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We introduce a new perfect sampling technique that can be applied to general Gibbs distributions and runs in linear time if the correlation decays faster than the neighborhood growth. In particular, in graphs with sub-exponential neighborhood growth like Z𝑑, our algorithm achieves linear running time as long as Gibbs sampling is rapidly mixing. As concrete applications, we obtain the currently best perfect samplers for colorings and for monomer-dimer models in such graphs.

We give a simple polynomial-time approximation algorithm for the total variation distance between two product distributions.

Self-supervised learning (SSL) has recently achieved promising performance for 3D medical image segmentation tasks. Most current methods follow existing SSL paradigm originally designed for photographic or natural images, which cannot explicitly and thoroughly exploit the intrinsic similar anatomical structures across varying medical images. This may in fact degrade the quality of learned deep representations by maximizing the similarity among features containing spatial misalignment information and different anatomical semantics. In this work, we propose a new self-supervised learning framework, namely Alice, that explicitly fulfills Anatomical invariance modeling and semantic alignment via elaborately combining discriminative and generative objectives. Alice introduces a new contrastive learning strategy which encourages the similarity between views that are diversely mined but with consistent high-level semantics, in order to learn invariant anatomical features. Moreover, we design a conditional anatomical feature alignment module to complement corrupted embeddings with globally matched semantics and inter-patch topology information, conditioned by the distribution of local image content, which permits to create better contrastive pairs. Our extensive quantitative experiments on two public 3D medical image segmentation benchmarks of FLARE 2022 and BTCV demonstrate and validate the performance superiority of Alice, surpassing the previous best SSL counterpart methods by 2.11% and 1.77% in Dice coefficients, respectively.

Supplementary Material 2

We present two approximate counting algorithms with $\widetilde{O}(n^{2-c}/\varepsilon^2)$ running time for some constant $c > 0$ and accuracy $\varepsilon$: (1) for the hard-core model when strong spatial mixing (SSM) is sufficiently fast; (2) for spin systems with SSM on planar graphs with quadratic growth, such as $\mathbb{Z}^2$. The latter algorithm also extends to (not necessarily planar) graphs with polynomial growth, such as $\mathbb{Z}^d$, albeit with a running time of the form $\widetilde{O}(n^2\varepsilon^{-2}/2^{c(\log n)^{1/d}})$ for some constant $c > 0$ and $d$ being the exponent of the polynomial growth. Our technique utilizes Weitz's self-avoiding walk tree (STOC, 2006) and the recent marginal sampler of Anand and Jerrum (SIAM J. Comput., 2022)., 18 pages, 3 figures

We investigate the gauge invariance of massive vector Kaluza-Klein (KK) modes in different brane models with two extra dimensions. We demonstrate that some additional constraint conditions on the geometry of branes are needed in order to get the gauge invariant effective action of the KK modes. Nevertheless, not all the conditions can be satisfied by the solutions of the branes, which will break the gauge invariance. Moreover, in the branes where the conditions can meet the brane solutions, we calculate mass spectra of vector and scalar KK modes, and the results show that when only one kind of scalar KK modes is found to be massive, the gauge invariance will also be broken., Comment: 14pages, 2 figures

Additional file 1:Supplementary Fig. 1. Flow chart of data analysis in this study. Supplementary Table 1. Parameters of two risk equations used in this study for men and women. Supplementary Table 2. Comparison of research objects between man and woman. Supplementary Table 3.1. Screening variable subsets based on Cox regression in man. Supplementary Table 3.2. Screening variable subsets based on Lasso-Cox regression in man. Supplementary Table 3.3. Screening variable subsets based on RSF in man. Supplementary Table 3.4. Screening variable subsets based on Cox regression in woman. Supplementary Table 3.5. Screening variable subsets based on Lasso-Cox regression in woman. Supplementary Table 3.6. Screening variable subsets based on RSF in woman. Supplementary Table 4. C statistic of different models on training and test sets.

Caspase-9 is the initiator caspase for the intrinsic apoptotic cell death pathway, and is critical to the activation of effector caspases during apoptosis, but how its levels and activities are maintained remains unclear. The gigantic Inhibitor of Apoptosis Protein (IAP) BIRC6/BRUCE/Apollon not only inhibits apoptosis, but also promotes ubiquitination of the key autophagic protein LC3 and inhibits autophagy. Here we show that BIRC6 forms an anti-parallel U-shaped dimer in a 3.6-Å cryo-EM structure with multiple previously unannotated domains, including a ubiquitin-like domain, and discover that the mitochondria-derived pro-apoptotic factor Smac/DIABLO binds BIRC6 by interacting with one BIR domain, two carbohydrate-binding modules and two helices in the central cavity. Notably, Smac outcompetes the effector caspase 3 and the pro-apoptotic protease HtrA2, but not caspase 9, for binding BIRC6. BIRC6 strongly inhibits cellular activity of caspase 9, but weakly suppresses that of caspase 3. Meanwhile, BIRC6 binds LC3 through an LC3-interacting region, probably following dimer disruption of this BIRC6 region. Deficiency in LC3 ubiquitination promotes autophagy and autophagic degradation of BIRC6, and inhibits apoptosis. Moreover, induction of autophagy promotes autophagic degradation of both procaspase-9 and active caspase-9, but not of effector caspases. These results are important to understand how the balance between apoptosis and autophagy is regulated under pathophysiological conditions.

