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Graphlet counting is a widely explored problem in network analysis and has been successfully applied to a variety of applications in many domains, most notatbly bioinformatics, social science, and infrastructure network studies. Efficiently computing graphlet counts remains challenging due to the combinatorial explosion, where a naive enumeration algorithm needs O(Nk) time for k-node graphlets in a network of size N. Recently, many works introduced carefully designed combinatorial and sampling methods with encouraging results. However, the existing methods ignore the fact that graphlet counts and the graph structural information are correlated. They always consider a graph as a new input and repeat the tedious counting procedure on a regular basis even if it is similar or exactly isomorphic to previously studied graphs. This provides an opportunity to speed up the graphlet count estimation procedure by exploiting this correlation via learning methods. In this paper, we raise a novel graphlet count learning (GCL) problem: given a set of historical graphs with known graphlet counts, how to learn to estimate/predict graphlet count for unseen graphs coming from the same (or similar) underlying distribution. We develop a deep learning framework which contains two convolutional neural network models and a series of data preprocessing techniques to solve the GCL problem. Extensive experiments are conducted on three types of synthetic random graphs and three types of real-world graphs for all 3-, 4-, and 5-node graphlets to demonstrate the accuracy, efficiency, and generalizability of our framework. Compared with state-of-the-art exact/sampling methods, our framework shows great potential, which can offer up to two orders of magnitude speedup on synthetic graphs and achieve on par speed on real-world graphs with competitive accuracy.
The Order Spiriferinida spanning the latest Ordovician to Early Jurassic is a small group of brachiopods overshadowed by other taxon-rich clades during the Paleozoic. It diversified significantly after the end-Permian extinction and became one of the four major clades of Triassic brachiopods. However, the phylogeny and recovery dynamics of this clade during the Triassic still remain unknown. Here, we present a higher-level parsimony-based phylogenetic analysis of Mesozoic spiriferinids to reveal their evolutionary relationships. Ecologically related characters are analyzed to indicate the variances in ecomorphospace occupation and disparity of spiriferinids through the Permian–Triassic (P-Tr) transition. For comparison with potential competitors of the spiriferinids, the pre-extinction spiriferids are also included in the analysis. Phylogenetic trees demonstrate that about half of the Mesozoic families appeared during the Anisian, indicating the greatest phylogenetic diversification at that time. Triassic spiriferinids reoccupied a large part of the ecomorphospace released by its competitor spiriferids during the end-Permian extinction; they also fully exploited the cyrtiniform region and developed novel lifestyles. Ecomorphologic disparity of the spiriferinids dropped greatly in the Early Triassic, but it rebounded rapidly and reached the level attained by the pre-extinction spiriferids in the Late Triassic. The replacement in ecomorphospace occupation between spiriferids and spiriferinids during the P-Tr transition clearly indicates that the empty ecomorphospace released by the extinction of Permian spiriferids was one of the important drivers for the diversification of the Triassic spiriferinids. The Spiriferinida took over the empty ecomorphospace and had the opportunity to flourish.
In this paper, CNTs reinforced foam aluminum matrix composites with small pore diameter were prepared by powder metallurgy method. When the mass fraction of CNTs was 0.75%, the tensile strength, flexural strength and compressive yield strength of the materials were 3.4 times, 2.4 times and 2.4 times of pure foam aluminum, respectively, reaching the maximum value, which obviously improved the mechanical properties of aluminum foam. The tensile property model of foam aluminum matrix composites was built to predict the properties of the composites, and the effects of defects and reinforcement on the mechanical properties of the composites were compared. The results show that the tensile fitting is consistent with the measured results when the mass fraction of CNTs is less than 0.75%, but the weakening effect of defects on the strength of aluminum foam is much greater than the enhancement of CNTs. With the increase of CNTs mass fraction, the damping loss factor of foam aluminum composites increases, dislocation damping and grain boundary damping play a role in advance, and the damping peak moves to the low temperature region.
