring client has achieved the effect of virtual reality.

In this paper, a novel human decision-making behavior model is proposed for human-robot interaction (HRI) for the control of multi-robot systems (MRS). The proposed human drift diffusion model (HDDM) combines the traditional drift diffusion model (DDM) and the null-space-based behavioral control (NSBC) method by introducing a data-processing station and a human cognitive system. In the HDDM, the evolution of human-decision information is computed. By using a threshold of such information to trigger human interaction, accurate human decision-making timing can be obtained. In addition, a cooperative controller is designed for robots to follow human instructions. Simulations under various scenarios show that by using the proposed HDDM and the controller, robots can complete human instructions more accurately comparing to traditional methods. An experiment using a group of quadrotors subject to external wind disturbances also demonstrate the effectiveness of the proposed HDDM in real-world uncertain environments.

The hyperspectral image superresolution (HSI-SR) problem aims to improve the spatial quality of a low spatial resolution HSI by fusing the LR-HSI with the corresponding high spatial resolution multispectral image. The generated HSI with high spatial quality, i.e., the target high spatial resolution hyperspectral image (HR-HSI), generally has some fundamental latent properties, e.g., the sparsity, and the piecewise smoothness along with the three modes (i.e., width, height, and spectral mode). However, limited works consider both properties in the HSI-SR problem. In this work, a novel unidirectional total variation (TV) based approach is been proposed. On the one hand, we consider that the target HR-HSI exhibits both the sparsity and the piecewise smoothness on the three modes, and they can be depicted well by the ℓ1-norm and TV, respectively. On the other hand, we utilize the classical Tucker decomposition to decompose the target HR-HSI (a three-mode tensor) as a sparse core tensor multiplied by the dictionary matrices along with the three modes. Especially, we impose the ℓ1-norm on core tensor to characterize the sparsity and the unidirectional TV on three dictionaries to characterize the piecewise smoothness. The proximal alternating optimization scheme and the alternating direction method of multipliers are used to iteratively solve the proposed model. Experiments on three common datasets illustrate that the proposed approach has better performance than some current state-of-the-art HSI-SR methods. Please find source code from: https://liangjiandeng.github.io/.

To reduce the energy-intensity and carbon footprint of Portland cement (PC), the prevailing practice embraced by concrete technologists is to partially replace the PC in concrete with supplementary cementitious materials [SCMs: geological materials (e.g., limestone); industrial by-products (e.g., fly ash); and processed materials (e.g., calcined clay)]. Chemistry and content of the SCM profoundly affect PC hydration kinetics; which, in turn, dictates the evolutions of microstructure and properties of the [PC + SCM] binder. Owing to the substantial diversity in SCMs’ compositions–plus the massive combinatorial spaces, and the highly nonlinear and mutually-interacting processes that arise from SCM-PC interactions–state-of-the-art computational models are unable to produce a priori predictions of hydration kinetics or properties of [PC + SCM] binders. In the past 2 decades, the combination of Big data and machine learning (ML)—commonly referred to as the fourth paradigm of science–has emerged as a promising approach to learn composition-property correlations in materials (e.g., concrete), and capitalize on such learnings to produce a priori predictions of properties of materials with new compositions. Notwithstanding these merits, widespread use of ML models is hindered because they: 1) Require Big data to learn composition-property correlations, and, in general, large databases for concrete are not publicly available; and 2) Function as black-boxes, thus providing little-to-no insights into the materials laws like theory-based analytical models do. This study presents a deep learning (DL) model capable of producing a priori, high-fidelity predictions of composition- and time-dependent hydration kinetics and phase assemblage development in [PC + SCM] pastes. The DL is coupled with: 1) A fast Fourier transformation algorithm that reduces the dimensionality of training datasets (e.g., kinetic datasets), thus allowing the model to learn intrinsic composition-property correlations from a small database; and 2) A thermodynamic model that constrains the model, thus ensuring that predictions do not violate fundamental materials laws. The training and outcomes of the DL are ultimately leveraged to develop a simple, easy-to-use, closed-form analytical model capable of predicting hydration kinetics and phase assemblage development in [PC + SCM] pastes, using their initial composition and mixture design as inputs.

Background: The autonomic nervous system (ANS) is crucial for acclimatization. Investigating the responses of acute exposure to a hypoxic environment may provide some knowledge of the cardiopulmonary system’s adjustment mechanism.Objective: The present study investigates the longitudinal changes and recovery in heart rate variability (HRV) in a young healthy population when exposed to a simulated plateau environment.Methods: The study followed a strict experimental paradigm in which physiological signals were collected from 33 healthy college students (26 ± 2 years, 171 cm ± 7 cm, 64 ± 11 kg) using a medical-grade wearable device. The subjects were asked to sit in normoxic (approximately 101 kPa) and hypoxic (4,000 m above sea level, about 62 kPa) environments. The whole experimental process was divided into four stable resting measurement segments in chronological order to analyze the longitudinal changes of physical stress and recovery phases. Seventy-six time-domain, frequency-domain, and non-linear indicators characterizing rhythm variability were analyzed in the four groups.Results: Compared to normobaric normoxia, participants in hypobaric hypoxia had significantly lower HRV time-domain metrics, such as RMSSD, MeanNN, and MedianNN (p