Aim:To pilot study the therapeutic effect of dexmedetomidine-induced sleep balance treatment (DISBT) on the chronic refractory primary insomnia patients. Methods:Forty-two patients with chronic refractory primary insomnia were randomly divided into two groups by random number table. Patients in DISBT group were given DISBT for 3 days, while patients in the control group were given conventional treatment for 3 day. Pittsburgh sleep quality index (PSQI), the hyperarousal scale (HAS), and Hamilton anxiety scale (HAMA) were evaluated and compared between the pre-treatment and post-1-week-treatment. Sleep architecture and electroencephalogram (EEG) spectrum were also recorded and compared pre-treatment and post-treatment. Results:The scores of PSQI and HAMA in both groups after treatment were lower than those before treatment (P < 0.05), DISBT group-reduced degree were higher than those of the control group (P < 0.05). Sleep architecture of Stage 2 sleep proportion, EEG spectrum beta, and gamma relative power value in DISBT group were lower than those before treatment (P < 0.05), Stage 3 sleep proportion and delta relative power value were higher than those before treatment (P < 0.05); Sleep architecture of Stage 2 sleep proportion,beta, and gamma relative power value in control group were higher than those before treatment (P < 0.05); rapid eye movement sleep, Stage 3 sleep proportion, and delta relative power value were lower than those before treatment (P < 0.05). The total scores of the hyperarousal scale (HAS) in both groups after treatment were lower than those before treatment (P < 0.05), DISBT group-reduced degree were higher than those of the control group (P < 0.05), the extreme score, introspectiveness score, react score of HAS in control group after treatment had no statistical significance compared to those before treatment (P > 0.05), the extreme score, introspectiveness score, react score of HAS in DISBT group after treatment were lower than those before treatment (P < 0.05). Conclusion:DISBT effectively reduced the insomnia patient cortex hyperarousal level, corrected disorder of sleep-awakening pathways and easedup insomnia symptom. It is an effective method for chronic refractory primary insomnia.

Background and Objective: Although growing evidence indicates that non-alcoholic fatty liver disease is related to diabetic retinopathy (DR), research results significantly vary. Therefore, we conducted a meta-analysis to assess the association between the progression of non-alcoholic fatty liver disease and the onset of DR.Methods: PubMed, Embase, and Cochrane databases were searched until 7 November 2021. Combined odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the association.Results: We identified 18 studies involving 12,757 patients. The pooled effect assessment showed that liver fibrosis was positively correlated with DR (OR = 1.69, 95%CI 1.30–2.20; p < 0.0001); non-alcoholic fatty liver disease was not associated with the risk of DR (OR = 1.15, 95%CI 0.75-1.76; p = 0.51); non-alcoholic fatty liver disease was positively correlated with DR in patients with type 1 diabetes (OR = 2.96, 95%CI 1.48–5.94; p = 0.002). In patients with type 2 diabetes, there was no association between non-alcoholic fatty liver disease and DR (OR = 0.92, 95%CI 0.59–1.43; p = 0.70). Subgroup analysis showed no correlation in both Asian and Caucasian races.Conclusion: There is a significant correlation between liver fibrosis and DR. This suggests that the ocular examination of DR could be helpful in predicting whether patients with non-alcoholic fatty liver disease would progress to liver fibrosis.

IntroductionDiabetes mellitus (DM) and diabetic retinopathy (DR) increase the global burden. Since their pathogenesis is complex, it is necessary to use the biopsychosocial model to discover the most effective strategies. The study is aimed to investigate the psycho-behavioral factors of DR and confirm the discrepancies from previous studies.Research design and methodsThe study comprised seven cycles of cross-sectional data of the National Health and Nutrition Examination Survey (NHANES) from 2005–2006 to 2017–2018. Samples of DM were selected from this complex multi-stage probability sample and divided into the non-DR and DR groups, where 4,426 samples represented 18,990,825 individuals after weighting. This study comprehensively explored the biological, social, and psychological risk factors of DR, among which the biological factors included blood pressure, blood routine, HbA1c%, blood glucose, the duration of DM, family history, comorbidities, and treatment methods. Social aspects include gender, education, income, insurance, smoking, drinking, sleep habits, and recreational activities. The Patient Health Questionnaire-9 (PHQ-9) was used to assess the psychological state. Taylor series regression was used to examine the connection between factors and DR.ResultsMen accounted for 55.5% of the DR group (P = 0.0174). Lymphocyte count, insulin treatment, heart failure, stroke, liver condition, and renal failure showed significant differences in DR (P < 0.05). The incidence of depression in DR was 40.5%. Mild to moderate depression [odds ratio was associated with DR [(OR) = 1.37, 95% confidence interval (CI): 1.06–1.79], but there was no statistical difference in severe depression (OR = 1.34, 95% CI: 0.83–2.17). Although ≤ 6 h of sleep was associated with DR (OR = 1.38, 95% CI: 1.01–1.88), we found no statistical differences in alcohol consumption, recreational activities, or sedentary time between the two groups in our current study (P > 0.05).ConclusionsThe biological risk factors of DR are significant. It showed that stroke is associated with DR, and retinal exams have the potential value as a screening tool for the brain. Besides, psycho-behavioral risk factors of DR should also be paid attention. Our study highlights that mild and moderate depression and ≤6 h of sleep are distinguishably associated with DM complicated with DR. It indicates that psycho-behavioral risk factors confer a vital influence on diabetic health care and DR.

