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Space-borne synthetic aperture radar (SAR), as an all-weather observation sensor, is an important means in modern information electronic warfare. Since SAR is a broadband active radar system, radio frequency interference (RFI) in the same frequency band will affect the normal observation of the SAR system. Untangling the above problem, this research explores a quick and accurate method for detecting and segmenting RFI-contaminated images. The purpose of the current method is to quickly detect the existence of RFI and to locate it in massive SAR data. Based on deep learning, the method shown in this paper realizes the existence of RFI by determining the presence or absence of interference in the image domain and then performs pixel-level image segmentation on Sentinel-1 RFI-affected quick-look images to locate RFI. Considering the need to quickly detect RFI in massive SAR data, an improved network based on MobileNet is proposed, which replaces some inverted residual blocks in the network with ghost blocks, reducing the number of network parameters and the inference time to 6.1 ms per image. Further, this paper also proposes an improved network called the Smart Interference Segmentation Network (SISNet), which is based on U2Net and replaces the convolution of the VGG blocks in U2Net with a residual convolution and introduces attention mechanisms and a modified RFB module to improve the segmentation mIoU to 87.46% on average. Experiment results and statistical analysis based on the MID dataset and PAIS dataset show that the proposed methods can achieve quicker detection than other CNNs while ensuring a certain accuracy and can significantly improve segmentation performance under the same conditions compared to the original U2Net and other semantic segmentation networks. [ABSTRACT FROM AUTHOR]

Large nitrogen (N) losses during fertilization in agricultural production may result in energy wastage, soil and water contamination, and potentially influence crop development. Thus, with the help of a 15N-labeled tracer, we carried out a field monitoring analysis of NH3 emissions in a long-term (9-year) conservation tillage agroecosystem of Mollisols in northeast China, in order to determine whether a no-tillage regime and four levels of stover mulching (0%, 33%, 67%, and 100%), combined with urease and nitrification inhibitors, could improve fertilizer utilization efficiency in agricultural systems by reducing ammonia volatilization. Our results showed that in comparison with ridge tillage, no-tillage with stover mulching levels of 33%, 67%, and 100% significantly reduced NH3 emission rates and cumulative volatilization from 159.67 to 130.42 g N ha−1 and 15N-NH3 cumulative volatilization emission by 26% (on average). Furthermore, the application of urease and nitrification inhibitors significantly reduced 15N-NH3 volatilization levels from 1.19 to 0.98 g N ha−1. Our research results demonstrate that a long-term no-tillage regime and straw mulching can significantly reduce NH3 volatilization in fertilizers. Furthermore, when combined with the use of urease and nitrification inhibitors, these practices further enhance the reduction in NH3 volatilization. Although the volatilization of 15N-NH3 is minimally studied in Mollisols, these findings provide a solid foundation for improving fertilizer utilization efficiency, reducing crop production costs and mitigating subsequent environmental pollution. [ABSTRACT FROM AUTHOR]

Background: Single-cell RNA sequencing (scRNA-seq) technology has enabled assessment of transcriptome-wide changes at single-cell resolution. Due to the heterogeneity in environmental exposure and genetic background across subjects, subject effect contributes to the major source of variation in scRNA-seq data with multiple subjects, which severely confounds cell type specific differential expression (DE) analysis. Moreover, dropout events are prevalent in scRNA-seq data, leading to excessive number of zeroes in the data, which further aggravates the challenge in DE analysis. Results: We developed iDESC to detect cell type specific DE genes between two groups of subjects in scRNA-seq data. iDESC uses a zero-inflated negative binomial mixed model to consider both subject effect and dropouts. The prevalence of dropout events (dropout rate) was demonstrated to be dependent on gene expression level, which is modeled by pooling information across genes. Subject effect is modeled as a random effect in the log-mean of the negative binomial component. We evaluated and compared the performance of iDESC with eleven existing DE analysis methods. Using simulated data, we demonstrated that iDESC had well-controlled type I error and higher power compared to the existing methods. Applications of those methods with well-controlled type I error to three real scRNA-seq datasets from the same tissue and disease showed that the results of iDESC achieved the best consistency between datasets and the best disease relevance. Conclusions: iDESC was able to achieve more accurate and robust DE analysis results by separating subject effect from disease effect with consideration of dropouts to identify DE genes, suggesting the importance of considering subject effect and dropouts in the DE analysis of scRNA-seq data with multiple subjects. [ABSTRACT FROM AUTHOR]

The present study aimed to investigate the essential oil composition of Liparis nervosa (Thunb.) Lindl., grown in China, and to determine its antioxidant and inhibitory effects on acetylcholinesterase. The essential oil was obtained by hydrodistillation, and the chemical compounds were analyzed by GC-MS and GC-FID. We used 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), 2,2-diphenyl-1-picrylhydrazyl (DPPH), and ferric reducing assay power (FRAP) to evaluate the antioxidant activity. The anti-acetylcholinesterase activity of the essential oil was also examined. Sixty-seven compounds were identified, representing 98.50 % of the total essential oil, which was shown to be rich in methyl (9E,11E)-octadeca-9,11-dienoate (31.69%), n-hexadecanoic acid (15.08%), isopropyl palmitate (12.44%), propyl tetradecanoate (7.20%), tetradecanoic acid (4.01%), 17-octadecynoic acid (3.71%), and pentacosane (2.24%). Its antioxidant ability was analyzed via ABTS (IC50 = 721.95 ± 9.93 μg/mL), DPPH scavenging capacity (IC50 > 10,000 μg/mL), and the FRAP method (Trolox equivalent antioxidant concentration 39.64 ± 3.38 μM/g). Acetylcholinesterase inhibition effects were evaluated and had an IC50 value of 51.96 ± 14.26 μg/mL. The results show that this essential oil has interesting biological potential, encouraging further investigations, especially regarding the mechanisms of action of its antioxidant and anti-acetylcholinesterase activity. This is the first time that the chemical composition, antioxidant activity, and acetylcholinesterase inhibition effects of essential oil from L. nervosa have been studied. [ABSTRACT FROM AUTHOR]

Vibrio parahaemolyticus has become an important public threat to human health. Rapid and robust pathogen diagnostics are necessary for monitoring its outbreak and spreading. Herein, we report an assay for the detection of V. parahaemolyticus based on recombinase aided amplification (RAA) combined with lateral flow dipstick (LFD), namely RAA-LFD. The RAA-LFD took 20 min at 36~38 ℃, and showed excellent specificity. It detected as low as 6.4 fg/µL of V. parahaemolyticus in genomic DNA, or 7.4 CFU/g spiked food samples with 4 h of enrichment. The limit of detection in shrimp (Litopenaeus Vannamei), fish (Carassius auratus), clam (Ruditapes philippinarum) evidenced that sensitivity was considerably affected by the food matrix. The presence of food matrix reduced the sensitivity of spiked food samples by 10 ~ 100 times. In the filed samples detection, RAA-LFD method showed good coincidence with GB4789.7-2013 method and PCR method at rates of 90.6% and 94.1%, respectively. RAA-LFD has high accuracy and sensitivity for the detection of V. parahaemolyticus, which can serve as a model tool to meet the growing need for point-of-care diagnosis of V. parahaemolyticus. [ABSTRACT FROM AUTHOR]

We have developed a generalized mean-field equation of state suitable for many-body dissipative particle dynamics method in a homogeneous system, which is accurate and valid at arbitrary level of coarse-graining in pressure prediction. Specifically, the truncation influences caused by finite cutoff radius have been mitigated to satisfy with the assumption of mean-field theory, and the so-called local density has been replaced with global one in the frame of homogeneous system. Our present work represents an advancement toward establishing a robust and reliable one-to-one parameter mapping protocol based on mean-field theory. [ABSTRACT FROM AUTHOR]

