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Abstract Background Although multiple measures of blood pressure variability (BPV) have been proposed, whether they are better than mean blood pressure in predicting target organs is unclear. We aimed to determine the relationship between short term BPV and target organ injury. Methods This study was a retrospective study, and 635 inpatients in the Department of Cardiology from 2015 to 2020 were selected. We divided participants into four groups on the basis of the quartiles of BPV. One‐way analysis of variance was used to compare the differences between the groups, and linear regression was used to analyze the relationship between BPV and target organ damage. Results The average age of 635 patients was 74.36 ± 6.50 years old. Among them, 354 of 627 patients had diminished renal function (56.5%), 221of 604 patients had associated left ventricular hypertrophy (36.6%), and 227 of 231 patients had carotid plaque formation (98.3%). The baseline data indicated significant differences in fasting glucose, total cholesterol, low‐density lipoprotein, creatinine, glomerular filtration rate, sex, calcium channel blocker use, and the rate of diminished renal function. Multiple linear regression analysis showed that BPV was negatively correlated with renal injury (creatinine: r = 0.306, p

In this paper, we introduce WindFormer, an innovative transformer-based model engineered for short-term wind speed forecasting, leveraging multivariate time series data. Unlike traditional approaches, WindFormer excels in processing diverse meteorological features—temperature, humidity, and power—to intricately map their spatiotemporal interdependencies with wind speeds. Utilizing a novel unsupervised pre-training strategy, WindFormer initially learns from vast volumes of unlabeled data to capture generalized feature representations. This foundation enhances the subsequent fine-tuning phase on labeled wind speed data, in which our model demonstrates exceptional predictive accuracy. Empirical evaluations across various public datasets illustrate that WindFormer markedly surpasses both conventional statistical models and contemporary deep learning techniques. The model not only achieves superior accuracy in forecasting wind speeds but also reveals a significant enhancement in handling complex spatiotemporal data dynamics. These advancements facilitate more effective wind farm management and power grid scheduling, making a substantial impact on operational efficiencies and renewable energy utilization. Our findings confirm the robustness of WindFormer in a real-world setting, underscoring its potential as a pivotal tool in meteorological and energy sectors. The integration of unsupervised pre-training with multi-task fine-tuning establishes a new benchmark for short-term wind speed prediction.

Abstract The advent of immunotherapy, a groundbreaking advancement in cancer treatment, has given rise to the prominence of the tumor microenvironment (TME) as a critical area of research. The clinical implications of an improved understanding of the TME are significant and far-reaching. Radiomics has been increasingly utilized in the comprehensive assessment of the TME and cancer prognosis. Similarly, the advancement of pathomics, which is based on pathological images, can offer additional insights into the panoramic view and microscopic information of tumors. The combination of pathomics and radiomics has revolutionized the concept of a “digital biopsy”. As genomics and transcriptomics continue to evolve, integrating radiomics with genomic and transcriptomic datasets can offer further insights into tumor and microenvironment heterogeneity and establish correlations with biological significance. Therefore, the synergistic analysis of digital image features (radiomics, pathomics) and genetic phenotypes (genomics) can comprehensively decode and characterize the heterogeneity of the TME as well as predict cancer prognosis. This review presents a comprehensive summary of the research on important radiomics biomarkers for predicting the TME, emphasizing the interplay between radiomics, genomics, transcriptomics, and pathomics, as well as the application of multiomics in decoding the TME and predicting cancer prognosis. Finally, we discuss the challenges and opportunities in multiomics research. In conclusion, this review highlights the crucial role of radiomics and multiomics associations in the assessment of the TME and cancer prognosis. The combined analysis of radiomics, pathomics, genomics, and transcriptomics is a promising research direction with substantial research significance and value for comprehensive TME evaluation and cancer prognosis assessment.

In this paper, we propose an improved Nested Error Regression model in which the random effects for each area are given a prior distribution using the Poisson–Dirichlet Process. Based on this model, we mainly investigate the construction of the parameter estimation using the Empirical Bayesian(EB) estimation method, and we adopt various methods such as the Maximum Likelihood Estimation(MLE) method and the Markov chain Monte Carlo algorithm to solve the model parameter estimation jointly. The viability of the model is verified using numerical simulation, and the proposed model is applied to an actual small area estimation problem. Compared to the conventional normal random effects linear model, the proposed model is more accurate for the estimation of complex real-world application data, which makes it suitable for a broader range of application contexts.