Cellulosic Juncus effusus fiber with porous structure, belonging to the carbohydrate polymers group, was chemically modified by a resin to form a cellulose-based adsorbent (FA–JE) for the removal of Disperse Red 3B dye. The structural characteristics and elemental changes of FA–JE were characterized by Fourier transform infrared spectroscopy and with an X-ray photoelectron spectrometer, while the morphology was observed via scanning electron microscopy. The pH, contact time, and adsorption temperature were investigated for optimal adsorption of disperse dyes. The adsorption of Disperse Red 3B dye by FA–JE was consistent with that observed by the Langmuir model. The maximum adsorption capacity of FA–JE was 103.95 mg/g, and the removal of disperse Red 3B dye was 99%. The data fitted well to pseudo-second-order kinetic model was followed. Thus, this natural cellulose-based adsorbent was determined to exhibit excellent performance for the removal of Disperse Red 3B dye.

In order to make better use of wool powder and explore the feasibility of replacing pigment with dyed wool powder, the dyeing behavior of wool powder was studied firstly. Then, we conducted a series of tests and analyses of the microcosmic structure and properties of powder before and after dyeing. BET test results revealed that the specific surface area of original powder was larger than that of dyed powder. TG and DMA tests indicated that the dyed powder had better thermal stability than the original powder. At last, the dyed wool powder and pigment were mixed and printed on cotton fabric. The dry/wet-rubbing fastness and moisture permeability of cotton fabric printed with dyed powder are better than those of cotton fabric printed with pigment. This indicates that the waste- wool fiber can be processed into applicable printing pigments, which is environmentally friendly and makes full use of natural resources.

The metal-support interfaces between metals and oxide supports have long been studied in catalytic applications, thanks to their significance in structural stability and efficient catalytic activity. The metal-rare earth oxide interface is particularly interesting because these early transition cations have high electrophilicity, and therefore good binding strength with Lewis basic molecules, such as H2O. Based on this feature, here we design a highly efficient composite Ni-Y2O3 catalyst, which forms abundant active Ni-NiOx-Y2O3 interfaces under the water-gas shift (WGS) reaction condition, achieving 140.6 μmolCO gcat−1 s−1 rate at 300 °C, which is the highest activity for Ni-based catalysts. A combination of theory and ex/in situ experimental study suggests that Y2O3 helps H2O dissociation at the Ni-NiOx-Y2O3 interfaces, promoting this rate limiting step in the WGS reaction. Construction of such new interfacial structure for molecules activation holds great promise in many catalytic systems.

Cotton fiber is a very rich natural polysaccharide material in nature, which is usually dyed with reactive dyes. However, a large number of salts remain in the dye bath waste, polluting the ecologi...

In order to figure out the redox conditions and paleo-sedimentary environment of the Middle Devonian shales in the northwest of Guizhong Depression, the trace element analysis was conducted on the Middle Devonian cores (320.35–938.50 m) of the typical shale gas investigation well (GY-1) at a 1.50 m sampling interval through X-ray fluorescence spectroscopy (XRF) and inductively coupled plasma mass spectrometry (ICP-MS). According to the test result, the average values of V/(V+Ni), V/Cr and Ni/Co in Nabiao formation (Fm.) are larger than 0.67, 4.65 and 7.71 respectively, and Nabiao Fm. is rich in biological assemblages such as tabasheer, ammonite, etc. These evidences indicate the rising sea level rose relatively in the sedimentation period of Nabiao Fm. and a deepwater shelf environment, which was favorable for the preservation of organic matters. The V/(V+Ni), V/Cr and Ni/Co in Luofu Fm. and Tangting Fm. are 0.38–0.65, 0.73–4.10 and 3.70–6.72 respectively, indicating that the sea level dropped relatively in their sedimentation period, during which the water bodies became shallow, and the sedimentary environment was a weak oxidizing shallow water shelf environment. In addition, the variation of TOC has a high correlation with the enrichment degree of Ba element, indicating the favorable conditions for the enrichment and preservation of organic matters under an oxygen-deficient environment. Moreover, according to the identification of trace element indexes, the northwest of Guizhong Depression experienced the sedimentary cycle of relative rise to relative fall of sea level from bottom to top in the Middle Devonian sedimentation period. The relative sea level rose to the highest in the sedimentation period of Nabiao Fm., in which the organic-rich shales with stable thickness and high organic content were deposited. Hence, the Nabiao Fm. could be regarded as the favorable exploration target interval in this area.