SUMMARY: In eukaryotes, meiotic recombination maintains genome stability and creates genetic diversity. The conserved Ataxia‐Telangiectasia Mutated (ATM) kinase regulates multiple processes in meiotic homologous recombination, including DNA double‐strand break (DSB) formation and repair, synaptonemal complex organization, and crossover formation and distribution. However, its function in plant meiotic recombination under stressful environmental conditions remains poorly understood. In this study, we demonstrate that ATM is required for the maintenance of meiotic genome stability under heat stress in Arabidopsis thaliana. Using cytogenetic approaches we determined that ATM does not mediate reduced DSB formation but does ensure successful DSB repair, and thus meiotic chromosome integrity, under heat stress. Further genetic analysis suggested that ATM mediates DSB repair at high temperature by acting downstream of the MRE11–RAD50–NBS1 (MRN) complex, and acts in a RAD51‐independent but chromosome axis‐dependent manner. This study extends our understanding on the role of ATM in DSB repair and the protection of genome stability in plants under high temperature stress. Significance Statement: Heat stress affects meiotic recombination and thus influences genome diversity and stability in plants. In eukaryotes, the conserved kinase ATM regulates multiple meiotic recombination processes; however, its role in meiotic recombination in plants under high‐temperature conditions remains unknown. In this study, we report that ATM, acting downstream of the MRN complex, mediates a RAD51‐independent but chromosome axis‐dependent DSB repair mechanism to protect meiotic genome integrity in Arabidopsis under heat stress. [ABSTRACT FROM AUTHOR]

High-resolution (HR) remote sensing images have important applications in many scenarios, and improving the resolution of remote sensing images via algorithms is one of the key research fields. However, current super-resolution (SR) algorithms, which are trained on synthetic datasets, tend to have poor performance in real-world low-resolution (LR) images. Moreover, due to the inherent complexity of real-world remote sensing images, current models are prone to color distortion, blurred edges, and unrealistic artifacts. To address these issues, real-SR datasets using the Gao Fen (GF) satellite images at different spatial resolutions have been established to simulate real degradation situations; moreover, a second-order attention generator adversarial attention network (SA-GAN) model based on real-world remote sensing images is proposed to implement the SR task. In the generator network, a second-order channel attention mechanism and a region-level non-local module are used to fully utilize the a priori information in low-resolution (LR) images, as well as adopting region-aware loss to suppress artifact generation. Experiments on test data demonstrate that the model delivers good performance for quantitative metrics, and the visual quality outperforms that of previous approaches. The Frechet inception distance score (FID) and the learned perceptual image patch similarity (LPIPS) value using the proposed method are improved by 17.67% and 6.61%, respectively. Migration experiments in real scenarios also demonstrate the effectiveness and robustness of the method. [ABSTRACT FROM AUTHOR]

[Display omitted] The rational design and fabrication of platinum group metal-free (PGM-free) electrocatalysts for oxygen reduction reaction (ORR) via economically feasible approach is essential for reducing the cost of fuel cells and metal-air batteries. Catalysts must have very high activity, and excellent mass diffusion of reactants. Herein, we display a high-performing dual-metal single atom catalyst (DM-SAC) composed of Fe and Ni SA active sites immobilized in porous carbon nanospheres (Fe/Ni-N-PCS), prepared via defects/vacancies anchoring strategy. The abundant and accessible edge-hosted Fe and Ni SA active sites can promote the adsorption/desorption behavior for ORR intermediates attributing to possible synergistic effects between dual-metal SA active sites. Thus, the as-developed Fe/Ni-N-PCS DM-SAC exhibits impressive ORR electrocatalytic performance in both alkaline (E onset = 1.04 V, E 1/2 = 0.9 V) and acid solutions (E onset = 0.87 V, E 1/2 = 0.71 V), and high stability, outperforming SACs with solo Fe-N x or Ni-N x active sites, and benchmark PGM. Fe/Ni-N-PCS also exhibits superior oxygen evolution reaction (OER) performance with low overpotential and long-term stability. Zn-air battery with Fe/Ni-N-PCS cathode yields encouraging performance, including working potential, peak power density, and the stability of charge and discharge cycles. Our synthesis method may promote the fabrication of other DM-SAC and the great promise in practical applications. [ABSTRACT FROM AUTHOR]

The initiation and progression of tumors are complex. The cancer evolution-development hypothesis holds that the dysregulation of immune balance is caused by the synergistic effect of immune genetic factors and environmental factors that stimulate and maintain non-resolving inflammation. Throughout the cancer development process, this inflammation creates a microenvironment for the evolution and development of cancer. Research on the inflammatory tumor microenvironment (TME) explains the initiation and progression of cancer and guides anti-cancer immunotherapy. Single-cell RNA sequencing (scRNA-seq) can detect the transcription levels of cells at the single-cell resolution level, reveal the heterogeneity and evolutionary trajectory of infiltrated immune cells and cancer cells, and provide insight into the composition and function of each cell group in the inflammatory TME. This paper summarizes the application of scRNA-seq in inflammatory TME. [ABSTRACT FROM AUTHOR]

Older adults needing assistance with activities of daily living can receive support in various settings. Senior housing communities, such as independent living, assisted living, and continuing care retirement communities, are an increasingly popular option for adults not requiring nursing home–level care. However, limited research exists due to a dearth of data on these types of communities. We use a proprietary data set to describe the market of private pay senior housing and community-level characteristics in 140 metropolitan statistical areas, from 2015 to 2019. Although the number of senior housing communities increased substantially, the supply of senior housing options supporting the continuum of care has not necessarily kept up with population growth. Describing the supply of senior housing communities across the spectrum of levels of care provides a more complete description of the formal noninstitutional long-term care supply among the 140 most populated metropolitan statistical areas. [ABSTRACT FROM AUTHOR]

Applying robots to mobile application testing is an emerging approach to automated black-box testing. The key to supporting automated robot testing is the efficient modeling of GUI elements. Since the application under testing often contains a large number of similar GUIs, the GUI model obtained often contains many redundant nodes. This causes the state space explosion of GUI models which has a serious effect on the efficiency of GUI testing. Hence, how to accurately identify isomorphic GUIs and construct quasi-concise GUI models are key challenges faced today. We thus propose a semantic similarity-based approach to identifying isomorphic GUIs for mobile applications. Using this approach, the information of GUI elements is first identified by deep learning network models, then, the GUI structure model feature vector and the semantic model feature vector are extracted and finally merged to generate a GUI embedding vector with semantic information. Finally, the isomorphic GUIs are identified by cosine similarity. Then, three experiments are conducted to verify the generalizability and effectiveness of the method. The experiments demonstrate that the proposed method can accurately identify isomorphic GUIs and shows high compatibility in terms of cross-platform and cross-device applications. [ABSTRACT FROM AUTHOR]

The graph convolutional network (GCN)-based clustering approaches have achieved the impressive performance due to strong ability of exploiting the topological structure. The adjacency graph seriously affects the clustering performance, especially for non-graph data. Existing approaches usually conduct two independent steps, i.e., constructing a fixed graph structure and then graph embedding representation learning by GCN. However, the constructed graph structure may be unreliable one due to noisy data, resulting in sub-optimal graph embedding representation. In this paper, we propose an adaptive graph convolutional clustering network (AGCCN) to alternatively learn the similarity graph structure and node embedding representation in a unified framework. Our AGCCN learns the weighted adjacency graph adaptively from the node representations by solving the optimization problem of graph learning, in which adaptive and optimal neighbors for each sample are assigned with probabilistic way according to local connectivity. Then, the attribute feature extracted by parallel Auto-Encoder (AE) module is fused into the input of adaptive graph convolution module layer-by-layer to learn the comprehensive node embedding representation and strengthen its representation ability. This also skillfully alleviates the over-smoothing problem of GCN. To further improve the discriminant ability of node representation, a dual self-supervised clustering mechanism is designed to guide model optimization with pseudo-labels information. Extensive experimental results on various real-world datasets consistently show the superiority and effectiveness of the proposed deep graph clustering method. [ABSTRACT FROM AUTHOR]