The flow around two tandem circular cylinders in proximity to a wall is investigated using particle image velocimetry (PIV) for Re = 2 × 103. The spacing ratios L/D are 1, 2, and 5, and the gap ratios G/D are 0.3, 0.6, and 1. The proper orthogonal decomposition (POD) method and λci vortex identification method are used to investigate the evolution of flow structure, and the influences of L/D and G/D on flow physics are shown. At L/D = 2 and G/D = 0.3, a “pairing” process occurs between the wall shear layer and the upstream cylinder’s lower shear layer, resulting in a small separation bubble behind the upstream cylinder. At L/D = 1, the Strouhal number (St) increases with decreasing G/D. At three gap ratios, the St gradually decreases as L/D increases. At G/D = 0.3, there is nearly a 49.98% decrease from St = 0.3295 at L/D = 1 to St = 0.1648 at L/D = 5, which is larger than the reductions in cases of G/D = 0.6 and G/D = 1. The effects of L/D on the evolution of flow structure at G/D = 0.6 are revealed in detail. At L/D = 1, the vortex shedding resembles that of the single cylinder. As L/D increases to 2, a squarish flow structure is formed between two cylinders, and a small secondary vortex is formed due to induction of the lower shear layer of the upstream cylinder. At L/D = 5, there is a vortex merging process between the upper wake vortices of the upstream and downstream cylinders, and the lower wake vortex of the upstream cylinder directly impinges the downstream cylinder. In addition, the shear layers and wake vortices of the upstream cylinder interact with the wake of the downstream cylinder as L/D increases, resulting in reductions in velocity fluctuations, and the production and turbulent diffusion of turbulent kinetic energy are decreased behind the downstream cylinder.

Abstract Current non-invasive prenatal screening (NIPS) analyzes circulating fetal cell-free DNA (cfDNA) in maternal peripheral blood for selected aneuploidies or microdeletion/duplication syndromes. Many genetic disorders are refractory to NIPS largely because the maternal genetic material constitutes most of the total cfDNA present in the maternal plasma, which hinders the detection of fetus-specific genetic variants. Here, we developed an innovative sequencing method, termed coordinative allele-aware target enrichment sequencing (COATE-seq), followed by multidimensional genomic analyses of sequencing read depth, allelic fraction, and linked single nucleotide polymorphisms, to accurately separate the fetal genome from the maternal background. Analytical confounders including multiple gestations, maternal copy number variations, and absence of heterozygosity were successfully recognized and precluded for fetal variant analyses. In addition, fetus-specific genomic characteristics, including the cfDNA fragment length, meiotic error origins, meiotic recombination, and recombination breakpoints were identified which reinforced the fetal variant assessment. In 1129 qualified pregnancies tested, 54 fetal aneuploidies, 8 microdeletions/microduplications, and 8 monogenic variants were detected with 100% sensitivity and 99.3% specificity. Using the comprehensive cfDNA genomic analysis tools developed, we found that 60.3% of aneuploidy samples had aberrant meiotic recombination providing important insights into the mechanism underlying meiotic nondisjunctions. Altogether, we show that the genetic deconvolution of the fetal and maternal cfDNA enables thorough and accurate delineation of fetal genome which paves the way for the next-generation prenatal screening of essentially all types of human genetic disorders.

The polysaccharides from Stemona tuberosa Lour, a kind of plant used in Chinese herbal medicine, have various pharmacological activities, such as anti-inflammatory and antioxidant properties. However, the effects of the extraction methods and the activity of polysaccharides from different parts are still unknown. Therefore, this study aimed to evaluate the effects of different extraction methods on the yields, chemical compositions, and bioactivity of polysaccharides extracted from different parts of Stemona tuberosa Lour. Six polysaccharides were extracted from the leaves, roots, and stems of Stemona tuberosa Lour through the use of hot water (i.e., SPS-L1, SPS-R1, and SPS-S1) and an ultrasound-assisted method (i.e., SPS-L2, SPS-R2, and SPS-S2). The results showed that the physicochemical properties, structural properties, and biological activity of the polysaccharides varied with the extraction methods and parts. SPS-R1 and SPS-R2 had higher extraction yields and total sugar contents than those of the other SPSs (SPS-L1, SPS-L2, SPS-S1, and SPS-S2). SPS-L1 had favorable antioxidant activity and the ability to downregulate MUC5AC expression. An investigation of the anti-inflammatory properties showed that SPS-R1 and SPS-R2 had greater anti-inflammatory activities, while SPS-R2 demonstrated the strongest anti-inflammatory potential. The results of this study indicated that SPS-L1 and SPS-L2, which were extracted from non-medicinal parts, may serve as potent natural antioxidants, but further study is necessary to explore their potential applications in the treatment of diseases. The positive anti-inflammatory effects of SPS-R1 and SPS-R2 in the roots may be further exploited in drugs for the treatment of inflammation.