This paper presents a near-light photometric stereo method that faithfully preserves sharp depth edges in the 3D reconstruction. Unlike previous methods that rely on finite differentiation for approximating depth partial derivatives and surface normals, we introduce an analytically differentiable neural surface in near-light photometric stereo for avoiding differentiation errors at sharp depth edges, where the depth is represented as a neural function of the image coordinates. By further formulating the Lambertian albedo as a dependent variable resulting from the surface normal and depth, our method is insusceptible to inaccurate depth initialization. Experiments on both synthetic and real-world scenes demonstrate the effectiveness of our method for detailed shape recovery with edge preservation.

Supplemental Document 1

Multispectral photometric stereo(MPS) aims at recovering the surface normal of a scene from a single-shot multispectral image captured under multispectral illuminations. Existing MPS methods adopt the Lambertian reflectance model to make the problem tractable, but it greatly limits their application to real-world surfaces. In this paper, we propose a deep neural network named NeuralMPS to solve the MPS problem under general non-Lambertian spectral reflectances. Specifically, we present a spectral reflectance decomposition(SRD) model to disentangle the spectral reflectance into geometric components and spectral components. With this decomposition, we show that the MPS problem for surfaces with a uniform material is equivalent to the conventional photometric stereo(CPS) with unknown light intensities. In this way, NeuralMPS reduces the difficulty of the non-Lambertian MPS problem by leveraging the well-studied non-Lambertian CPS methods. Experiments on both synthetic and real-world scenes demonstrate the effectiveness of our method.

Critical scenario generation requires the ability of sampling critical combinations from the infinite parameter space in the logic scenario. Existing solutions aim to explore the correlation of action parameters in the initial scenario rather than action sequences. How to model action sequences so that one can further consider the effects of different action parameters in the scenario is the bottleneck of the problem. In this paper, we attack the problem by proposing the ECSAS framework. Specifically, we first propose a description language, BTScenario, allowing us to model action sequences of the scenarios. We then use reinforcement learning to search for combinations of critical action parameters. To increase efficiency, we further propose several optimizations, including action masking and replay buffer. We have implemented ECSAS, and experimental results show that it is more efficient than native approaches such as random and combination testing in various nontrivial scenarios.

Additional file 2: Supplement 2. Figure S1. Survival curve of cumulative incidence of CVDamong different WC groups. Figure S2. Survival curve of cumulative incidence of CVD among different eCRF groups.

Additional file 1: Supplement 1. Supplement Table1. Updated Framingham risk prediction model coefficients reestimated bygender.

To analyze the research hotspots and trends of traditional Chinese medicine(TCM) for neurogenesis with use of CiteSpace 5.7.R3 software. The bibliometrics analysis on the literatures of TCM for neurogenesis from 1987 to 2020 included in the CNKI database was conducted to visualize the number of papers, authors, institutions and keywords. Totally 736 literatures were included and the volume of annual publications showed an upward in volatility. At present, several stable research teams have been formed, which were represented by DING Fei, ZHOU Chong-jian and ZHOU Yong-hong, but the cooperation was not close among the teams. According to the analysis of research institutions, Institute of Diagnostics of Hunan University of Chinese Medicine and Acupuncture Research Center of Tianjin University of Traditional Chinese Medicine produced largest number of literatures. The cooperation among institutions, with universities of TCM and affiliated hospitals as the main research force, was characterized by dominant cooperation among regional institutions and less cross-regional cooperation. Keywords analysis showed that in the field of TCM for neurogenesis, a lot of studies mainly focused on the disease field, treatment and medication, TCM therapy and molecular mechanism. The research on TCM therapy and molecular mechanism for neurogenesis of central nervous system will be the research hotspots in future.

The metal-support interfaces between metals and oxide supports have long been studied in catalytic applications, thanks to their significance in structural stability and efficient catalytic activity. The metal-rare earth oxide interface is particularly interesting because these early transition cations have high electrophilicity, and therefore good binding strength with Lewis basic molecules, such as H

We theoretically investigated a second-order optomechanical-induced transparency (OMIT) process of a hybrid optomechanical system (COMS), which a Bose–Einstein condensate (BEC) in the presence of atom–atom interaction trapped inside a cavity with a moving end mirror. The advantage of this hybrid COMS over a bare COMS is that the frequency of the second mode is controlled by the s-wave scattering interaction. Based on the traditional linearization approximation, we derive analytical solutions for the output transmission intensity of the probe field and the dimensionless amplitude of the second-order sideband (SS). The numerical results show that the transmission intensity of the probe field and the dimensionless amplitude of the SS can be controlled by the s-wave scattering frequency. Furthermore, the control field intensities, the effective detuning, the effective coupling strength of the cavity field with the Bogoliubov mode are used to control the transmission intensity of the probe field and the dimensionless amplitude of the SS.