A combined hydroxyl-functionalized and NH 4 Cl-assisted etching strategy is developed to effectively promote the yield of edge-hosted single-atomic Cu-N4 sites. The developed CuSAs@DCSs renders outstanding ORR activity (E onset =1.02 V, E 1/2 = 0.90 V), and excellent stability. CuSAs@DCSs-based Zn-air battery achieves ultralong cycle life and large power density. Rich edge-hosted active sites are responsible for the remarkable ORR performance. [Display omitted] • A hydroxyl-functionalized and NH 4 Cl-assisted etching strategy is developed to promote the yield of edge-hosted Cu-N4 sites. • Rich accessible edge-hosted Cu-N4 sites are responsible for the remarkable ORR performance. • CuSAs@DCSs exhibits extraordinarily ORR activity and excellent stability in both alkaline and acid solution. • CuSAs@DCSs exhibits superb performance when used as air cathode for Zn–air battery. • This strategy can be extended to fabricate other single atoms catalyst with controlled electronic structure. Single-atom electrocatalysts with metal-nitrogen-carbon (M N C SACs) moieties in carbon support display outstanding electrocatalytic performance towards oxygen reduction reaction (ORR) and have received widespread attentions. Only active sites on the edges of pores in carbon support are electrochemically accessible and contribute to ORR. Herein, we report a combined hydroxyl-functionalized and NH 4 Cl-assisted etching strategy to effectively promote the yield of edge-hosted Cu SAs. Thus, well-defined SAs with Cu-N 4 configuration are generated into the defect of carbonaceous nanospheres (CuSAs@DCSs). Impressively, the obtained SACs renders outstanding electrocatalytic ORR activity with onset, half-wave potentials of 1.02 V, 0.90 V, and extremely high stability, which transcends the noble-metals and most of the previously reported catalysts. When used in rechargeable Zn-air batteries, CuSAs@DCSs achieves ultralong cycle life at the large current density of 10 mA cm−2 (over 260 h) with low charge–discharge potential gap. Our study demonstrates that the creation of abundant micropores enriches the electrochemically accessible SAs, which locate at the edge-defects and are responsible for the remarkable ORR performance. This work sheds a facile strategy for designing and developing efficient electrocatalyst for various energy-related electrocatalytic reactions. [ABSTRACT FROM AUTHOR]

Accurate channel state information (CSI) is important for MIMO systems, especially in a high-speed scenario, fast time-varying CSI tends to be out of date, and a change in CSI shows complex nonlinearities. The kernel recursive least-squares (KRLS) algorithm, which offers an attractive framework to deal with nonlinear problems, can be used in predicting nonlinear time-varying CSI. However, the network structure of the traditional KRLS algorithm grows as the training sample size increases, resulting in insufficient storage space and increasing computation when dealing with incoming data, which limits the online prediction of the KRLS algorithm. This paper proposed a new sparse sliding-window KRLS (SSW-KRLS) algorithm where a candidate discard set is selected through correlation analysis between the mapping vectors in the kernel Hilbert spaces of the new input sample and the existing samples in the kernel dictionary; then, the discarded sample is determined in combination with its corresponding output to achieve dynamic sample updates. Specifically, the proposed SSW-KRLS algorithm maintains the size of the kernel dictionary within the sample budget requires a fixed amount of memory and computation per time step, incorporates regularization, and achieves online prediction. Moreover, in order to sufficiently track the strongly changeable dynamic characteristics, a forgetting factor is considered in the proposed algorithm. Numerical simulations demonstrate that, under a realistic channel model of 3GPP in a rich scattering environment, our proposed algorithm achieved superior performance in terms of both predictive accuracy and kernel dictionary size than that of the ALD-KRLS algorithm. Our proposed SSW-KRLS algorithm with M = 90 achieved 2 dB NMSE less than that of the ALD-KRLS algorithm with v = 0.001 , while the kernel dictionary was about 17% smaller when the speed of the mobile user was 120 km/h. [ABSTRACT FROM AUTHOR]

Mucin1 (MUC1) is an extensively glycosylated transmembrane protein that is widely distributed and overexpressed on the surface of cancer cells, playing an important role in tumor occurrence and metastasis. Therefore, highly sensitive detection of MUC1 is of great significance for early diagnosis, treatment monitoring, and prognosis of cancer. Here, an ultra-sensitive photoelectrochemical (PEC) sensing platform was developed based on an aptamer amplification strategy for highly selective and sensitive detection of MUC1 overexpressed in serum and on cancer cell surfaces. The sensing platform utilized copper phthalocyanine to fabricate porous organic polymers (CuPc POPs), and was effectively integrated with g-C 3 N 4 /MXene to form a ternary heterojunction material (g-C 3 N 4 /MXene/CuPc POPs). This material effectively improved electron transfer capability, significantly enhanced light utilization, and greatly enhanced photoelectric conversion efficiency, resulting in a dramatic increase in photocurrent response. MUC1 aptamer 1 was immobilized on a chitosan-modified photoelectrode for the selective capture of MUC1 or MCF-7 cancer cells. When the target substance was present, MUC1 aptamer 2 labeled with methylene blue (MB) was specifically adsorbed on the electrode surface, leading to enhanced photocurrent. The concentration of MUC1 directly correlated with the number of MB molecules attracted to the electrode surface, establishing a linear relationship between photocurrent intensity and MUC1 concentration. The PEC biosensor exhibited excellent sensitivity for MUC1 detection with a wide detection range from 1 × 10−7 to 10 ng/mL and a detection limit of 8.1 ag/mL. The detection range for MCF-7 cells was from 2 × 101 to 2 × 106 cells/mL, with the capability for detecting single MCF-7 cells. The aptamer amplification strategy significantly enhanced PEC performance, and open up a promising platform to establish high selectivity, stability, and ultrasensitive analytical techniques. [Display omitted] • G-C 3 N 4 /MXene/CuPc POPs as an ideal photo-driven substrate material was successfully prepared. • Electron transfer mechanism of PEC Electrodes was proposed. • A highly sensitive and selective PEC sensor for MUC1 and MCF-7 was constructed based on aptamer signal amplification. • The developed sensor was applied to real sample analysis. [ABSTRACT FROM AUTHOR]

The many-body dissipative particle dynamics (MDPD) is a promising mesoscopic method for solving various interfacial issues. However, an accurate mapping between simulation parameters and corresponding fluid properties is still ambiguous in MDPD due to its additional many-body interaction. In the present paper, we adopt the back-propagation Neural Network (BPNN) model with high-fidelity database as a rigorous calibration approach for MDPD. The relations between three main, simulation parameters (i.e. attractive and repulsive coefficient A,B and cut-off radius of repulsive force r d ) and four real-fluid static and dynamic properties (i.e. density, viscosity, self-diffusion coefficient and surface tension) are achieved accurately with the frame of BPNN. The influences of hyperparameters and training sets on mean squared errors (MSE) are also provided. Moreover, in order to improve the training efficiency of the model, we put forward three data selection methods: random data selection, extreme value data selection and the orthogonal experiment data selection. We compare three sampling methods for training data, and the orthogonal experiment design data selection is proved to be the most effective way to reduce MSE. The BPNN model is the potential to be a powerful tool for determining the simulation parameters within given fluid properties accurately and efficiently in the MDPD system. [ABSTRACT FROM AUTHOR]