With the rise of online social media, users from across the world can participate in opinion formation processes, and some discussions lead to controversial debates around this phenomenon. Controversy detection in social media can help explore public discourse spaces and understand topical issues. Previous controversial detection studies focus more on identifying the opinion or emotional orientation of a comment, while we focus on whether there is a controversial relationship between a comment and its replies. Here, we collect a dataset consisting of 511 news articles, 103,787 comments, and 71,579 users on the Chinese social media platform, Toutiao, and we study the controversial interactions on the subsets of this dataset. Our approach treats news, comments, and users as different types of nodes and constructs multiplex networks connected by user–comment links (i.e., publishing relationship), comment–news links (i.e., comment relationship), and comment–comment links (i.e., replying relationship). Furthermore, we propose a model based on deep learning to detect controversial interactions from these multiplex networks. Our supervised model achieves 83.24% accuracy, with an improvement compared to competitive models. Moreover, we illustrate the applicability of our approach using different ratios of training and testing sets. Our results demonstrate the usefulness of the multiplex networks model for controversial interaction detection and provide a new perspective on controversy detection problems.

Abstract Background Increasing evidence suggests that human gut microbiome plays an important role in variation of skeletal muscle mass (SMM). However, specific causal mechanistic relationship of human gut microbiome with SMM remains largely unresolved. Understanding the causal mechanistic relationship may provide a basis for novel interventions for loss of SMM. This study investigated whether human gut microbiome has a causal effect on SMM among Chinese community‐dwelling healthy menopausal women. Methods Estimated SMM was derived from whole‐body dual‐energy X‐ray absorptiometry. We performed integrated analyses on whole‐genome sequencing, shotgun metagenomic sequencing, and serum short‐chain fatty acids (SCFAs), as well as available host SMM measurements among community‐dwelling healthy menopausal women (N = 482). We combined the results with summary statistics from genome‐wide association analyses for human gut microbiome (N = 952) and SMM traits (N = 28 330). As a prerequisite for causality, we used a computational protocol that was proposed to measure correlations among gut metagenome, metabolome, and the host trait to investigate the relationship between human gut microbiome and SMM. Causal inference methods were applied to assess the potential causal effects of gut microbial features on SMM, through one‐sample and two‐sample Mendelian randomization (MR) analyses, respectively. Results In metagenomic association analyses, the increased capacity for gut microbial synthesis of the SCFA butyrate was significantly associated with serum butyrate levels [Spearman correlation coefficient (SCC) = 0.13, P = 0.02] and skeletal muscle index (SCC = 0.084, P = 0.002). Of interest was the finding that two main butyrate‐producing bacterial species were both positively associated with the increased capacity for gut microbial synthesis of butyrate [Faecalibacterium prausnitzii (SCC = 0.25, P = 6.6 × 10−7) and Butyricimonas virosa (SCC = 0.15, P = 0.001)] and for skeletal muscle index [F. prausnitzii (SCC = 0.16, P = 6.2 × 10−4) and B. virosa (SCC = 0.17, P = 2.4 × 10−4)]. One‐sample MR results showed a causal effect between gut microbial synthesis of the SCFA butyrate and appendicular lean mass (β = 0.04, 95% confidence interval 0.029 to 0.051, P = 0.003). Two‐sample MR results further confirmed the causal effect between gut microbial synthesis of the SCFA butyrate and appendicular lean mass (β = 0.06, 95% confidence interval 0 to 0.13, P = 0.06). Conclusions Our results may help the future development of novel intervention approaches for preventing or alleviating loss of SMM.