Background and Objective. Shennao Fuyuan Tang (SNFYT) is an effective herbal formula for ischemic stroke (IS). It has been in China for more than 20 years, but its effective biologically active components and underlying mechanisms remain to be elucidated. This study aimed to investigate the mechanism of action of SNFYT for the treatment of IS from both network pharmacology and molecular docking aspects. Methods. Screen the biologically active components and potential targets of SNFYT through Traditional Chinese Medicine Systems Pharmacology (TCMSP), Traditional Chinese Medicines Integrated Database (TCMID), and related literature. In addition, DrugBank, OMIM, DisGeNET, and the Therapeutic Target Database were searched to explore the therapeutic targets of IS. The cross-targets of SNFYT potential targets and IS treatment targets were taken as candidate gene targets, and GO and KEGG enrichment analyses were performed on the candidate targets. On this basis, the SNFYT-component-target network and protein-protein interaction (PPI) network were constructed using Cytoscape 3.7.2. Finally, AutoDock was used to verify the molecular docking of core components and core targets. Results. We screened out 95 potentially active components and 143 candidate targets. SNFYT-component-target network, PPI network, and Cytoscape analysis identified four core active ingredients and 14 core targets. GO enrichment analyzed 2333 biological processes, 79 cell components, and 149 molecular functions. There are 170 KEGG-related signal pathways P < 0.05 , including the IL-17 signal pathway, TNF signal pathway, and HIF-1 signal pathway. The molecular docking results of the core components and the core targets showed good binding power. Conclusions. SNFYT may achieve the effect of treating ischemic stroke through its anti-inflammatory effect through a signal pathway with core targets as the core.

A bacterial strain M05W1-28T was isolated from a well that collected water for irrigation from a deep aquifer at a depth of 400 m. Cells were observed to be rod-shaped, non-motile, aerobic, stained Gram-negative. Optimal growth was obtained at pH 7.0 (range: 6.0–9.0), 28 °C (range: 15–37 °C) and 0 % NaCl (range: 0–1.5 %, w/v) in modified tryptic soy broth (mTSB) without added NaCl and R2A. The cells were found to be positive for catalase and oxidase activities. The major fatty acids (>10 %) were identified as summed feature 3 (C16 : 1 ω7c / C16 : 1 ω6c) and iso-C15 : 0. The major polar lipids were phosphatidylethanolamine, glycolipid, phosphoglycolipids, phospholipids, and unidentified lipids. The major respiratory quinone was menaquinone-7 (MK-7). The genomic G+C content of strain M05W1-28T was 40.7 %. Based on similarities of 16S rRNA gene sequences, strain M05W1-28T was affiliated with the genus Sphingobacterium , exhibiting the highest sequence similarities with S. multivorum LMG 8342T (97.5 %), S. ginsenosidimutans THG07T (97.1 %) and less than 97.0 % to other members of the genus. The average nucleotide identity (ANI) and digital DNA–DNA hybridisation values (dDDH) between M05W1-28T and S. multivorum LMG 8342T were 78.1 and 22.5 %, respectively. Phenotypic characteristics including enzyme activities and carbon source utilisation differentiated the strain from other Sphingobacterium species. The phenotypic, chemotaxonomic and phylogenetic properties suggested that strain M05W1-28T represented a novel species within the genus Sphingobacterium , for which the name Sphingobacterium puteale sp. nov. is proposed. The type strain is M05W1-28T (=CGMCC 1.13711T=KCTC 72027T).

At present, most shale gas exploration and development areas in China are difficult to provide sufficient and effective production data to support economic evaluation, since they are still in the initial stage of low exploration level. In addition, ecological and environmental factors are not taken into account in the evaluation process, which does not meet the needs of green energy development of China. Aiming at above problems, the dynamic economic evaluation method of shale gas resources based on calculus principle is proposed. The Arps hyperbolic decreasing curve model will be used in the evaluation of single shale gas well production, which can evaluate single well production of shale gas by fitting the existing dynamic production data to generate the production decreasing curve. Therefore, the variation regularity of the cumulative production of single well shale gas within the study area can be obtained by the model mentioned above. According to the variation regularity of the cumulative production obtained from the Arps hyperbolic decreasing curve model, the recovery period of single well cost, ultimate economic life and the ultimate economic resource can be evaluated dynamically by analyzing the variation regularity of the cumulative sales revenue and cumulative input cost of single shale gas well. Then the evaluation result can be further extend to the whole evaluation areas, in order to analyze shale gas resources ’ economic value in evaluation regions under different shale gas price conditions. The results of the above evaluation methods are not only conducive to improving the economic benefits of relative shale gas development enterprises, but also provide a basis for the national energy strategy deployment. © 2019 China Geology Editorial Office.