Major depressive disorder is characterized by a high risk of relapse. We aimed to compare the prophylactic effects of different antidepressant medicines (ADMs).
PubMed, Cochrane Central Register of Controlled Trials, Embase and the Web of Science were searched on 4 July 2019. A pooled analysis of parametric survival curves was performed using a Bayesian framework. The main outcomes were hazard ratios (HRs), relapse-free survival and mean relapse-free months.
Forty randomized controlled trials were included. The 1-year relapse-free survival for ADM (76%) was significantly better than that for placebo (56%). Most of the relapse difference (86.5%) occurred in the first 6 months. Most HRs were not constant over time. Proof of benefit after 6 months of follow-up was not established partially because of small differences between the drug and placebo after 6 months. Almost all studies used an ‘enriched’ randomized discontinuation design, which may explain the high relapse rates in the first 6 months after randomization.
The superiority of ADM v. placebo was mainly attributed to the difference in relapse rates that occurred in the first 6 months. Our analysis provided evidence that the prophylactic efficacy was not constant over time. A beneficial effect was observed, but the prevention of new episodes after 6 months was questionable. These findings may have implications for clinical practice.
Since December 2019, China has experienced a widespread outbreak of COVID-19. However, at the early stage of outbreak, investigations revealed a variety of patterns resulting in the transmission of COVID-19. Thus, it is essential to understand the transmission types and the potential for sustained human-to-human transmission. Moreover, the information regarding the characteristics of transmission helps in coordinating the current screening programme, and controlling and containing measures, and also, helps in deciding the appropriate quarantine duration. Thus, this investigation reports an outbreak of COVID-19 in a family residing in Wenzhou, Zhejiang, China during the month of January−February 2020.
This paper presents a soft robot which can imitate the crawling locomotion of an earthworm. Locomotion of the robot can be achieved by expanding and contracting the body that is made of flexible material. A link of the earthworm-like robot is combined with three modules, and a multi-cavity earthworm-like soft robot is combined with multiple links. The multiple links of the earthworm-like soft robot are fabricated by silicone in the three-dimensional printed customized molds. Experiments on a single module, two-links, and three-links show that the soft robot can move and bend on condition of modules extension and contraction in a specified gait. The development of the earthworm-like soft robot shows a great prospect in many complicated environments such as pipeline detection.
The isolation of male and female gametes is an effective method to study the fertilization mechanisms of higher plants. An osmotic shock method was used to rupture pollen grains of Allium tuberosum Roxb and release the pollen contents, including generative cells, which were mass collected. The pollinated styles were cut following 3 h of in vivo growth, and cultured in medium for 6–8 h, during which time pollen tubes grew out of the cut end of the style. After pollen tubes were transferred into a solution containing 6% mannitol, tubes burst and released pairs of sperm cells. Ovules of A. tuberosum were incubated in an enzyme solution for 30 min, and then dissected to remove the integuments. Following transfer to a dissecting solution free of enzymes, each nucellus was cut in the middle, and squeezed gently on the micropylar end, resulting in the liberation of the egg, zygote and proembryo from ovules at selected stages. These cells can be used to explore fertilization and embryonic development using molecular biological methods for each cell type and development stage.
Uranium–35 wt.% zirconium (U–35 wt.% Zr) alloy was annealed for 1 h and 24 h at 650 °C and characterized to understand the early-stage microstructure evolution. Dendritic microstructure with fine (∼300 nm in length) α-U precipitates clustered between dendrite branches were observed in the 1-h annealed sample. After 24-h annealing at 650 °C, the α-U precipitates coarsened, and the dendritic microstructure disappeared because of microstructure homogenization. Furthermore, microchemical homogenization observed with energy-dispersive X-ray spectroscopy analysis suggests that α-U precipitates are approaching thermodynamic equilibrium in the 24-h annealed sample. The findings from this study have potential impacts on the manufacturing and computer modeling of metallic nuclear fuel.