In recent times, deep learning models have achieved state-of-the-art performances in image classification. However, the classification and generalization ability of most achievements have highly relied on the availability of large-scale accurate labeled training data, which are time-consuming, laborious, and expensive to collect. Moreover, in the generalizing process of deep learning models, the noisy labels are the challenges for multi-category classification. Hence, it is essential to explore effective methods that can efficiently and correctly train deep models under label noise to conduct multi-category classification. This paper proposes using robust binary loss functions to train deep models under label noise to address this problem. Specifically, we suggest handling the K -class classification task by using K binary classifiers, which can be completed by a joint adoption of multi-category large margin classification approaches, e.g., Pairwise-Comparison (PC) or One-versus-All (OVA). We also theoretically demonstrate that our method is inherently tolerant to label noise by using symmetric binary loss functions in multi-category classification tasks. Moreover, we designed a truncated CCE loss to combine with the proposed losses to improve the learning ability. Finally, we test our method on three different benchmark datasets with different types of label noise. The experimental results have clearly confirmed the effectiveness of our method, which can reduce the negative effect of noisy labels and improve the generalization ability. [ABSTRACT FROM AUTHOR]

Serving as a key component of the core engine, the high-load axial compressor is expected to have high performance, which determines several critical parameter levels of the aero-engine. The unsteady effect on the performance induced by the interaction among different rotors should not be ignored during the design of a high-load compressor. The interaction between R1 (the first rotor row) and R2 (the second rotor row) rotors of a transonic axial compressor was measured in detail using high-frequency pressure fluctuation sensors, aiming to reveal the evolution and distribution characteristics of the R1 sweep effect inside the R2 passage. The results show that near choke and design points, the interaction between the R1 oblique shock wave at the leading edge and the high-pressure region on the blade pressure side triggers the R1-2BPF (blade passing frequency) disturbance, which is different from the traditional harmonic of the blade wake disturbance. A 'long tail' flow structure, which indicates the major influence of the R1 shock wave, fluctuation obviously reaches the exit of R1 and influences the upper part of S1 and R2. The combination of the R1-2BPF and the R1-1BPF (mainly caused by the R1 wake disturbance) influences the R2 flow field significantly, and both of them sharply grow at the middle and rear parts of the R2 passage where the strength of the two disturbances increases by 24% and 68%, respectively, compared to the leading edge of R2. Moreover, the circumferential non-uniformity of the R1-1BPF and R1-2BPF disturbances significantly increase at some locations of the R2 passage compared to the R1 exit, which is attributed to the relative clocking positions of the R1 and R2 blades. [ABSTRACT FROM AUTHOR]

In electrowetting, an applied electric voltage can induce spreading, sliding, or even jumping of an individual droplet by changing the intrinsic balance of the three-phase interfacial tensions. This technique has been widely used for manipulating droplets in microfluidics and by lab-on-a-chip devices in recent decades. In the present paper, we present an analytical prediction of the jumping velocity for droplets undergoing electrowetting on textured hydrophobic surfaces with different wetting states. In particular, we consider wetting a liquid droplet on a textured hydrophobic substrate with a voltage applied between the droplet and the substrate. Once the voltage is turned off, the energy stored in the droplet during electrowetting is released and could even result in the detachment of the droplet. The effects of the initial and electrowetting states, i.e., the Cassie–Baxter state and the Wenzel state, on the jumping velocity of droplets are systematically discussed. Based on energy conservation, the energy conversion between the surface energy, the elastic energy of the contact line, and the kinetic energy of droplets due to internal viscous dissipation in different wetting states is analyzed. Closed-form formulas for the jumping velocity of different droplet wetting states are systematically derived. Finally, a unified form for predicting the electrowetting-induced jumping velocity of droplets on both flat and textured substrates with different wetting states is obtained. It can describe the jumping motion under various wetting conditions, which is validated by some experimental results. This work provides theoretical insights into the accurate control of the electrowetting-induced jumping motion of droplets on textured hydrophobic surfaces. [ABSTRACT FROM AUTHOR]

Many-body dissipative particle dynamics (MDPD) is a novel coarse-grained numerical method that originated from dissipative particle dynamics. In the MDPD system, a density-dependent repulsive interaction and an attractive term are introduced into a conservative force, enabling the formation of vapor–liquid coexistence. In the last two decades, the MDPD is becoming a powerful tool to study various interfacial problems at mesoscale due to its Lagrangian and adaptive features. In the present paper, we review the developments in the theoretical models and applications for the MDPD. First, the MDPD theoretical backgrounds of single- and multi-component system are introduced. Then, the parameter analysis and mapping protocols in the MDPD are discussed. Furthermore, recent applications based on the MDPD, including droplet and microbubble dynamics, evolution of liquid bridges, capillary wetting, polymer solutions, and phase change, are revisited with some comments. Finally, we summarize several unsolved issues in the MDPD and outline its future developments. [ABSTRACT FROM AUTHOR]

Free-surface fluid dynamics at the nanoscale is shown to strongly depend on thermal fluctuations. These fluctuations can be predicted by particle-based models numerically and analyzed by stochastic partial differential equations theoretically. In this work, we employ one of the particle methods, known as many-body dissipative particle dynamics (mDPD), to investigate the influence of thermal fluctuations on nanoscale free-surface flows. After enough independent simulations are performed for convincing ensemble-averaged results, mDPD not only shows good consistency with theories derived from the Landau–Lifshitz Navier–Stokes equations, but also indicates high efficiency in contrast with traditional molecular dynamics (MD). These results confirm that mDPD has capabilities of capturing the physics of fluctuating hydrodynamics in nanoscale free-surface flows, especially the complicated three-dimensional behaviors that cannot be predicted by theoretical models, both accurately and efficiently. [ABSTRACT FROM AUTHOR]

This study focused on using "General Practitioners–Specialists" (GP-S) mode to teach the patients with asthma to master inhalation skills. 200 patients with asthma being admitted to the respiratory department of Shanghai Changhai Hospital were included in the study from January to December in 2018. There were 100 cases in the control group and 100 cases in the experimental group. The control groups received routine instruction and the experimental group adopted GP-S mode education, respectively, to learn mastering dry powder inhaler skills. The level of mastery and errors in the use of inhaled medications were recorded after each guidance. After four times' instruction in two different ways, the patient's mastery of inhalation skills gradually improved. After the guidance through the GP-S mode, the incidence of inhalation errors after each times instruction was 67%, 28%, and 7%, respectively. The later one was significantly lower than the previous one (67% vs. 28%, χ2 = 30.496, p < 0.001; 28% vs. 7%, χ2 = 15.273, p < 0.001). After twice instructions, the GP-S mode was associated with the lower incidence of inhaler device operating errors versus the regular guidance method (10% vs. 26%, χ2 = 8.672, p = 0.005); the same as the third guidance (2% vs. 11%, χ2 = 6.664, p = 0.018). Similarly, after thrice instructions, the incidence of inhalation method errors in the GP-S mode group was significantly lower than the regular guidance mode group (4% vs. 15%, χ2 = 7.037, p = 0.018), and there was still existing statistical difference of inhalation method errors between the two groups after four times instructions (3% vs. 11%, χ2 = 4.916, p = 0.049). General Practitioners–Specialists mode can effectively improve the patient's mastery of inhalation skills, which significantly reduced the incidence of errors in the use of inhaled drugs and improved the overall management effectivity of asthma and patients' compliance. [ABSTRACT FROM AUTHOR]

Reference 1 Liu Y. iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects. Correction: iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects. [Extracted from the article]