The Sinian Doushantuo Formation is the oldest shale gas reservoir discovered in the world, which contains good shale gas shows as the Eyangye-1 and Zidi-1 wells in the Yichang Region of western Hubei province, China. The shales in the Doushantuo Formation feature considerable thickness (135 m), high gas content (4.83 m3/t) and high fragile mineral content (up to 75%). Due to the influences of the sedimentary environment, the shale reservoirs here have high dolomitic content (54%) and abruptly changes in vertical lithofacies. Moreover, the characteristics of the shale sweet-spot differ significantly from that in the Wufeng Formation and Longmaxi Formation in southeast Sichuan Basin. A high-resolution sequence stratigraphic correlation was performed on the shales of the Doushantuo Formation at the Eyangye-1 well, Zidi-1 well, Zidi-2 well and some outcrop profiles in Yichang area for the identification of their sedimentary microfacies characteristics. A comprehensive comparative analysis was made by incorporating the elemental geochemistry, wireline and mud logging data of the well to further identify the sweet-spot interval therein. With the analysis of Eyangye-1 well, the sweet-spot interval of the Doushantuo Formation is 3360−3408 m, of which sedimentary microfacies is deepwater reduced environment with many pyrite laminaes, and the TOC is high to 3.42%, the Ro is 3.3%, the organic and matrix pore are well developed and the aperture more than 50 nm, the porosity is 2.7%, the desorption gas content average is 2.16%, and the main mineral is dolomitic (54%) and siliceous quartz (21%). Additionally, these parameters combined with previous studies will shed light on evaluating and characterizing the layers therein, also provide referential geological data for the following exploration and development activities of this shale system.

Traditional cotton fiber dyeing requires an abundance of salt, which leads to environmental pollution. Consequently, decreasing or eliminating the use of salt has become the primary focus of current research. In this study, Crocein Orange G was used to dye carboxymethyl cotton. Carboxymethyl cotton has better color shades than raw cotton and it is used along with a mordant in a simultaneous-mordant dyeing process, at a pH of 7, Al2(SO4)3·18H2O as the mordant. In addition, it was found that the adsorption kinetics of carboxymethyl cotton followed a pseudo-second-order kinetic model. The equilibrium adsorption capacity increased as the temperature increased from 30 to 50 °C, and the maximum equilibrium adsorption was 8.21 mg g−1 at 50 °C. Furthermore, the adsorption isotherm data exhibited good agreement with the Freundlich isotherm. These results will help achieve salt-free dyeing of cotton fabric in the textile industry.

Based on the “SunWay TaihuLight” system, it designs high performance batch-processing algorithm of unstructured-grid discreted accessing memory, which is suitable for different application scenarios. This method uses coordinate preprocessing technology to improve the bandwidth utilization of the slave core on-chip array by establishing a grouped message queue model, and uses barrier-free data distribution technology to make full used of the network performance of the domestic heterogeneous many-core architecture. Through testing different types of applications and combining performance models and experimental results to verify, it is found that the average effective memory bandwidth utilization of the algorithm is more than 70% under different grid models and scales, which is an average of 10 times and the highest performance acceleration is of up to 45 times compared with the master-core serial algorithm. The test and analysis of the application in many different fields have proved the universality of the algorithm, and though a large number of experimental results show that the algorithm has good acceleration performance for different grid types and scales in different application fields.

Additional file 2 Fig. S1. Distribution of risk estimated from the PCE, PAR, and FRS among men and women.

We give a local-to-global principle for relative entropy contraction in simplicial complexes. This is similar to the local-to-global principle for variances obtained by Alev and Lau (2020)., Comment: v2: improved presentation, updated reference

Additional file 1 Table S1. Parameters of three risk equations used in this study for men and women. Table S2. Summary of risk factors and outcome of three risk equations used in this external validation study. Table S3. Net benefit analysis for preventing ASCVD at different thresholds of Pt after recalibration. Table S4. Net benefit analysis for preventing ASCVD at different thresholds of Pt before recalibration. Table S5. Comparisons of baseline characteristics between three risk equations and the study population.

In order to meet the requirement of frequent start-stop of the units, it is significant to optimize the operation scheme of the unit. A novel optimized mathematical model of a steam turbine was proposed at a previous paper of this study’s authors. In this study the supported vector machine (SVM) stress model of a 320 MW steam turbine was established based on 13 groups of start-up schemes. According to the novel optimized mathematical model and SVM stress model of the turbine, Genetic algorithm-particle swarm optimization was employed to search for the best values of the steam temperature rise rate. The optimization schedule can shorten the start-up time of 170 min in the premise of meeting the stress requirement. It is necessary to testify the feasibility of the optimized schedule, the fatigue, creep, and creep-fatigue life of the steam turbine rotor were analyzed by continuous damage mechanics (CDM) model. The results shown that the life assessment of the rotor from the nonlinear CDM is accordance with the bilinear failure criterion of ASME Section III, and the critical creep-fatigue damage of the rotor is 0.2083, and the life loss of the rotor after working 30 years under the optimized start-up schedule is 19.25%.