Background: Accumulating evidence has suggested that there is a positive association between asthma and cardiovascular diseases (CVDs), implying a common architecture between them. However, the shared genetic architecture and causality of asthma and CVDs remain unclear.Methods: Based on the genome-wide association study (GWAS) summary statistics of recently published studies, our study examined the genetic correlation, shared genetic variants, and causal relationship between asthma (N = 127,669) and CVDs (N = 86,995–521,612). Statistical methods included high-definition likelihood (HDL), cross-trait meta-analyses of large-scale GWAS, transcriptome-wide association studies (TWAS), and Mendelian randomization (MR).Results: First, we observed a significant genetic correlation between asthma and heart failure (HF) (Rg = 0.278, P = 5 × 10−4). Through cross-trait analyses, we identified a total of 145 shared loci between asthma and HF. Fifteen novel loci were not previously reported for association with either asthma or HF. Second, we mapped these 145 loci to a total of 99 genes whose expressions are enriched in a broad spectrum of tissues, including the seminal vesicle, tonsil, appendix, spleen, skin, lymph nodes, breast, cervix and uterus, skeletal muscle, small intestine, lung, prostate, cardiac muscle, and liver. TWAS analysis identified five significant genes shared between asthma and HF in tissues from the hemic and immune system, digestive system, integumentary system, and nervous system. GSDMA, GSDMB, and ORMDL3 are statistically independent genetic effects from all shared TWAS genes between asthma and HF. Third, through MR analysis, genetic liability to asthma was significantly associated with heart failure at the Bonferroni-corrected significance level. The odds ratio (OR) is 1.07 [95% confidence interval (CI): 1.03–1.12; p = 1.31 × 10−3] per one-unit increase in loge odds of asthma.Conclusion: These findings provide strong evidence of genetic correlations and causal relationship between asthma and HF, suggesting a shared genetic architecture for these two diseases.

Studies have found that spatial mismatch is a universal phenomenon, although both their substantive and methodological focus can differ substantially. In China, there is a growing body of literature on spatial mismatch, but few studies have measured the degree of spatial mismatch between local and migrant workers in different occupations. To fill this gap, this research investigates the spatial mismatch for different socioeconomic groups in Xiamen according to their “hukou” status and occupation. As one of the country’s first four special economic zones, Xiamen achieved housing marketization earlier than most other Chinese cities, attracting a large amount of capital and migrants, and shaping different spatial patterns of local workers and migrant workers. The findings show that blue-collar, pink-collar, and white-collar workers, who are further categorized as either locals or migrants, experience varying degrees of job accessibility and spatial mismatch. In addition, even though migrant workers experience less spatial mismatch, they still have disadvantages in terms of commuting time due to their travel mode. The results presented in this paper are helpful for understanding the spatial mismatch for various social groups and facilitating sustainable mobility and social equity.

Due to the presence of capacitance in the transmission line, the current collected by the retarding field analyzer (RFA) becomes asymmetrical (i.e., hysteresis) during voltage scanning, and it further affects the measurement of the ion temperature (Ti). In this article, we first analyze the hysteresis of the RFA’s I–V characteristics measured in the edge plasma of the J-TEXT tokamak, and we found that the ion temperature fitted from the falling side of the collector current is about 14% higher than that fitted from the rising side. An analytic model is built and verified by experimental results. Based on the model, the influence of the capacitance of transmission lines and the frequency of the scanning voltage on the hysteresis is investigated. It is found that the hysteresis becomes more remarkable with increasing capacitance or scanning frequency. Besides, the impact of the capacitance and the scanning frequency on the Ti measurement is also studied, which indicates that Ti is overestimated due to the hysteresis. The temperature error is linearly dependent on the capacitance and the scanning frequency. Furthermore, the analytical results are expected to be used in the prediction of scanning frequency for RFA applications.

Neoclassical properties in quasi-axisymmetric (QA) stellarators are analogous to these in tokamaks. Consequently, a substantial bootstrap current could significantly modify the MHD equilibrium properties of a QA stellarator, which is an important characteristic in this type of stellarator. This paper is dedicated to systemically investigate the effects of bootstrap current on the magnetic configuration in Chinese first quasi-axisymmetric stellarator (CFQS). For the first time, self-consistent bootstrap currents in free-boundary equilibria are calculated with an accurate Fokker–Planck neoclassical numerical mode in CFQS. Several important results are achieved: (a) as the bootstrap current grows with increasing volume-averaged normalized pressure $\beta $ , magnetic shear develops in the bulk plasma and meanwhile, a deep magnetic well is robustly sustained, which leads to improved stabilization of interchange modes up to $\beta \sim 2.0{{\% }}$ . (b) In the analysis of global ideal MHD instability, as the bootstrap current rises to 39 kA ( $\beta \sim 1.3{{\% }}$ ), external kink modes become destabilized and the unstable mode with m / n = 2/1 is dominant. (c) From $\beta = 0$ to 1.5%, the bootstrap current hardly changes the QA property and a low neoclassical transport is maintained. However, as $\beta $ is enhanced beyond 2.0%, the substantial bootstrap current gives rise to an increase of non-QA magnetic field components, which weakens the neoclassical transport properties. (d) An increase of the negative magnetic shear at the core region by the bootstrap currents has a favorable effect on the properties of J (second adiabatic invariant). The maximum- J region can be extended by raising bootstrap currents.