Oral ulcer is a common inflammatory disease of oral mucosa, causing severe burning pain and great inconvenience to daily life. In this study, compound 3J with anti-inflammatory activity was synthesized beforehand. Following that, an intelligent composite hydrogel supported 3J was designed with sodium alginate, carboxymethyl chitosan, and chitosan quaternary ammonium salt as the skeleton, and its therapeutic effect on the rat oral ulcer model was investigated. The results show that the composite hydrogel has a dense honeycomb structure, which is conducive to drug loading and wound ventilation, and has biodegradability. It has certain antibacterial effects and good anti-inflammatory activity. When loaded with 3J, it reduced levels of TNF-α and IL-6 in inflammatory cells by up to 50.0%. It has excellent swelling and water retention properties, with a swelling rate of up to 765.0% in a pH 8.5 environment. The existence of a large number of quaternary ammonium groups, carboxyl groups, and hydroxyl groups makes it show obvious differences in swelling in different pH environments, which proves that it has double pH sensitivity. It is beneficial to adapt to the highly dynamic changes of the oral environment. Compared with single hydrogel or drug treatment, the drug-loaded hydrogel has a better effect on the treatment of oral ulcers.

Abstract Background To examine the value of energetic-spectrum computed tomography (spectral CT) quantitative parameters in renal cell carcinoma (RCC) microvascular angiogenesis. Methods The authors evaluated 32 patients with pathologically confirmed RCC who underwent triple-phase contrast-enhanced CT with spectral CT imaging mode from January 2017 to December 2019. Quantitative parameters include parameters derived from iodine concentration (IC) and water concentration (WC) of 120 keV monochromatic images. All specimens were evaluated including the microvascular density (MVD), microvascular area (MVA) and so on. The correlation between IC and WC (including average values and random values) with microvascular parameters were analyzed with Pearson or Spearman rank correlation coefficients. Results The MVD of all tumors was 26.00 (15.00–43.75) vessels per field at × 400 magnification. The MVD of RCC correlated positively with the mean IC, mean WC, mean NWC, mean NIC, random IC, random NIC in renal cortical phase, WCD1, WCD2, NWCD2 and ICD1 (Spearman rank correlation coefficients, r range, 0.362–0.533; all p

Few previous studies have investigated the relationship between global perspective (GP) and willingness to communicate (WTC) in English. Hence, more studies are needed to validate their correlation. Furthermore, hardly any pertaining studies have been conducted at English Medium Instruction (EMI) universities. As such, the current study aimed to fill these gaps in the context of an EMI university in China, by investigating whether GP correlates with second language (L2) WTC and what factors impact the two variables. Data were collected from students via an online questionnaire (n = 315) and follow-up interviews (n = 11). The questionnaire findings confirmed a moderate positive correlation between GP and L2 WTC. The interview data unraveled that several factors influenced students’ L2 WTC, including needs and motivations driving L2 WTC, concerns constraining L2 WTC, and intercultural cognition facilitating L2 WTC. These findings suggest that: (A) students could be more determined to practice their English if they realize the significance of the role of English in their life; (B) teachers could foster students’ WTC by creating a non-threatening English-speaking environment and encouraging students to communicate in English in and outside the classroom; and (C) teachers could educate students about GP and L2 WTC, which might help to expand students’ horizon and stimulate their interests in foreign cultures and global affairs, so as to facilitate the sustainable growth of their English learning.

The flow characteristics and vortex evolution behind a circular cylinder near a wavy wall are studied using a large-eddy simulation framework. The Reynolds number based on the cylinder diameter D is ReD = 1500, the gap ratio G/D is fixed to 1, and the slope S = λ/2k varies from 2 to 8 (where G is the distance between the lower surface of the cylinder and the crest, λ is the wavelength, and k is the wave amplitude). The flow field characteristics, hydrodynamic coefficients, pressure distributions, vortex evolution, and three-dimensional flow features are presented and discussed. The phase of the flow field is determined by proper orthogonal decomposition, and the vortex identification method is applied to capture vortex structures. Compared with a smooth wall, the wavy wall changes the pressure distribution of the flow field and decreases (increases) the mean drag (lift) coefficient. As the wall amplitude increases, the Strouhal number increases slightly, attaining values of 0.25 for S = 8, 0.25 for S = 4, and 0.26 for S = 2. The wall pressure coefficient has an approximately periodic distribution, while the wall friction coefficient varies according to the evolution of secondary vortices on the wall. Two small secondary vortices appear either side of the crest before merging into a new secondary vortex that moves downstream with the upper and lower wake vortices. The energy of the first two modes obtained by proper orthogonal decomposition decreases compared with the smooth-wall case, whereas that of the third and fourth modes increases, reflecting the greater large-scale vortex structures between the wavy walls. This is confirmed by examining the instantaneous three-dimensional vortex structures using the Q-criterion.