The ecological pattern research on urban forest landscape is the foundation and premise of urban forest system planning and urban ecological construction, as well as an important way of optimizing urban spatial structure, giving full play to urban forest ecological function and creating ecological and livable environment. Ecological pattern of urban forest landscape in built-up area of Ji'nan city was quantitatively analyzed and the corresponding optimization countermeasures were put forward through quantitative analysis and gradient analysis of the overall landscape ecological pattern by RS and GIS technology with 10 landscape indices at patch level and landscape level. The results showed that urban forest coverage rate in built-up areas was 15.8%. At the landscape level, the overall landscape ecological pattern of urban forest showed following patterns: relatively complete types of urban forest landscape patches, greater degree of landscape fragmentation, different area of various types of urban forest, large major patches, and highly connected same patch types. At the level of patch type, the ecological public welfare forest was dominated by large patches. The shape of scenic recreational forest was regular and dominated by large and medium patches. The shape of road forest and subsidiary forest was complex and dominated by small patches. The production and management forest was lacking. At the level of patch type, landscape recreational forest was the dominant type, ecological public welfare forest patch area was the largest, road forest and ancillary forest fragmentation was large. At the level of landscape, urban central forest landscape fragmentation was large, human interference was serious, and landscape shape was complex. Based on the analysis of the ecological pattern of urban forest landscape, we proposed the construction scheme of Ji'nan urban forest ecological network, which was "one ring, two networks, three four axes, and multi-point chessboard". Such scheme would help strengthen the connectivity of various types of urban forests and exert overall ecological benefits of large-scale ecosystems.城市森林景观生态格局研究不仅是城市森林系统规划与城市生态建设的基础和前提,而且是优化城市空间结构、充分发挥城市森林生态功能以及创建生态宜居环境的重要途径和手段.本研究以RS和GIS技术为支撑,通过总体景观生态格局定量分析和梯度分析等研究方法,采用10个景观指数从斑块水平和景观水平两方面,对济南市建成区城市森林景观生态格局进行定量分析,并提出优化对策.结果表明: 济南市建成区城市森林覆盖率为15.8%;城市森林总体景观生态格局在景观水平上表现为城市森林景观斑块类型较齐全、景观破碎化程度较大、各类型城市森林所占面积存在差异、以大斑块为主且同种斑块高度连接,在斑块类型水平上表现为生态公益林以大斑块为主且占优势地位、风景游憩林形状较规则且以大中型斑块为主、道路林及附属林形状复杂且以小斑块为主、生产经营林缺乏;在斑块类型水平上,以风景游憩林为主导类型、生态公益林斑块面积最大、道路林及附属林破碎度大,在景观水平上,城市中心森林景观破碎度大、人为干扰严重、景观形状复杂;在城市森林景观生态格局分析基础上,提出“一环二网、三片四轴、多点棋布”的济南市城市森林生态网络构建方案,从而加强各类型城市森林的连接度,发挥大尺度生态系统的整体生态效益.

This paper seeks to investigate the motivations of countries that participate in the One Belt and One Road (B&R) Initiative, a China-led economic development program with the intention of enhancing regional economic cooperation. We examine the income convergence hypothesis for B&R countries with both linear and nonlinear unit root tests to detect the presence of economic integration over the periods 1960–2016 and 1979–2016. For the B&R countries that are found to show income convergence to China in our income convergence testing, we argue that they tend to have a strong existing economic relationship with China. By contrast, the countries that have relatively weak economic relationships with China tend to show no convergence to China, and they take advantage of the B&R as an opportunity to catch up. Moreover, we find evidence that more countries converge to China’s real per capita income for the years after 1978 when China started its transition to a market economy and initiated the open-door policy to embrace globalization. The results suggest that China contributes to a higher degree of income convergence in regional integration.

It is reported that the response is dependent on its specific surface area, and the response/recovery rates are on the electron transfer channels. In this work, the authors have designed a type of fluffy hematite (α-Fe2O3) microtubes. Results indicate that these fluffy α-Fe2O3 microtubes are highly porous and composed of interconnected ultrafine nanorods. And the assembled gas sensors show a response of 16.8 to 100-ppm ethanol gas at 260 °C, the response time is of 2 s and the recovery time is of 25 s. Moreover, the sensors also show good gas selectivity and long-term stability.

Conventional cotton dyeing methods rely on high salt concentrations and consume large amounts of water. To decrease the ecological impact of the textile industry, the development of a green and sustainable dyeing method for cotton fibres is essential. In the present work, ethanol was used to reduce the amounts of salt and water required for cotton dyeing. Cotton yarns were pretreated with alkali and then dyed with six reactive dyes in a 90 : 10 (v/v) ethanol–water mixture. Using various techniques, including transmission electron microscopy, the effects of ethanol on the particle size and zeta potential of the reactive dyes were examined in detail. Compared with conventionally dyed samples, the cotton yarns dyed in the ethanol–water system using the investigated reactive dyes exhibited enhanced exhaustion, total fixation, and colour strength in the absence of salt. Industrial-scale cotton bobbins produced using the developed method showed commercially acceptable levelness and reproducibility. This method affords a substantial reduction in eutrophication potential and wastewater effluent load, which would considerably improve the environmental cost of cotton dyeing processes. This eco-friendly dyeing process has considerable potential for application to a broad range of natural fibres.