The heating and impact of arc and droplet acting on the weld pool lead to the transfer of mass, heat, and momentum, which affects the dynamic behavior of the weld pool and the microstructure in the P-GMAW process. In this paper, an image processing program is used to extract the dynamic behavior characteristics of the droplet transition and the weld pool in high-speed photography. The influence of the current waveform on the arc pressure and the impact of the droplet is quantitatively analyzed with different parameters. The dynamic behavior of the weld pool and the microstructure under different current waveform conditions are further studied. The internal relation of current waveform parameters to weld pool behavior and weld microstructure was expounded. The results show that the droplet impact is positively correlated with the pulse peak current. The rectangular wave pulse has a more significant droplet impact than the exponential wave with the same waveform parameters. The impact of droplet transition on the weld pool enhances the convective intensity of the weld pool. It slows down the cooling rate of the solidified weld microstructure below the tail of the weld pool, increasing the grain size of the weld microstructure.

Accurate analysis of the spatial correlation effects, spatial aggregation patterns, and critical factors in the development of China’s digital economy is of great significance to the high-quality development of China’s economy. Based on the monthly data of “The Tencent Internet Plus” digital economy index for 31 provinces in China from 2018 to 2020, the non-linear Granger causality test and social network analysis were applied to reveal the spatial correlation effects of China’s digital economy. The quadratic assignment procedure (QAP) was used to empirically examine the factors influencing the formation of non-linear spatial association networks. The results show that the spatially linked relationships of the digital economy in 31 Chinese provinces exhibit a significant non-linear spatially correlated network structure. Block model analysis reveals that the development of the digital economy between the four major sectors is closely linked, and the national linkage effect is significant. The results of the secondary assignment procedure indicate that capital stock, information infrastructure, and geographical proximity have a significant positive impact on the formation of spatial linkages in the digital economy. In contrast, technological innovation has a significant negative impact.

At present, there are few studies on the epidemiology of diseases in wild Chinese white shrimp Penaeus chinensis. In order to enrich the epidemiological information of the World Organisation for Animal Health (WOAH)-listed and emerging diseases in wild P. chinensis, we collected a total of 37 wild P. chinensis from the Yellow Sea in the past three years and carried out molecular detection tests for eleven shrimp pathogens. The results showed that infectious hypodermal and hematopoietic necrosis virus (IHHNV), Decapod iridescent virus 1 (DIV1), yellow head virus genotype 8 (YHV-8), and oriental wenrivirus 1 (OWV1) could be detected in collected wild P. chinensis. Among them, the coexistence of IHHNV and DIV1 was confirmed using qPCR, PCR, and sequence analysis with pooled samples. The infection with YHV-8 and OWV1 in shrimp was studied using molecular diagnosis, phylogenetic analysis, and transmission electron microscopy. It is worth highlighting that this study revealed the high prevalence of coinfection with YHV-8 and OWV1 in wild P. chinensis populations and the transmission risk of these viruses between the wild and farmed P. chinensis populations. This study enriches the epidemiological information of WOAH-listed and emerging diseases in wild P. chinensis in the Yellow Sea and raises concerns about biosecurity issues related to wild shrimp resources.

Polyetheretherketone (PEEK) is a thermoplastic polymer that has been recently employed for bone tissue engineering as a result of its biocompatibility and mechanical properties being comparable to human bone. PEEK, however, is a bio-inert material and, when implanted, does not interact with the host tissues, resulting in poor integration. In this work, the surfaces of 3D-printed PEEK disks were functionalized with: (i) an adhesive peptide reproducing [351–359] h-Vitronectin sequence (HVP) and (ii) HVP retro-inverted dimer (D2HVP), that combines the bioactivity of the native sequence (HVP) with the stability toward proteolytic degradation. Both sequences were designed to be anchored to the polymer surface through specific covalent bonds via oxime chemistry. All functionalized PEEK samples were characterized by Water Contact Angle (WCA) measurements, Atomic Force Microscopy (AFM), and X-ray Photoelectron Spectroscopy (XPS) to confirm the peptide enrichment. The biological results showed that both peptides were able to increase cell proliferation at 3 and 21 days. D2HVP functionalized PEEK resulted in an enhanced proliferation across all time points investigated with higher calcium deposition and more elongated cell morphology.