As a common-used pothole repairing material, cold mix patching asphalt (CMA) has been widely used in practice. This article aims to develop a novel CMA with good overall performance and better environmental-friendliness. A few environmental-friendly ingredients, including a modifier named Usual-temperature Synthetic Pitch (USP), polyester-basalt composite fibers, a commercial anti-stripping agent, a commercial tackifier and biodiesel, were utilized for preparing Fiber-reinforced USP modified CMAs (FUAs). Laboratory tests, including workability assessment tests, Marshall stability tests, boiling water tests, rolling sieve cohesion tests, freeze-thaw splitting tests, wheel tracking tests and three-point bending tests, etc. were conducted to evaluate the workability, Marshall stability, adhesion, moisture susceptibility, rutting resistance, bending resistance and storage stability. Two mix designs of the cutback (termed as Scheme 1 and 2) with weight ratios of 100:6:18:0.3:0.6 and 100:6:20:0.4:0.8 for binder: USP: biodiesel: anti-stripping agent: tackifier were considered. Effect of fiber content (0.2%, 0.3%, 0.4% and 0.5% by aggregate weight) was also investigated considering an optimal polyester to basalt fiber weight ratio of 3:2. The results show that the optimal fiber content is 0.4%. The engineering properties of FUAs meet the construction requirements, and they also present good storage stability. Scheme 2-based cutback shows better workability, smaller penetration and better binder-aggregate adhesion than the Scheme 1-based cutback; consequently, the Scheme 2-based FUA presents advantages over Marshall stability, rutting resistance and bending resistance. Compared with Styrene-Butadiene-Styrene (SBS) modified CMAs, FUAs possess better overall performance and advantages over environmental conservation. The FUAs, therefore, have good application prospects in pavement repair.

Turbulent channel flows around a wall-mounted hemisphere numerically are investigated by large eddy simulation, and the Reynolds number based on the hemisphere’s diameter is 3 × 104. The statistical characteristics and turbulent structure evolution are revealed in the Eulerian frameworks and Lagrangian frameworks. The vortex identification and Dynamic Mode Decomposition (DMD) are used to study the evolution of turbulent structure in the Eulerian frameworks, and the finite-time Lyapunov exponents are applied to identify Lagrangian coherent structures (LCS) in the Lagrangian framework. It is found that the developing angle of the hairpin vortex is ∼7° at two frameworks. What is more, there are some hairpin vortices formed behind the hemisphere and some turbulent structures formed near the wall by DMD method. The correlation analysis is applied to investigate the angle variation and scale variation of turbulent structures, and it is observed that the angle of turbulent structures is negative at Y/d ≥ 1.2 and the spanwise length scales of turbulent structures increase as it moves downstream. By studying the LCS behind a wall-mounted hemisphere, there is formation of “kink” caused by viscous interaction between some hairpin vortex legs, which is the characteristic of hairpin vortex deformation. The comparisons of statistical characteristics between Eulerian frameworks and Lagrangian frameworks are conducted by the correlation analysis, the spectrum analysis, and the structure functions.

Generative adversarial networks and variational autoencoders (VAEs) provide impressive image generation from Gaussian white noise, but both are difficult to train, since they need a generator (or encoder) and a discriminator (or decoder) to be trained simultaneously, which can easily lead to unstable training. To solve or alleviate these synchronous training problems of generative adversarial networks (GANs) and VAEs, researchers recently proposed generative scattering networks (GSNs), which use wavelet scattering networks (ScatNets) as the encoder to obtain features (or ScatNet embeddings) and convolutional neural networks (CNNs) as the decoder to generate an image. The advantage of GSNs is that the parameters of ScatNets do not need to be learned, while the disadvantage of GSNs is that their ability to obtain representations of ScatNets is slightly weaker than that of CNNs. In addition, the dimensionality reduction method of principal component analysis (PCA) can easily lead to overfitting in the training of GSNs and, therefore, affect the quality of generated images in the testing process. To further improve the quality of generated images while keeping the advantages of GSNs, this study proposes generative fractional scattering networks (GFRSNs), which use more expressive fractional wavelet scattering networks (FrScatNets), instead of ScatNets as the encoder to obtain features (or FrScatNet embeddings) and use similar CNNs of GSNs as the decoder to generate an image. Additionally, this study develops a new dimensionality reduction method named feature-map fusion (FMF) instead of performing PCA to better retain the information of FrScatNets,; it also discusses the effect of image fusion on the quality of the generated image. The experimental results obtained on the CIFAR-10 and CelebA datasets show that the proposed GFRSNs can lead to better generated images than the original GSNs on testing datasets. The experimental results of the proposed GFRSNs with deep convolutional GAN (DCGAN), progressive GAN (PGAN), and CycleGAN are also given.