The hydrogeochemical characteristics of geothermal fluids can reveal the genesis of geothermal systems and act as important references for developing and using geothermal resources. This study presents hydrogeochemical processes and thermal cycle mechanisms of typical geothermal fields in Western Sichuan. Based on the geological conditions in Western Sichuan, 29 hot springs in three geothermal fields in the Batang and Litang areas were selected for hydrochemical and isotopic (δD and δ18O) analyses. Furthermore, the temperature of the thermal reservoir was calculated and the upflow cooling process of the hot springs was analyzed. Most of the subterranean hot waters in Batang and Litang are of the HCO3‐Na hydrochemical type. The ion variation in Batang is primarily affected by water‐rock interactions. There is a strong positive correlation between Na+, B−, and Cl− in Litang, suggesting that they have the same material source. The Na+ and metaboric acid content is relatively high, which indicates that the groundwater runoff in both areas is relatively long‐lasting, with reduced flow velocity; moreover, the metasilicic acid content is relatively high, which supports this conclusion. Both hydrogen and oxygen isotopes plot near the atmospheric precipitation line, indicating that groundwater recharge is functionally obtained from precipitation. The calculated thermal storage temperatures in Batang and Litang were 88–199°C and 96–154°C, respectively. The proportion of cold water mixing in Batang was 64%–67%, while that in Litang was 60%–68%. According to the calculated results, the initial thermal cycle depth of the Batang area (4540–4780 m) was greater than that of the Litang area (3150–3960 m). The enthalpy of the deep parental geothermal fluid in Batang was 1550 J/g with a Cl− concentration of 37 mg/L, while that in Litang was 2100 J/g with a Cl− concentration of 48 mg/L. [ABSTRACT FROM AUTHOR]

Background: Apathy is a neuropsychiatric symptom frequently observed in patients with cognitive impairment. It has been found to be a predictor of conversion from mild cognitive impairment (MCI) to dementia of Alzheimer disease type. However, this association between apathy and dementia conversion has not yet been confirmed in vascular MCI, especially post‐stroke MCI. The aim of this study was to evaluate whether apathy would increase the risk of dementia conversion in patients with post‐stroke MCI after 6 months. Method: A prospective multi‐centre cohort study was performed in 14 clinics in seven provinces and cities of China. A total of 989 subjects were included 2 weeks to 6 months after stroke, and met the diagnostic criteria of International Working Group for MCI. Symptoms of apathy were assessed using the apathy subscale of Geriatric Depression Scale. Subjects were divided into an apathy group (n = 128) and a non‐apathy group (n = 861). The primary outcome was the dementia conversion after 6 months. To eliminate potential biases, subjects were chosen from 861 non‐apathy patients with similarity in seven potential predictors of cognitive impairment to match with the apathy group (n = 128) at a 1:1 ratio, as a matched non‐apathy group (n = 128). The dementia conversion rate was compared between the apathy group (n = 128) and its correspondingly matched non‐apathy group (n = 128), and the relative risk (RR) was calculated. Results: The prevalence of apathy in post‐stroke MCI was 12.9%. After 6 months, 5.2% of patients with post‐stroke MCI converted to dementia. The dementia conversion rate of the apathy group was significantly higher than that of the non‐apathy group before case‐matching (17.2% vs 3.4%, P < 0.001), and also after case‐matching (17.2% vs 6.3%, P < 0.001). Symptoms of apathy increased the risk of conversion from MCI to dementia (RR 2.75, 95% CI 1.272–5.947, P < 0.001). Conclusions: For patients with post‐stroke MCI, apathy symptoms increase the risk of conversion from MCI to dementia. [ABSTRACT FROM AUTHOR]

This study focused on using "General Practitioners–Specialists" (GP-S) mode to teach the patients with asthma to master inhalation skills. 200 patients with asthma being admitted to the respiratory department of Shanghai Changhai Hospital were included in the study from January to December in 2018. There were 100 cases in the control group and 100 cases in the experimental group. The control groups received routine instruction and the experimental group adopted GP-S mode education, respectively, to learn mastering dry powder inhaler skills. The level of mastery and errors in the use of inhaled medications were recorded after each guidance. After four times' instruction in two different ways, the patient's mastery of inhalation skills gradually improved. After the guidance through the GP-S mode, the incidence of inhalation errors after each times instruction was 67%, 28%, and 7%, respectively. The later one was significantly lower than the previous one (67% vs. 28%, χ2 = 30.496, p < 0.001; 28% vs. 7%, χ2 = 15.273, p < 0.001). After twice instructions, the GP-S mode was associated with the lower incidence of inhaler device operating errors versus the regular guidance method (10% vs. 26%, χ2 = 8.672, p = 0.005); the same as the third guidance (2% vs. 11%, χ2 = 6.664, p = 0.018). Similarly, after thrice instructions, the incidence of inhalation method errors in the GP-S mode group was significantly lower than the regular guidance mode group (4% vs. 15%, χ2 = 7.037, p = 0.018), and there was still existing statistical difference of inhalation method errors between the two groups after four times instructions (3% vs. 11%, χ2 = 4.916, p = 0.049). General Practitioners–Specialists mode can effectively improve the patient's mastery of inhalation skills, which significantly reduced the incidence of errors in the use of inhaled drugs and improved the overall management effectivity of asthma and patients' compliance. [ABSTRACT FROM AUTHOR]

The transfer of the liquid from groove to plate is significantly affected by the breakup process of liquid bridge, which is the core problem of gravure. In this paper, many-body dissipative particle dynamics method (MDPD) is used to simulate the behaviors of the stretching liquid cylinder between the plate and the groove, and the influence of surface wettability, stretching velocity and groove structure on the liquid cylinder rupture and the transfer rate of liquid are studied. The results show that both of the slipping velocity of the contact line on the plate and the thinning velocity of the liquid cylinder determine the breakup state of the liquid bridges and the liquid transfer rate from the groove to the plate. In the cases with the same surface wettability, at high hydrophilicity surface, the transfer rate increases firstly and then decreases with the increase of the stretching velocity. In the cases with different surface wettability of the plate and the groove, reducing the stretching velocity and the inclination angle of the groove are helpful to pull the liquid out of the groove and increase the transfer rate, and it could also be achieved by increasing the wettability of the plate and decreasing the wettability of the groove. This study provides some new insights into the effects of surface wettability, stretching velocity and groove structure on the dynamics of breakup process and liquid transfer in stretching. [ABSTRACT FROM AUTHOR]

• USP8 protected against LPS-induced cognitive and motor impairments in mice. • USP8 promoted pro-inflammatory to anti-inflammatory shifts in microglial phenotype. • USP8 reduced serum and brain TNF-α, IL-1β, PGE 2 , and NO, and brain iNOS and COX-2. • USP8 upregulated anti-inflammatory mediators in the brain and serum. • USP8 alters microglia via TLR4/MyD88/NF-kB pathway to ameliorate LPS-induced damage. Ubiquitin-specific protease 8 (USP8) regulates inflammation in vitro ; however, the mechanisms by which USP8 inhibits neuroinflammation and its pathophysiological functions are not completely understood. In this study, we aimed to determine whether USP8 exerts neuroprotective effects in a mouse model of lipopolysaccharide (LPS)-induced cognitive and motor impairment. We commenced intracerebroventricular USP8 administration 7 days prior to i.p. injection of LPS (750 μg/kg). All treatments and behavioral experiments were performed once per day for 7 consecutive days. Behavioral tests and pathological/biochemical assays were performed to evaluate LPS-induced hippocampal damage. USP8 attenuated LPS-induced cognitive and motor impairments in mice. Moreover, USP8 downregulated several pro-inflammatory cytokines [nitric oxide (NO), tumor necrosis factor α (TNF-α), prostaglandin E 2 (PGE 2), and interleukin-1β (IL-1β)] in the serum and brain, and the relevant protein factors [inducible nitric oxide synthase (iNOS) and cyclooxygenase 2 (COX-2)] in the brain. Furthermore, USP8 upregulated the anti-inflammatory mediators interleukin (IL)-4 and IL-10 in the serum and brain, and promoted a shift from pro-inflammatory to anti-inflammatory microglial phenotypes. The LPS-induced microglial pro-inflammatory phenotype was abolished by TLR4 inhibitor and in TLR4−/− mice; these effects were similar to those of USP8 treatment. Mechanistically, we found that USP8 increased the expression of neuregulin receptor degradation protein-1 (Nrdp1), potently downregulated the expression of TLR4 and myeloid differentiation primary response protein 88 (MyD88) protein, and inhibited the phosphorylation of IκB kinase (IKK) β and kappa B-alpha (IκBα), thereby reducing nuclear translocation of p65 by inhibiting the activation of the nuclear factor-kappaB (NF-κB) signaling pathway in LPS-induced mice. Our results demonstrated that USP8 exerts protective effects against LPS-induced cognitive and motor deficits in mice by modulating microglial phenotypes via TLR4/MyD88/NF-κB signaling. [ABSTRACT FROM AUTHOR]