Optical resolution photoacoustic microscopy (ORPAM) is a promising tool for investigating anatomical and functional dynamics in the cerebral cortex. However, observation in freely moving mice has been a longstanding challenge for ORPAM. In this Letter, we extended ORPAM from anesthetized, head-restrained to awake, freely moving mice by using a detachable head-mounted ORPAM probe. We used a micro-electro-mechanical-system scanner and a miniaturized piezoelectric ultrasonic detector to scan the excitation laser beam and detect generated photoacoustic signals, respectively. The probe weighs 1.8 g and has a large field of view of ∼ 3 m m × 3 m m . We evaluated the performance of the probe by carrying out phantom experiments and the imaging of vascular networks in a mouse cerebral cortex. The results suggest that the ORPAM probe is capable of providing stable and high-quality ORPAM images in freely moving mice.

To investigate the formability of a T-shaped tube hydroforming by a three-stage punch shape, numerical simulations and experiments were utilized to analyze the three-stage punch shape effect on the branch height, the thickness distribution, the deformation behavior and the microstructure compared to the traditional punch. The results demonstrated that the branch height could be increased and the maximum thinning could be decreased by the three-stage punch shape without bursting, compared to the traditional punch. The stress and strain distributions for the T-shaped tube were changed due to the three-stage punch shape utilization, whereas an increased amount of material at the main tube zone was pushed into the branch zone. Also, the original grains could be refined significantly and homogeneously, in order for the hardness to be improved by 15% at region 3 by the three-stage punch shape. Consequently, the formability for the T-shaped tube hydroforming by the three-stage punch shape could be improved compared to the traditional punch.

A kind of novel ZnSnO 3 hollow polyhedrons with open nanoholes was synthesized via facile hydrothermal method and characterized by X-ray diffraction (XRD), energy dispersive X-Ray spectroscopy (EDX), scanning electronmicroscopy (SEM) and transmission electron microscopy (TEM) analyses. A possible formation mechanism of such microstructure was speculated. Moreover, the sensor based on these ZnSnO 3 hollow polyhedrons exhibited good gas sensing performance at 240 °C to 50 ppm acetone, and the response and recovery times were about 17 and 10 s, respectively. The significant decrease in optimal operating temperature and the ability of detecting low-concentration acetone gas were attributed to the unique structure of the products which possessed hollow interior and good-permeation surface.

Cotton fiber is a natural polysaccharide material with excellent properties, which is widely used in textile industry. However, the poor ultraviolet (UV) protection and electrical conductivity limit its application in other fields. In this study, reduced graphene oxide (rGO) loaded carboxymethyl cotton fabrics were prepared by layer-by-layer (LBL) self-assembly technique. The structure and surface morphology of the fabrics were studied by K/S value, scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR). Furthermore, the electrical conductivity, thermal properties, light absorption properties and UV protection properties of rGO-loaded carboxymethyl cotton fabrics were also studied. The results indicated that rGO-loaded fabrics possessed excellent electrical conductivity, UV protection properties and high light absorption. In addition, washing durability of rGO-loaded carboxymethyl cotton fabric is very good. This technique provides a simple method for people to prepare multifunctional cotton fabrics.

Computed tomography (CT) can provide a 3D view of the patient's internal organs, facilitating disease diagnosis, but it incurs more radiation dose to a patient and a CT scanner is much more cost prohibitive than an X-ray machine too. Traditional CT reconstruction methods require hundreds of X-ray projections through a full rotational scan of the body, which cannot be performed on a typical X-ray machine. In this work, we propose to reconstruct CT from two orthogonal X-rays using the generative adversarial network (GAN) framework. A specially designed generator network is exploited to increase data dimension from 2D (X-rays) to 3D (CT), which is not addressed in previous research of GAN. A novel feature fusion method is proposed to combine information from two X-rays. The mean squared error (MSE) loss and adversarial loss are combined to train the generator, resulting in a high-quality CT volume both visually and quantitatively. Extensive experiments on a publicly available chest CT dataset demonstrate the effectiveness of the proposed method. It could be a nice enhancement of a low-cost X-ray machine to provide physicians a CT-like 3D volume in several niche applications.

In this paper, a matter-element extenics method is adopted to combine the information of each layer and each eigenvalue, so as to realize the evaluation of the current state of switch cabinet. The calculation of correlation degree is improved in the traditional matter-element extenics method. And the actual evaluation effect is optimized. This paper illustrates the evaluation process with practical examples, and compares the current evaluation results with the actual status of switch cabinets and the evaluation results obtained by traditional matter-element extension method. They proved the advance and effectiveness of the proposed method.