Background: Recently, single-cell RNA sequencing (scRNA-seq) technology was increasingly used to study transcriptomics at a single-cell resolution, scRNA-seq analysis was complicated by the “dropout”, where the data only captures a small fraction of the transcriptome. This phenomenon can lead to the fact that the actual expressed transcript may not be detected. We previously performed osteoblast subtypes classification and dissection on freshly isolated human osteoblasts. Materials and Methods: Here, we used the scImpute method to impute the missing values of dropout genes from a scRNA-seq dataset generated on freshly isolated human osteoblasts. Results: Based on the imputed gene expression patterns, we discovered three new osteoblast subtypes. Specifically, these newfound osteoblast subtypes are osteoblast progenitors, and two undetermined osteoblasts. Osteoblast progenitors showed significantly high expression of proliferation related genes (FOS, JUN, JUNB and JUND). Analysis of each subtype showed that in addition to bone formation, these undetermined osteoblasts may involve osteoclast and adipocyte differentiation and have the potential function of regulate immune activation. Conclusions: Our findings provided a new perspective for studying the osteoblast heterogeneity and potential biological functions of these freshly isolated human osteoblasts at the single-cell level, which provides further insight into osteoblasts subtypes under various (pathological) physiological conditions.

To study the mechanical characteristics of the disintegrated carbonaceous mudstone (DCM), consolidated drained triaxial tests were conducted on the DCM with three degrees of compaction (i.e., 90%, 93%, and 96%). Then, the nonlinear constitutive model suitable for the DCM was established based on test results using a logarithmic function. The stress-strain characteristics of the DCM were analyzed. The results revealed that the axial strain of the DCM was positively correlated with the deviatoric stress and lateral strain. The slopes of deviatoric stress-axial strain curves decreased with the increase of axial strain and so did the slopes of the axial strain-volumetric strain curves. The strength of the DCM increased with the increase of the confining pressure and the degree of compaction. In addition, the axial strain induced by dilatancy was also positively correlated with the degree of compaction and the confining pressure. Furthermore, under triaxial loading conditions, the relationship between the stress and strain of the DCM can be expressed by a logarithmic function; based on this, a nonlinear constitutive model with ten material parameters was derived. In addition, the results of numerical tests using the model showed similar stress-strain characteristics of the DCM comparing with the triaxial tests. Hence, it indicated that the nonlinear constitutive model based on the logarithmic function can reflect the nonlinear stress-strain characteristics of the DCM.

Accurate wind speed prediction is a premise that guarantees the reliable operation of the power grid. This study presents a combined prediction model that integrates data preprocessing, cascade optimization, and deep learning prediction to improve prediction performance. In data preprocessing, the wavelet soft threshold denoising (WSTD) is employed to filter the blurring noise of the original data. Then, the robust empirical mode decomposition (REMD) and adaptive variational mode decomposition (AVMD) are adopted to carry out a two-stage adaptive decomposition. Spearman correlation is used to quantify the mode that need to be decomposed for the second time. In the cascade optimization, the hybrid grey wolf algorithm (HGWO) is employed to optimize the parameters of the VMD and the gated recurrent unit (GRU), which overcomes the problem of empirical parameter adjustment. The HGWO is also adopted in the prediction strategy to optimize the GRU model to predict the grouped intrinsic mode functions (IMFs). Lastly, the final wind speed prediction result is obtained by superimposing the values of all the predicted models. The proposed model was validated with the measured wind speed data of the four quarters in the Bay area of China and was compared with 20 models of the classic method to further evaluate the effectiveness of the model. The results show that the whole process of the proposed model is adaptive, the final multi-step prediction performance is good, and high prediction accuracy can be attained.