A promising intervention for Alzheimer's disease (AD) would ideally target key pathological factors that are involved in AD pathogenesis. Soluble factors produced by engrafted mesenchymal stem cells (MSCs) mediate potential therapeutic effects in AD. However, these therapeutic benefits are largely hampered by the limited paracrine capacity of MSCs. In this study, we used adenovirus-mediated gene transduction of bone marrow MSCs to deliver exogenous proteins into the brain of APPswe/PSEN1dE9 (APP/PS1) mice in the early stage of impairment. We observed that engrafted MSCs carrying exogenous (C-X3-C motif) ligand 1 (CX3CL1) alone reduced the production of the inflammatory cytokine TNF-ɑ and improved synapse-related protein expression but not cognitive function. Transplantation of MSCs carrying CX3CL1 and Wnt3a (CX3CL1-Wnt3a-MSC) significantly attenuated the learning and memory impairment when compared with a control group. The improvement of neurobehavioral functions in APP/PS1 mice treated with CX3CL1-Wnt3a-MSC was related to the inhibition of microglial neurotoxicity and promotion of hippocampal neurogenesis. Transplantation of CX3CL1-Wnt3a-MSC also regulated phosphoinositide 3-kinase/activated protein kinase B (PI3K/AKT) signaling to inhibit the activity of glycogen synthase kinase 3 beta (GSK3β). Taken together, these results indicate that the delivery of exogenous proteins via MSCs can modulate microglial function and enhance neurogenesis, thereby providing new insights into AD intervention. • CX3CL1-MSCs attenuate microglial activation and prevent synaptic loss. • CX3CL1-Wnt3a-MSCs transplantation alleviates cognitive impairment. • The cognitive improvements are related to enhanced hippocampal neurogenesis. • CX3CL1-Wnt3a-MSCs transplantation inhibits GSK3β via PI3K/Akt signaling. [ABSTRACT FROM AUTHOR]

Among numerous dynamic scheduling strategies for low‐density parity‐check codes, many of them are of high complexity due to repetitive computation and ordering of belief residuals. To address these challenges, two novel approaches are proposed: the derived informed variable‐to‐check residual belief propagation and the derived variable‐node and variable‐to‐check‐edge residual belief propagation for low‐density parity‐check codes. Simulation results show that the derived dynamic scheduling exhibits a substantial gain of approximately 0.15 dB in signal‐to‐noise ratio over the non‐derived one with considerably lower decoding complexity when targeting a bit‐error rate of 10−4. [ABSTRACT FROM AUTHOR]

As a hybrid method, many-body dissipative particle dynamics with energy conservation (MDPDe), promises to simulate heat transport process with free surface fluids. However, the temperature-dependent surface tension cannot be modelled accurately in MDPDe so far, which greatly limits its further applications. In the present study, semi-empirical relationships between the attractive coefficient and temperature obtained by mapping with real liquids (i.e., water, ethylene glycol and benzaldehyde) are introduced into MDPDe. The simulation results are validated by comparing with the relevant experimental, theoretical and numerical results, respectively. The improved MDPDe model in the present work opens the door to study various thermocapillary phenomena with free surface fluids at mesoscopic scale. [ABSTRACT FROM AUTHOR]

The present study explored the association between KRAS proto-oncogene GTPase (KRAS), phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit α (PIK3CA) and tumor protein p53 (TP53) mutations, and the clinical features and survival prognosis in 50 patients with non-small cell lung cancer (NSCLC). The most common concurrent single gene mutation was TP53, followed by KRAS and PIK3CA. Co-existing mutations were found in 17 patients. KRAS, PIK3CA and TP53 mutations were associated with carbohydrate antigen 19-9 expression, invasive growth, vacuolar signs and margin lobulation on chest CT. The incidence of distant metastasis (bone and adrenal) with KRAS and TP53 mutations was greater than that of local metastasis (pleura). Patients with the wild-type genes experienced longer progression-free survival (PFS) times than those with KRAS, TP53, KRAS/TP53 or PIK3CA/TP53 mutations. Patients with KRAS/TP53 or PIK3CA/TP53 mutations experienced shorter PFS times than those with a single KRAS or TP53 mutation. KRAS, PIK3CA and TP53 mutations were associated with distant metastases and a poor prognosis. Patients with NSCLC should receive routine KRAS, PIK3CA and TP53 gene sequencing to determine mutations for the analysis of clinical characteristics and prognosis. [ABSTRACT FROM AUTHOR]

Highlights • A network theoretic metric for comparing HAZID methods was presented. • The metric counts socio-technical interactions in accident scenarios. • The metric is called the P3 Interaction Contribution (PIC). • The PIC results showed clear differences in HAZID results. • Future experiments to validate the PIC were presented. Abstract Comparing the results of hazard identification (HAZID) methods is a complex task, but the question that drives this activity is vitally important: which HAZID method should be used to best identify an accident scenario? Despite many efforts to address this, effective metrics do not yet readily exist for clearly comparing HAZID results for a particular scenario. The complexity of socio-technical systems is often cited as a key factor that limits effective scenario identification, calling into question traditional HAZID efforts. Motivated by the observation that interactions between multiple component types, such as People, Plant and Procedures (P3), often significantly contribute to major process system accidents, being an expression of the complexity of the system, a novel, precise, network topology-based metric for calculating the contribution of P3 Interactions to accident scenarios is presented. This metric, called the P3 Interaction Contribution (PIC), is intended to be used for comparing the HAZID results. An illustrative example of using the PIC for HAZID comparison is included, whereby Failure Mode and Effects Analysis (FMEA), Blended Hazard Identification methodology (BLHAZID) and Systems Theoretic Process Analysis (STPA) were each applied to a heat exchanger start-up operation. The results show initial promise that the PIC can be effective as a HAZID comparison tool. The main outputs of this paper are the presentation of the PIC calculation process and the method for applying the PIC to HAZID results. The paper concludes with recommendations for further experimental work to explore the validation and assess the true value of the PIC. [ABSTRACT FROM AUTHOR]

The spontaneous wetting transition of droplet coalescence on immersed micropillared surfaces was investigated by using many-body dissipative particle dynamics (MDPD). The simulation results show that wetting states are influenced by both the interpillar spacing and intrinsic contact angle of surfaces during droplet coalescence. The overestimation of the contact angle by the Cassie equation was modified by introducing a penetration factor, and the energy analysis suggests that the spontaneous Wenzel-to-Cassie transition could be predicted from critical contact angles. For surfaces with small interpillar spacing and large intrinsic contact angle, the spontaneous Wenzel-to-Cassie transition occurs during droplet coalescence, irrespective of the size of the immersed area. The contact angle hysteresis was also studied, in which the droplet was driven on immersed micropillared surfaces. It was found that reducing interpillar spacing is a feasible option to maintain robust superhydrophobicity, and that it is possible to realize the spontaneous Wenzel-to-Cassie transition. Otherwise, larger interpillar spacing and larger size of the immersed region will result in longer contact lines pinned by pillars if the spontaneous Wenzel-to-Cassie transition fails to occur. Meanwhile, it leads to the weakening of droplet mobility during transportation. The outcomes demonstrate that appropriate geometrical structures and wettability properties should be taken into consideration in order to achieve robust superhydrophobicity and high efficiency of the droplet transportation. [ABSTRACT FROM AUTHOR]