The pathophysiology of obsessive-compulsive disorder (OCD) remains unclear despite extensive neuroimaging work on the disorder. Exposure to medication and comorbid mental disorders can confound the results of OCD studies. The goal of this study was to explore differences in brain functional connectivity (FC) within the cortico-striato-thalamo-cortical (CSTC) loop of drug-naïve and drug-free OCD patients and healthy controls (HCs).
A total of 29 drug-naïve OCD patients, 22 drug-free OCD patients, and 25 HCs matched on age, gender and education level underwent functional magnetic resonance imaging scanning at resting state. Seed-based connectivity analyses were conducted among the three groups. The Yale Brown Obsessive Compulsive Scale and clinical inventories were used to assess the clinical symptoms.
Compared with HCs, the drug-naïve OCD patients had reduced FC within the limbic CSTC loop. In the drug-naïve OCD participants, we also found hyperconnectivity between the supplementary motor area and ventral and dorsal putamen (p < 0.05, corrected for multiple comparisons).
Exposure to antidepressants such as selective serotonin reuptake inhibitors may affect the function of some brain regions. Future longitudinal studies could help to reveal the pharmacotherapeutic mechanisms in these loops.
In this work, two types of zinc adipate β-nucleating agents, Adi-Zn(OH)2 (1:1) and Adi-ZnO (1:1), for polypropylene (PP) were prepared and their performances were evaluated and compared with commercial β-nucleating agent (named CNA). Results showed that Adi-Zn(OH)2 (1:1) was more effective in promoting PP to form β-crystals and improving the impact strength of PP in the range of nucleating agent addition (0–0.4 wt%). Based on these findings, the ratio of adipic acid to zinc hydroxide and the nonisothermal crystallization kinetics of the optimum ratio of adipic acid to zinc hydroxide were systematically studied; results showed that at 0.2 wt%, Adi-Zn(OH)2 (1:2), the nucleated PP displayed the highest impact strength, which was 2.6 times that of pure PP and 42% higher than that of CNA. Besides, Adi-Zn(OH)2 (1:2) could also afford to induce the formation of a high content of β-crystals and shorten the crystallization half time (t1/2) and accelerate the crystallization of PP.
l-Carnitine is essential for mitochondrial β-oxidation and has been used as a lipid-lowering feed additive in humans and farmed animals. d-Carnitine is an optical isomer of l-carnitine and dl-carnitine has been widely used in animal feeds. However, the functional differences between l- and d-carnitine are difficult to study because of the endogenous l-carnitine background. In the present study, we developed a low-carnitine Nile tilapia model by treating fish with a carnitine synthesis inhibitor, and used this model to investigate the functional differences between l- and d-carnitine in nutrient metabolism in fish. l- or d-carnitine (0·4 g/kg diet) was fed to the low-carnitine tilapia for 6 weeks. l-Carnitine feeding increased the acyl-carnitine concentration from 3522 to 10 822 ng/g and alleviated the lipid deposition from 15·89 to 11·97 % in the liver of low-carnitine tilapia. However, as compared with l-carnitine group, d-carnitine feeding reduced the acyl-carnitine concentration from 10 822 to 5482 ng/g, and increased lipid deposition from 11·97 to 20·21 % and the mRNA expression of the genes involved in β-oxidation and detoxification in the liver. d-Carnitine feeding also induced hepatic inflammation, oxidative stress and apoptosis. A metabolomic investigation further showed that d-carnitine feeding increased glycolysis, protein metabolism and activity of the tricarboxylic acid cycle and oxidative phosphorylation. Thus, l-carnitine can be physiologically utilised in fish, whereas d-carnitine is metabolised as a xenobiotic and induces lipotoxicity. d-Carnitine-fed fish demonstrates increases in peroxisomal β-oxidation, glycolysis and amino acid degradation to maintain energy homeostasis. Therefore, d-carnitine is not recommended for use in farmed animals.