Colorectal cancer occurrence and progression involve multiple aspects of host immune deficiencies. In these events, immune cells vary their phenotypes and functions over time, thus enabling the immune microenvironment to be “tumor-inhibiting” as well as “tumor-promoting” as a whole. Because of the association of tumoricidal T cell infiltration with favorable survival in cancer patients, the Immunoscore system was established. Critically, the tumoral Immunoscore serves as an indicator of CRC patient prognosis independent of patient TNM stage and suggests that patients with high Immunoscores in their tumors have prolonged survival in general. Accordingly, stratifications according to tumoral Immunoscores provide new insights into CRC in terms of comparing disease severity, forecasting disease progression, and making treatment decisions. An important application of this system will be to shed light on candidate selection in immunotherapy for CRC, because the T cells responsible for determining the Immunoscore serve as responders to immune checkpoint inhibitors. However, the Immunoscore system merely provides a standard procedure for identifying the tumoral infiltration of cytotoxic and memory T cells, while information concerning the survival and function of these cells is still absent. Moreover, other infiltrates, such as dendritic cells, macrophages, and B cells, can still influence CRC prognosis, implying that those might also influence the therapeutic efficacy of immune checkpoint inhibitors. On these bases, this review is designed to introduce the Immunoscore system by presenting its clinical significance and application in CRC.

An innovative approach is designed to fabricate Ti/steel clad plates. Instead of using Ti sheets, pure Ti powder was initially deposited on steel plates using cold spray additive manufacturing (CSAM). Then well bonded Ti/steel clad plates were obtained through hot-rolling and annealing operations. The mechanical properties of the clad plates at different processing stages were evaluated by performing a series of tensile tests and shear tests. It was revealed that the Ti/steel clad plates had excellent shear strength (280 Mpa), ultimate tensile strength (UTS, 564 Mpa) and decent elongation (EL, 18%). Microstructural investigation of the specimens was performed by scanning electron microscopy (SEM), electron backscattered diffraction (EBSD) and transmission electron microscopy (TEM). It was revealed that cold spraying offers good pre-bonding of Ti with the steel plate thereby suppressing cracking and oxidation at the interface. Hot-rolling treatment repaired the pores/defects in the as-sprayed Ti coating and resulted in metallurgical bonding between Ti particles as well as Ti/steel interface, which remarkably improved the strength of the material. High dislocation density in the clad plates were further eliminated by the annealing treatment through recovery, recrystallization and grain growth mechanisms, which greatly improved the toughness of the samples. Keywords: Ti/steel clad plate, Cold spray additive manufacturing (CSAM), Heat treatment, Mechanical properties, Microstructure

From a one-frame off-axis interferogram with unknown carrier-frequency, a rapid spatial carrier-frequency phase-shifting (SCFPS) method is proposed to achieve the phase measurement of the dynamic process. First, based on the SCFPS technique, four-frame phase-shifting subinterferograms are constructed from one-frame off-axis interferogram. Second, by using the orthogonality of diamond diagonal vectors, respectively, achieved through the subtraction and addition operations between two equal length vectors, which are generated from above four-frame phase-shifting subinterferograms, the accurate phase can be retrieved rapidly. Compared with current SCFPS methods, in addition to maintaining high accuracy of phase-shifting method, as well as no requirement for carrier-frequency calibration, the proposed method reveals an obvious advantage in processing speed of phase retrieval, and this will greatly facilitate its application prospect for dynamic phase measurement.

Observational studies have demonstrated that cardiovascular risk factors are associated with chronic kidney disease (CKD). However, these observational associations are potentially influenced by the residual confounding, including some unmeasured lifestyle factors and interaction risk factors. Two-sample mendelian randomization analysis was conducted in this study to evaluate whether genetically predicted cardiovascular risk factors have a causal effect on the risk of CKD. We selected genetic variants associated with cardiovascular risk factors and extracted the corresponding effect sizes from the largest GWAS summary-level dataset of CKD. Cardiovascular risk factors contain high density lipoprotein (HDL) cholesterol, low density lipoprotein (LDL) cholesterol, total cholesterol (TC), triglyceride (TG), glycated hemoglobin (HbA1c), fasting glucose, systolic blood pressure (SBP) and diastolic blood pressure (DBP). A Bonferroni corrected threshold of P = 0.006 was considered as significant, and 0.006 < P < 0.05 was considered suggestive of evidence for a potential association. Genetically predicted DBP was significantly associated with CKD [odds ratio (OR) was 1.35 (95% confidence interval (CI) (1.10, 1.65); P = 0.004)]. There was suggestive evidence for potential associations between genetically predicted higher HDL cholesterol [OR: 0.88, 95%CI (0.80, 0.98), P = 0.025] and lower adds of CKD, and between higher SBP [OR: 1.36, 95%CI (1.07, 1.73), P = 0.013] and higher adds of CKD. However, genetically predicted LDL cholesterol, TC, TG, HbA1c, and fasting glucose did not show any causal association with CKD.