• Across age, moderate-to-strong correlations between standard and high-resolution DWI. • Higher gray matter FA/MD in high-resolution DWI, and stronger age correlation. • Higher white matter connectivity in high-resolution DWI, but weaker age correlation. • Only high-resolution MD/connectivity strength mediated age-related cognitive decline. Healthy neurocognitive aging has been associated with the microstructural degradation of white matter pathways that connect distributed gray matter regions, assessed by diffusion-weighted imaging (DWI). However, the relatively low spatial resolution of standard DWI has limited the examination of age-related differences in the properties of smaller, tightly curved white matter fibers, as well as the relatively more complex microstructure of gray matter. Here, we capitalize on high-resolution multi-shot DWI, which allows spatial resolutions < 1 mm3 to be achieved on clinical 3T MRI scanners. We assessed whether traditional diffusion tensor-based measures of gray matter microstructure and graph theoretical measures of white matter structural connectivity assessed by standard (1.5 mm3 voxels, 3.375 μl volume) and high-resolution (1 mm3 voxels, 1μl volume) DWI were differentially related to age and cognitive performance in 61 healthy adults 18–78 years of age. Cognitive performance was assessed using an extensive battery comprising 12 separate tests of fluid (speed-dependent) cognition. Results indicated that the high-resolution data had larger correlations between age and gray matter mean diffusivity, but smaller correlations between age and structural connectivity. Moreover, parallel mediation models including both standard and high-resolution measures revealed that only the high-resolution measures mediated age-related differences in fluid cognition. These results lay the groundwork for future studies planning to apply high-resolution DWI methodology to further assess the mechanisms of both healthy aging and cognitive impairment. [ABSTRACT FROM AUTHOR]

The Schmidt number effect on the rheology of finitely extensible nonlinear elastic chains (FENE) in many-body dissipative particle dynamics (MDPD) is investigated in this work. We find that the Schmidt number, ranging from (101) to (103), has limited influence on the polymer properties, such as its radius of gyration (Rg), diffusion coefficient (D) and relaxation time (τ). The simulation results follow Zimm model's predictions well. The hydrodynamic interaction strength parameter h* demonstrates that the full hydrodynamic interaction can be simulated for Schmidt number from (100-106) in MDPD. Next, the rheology of FENE polymers is studied using Lees-Edward boundary condition in shear flow. The shear-thinning and normal stress difference are measured and analysed with MDPD; meanwhile, the volume fraction, solvent quality and chain length are varied to explore their effects on the extent of the Newtonian region. Finally, the non-Newtonian droplet is firstly simulated in MDPD. Its maximum spreading diameter is measured for both Newtonian and non-Newtonian droplet with Weber number (We) ranging from 4.37 to 109.2 on hydrophilic, moderate and hydrophobic surfaces, respectively. The fluid shear-thinning property increases at high shear rate and is further enhanced on more hydrophobic surface, from the maximum spreading diameter results. The non-Newtonian (FENE) droplet can be now well simulated in MDPD and this provides additional insight to further research concerning polymer-solvent-surface interactions, which is crucial in various applications. [ABSTRACT FROM AUTHOR]

Viscometric properties of polymer are explored by the many-body dissipative particle dynamics (MDPD) using Lees–Edwards boundary conditions. The equation of state for the MDPD system is modified by fitting the density correction to different values of the cut-off radius. Due to the many-body interactions in MDPD, the viscosity contributed from the conservative force increases considerably with increasing repulsive coefficient, density and cut-off radius, and cannot be ignored compared to the ‘standard’ DPD case. The influence of these parameters on the MDPD viscosity is investigated, and we propose an equation to predict the viscosity in MDPD model. Additionally, the dumbbell polymer suspension model is investigated in the MDPD fluid, and the relations concerning first normal stress difference and shear rate, the relaxation time and spring constant, are consistent to theoretical works. We conclude that the MDPD model can be used to investigate the dynamics of non-Newtonian droplets. [ABSTRACT FROM PUBLISHER]

• Invar alloy butt joints are connected via circular oscillating welding. • Increasing oscillating frequency leads to the improved degree of energy coincidence and heat accumulation. • The influence of stirring effect by beam oscillation and heat accumulation on microstructure is analyzed. • The elongation of laser oscillated weld is increased by 23.7% compared with non-oscillated weld. In the present work, the 3 mm thick Invar alloy butt joints are connected via circular oscillating welding. The macro appearance, microstructure morphology and mechanical property of the welded joints obtained under different oscillating frequencies are studied. The laser energy distribution is simulated to visually exhibit the range of laser radiation and the degree of energy coincidence for better explaining the formation mechanism of weld geometry. A CFD model for laser oscillating welding process is developed. The powerful vortexes induced by beam oscillation are observed which have a stirring effect on the molten pool and the heat accumulation in the weld center is much severer with increasing oscillating frequency. The influence of beam oscillation on grains around the fusion line is significant but the increase of oscillating frequency is not always beneficial for the microstructure in the weld center. For the situation with a relatively lower frequency (50 Hz), several grains are broken and smaller grain size is obtained. However, the grain refining effect caused by beam oscillation is not obvious as the frequency grows to 100 Hz. This phenomenon is ascribed to the increasing heat accumulation. The tensile test results show that the maximal tensile strength reaches 410.7 Mpa and the elongation is increased by 23.7 % compared with the non-oscillated weld when f = 50 Hz, a mass of equiaxed dimples and a small quantity of serpentine sliding are observed on the fracture surface. [ABSTRACT FROM AUTHOR]

By using many-body dissipative particle dynamics (MDPD), dynamical behaviors of droplet impingement and spreading on chemically heterogeneous surfaces is presented in this paper. The influences of Weber number ( We ) and fraction ( Φ l i c ratio of hydrophilic area to whole region) on dimensionless spreading diameter (D* ratio of spreading diameter to initial droplet diameter), dimensionless height (H* ratio of height of droplets to initial droplet diameter), advancing contact angle ( θ a ) and receding contact angle ( θ r ) are systematically analyzed. The simulated results show that larger We and Φ l i c lead to larger spreading diameter, even overspreading. Particularly, the stick-slip motion of droplet during recoiling stage is found to be affected both by Weber number ( We ) and fraction ( Φ l i c ), which cannot be captured on homogenous surface. As a result, the stick-slip motion could be divided into two sub-stages during recoiling stage, which is novel to the situation involving droplet with fixed impact velocity. It provides an insight to understand the mechanism of stick-slip motion for droplet impingement on chemically heterogeneous surfaces. [ABSTRACT FROM AUTHOR]

Conductive bridging random access memory (CBRAM) has been considered as a promising candidate for next-generation non-volatile memory. However, there are always problems of high-power consumption in CBRAM. In this study, a GeTe-based resistive random access memory (RRAM) with an active Cu electrode is fabricated, which reveals significant behavior of low forming voltage (<|-2|V). At the same time, the device exhibits the property of self-compliance, which is essential for protection of the device and reduction of the leakage current. Furthermore, the resistance switching (RS) mechanism of the device is proved to be filament-type, which helps explain the self-compliance phenomenon in detail. These properties provide an effective solution to the achievement of low-power consumption in CBRAM, and show a potential for the scalability of the device and high-density integration in the cross-bar array. [ABSTRACT FROM AUTHOR]

We present a numerical study of droplets sliding across chemically heterogeneous surfaces formed by a periodic pattern of alternating hydrophobic and hydrophilic stripes, or topographically heterogeneous surfaces which are microgrooved. The numerical simulation performed by using a particle-based numerical method, Many-body Dissipative Particle Dynamics (MDPD), is adopted to observe the stick-slip motion of droplets driven by a constant body force. The fractions of two types of surfaces are varied from 0.3 to 0.7 to investigate their influence on stick-slip motion of droplets. The dynamic contact angles and the variation in distanceDfrbetween the front and the rear contact points are shown for different fractions. The jerky motion characterised by stick-slip motion can be found on chemically heterogeneous surfaces for all fractions we choose and the partial stick-slip motion can also be discovered on topographically heterogeneous surfaces except for fraction Φs = 0.3. The snapshots of droplet show that stick-slip motion is the consequence of the periodic deformation of droplet interface during crossing heterogeneous surfaces and can be controlled by fractions. [ABSTRACT FROM PUBLISHER]

A novel all optical up-converted signal generation scheme with optical single-sideband (OSSB) technique for radio over fiber (RoF) application is presented and experimentally demonstrated using low-bandwidth devices. The OSSB signal is generated by one low-bandwidth intensity LiNbO 3 Mach-Zehnder modulator (LN-MZM) under frequency quadrupling modulation scheme and one low-bandwidth LN-MZM under double sideband carrier suppressed modulation (DSB-CS) scheme. The proposed all OSSB generation scheme is capable of high tolerance of fiber chromatic dispersion induced power fading (DIPF) effect. Benefiting from this novel OSSB generation scheme, a 26 GHz radio frequency (RF) signal up-conversion is realized successfully when one sideband of the optical LO signal is reused as the optical carrier for intermediate frequency (IF) signal modulation. The received vector signal transmission over long distance single-mode fiber (SMF) shows negligible DIPF effect with the error vector magnitude (EVM) of 15.7% rms. In addition, a spurious free dynamic range (SFDR) of the OSSB up-converting system is measured up to 81 dB Hz 2/3 . The experiment results indicate that the proposed system may find potential applications in future wireless communication networks, especially in microcellular personal communication system (MPCS). [ABSTRACT FROM AUTHOR]

Background: Osteosarcoma (OS) is a prevalent bone cancer characterized by its aggressive nature, which often metastasizes to the lungs and contributes to a poor prognosis. Treatment progress has been hindered by drug resistance, distant metastases, and significant patient heterogeneity. However, recent advancements in technologies such as sequencing and multi‐omics have enabled more in‐depth investigations at the micro level. Aim: By undertaking a critical analysis of related studies, the present work intends to provide an overview of the microenvironmental features of osteosarcoma discovered through single‐cell RNA sequencing (scRNA‐seq) analysis. The articles included in this review were from several medical and health databases. Results and discussion: We also discuss drug resistance traits, taking into account the heterogeneity of OS cells within the tumor microenvironment (TME). This includes inherent and acquired resistance in both pre‐ and post‐chemotherapy osteosarcoma, as well as the close association between cancer stem cells (CSCs) and drug resistance. Additionally, we examine the intercellular communication between OS cells and other cell types, as revealed by both traditional and single‐cell studies, and suggest several promising therapeutic targets. Conclusion: Single‐cell RNA sequencing (scRNA‐seq) provides a detailed view of the tumor microenvironment, revealing intercellular communication between osteosarcoma cells and other cells, and aiding in the identification of potential therapeutic targets. [ABSTRACT FROM AUTHOR]

Casing treatment is one of the important solutions to enhancing compressor stability. A new concept of controllable speed casing was proposed in this paper, aimed at weakening the loss of efficiency and achieving off-design regulation. In the context of controllable speed casing, the whole casing structure was divided into stationary ring section and rotatable ring section. With adjustment made to the rotating direction and speed of the rotatable ring, different additional effects could be exerted on the tip flow field. In the paper, a numerical research was carried out on the flow stability of different rotating directions and speeds of the rotatable ring. The results show that the controllable speed casing rotating in whether same or opposite direction of the rotor can improve the stability margin of the rotor by controlling the interaction between shock wave/leakage vortex. Moreover, the controllable speed casing with different rotating speeds produces different stable operating margin improvements. When the casing is in the same rotating direction and speed as the rotor, the improvement of the flow field is the most obvious, and the stable operating margin could be increased by 52.56% on the premise the efficiency is basically unchanged. [ABSTRACT FROM AUTHOR]

• Dual laser-beam bilateral synchronous welding-brazing experiments of Ti/Al butt joints have been carried out. • IMCs inhomogeneity improves and inhomogeneous interfacial reaction is well regulated. • The relationship of the morphology of IMCs layer between laser power and offset is studied, and their effect on tensile property of joints is investigated. • A favorable tensile strength (reach up to 71% of aluminum alloy base metal) is obtained. To regulate the inhomogeneous interfacial reaction during laser welding-brazing of Ti/Al dissimilar alloys, an advanced method of dual laser-beam bilateral synchronous welding-brazing was proposed. The formation mechanism of the intermetallic compounds (IMCs) with various dual laser-beam input was analyzed. The experimental results revealed that sound brazing joints with homogeneous serrated-shaped IMCs along the Ti/Al interface were obtained when the laser power on both sides is the same. An interesting phenomenon can be found that the thickness of IMCs layer on both sides is thicker than the middle. The highest bonding strength of Ti/Al butt joints could reach up to 71% of aluminum alloy base metal due to homogeneous serrated-shaped IMCs with a thickness of 3–4 μm. [ABSTRACT FROM AUTHOR]

• Dual laser-beam bilateral synchronous welding (DLBSW) experiments of Ti6Al4V double lap-fillet joints have been carried out. • The relationship of thermal cycle and microstructural evolution is studied. • Narrow HAZ width and fine acicular α'-martensite for low welding speed is observed. • Residual stress distribution has a great influence on fracture behavior of lap-fillet joint. • Slower welding speed is in favor of higher tensile strength. Employing prefabricated "boss" on the substrate to replace wire feeding, an attempt is made to explore the non-filler welding process of Ti6Al4V double lap-fillet welded joints with the technology of dual laser-beam bilateral synchronous welding (DLBSW). The weld quality is evaluated in terms of bead geometry, microstructural morphology and mechanical property. An optimal range of welding speed (1.3 m/min) with constant unilateral laser power of 950 W is identified to achieve satisfactory weldments with no underfill defect and acceptable porosity. Phase transformation and microstructural evolution occurring through thermal history in different regions of the welded joint are clarified. The average length of α'-martensite in the weld seam (WS) decreases significantly as welding speed increases. A connection between dimensional variation of α'-martensite and tensile strength is developed, and the fracture mechanism of the lap-fillet joint is discussed. The existence of fine α'-martensites helps to attain high-performance joints with strength comparable to the base metal (BM). The fracture position of tensile specimens is located in the region near the weld toe where stress concentration occurs. Fractography analysis indicates that the failure of weldments is in ductile mode with the feature of a great number of dimples. [ABSTRACT FROM AUTHOR]

Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases. However, the intrinsic ill-posed inverse problem relating the tissue phase to the underlying susceptibility distribution affects the accuracy for quantifying tissue susceptibility. Recently, deep learning has shown promising results to improve accuracy by reducing the streaking artifacts. However, there exists a mismatch between the observed phase and the theoretical forward phase estimated by the susceptibility label. In this study, we proposed a model-based deep learning architecture that followed the STI (susceptibility tensor imaging) physical model, referred to as MoDL-QSM. Specifically, MoDL-QSM accounts for the relationship between STI-derived phase contrast induced by the susceptibility tensor terms (χ 13 , χ 23 and χ 33) and the acquired single-orientation phase. The convolutional neural networks are embedded into the physical model to learn a regularization term containing prior information. χ 33 and phase induced by χ 13 and χ 23 terms were used as the labels for network training. Quantitative evaluation metrics were compared with recently developed deep learning QSM methods. The results showed that MoDL-QSM achieved superior performance, demonstrating its potential for future applications. [Display omitted] [ABSTRACT FROM AUTHOR]