The parameter sensitivity analysis of a hydraulically interconnected suspension (HIS) system shows that the sensitivity of the vibration responses in the bounce and roll modes to the hydraulic parameters are complementary. A novel HIS-based semiactive control method was thereby proposed to improve ride comfort and antiroll performance. In addition, the classic sky-hook max-min damping switched strategy provides significant benefits around the body resonance, but otherwise performs similarly to, or sometimes even worse than, passive suspension. Therefore, a dual-frequency-range switching strategy, which has optimal max-min damping in both frequency ranges, was developed for improving the ride comfort in a wider frequency bandwidth. In this study, a 9-DOF HIS system dynamics model was established, and the hydraulically interconnected subsystem model was validated experimentally. Subsequently, the elastic and damping characteristics of the hydraulically interconnected subsystem, as well as the parameter sensitivity in bounce mode and roll mode, were analyzed. Next, the sensitive parameters were optimized under sinusoidal excitation at various frequencies, and a frequency-range selector used to determine the excitation frequency range and adjust the shock absorber damping was designed. Finally, simulations in the frequency domain and time domain show that the proposed HIS-based semiactive dual-frequency-range switching control suspension improves the ride comfort in a wider frequency bandwidth and enhances the antiroll performance in the transient and steady steering process.

Fault size estimation is of great importance to bearing performance degradation assessment and life prediction. Until now, fault size estimation has generally been based on acoustic emission signals or vibration signals; an approach based on current signals has not yet been mentioned. In the present research, an approximate estimation approach based on current is introduced. The proposed approach is easy to implement for existing inverter-driven induction motors without complicated calculations and additional sensors, immune to external disturbances, and suitable for harsh conditions. Firstly, a feature transmission route from spall, to Hertzian forces, and then to friction torque is simulated based on a spall model and dynamic model of the bearing. Based on simulated results, the relation between spall size and the multiple characteristic vibration frequencies in friction torque is revealed. Secondly, the multiple characteristic vibration frequencies modulated in the current is investigated. Analysis results show that those frequencies modulated in the current are independent of each other, without spectrum overlap. Thirdly, to address the issue of which fault features modulated in the current are very weak, a fault-feature-highlighting approach based on reduced voltage frequency ratio is proposed. Finally, experimental tests were conducted. The obtained results validate that the proposed approach is feasible and effective for spall size estimation.

A modified 3D numerical model on the energy conversion process in the anode side of a Direct Methanol Fuel Cell (DMFC) system was constructed and validated to published experimental results. Systematic simulations were performed to investigate the underlying mechanisms of the energy conversion process, and the combined effects of inlet flow rate and input methanol concentration were summarized systematically. The increase of flow rate was found to be an effective strategy to accelerate the internal flow fields, while the diffusion layer was proposed to be a critical component in the design of high-performance DMFC. The frontier for optimal conditions of DMFC’s output was also determined, which can be helpful to improve the energy conversion performance of DMFC in practical applications.

Portunus trituberculatus holds significant economic value. The spermatogenesis is regulated by numerous signaling pathways. Among them, the TGF-β signaling pathway plays an important role in the development of testes and spermatogenesis. Smad4 is a Co-Smad protein that forms a complex with R-Smad to regulate the expression of target genes. The sperm structure in crustaceans differs greatly from that in mammals, with mature sperm lacking tails. Our previous studies have reported the function of R-Smad in the spermatogenesis of P. trituberculatus. In this study, we cloned the full-length cDNA sequence of PTSMAD4; immunofluorescence technology revealed that PTSMAD4 is expressed throughout all stages of spermatogenesis. We knocked down the expression of PTSMAD4 in P. trituberculatus using RNAi technology, and the immunofluorescence results show abnormal co-localization and weakened signals of PTSMAD4 and PTSMAD2. Additionally, transcriptome sequencing results enriched functional genes and pathways related to spermatogenesis. This study indicates that PTSMAD4 may participate in the spermatogenesis process through its involvement in signal transduction. This research not only lays the foundation for further study of the function of the TGF-β signaling pathway in spermatogenesis but also provides a theoretical basis for further investigation of the spermatogenesis mechanism in crustaceans. [ABSTRACT FROM AUTHOR]